Resilience of Rock Engineering: Concept, Mechanism, Evaluation and Enhancement

Resilience of Rock Engineering: Concept, Mechanism, Evaluation and Enhancement | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Resilience of Rock Engineering: Concept, Mechanism, Evaluation and Enhancement Zhou Chang, Han Chunni, Sui Wanghua This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5483583/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 26 May, 2025 Read the published version in Geoenvironmental Disasters → Version 1 posted 9 You are reading this latest preprint version Abstract Rock engineering systems face escalating threats from extreme climatic events and the complexities of deep engineering, necessitating robust resilience to withstand multi-hazard disturbances. Traditional methods, based on static equilibrium analysis, prove unsuited to address the dynamic, nonlinear interactions inherent in these systems. This study proposes a resilience-oriented framework for rock engineering, emphasizing the system's capacity to maintain or rapidly recover functionality following disturbances. The study proposes a conceptual model, evaluation method, and enhancement techniques to improve rock engineering resilience, based on the complex system science. A unified disaster resilience management system is proposed, synergizing multi-field monitoring, risk assessment, and rapid recovery strategies. Three resilience-enhancing techniques are presented, including grouting reinforcement, resilient anchor support, and high-pressure anchor injection-spraying collaborative control, optimize stress redistribution and fracture resistance in rock masses. The research provides theoretical foundations and actionable strategies to reconcile the safety-sustainability dichotomy in rock engineering, particularly for deep tunneling and slope stabilization projects. By redefining resilience as a quantifiable system property rather than a qualitative goal, the framework enables data-driven lifecycle management of geotechnical infrastructure. Rock Engineering Resilience Dynamic Evolution Process Complex System Science Resilience Evaluation Bolt-Grouting System Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 1. Introduction Rock engineering systems, characterized by complex rock -engineering structure interactions, face escalating challenges from the compounding effect of global climate change and the intensifying demands of deep engineering development (Xie et al., 2019; Tellman et al., 2021 ; Ward et al., 2015 ; He et al., 2005 ). The inherent uncertainty and fragility of rock engineering systems are significantly exacerbated by Natural (e.g., earthquakes, climate change) and anthropogenic disturbances (e.g., mining, tunneling) amplify systemic fragility by inducing spatiotemporal alterations in rock mass structure, stress regimes, and hydraulic conditions. (Hu et al., 2019 ; Ying et al., 2021 ; Sui et al., 2022b,2023; Zhou et al., 2022 ). These disturbances induce a series of complex changes in rock mass. These include temporal, spatial, stress, hydrological changes to the rock’s structure and mechanical properties (Cerfontaine et al., 2018; Ying et al., 2021 ; Zhu et al., 2022). The far-reaching impact of these changes on engineering structure and their functional performance are substantial. For example, the time-dependent propagation of fractures in the rock mass causes the progressive deformation and failure of tunnel linings as well as large-scale deformation in roadways. Meanwhile, variation in hydrological conditions may result in water inrush and sand production, which can completely bury roadways (Sui et al., 2022a). These catastrophic events lead to severe consequences, including the loss of human life and significant property damage. Consequently, it is both urgent and essential to conduct a thorough evaluation of the resilience of rock engineering. This evaluation primarily focuses on the system’s capacity to maintain its functionality during disturbances or to rapidly recover it afterward. (Kuang et al., 2021 ; Zhou et al., 2023 ). The concept of resilience was firstly proposed by Holling in 1973 to characterize the adaptive capacity of ecosystems in response to external disturbances (Holling 1973 ; Liu et al., 2022 ; Mohanty et al., 2024 ; Fouda et al., 2023). Subsequently, this concept has been widely adopted in various fields, such as urban planning, transportation, water resources engineering. The aim is to accurately assess and improve the resistance and recovery capacity of these systems in the event of disasters (Bruneau et al., 2003 , 2006; Yan et al., 2023). However, in the field of rock engineering, the practical application of the resilience concept is still in its infancy (Shadabfar et al., 2022 ). By integrating the concept of resilience, we can gain a more comprehensive and dynamic understanding of the challenges in discontinuous rock engineering. This view goes beyond to traditional focus on static stability and reliability, and also takes into account the crucial aspects of dynamic recoverability and adaptability. The resilience of rock engineering, characterized by the complex interactions between rock and engineering systems, has received relatively theoretical attention. Current research mainly revolves around two critical aspects: robust design and the post-disaster recoverability of rock engineering. Robust design involves optimizing the structural design of rock engineering system under parameter uncertainty. By minimizing their sensitivity to uncertain parameters, it substantially enhances the systems’ adaptability to unforeseen events (Joint TC205/TC304 Working Group, 2017). There are diverse robust design methods, such as those based on failure probability standard deviation, gradient, functional function variability, Monte-Carlo weighting technique (Juang et al., 2013 ; Gong et al., 2014 ; Khoshnevisan et al., 2015 ; Peng et al., 2017 ). This approach has been applied and validated in multiple fields, including retaining walls, shield tunnels, shallow foundations, bored pile (Zhang et al., 2019 ). However, existing robust design methodologies primarily focus on preventing localized failures and optimizing structural design. Resilience-oriented design strategies have significant limitations in dealing with progressive damage accumulation and dynamic instability mechanism caused by long-term disturbances (Zheng et al., 2022 ). For example, reservoir operations can lead to stepwise landslide deformation, and deep underground roadways may experience cyclic stress redistribution combined with dynamic load superposition under mining disturbances. These continuous perturbations push the structural systems towards gradual failure. This gap between theory and practice highlights the shortcomings of current methods in analyzing the long-term evolutionary processes of rock engineering systems, especially their inability to effectively control continuous instability processes or limit the propagation of failure zone. Post-disaster recoverability research focuses on using recoverable structures or advanced technologies to repair or replace the original rigid structures/connections in rock engineering. This goal is to restore the functionality of the rock engineering structure after a disaster (Anastasopoulos et al., 2010 ). Commonly used recoverable structures include rocking structures, self-resetting structures, replaceable structures, and those made of shape memory alloy material (Lu et al., 2011 ; Wang et al., 2021 ; Wu et al., 2014; Zhou et al., 2023 ). Considering the complex geological structures in rock engineering, especially in deep underground projects like tunnels and roadways, post-disaster repair is extremely challenging. Damage can include water inrush and sand production due to mining activities, roof failures, and tunnel deformations, settlements, faulting, and even collapse triggered by seismic events. Therefore, rapid recovery after significant deformations or catastrophic collapses is of utmost importance in rock engineering (Zhou et al., 2023 a). Unfortunately, the current research in rock engineering lacks essential key technologies and theoretical guidance. Nevertheless, some successful cases exist. Huang et al. (2016) effectively used grouting techniques to quickly repair severely deformed tunnels, greatly improving the recovery rate and overall tunnel resilience. Moreover, Zheng ( 2022 ) proposed an innovative approach, the capsule mine leader active control technology to actively and promptly address tunnel deformations. The theory and methodology of rock engineering resilience represent an emerging and highly promising research field. This field aims to bolster the resistance and recovery capacities of rock engineering systems when confronted with various disturbances and disasters. It plays a crucial role in protecting human live, property, as well as promoting social and economic development. However, the current research on rock engineering resilience still grapples with numerous deficiencies and challenges. These include as the need for clearer conceptual clarification, the development of appropriate resilience indicators, the establishment of effective evaluation methods, the formulation of resilience-based design and optimization strategies, and the innovations of resilience-enhancing structures and technologies. According to the mechanical properties and failure modes of discontinuous rock mass, this paper undertakes a comprehensive review of resilience concepts applicable to geotechnical engineering. It synthesizes key concepts related to rock engineering resilience and constructs a comprehensive framework for mechanism analysis and governance model for rock engineering resilience, taking into account the dynamic evolution process. Moreover, this paper proposes reinforcement methods according to the characteristics of rock engineering at different stages-before, during and after disturbances. It also briefly introduces three key technologies for enhancing rock engineering resilience. Furthermore, it introduces the theory of rock engineering resilience support. 2. Literature review of resilience suitable for geotechnical engineering The resilience of geotechnical engineering is a novel and interdisciplinary topic that encompasses engineering, geology and system science. This review focuses on resilience studies within geotechnical engineering felid. To conduct the literature search, we utilized databases such as Web of Science (WoS), Scopus, and Google Scholar. Figure 1 provides a detailed account of the methodology employed for selecting relevant publications. In total, 93 publications, spanning from 1935 to 2024, were reviewed (Fig. 1 ). We analyzed the temporal distribution of these literatures and keyword co-occurrence related to resilience in geotechnical engineering. The first relevant literature was published in 2011, with a significant increase in the number of publications starting from 2015. By 2024, the number of publications reached 18, and these publications had approximately 308 citations. Regarding the geographic distribution of these publications, 42.5% originated from Asia, Europe and Australia followed, each contributing 18–19%. The five journals with the highest number of publications on this topic are the Soil Dynamic Earthquake Engineering, Journal of Geotechnical and Geoenvironmental Engineering, Bulletin of Earthquake Engineering, Natural Hazards, Engineering Geology, Frontiers in Earth Science. Among them, Soil Dynamic Earthquake Engineering has published 19 articles, accounting for 20.43% of the total, higher than other journals. These journals have a long-standing reputation and wield significant academic influence. An analysis of their topic and keywords of those publication finds that the proportion of papers with the theme of "earthquake" and “seismic” exceeded 40%, indicating that current publications mainly focus on earthquake-related research. It is further corroborated by keyword co-occurrence analysis (Fig. 2 ). In analysis, the nodes "Earthquake," "Landslides," and "Simulation" are closely interconnected, forming a distinct cluster. Meanwhile, "Risk Management" forms another cluster with "Model," "Performance," and "Resilience," suggesting that model performance and system resilience are key topics in risk management studies. The keywords co-occurrence also reveals that current research topics are primarily concentrated on soil mechanisms (especially related to sand), engineering behavior, and geotechnical engineering. The strong association between "Geotechnical Engineering" and "Risk Management" suggests that risk management is a crucial research avenue within geotechnical engineering. Furthermore, the connection between "Resilience" and "Sustainability" points to a close relationship in research, possibly involving studies into system durability and environmental adaptability. The density of nodes and connection lines in the analysis reflects a strong focus on resilience and sustainability research in the environment and engineering fields in recent years. Thus, resilience in geotechnical engineering has emerged as a prominent research topic and is expected to continue attracting attention, especially in the context of extreme climate and the pursuit of sustainable development. 3. Resilience of rock engineering To ensure the long-term safety and stability of engineering projects, it is essential to effectively reinforce fractured rock mass, which form the foundation of rock engineering. Commonly used reinforcement methods, such as rock bolts/cables, anti-slide piles, concrete structures, and grouting transformation methods, are classic approaches for dealing with rock mass failure. However, under complex geological dynamic conditions, these methods may encounter difficulties in effectively preventing or recovering rock mass failure. This is particularly true when the rock mass experiences great deformations or catastrophic collapses due to severe disturbances. Therefore, there is an urgent need to develop innovative methods and technologies to further enhance the resilience of rock engineering. In this paper, Resilience is defined as the system’s capacity to either maintain its function or quickly recover it after being subjected to disturbances. 3.1 Resilience concept of rock engineering Bruneau et al. ( 2003 ) was the first to introduce the concept of recoverability into civil engineering. They proposed a conceptual framework of seismic resilience and pioneered the application of resilience enhancement theory in this field. With the development of engineering technology and economy, this resilience focused approach has gradually made its way into geotechnical engineering. As underground engineering ventures deeper, the complexity of the geological, ecological and engineering environment has increased significantly. Consequently, rock engineering is confronted with higher requirements and daunting challenges. The concept of resilience in rock engineering can be derived from seismic resilience theory. This theory defines resilience in four dimensions, characterized by four evaluation indicators and three critical features. In the context of rock engineering, resilience refers to the system’s innate capacity of the system to adjust its function before, during, or after various disturbances. This adaptability enables the system to maintain its engineering performance under both expected and unexpected disturbance conditions. Robustness is used to evaluate the system’s reliability prior to a disaster. Resourcefulness and redundancy are crucial for assessing the system’s post-disaster recover ability. Rapidity measures the efficiency of post-disaster recovery. The theory of enhancing rock engineering resilience measures to adjust the system’s function at different stages of disturbances. These measures greatly improve the system’s capacity to maintain engineering performance even in the face of challenging disturbance scenarios (Peer 2010 ; lv et al., 2017 ). 3.2 Resilience mechanism analysis framework of rock engineering In the rock engineering system, rock engineering structures, disturbance and engineering performance are three elements that are intricately interrelated, interdependent and mutually constrained. Together, they form the dynamic evolution process of rock engineering system. Therefore, to enhance the resilience and sustainability of the rock engineering system, research must comprehensively consider the interaction mechanism among rock engineering structure, disturbance and engineering performance from a holistic perspective throughout the entire life cycle of the system. This paper integrates three elements: disturbance, rock engineering structure and engineering performance, into a comprehensive analysis framework. It clarifies the interaction mechanism among disturbance, rock mass and engineering structure. Specially, it examines the dynamic change in functional robustness. By analyzing the evolution of geological structure and its strength, engineering support resistance, and deformation under disturbance, the paper identifies the inherent dynamic changes and threshold in rock engineering, and reveals the resilience evolution mechanism of rock engineering. (1) The impact of disturbance on the rock engineering system The spatial framework of rock engineering consists of geological structures, stratum lithology, stress, hydrological features, and others. The functional integrity of this system is controlled by the coordination effect between the geological structural plane network and engineering structures (such as anchor bolts, grouting bodies). Disturbance loads, from engineering activities, disasters impact, geological time-varying effect, change the state of rock mass. According to their mechanisms for rock function degradation, these disturbances can be classified into three types: elastic action (disturbance load < elastic limit load, the rock deforms reversibly without any loss of functional), plastic action (elastic limit load < disturbance load yield limit, local functional loss triggers rock failure). Considering the effect of the rock structural planes, rock mass failure under disturbances can be divided into three types: 1) Physical failure, where the disturbance directly causes physical damage on the rock (equivalent to critical action). This results in the loss of function of system nodes, which are the points where components of the rock mass engineering interact. However, it does not affect the overall system function. 2) Related failure, because of the interactions within the system’s networks, the loss or improvement of the function of local network and nodes can impact the function of other parts of the network (Yan et al., 2023). For example, an anchor bolt failure can lead to the instability of the rock block it supports. 3) Potential field transformation, where the disturbances can modify the original stress-strain field of the rock mass. This transformation leads to significant changes in the interaction relationships between networks. For example, a disturbance that causes side-wall failure in a roadway leads to the formation of a new stress arch in the surrounding rock, creating a new stable system. In other words, local physical damage causes stress and energy transfer. These three action mechanisms are involved in an interactive dynamic process. They transforms the rock engineering system, and affects its structural and mechanical properties (Fig. 3 ). (2) Dynamic evolution of rock engineering spatial structure under disturbance Rock engineering is a complex system with a spatial structure defined by stratum lithology, geological structures, and engineering components. Stratum lithology is fundamental as it determines the physical properties and spatial distribution of rock masses, forming the cornerstone of the rock engineering spatial structure. The geological structure, conversely, acts as the controlling elements. They mirror the complex processes of rock mass formation, deformation, and failure, which introduce heterogeneity and discontinuity into the rock mass. These characteristics increase the complexity and uncertainty of the rock engineering system. Engineering structures involve critical operations such as excavation, support, and reinforcement of rock masses. These activities are integral to the complex rock engineering system. As these engineering interventions are carried out, they dynamically modify the structure and stress state of the rock mass. The interplay among stratum lithology, geological structure, and engineering interventions shapes the overall structure and stress distribution of rock engineering projects, ultimately exerting significant influences on their stability and safety. Zhu ( 2011 ) proposed the hierarchical rock mass structure model. This three-dimensional modeling approach classifies the structural planes within the rock mass into deterministic structural planes (e.g., faults, stratum interfaces, and ground surfaces) and random structural planes. Using a hierarchical modeling method, this model constructs a three-dimensional representation that captures the internal structural features of the rock mass, providing a geometric basis for stability analysis. Then, we have developed a three-dimensional spatial system for complex rock engineering. Firstly, based on stratum lithology, the stratum is abstracted as a spatial set \(\:{R}_{S}=\left\{{R}_{1},{R}_{2},\cdots\:,{R}_{n}\right\}\) . Definite interface such as structural planes, engineering interfaces, ground surfaces and other definite interfaces abstracted as a three-dimensional planar set \(\:{P}_{S}=\left\{{P}_{1},{P}_{2},\cdots\:,{P}_{n}\right\}\) . The anchor bolt structure is abstracted as a line set \(\:{L}_{S}=\left\{{L}_{1},{L}_{2},\cdots\:,{L}_{n}\right\}\) , and the underground hydrological system is abstracted as a spatial set \(\:{W}_{S}=\left\{{W}_{1},{W}_{2},\cdots\:,{W}_{n}\right\}\) . Grouting reinforcement involves injecting grouting material into the structural plane spaces such as structural fissures, layers, effectively filling the interface. This is abstracted as \(\:{{P}_{S}}^{\prime }=\left\{{{P}_{1}}^{\prime },{{P}_{2}}^{\prime },\cdots\:,{{P}_{n}}^{\prime }\right\}\) . The degree of overlap between the interface \(\:{P}_{i}\) and the grouting reinforcement \(\:{{P}_{i}}^{\prime }\) is used as the integrity weight of the grouting rock mass, and an integrity matrix \(\:\left\{{l}_{i}\right\}\) is constructed. These networks are superimposed to form a composite spatial network of the grouting rock mass-structure system \(\:\text{G}=({R}_{S}\cup\:{P}_{S}\cup\:{L}_{1}\cup\:{{P}_{1}}^{\prime })\) (Fig. 4 ). Stratum information, rock mass structure and grouting effect can be obtained through field tests such as drilling and water injection. The input of energy as a disturbance to the rock mass triggers changes in its internal stress and strain. These changes propagate and transform in the form of energy, stress, and strain. To better understand this complex behavior, we conceptualize the engineering unit rock mass (labeled A-F) and the engineering structure (labeled a-c) as nodes. The pathways through which energy, stress, and strain propagate within the rock mass and structure are regarded as edges, thus forming an intricate interaction spatial network in rock engineering (Fig. 5 ). As the input energy escalates, the rock groups and structures gradually undergo physical damage, resulting in the release of energy. Meanwhile, due to the related failure mechanisms and potential field transformations (Yan et al., 2023), there are synchronous changes in accessibility and stress at each node. These changes have a great impact the load-bearing capacity and overall stability of the rock engineering system. The continuous increase in the number of physically damaged nodes progressively damages the integrity of rock engineering. As proportion of affected nodes expands, it may ultimately lead to severe instability and functional impairment of the entire rock engineering system. By analyzing the proportion of stable block and the risk index associated with each disaster scenario, we can construct curves depicting the variation of these characteristic indicators with respect to the disturbance intensity. These curves reveal the resilience characteristics of the rock engineering spatial structure. When a disturbance occurs, it promotes the expansion and penetration of internal joints and fissures in the rock mass, thereby increasing risk indicators such as the failure probability of water inrush and sand production. As the system deformation intensifies, the rock bolt b begins to Sustain initial physical damage. This leads to a rapid drop in the stress within the related rock block A, followed by gradual physical damage and slippage. Subsequently, the stress gradually transfers to other parts of the rock mass, giving rise to an ear of increased stress (associated with potential energy transformation) (C/D). When the rock bolt A also gets damage, the related rock mass E and F experience related failure, which significantly impacts the overall performance of the entire rock engineering system. 3.3 Resilience evaluation index and method The resilience index Q(t) is a metric that quantifies the system’s ability to recover from disturbances over time (Bruneau et al., 2003 ). To standardize the dimensions, we define the resilience indicator Q(t) as the ratio of the actual resilience R(t) to the maximum possible resilience R max . Here, R(t) denotes the distance between the system’s current state and its equilibrium or reference state, while R max represents the maximum distance the system can withstand before undergoing a state transition or collapse. The value of the resilience indicator Q(t) ranges from 0 to 1. A value of 0 indicates that the system has no resilience, whereas a value of 1 represents full resilience. When evaluating the resilience indicator Q for a discontinuous rock mass structure, the appropriate performance indicator R(t) must be carefully selected according to the specific engineering types and objectives. For certain important or critical projects, such as nuclear waste disposal projects and underground gas storage projects, long-term stability or sealing performance should be prioritized as the chosen R(t). In conventional or general projects, such as tunnels, foundation pits, slopes, displacement or stress can serve as suitable performance indicator R(t). For some special or complex projects, such as underground reservoirs, underground power stations, a combination of relevant or complementary performance indicators R(t) can be selected, with each assigned different weight. Bruneau et al. ( 2003 ) proposed four evaluation indicators of resilience in seismic engineering: robustness, rapidity, resourcefulness, and redundancy, which are used to assess engineering performance before and after a disaster respectively. When evaluating the robustness of the system, multiple geological factors need to be considered simultaneously. For example, the rock mass structural plane network controls the stress-failure path and affects the deformation resistance of the system. The crustal stress could cause the loss of the prestress in the supporting structure, reducing its restraint efficiency. Support structures enhance the robustness of rock engineering through synergistic mechanisms. Rock bolts prevent structural slippage; grouting homogenizes stress to form a composite arch; yielding bolts release energy at a constant resistance, slowing strain accumulation; multi-layer cables redistribute stress when they fail, maintaining integrity through redundancy and resistance to cascading failure. These factors have a significantly impacts on the overall robustness of the system. Therefore, when evaluating the robustness of discontinuous rock mass structure, it is advisable to use numerical methods that can accurately capture the discontinuity characteristics, such as the discrete element method and the continuous-discontinuous method. Moreover, the coupling effect between the rock mass and the support structure should be considered during the assessment process. When assessing the rapidity and resourcefulness of a rock engineering system, it is crucial to take into account secondary disasters that may occur during the recovery process of rock engineering after disturbances. These secondary disasters include slips, collapses, water inrushes. These additional challenges greatly extend the recovery time and thus reduce the rapidity and resourcefulness of the rock mass structure. To effectively evaluate these aspects, numerical methods capable of capturing dynamic change and nonlinear effect should be used, such as the finite difference method, the finite element method. Redundancy in a rock engineering system is influenced by the presence of structural planes, like fissures and joints. These structural planes introduce dispersion and changes in the force transmission path, thereby impacting the overall redundancy of the rock mass structure. When evaluating the redundancy of a rock engineering system, numerical methods that can account for changes in the force transmission path, such as the discrete element method and the continuous-discontinuous method, should be employed. Additionally, the influence of discontinuous planes on force transmission paths must be carefully considered. 3.4 Resilience governance model of rock engineering Geotechnical engineering design methods have transitioned from traditional single safety factor approaches towards a multi-tiered framework integrating reliability, robustness, and recoverability designs (Zheng et al., 2022 ). While lifecycle management has gradually been incorporated into geotechnical design (e.g., Behnia et al., 2018), existing approaches predominantly focus on structural durability and cost control, often neglecting the dynamic degradation of geological conditions (e.g., rock mass strength attenuation, fracture network evolution). Moreover, current practices often neglect cross-phase integration across the lifecycle of rock engineering projects. This necessitates a paradigm shift toward a lifecycle-oriented resilience governance framework that prioritizes not only static stability and probabilistic reliability, but also dynamic resilience mechanisms. Our framework addresses this gap by integrating real-time monitoring of geological deterioration (e.g., microseismic events, hydraulic conductivity changes) with adaptive interventions (e.g., staged grouting, resilient anchor adjustments), thereby enabling proactive lifecycle resilience governance. By advancing systematic resilience modeling of geological systems evolution, such a framework could \transition disaster mitigation from reactive to proactive strategies through integrated, informatized, and automated management system. These systems unify disturbance scenarios, such as excavation, groundwater fluctuations, and seismic activity, with real-time risk assessment, monitoring, emergency response coordination, and rapid recovery protocols. Finally, advance a unified paradigm for engineering geological disaster prevention and sustainable resilience governance in critical infrastructure projects (Fig. 6 ). Central to this framework is a dynamic resilience evaluation model: $$\:Q\left(t\right)=\alpha\:S\left(t\right)+\beta\:D\left(t\right)+\gamma\:E\left(t\right)$$ where S denotes stress state coefficient, D represents deformation rate, and E quantifies energy dissipation. Coupled with multi-source monitoring data, this framework could enable real-time quantitative diagnosis and AI-driven prediction of instability probabilities under varying disturbance conditions. A three-dimensional decision matrix (risk intensity × exposure × vulnerability) dynamically optimizes hierarchical warning thresholds. During emergencies, an intelligent decision-making system, built on digital twin platforms, performs multi-objective optimization by aligning resilience evolution trajectories with resource allocation and structural redundancy, generating tailored contingency plans (e.g., personnel evacuation, emergency drainage, grout-based water inrush mitigation). Post-disaster recovery leverages adaptive materials such as self-compensating prestressed anchors and shape-memory polymer grouts, with reconstruction efficacy quantified via the resilience gain coefficient (ΔQ). This establishes a closed-loop control mechanism spanning disturbance identification → resilience degradation → functional reconstruction, culminating in a novel resilience governance paradigm characterized by proactive defense, intelligent coordination, and resilient recovery. To advance the rock engineering resilience, a comprehensive multi-field monitoring framework is required to quantify real-time stress state coefficients (S), development rates (D), and energy dissipation factor (E). This framework integrates advanced sensing modalities such as acoustic emissions, microseismic events, and electromagnetic signals. Coupling this data with AI-driven predictive algorithms enables the identification time-dependent disturbance models, ranging from sudden seismic events (requiring rapid-response strategies like controlled blasting, temporary supports) to gradual creep and excavation effects. The latter are addressed via adaptive reinforcement using resilience-enhanced materials and technologies (Table 1 ), including tunnel lining spring structures, self-compensating prestressed anchors, and anchor-grouting integrated systems. Moreover, three-dimensional risk matrices (risk intensity× exposure× vulnerability) optimize warning thresholds and guide intelligent digital twin platforms in matching resilience evolution trajectories with multi-objective emergency protocols (e.g., grouting, drainage). Post-recovery structural durability and functionality are ensured through long-term monitoring, inspection, and maintenance that validate resilience gain coefficients (ΔQ) and enhance system adaptability via modular redundancy (Figs. 7 a, b). This closed-loop "disturbance-damage-repair-recovery" paradigm embeds resilience principles (robustness, resourcefulness, redundancy) into reconstruction phases (Fig. 7 c), employing shape-memory polymer grouts and staged reinforcement to mitigate progressive damage, reduce disaster consequences, and elevate recovery rates (Fig. 7 d). Thereby, the passive mitigation is transitioned to proactive governance through systematic diagnostics of rock mass damage space, failure mode prognostics, and sustainability-driven lifecycle management of critical infrastructure. Table 1 Resilient reinforcement method for rock mass engineering based on evolution process analysis Stage Reinforcement/design methods Reinforcement mechanism Methods Pre-disaster Robust design, restorable design Improve the robustness, resource and redundancy of rock mass engineering system and recovery after disaster 1. Recoverable structure 2. Resilient anchoring technology 3. Anchor grouting technology 4. Relieve pressure 5. Steel structure, anchoring and spraying In-disaster Based on the monitoring system, the rock engineering damage is predicted and the repair damage space is adaptive Evolution of system performance into a cyclical pattern, i.e. "Disturbance - damage - repair - recovery" 1. Temporary structure 2. Adaptive management: compensation for prestress, grouting, channel blocking 3. Controlled blasting technology Post-disaster Assess system damage and vulnerability to quickly repair critical parts/functions of rock mass and systems Improve system recovery 1. Grouting 2. Controlled blasting technology 3. Recoverable structure 4. Resilient reinforcement techniques for rock mass engineering 4.1 Resilient bolt support technology Resilient anchor bolts represent an innovative advancement in rock bolt support technology, characterized by high support resistance and dynamic adaptability to address the limitations of conventional and energy-absorbing bolts in complex geodynamic environments. Unlike traditional bolts optimized for static loads and minimal deformation, resilient bolts integrate a dual-threshold mechanism (Fig. 8 c): the maximum anchoring force ensures structural stability under peak disturbances (e.g., seismic events), while the minimum anchoring force maintains functionality during resilience degradation, enabling phased recovery through periodic energy release (0.10 mJ·m⁻³ per cycle) (Zhou et al., 2023 b,c). This technology dynamically modulates support resistance to accommodate large shear deformation and time-dependent creep (Fig. 8 b), suppressing stress concentration and crack propagation by redistributing energy via controlled yield-reset cycles. For instance, in deep coal roadways, resilient bolts reduced shear displacement by 40% compared to conventional bolts, demonstrating superior adaptability to cyclic mining-induced stress redistribution (Zhou et al., 2023 c). By converting brittle fractures into elastoplastic progressive damage, resilient bolts synergize with AI-driven monitoring systems to translate experimental data (e.g., axial force fluctuations > 20%) into actionable repair protocols, bridging the "disturbance-damage-repair" cycle from conceptual models to data-driven resilience management. 4.2 Grouting reinforcement Rock, as a naturally brittle material, exhibits rigid contact between constituent blocks, rendering it susceptible to fracturing and fragmentation under external forces. This behavior precipitates abrupt reductions in strength and stiffness, limiting its capacity to effectively withstand deformation and impact (Fig. 9 a). Grouting reinforcement is redefined through a multi-stage lifecycle strategy that transitions from passive repair to proactive resilience management (Fig. 9 b). In the pre-disturbance phase, high-pressure pre-grouting fills deterministic structural planes (such as faults, bedding interfaces) with high-fluidity slurries, reducing permeability (< 10⁻⁷ m/s) and blocking seepage paths. This preemptive reinforcement improves the overall stability of the rock mass and the system's robustness by decreasing hydraulic-mechanical coupling risks prior to external disturbance (Zhang 2022 ; Kang et al., 2022 ; Wang et al., 2024 ). During active disturbances, real - time microseismic monitoring acts as an important trigger for adaptive grouting. When event rate exceeds redefined threshold, indicating evolving fracture networks, gradient grouting using elastoplastic materials (epoxy resins) is initiated. This approach dynamically seals propagating fractures while redistributing stress concentrations, thereby preserving structural integrity and system functionality (Fig. 9 c). The grouting parameters (e.g., pressure, material rheology) are systematically adjusted in response to resilience performance metrics, ensuring engineering efficiency remains above minimum safety thresholds even under multi-phase disturbances (Jin et al., 2021; Zheng et al., 2023 ). Post-disaster, self-healing shape-memory polymer (SMP) grouts enable autonomous repair of critical damage zones. These advanced materials achieve rapid crack closure through hydration-activated expansion, restoring structural continuity while maximizing the resilience gain coefficient (ΔQ). Collectively, this strategy transitions rock failure modes from brittle to ductile via two synergistic mechanisms: 1) Stress homogenization through grouted composite arches that redistribute loads across reinforced zones (Fig. 9 a); 2) Energy dissipation via localized plastic deformation within elastoplastic grouted matrices, effectively buffering dynamic impacts (Tani, 2012 ). It aligns with the requirements of a lifecycle - oriented resilience governance framework, enabling the rock engineering system to better withstand various disturbances throughout its life cycle (Fig. 9 c). 4.3 High-pressure anchor grouting-spraying collaborative control technology High-pressure anchor grouting-spraying collaborative control technology, developed by Prof. Kang’s research group, addresses large deformation challenges in kilometer-deep soft coal roadway The approach integrates high-strength, high-pressure composite grouting anchor bolts, high-pressure grouting anchor cables, high-prestress anchor bolts. It also combines support with high-pressure splitting grouting modification and surface spraying. When implemented together, this significantly enhances the structure, integrity, and strength of roadway coal sides. As a result, it effectively controls large deformations in soft coal side roadways (Kang et al., 2020 ). The mechanism of the high-pressure anchor grouting-spraying collaborative control technology encompasses the following main aspects (Kang et al., 2023): (1) High-prestress anchor bolts and anchor cables support can increase the initial stress level in the roadway’s surrounding rock. This action enhances the stability and anti-deformation capacity of the rock mass. (2) High-pressure splitting grouting modification forms a continuous grouting crack network within the roadway surrounding rock. This not only improves the integrity and strength of the rock, but also releases a portion of the ground stress, thereby reducing the overall stress level; (3) Surface spraying creates a uniform, dense and durable protective layer on the roadway’s surface. This layer prevents weathering and rock detachment, thereby improving the overall durability and stability of the roadway. The technology substantially improves the anti-deformation and anti-failure capacity of the roadway. It enables the roadway to endure larger deformations and higher stress levels without experiencing instability or failure. Additionally, the self-healing and self-adaptive capabilities of the roadway are enhanced. When the roadway is deformed or damaged, the grouting crack network allows for repair and adjustment, restoring or maintaining the rock mass structure and its function. Moreover, the technology enhances the redundancy and diversity of the roadway surrounding rock. In cases where certain parts or functions fail, other components can compensate or replace them. This ensures overall safety and operational efficiency. 5. Discussion 5.1 Reinforcement theory of resilient rock bolt Resilient bolt support technology, a critical advancement in enhancing the engineering resilience of discontinuous rock masses, fundamentally transforms conventional rigid confinement through thermodynamic energy regulation mechanisms, enabling dynamic adaptability and controlled damage in rock engineering under disturbances by periodically releasing support resistance to dissipate accumulated strain energy—thereby converting brittle fractures into elastoplastic progressive damage and suppressing microcrack propagation—while exhibiting intrinsic compatibility with the cyclic "disturbance-damage-recovery" evolution of discontinuous rock systems, with optimized parameters (constant-resistance thresholds and energy-release intervals) tailored to structural discontinuities and disturbance types (e.g., stress-redistribution matching in mining-induced high-stress zones versus shock-absorption coordination for seismic shear mitigation), synergistically integrating with grouting reinforcement and high-pressure anchoring to establish multi-scale resilience through macro-stabilization via energy regulation and micro-continuity improvement via fracture filling, thereby advancing the quantification of robustness (energy-absorption density) and redundancy (recovery-rate potential) in resilience metrics while providing a technical framework for autonomous disturbance-adaptive recovery throughout engineering lifecycles. The disturbance energy imposed on rock is divided in to elastic strain energy and irreversible dissipative strain energy (Xie, 2005; Wang et al., 2023 ). $$\:U={U}_{e}+{U}_{d}$$ 1 where \(\:U\) is disturbance energy. \(\:{U}_{e}\) is the elastic strain energy release of the unit. \(\:{U}_{d}\) is the dissipated strain energy of the unit。 During compression tests, the releasable elastic strain energy ( \(\:{U}_{e}\) ) within rock gradually increases as the rock enters the elastic deformation stage. As internal microcracks propagate in uniaxial compression or the material approaches failure (under cyclic loading), the internal damage increases rapidly. Consequently, \(\:{U}_{e}\) decreases rapidly, while the dissipative strain energy ( \(\:{U}_{d}\) ) per unit increases sharply (Fig. 10 a) (Zhao et al., 2020 , 2023 ; Gong et al., 2019 ; Li et al., 2017 ). The coordinate deformation of the resilient anchor bolt-rock system alters the energy evolution in rock mass (Wang et al., 2022 ; Zhou et al., 2023 a). The disturbance energy could be divided into three parts: (1) elastic strain energy in rock mass, (2) dissipative strain energy through irreversible damage mechanism, and (3) cyclic energy release via bolt yield-adaptation (Fig. 10 c) (Zhou et al., 2023 c). There are three distinct conditions: (1) when bolt resistance remains below the rock's elastic limit, system resilience is enhanced through bolt-dominated energy absorption that elevates disturbance resistance thresholds; (2) at bolt resistance levels between elastic limit and peak strength, delayed damage accumulation through scheduled energy release enables elevated energy capacity thresholds; and (3) when bolt resistance exceeds ultimate failure strength, energy redistribution prioritizes bolt-mediated dissipation pathways. Each condition dictates distinct energy partitioning ratios between rock damage processes and bolt-controlled energy regulation mechanisms. $$\:U=\left\{\begin{array}{c}{U}_{e}+{U}_{b}\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:{\sigma\:}_{b}\le\:{\sigma\:}_{e}\\\:{U}_{e}+{U}_{b}+{U}_{d}\:\:\:\:\:\:\:\:\:\:\:\:\:\:{\sigma\:}_{e}\le\:{\sigma\:}_{b}<{\sigma\:}_{l}\\\:{U}_{d}\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:{\sigma\:}_{l}\le\:{\sigma\:}_{b}\end{array}\right.$$ 2 where \(\:U\) is the total strain energy generated by the disturbance. \(\:{U}_{b}\) is the dissipated strain energy of resilient bolt resistance with periodic variation. \(\:{\sigma\:}_{b}\) is the maximum support resistance of resilient bolt. \(\:{\sigma\:}_{e}\) is the elastic limit load of the rock. \(\:{\sigma\:}_{l}\) is the ultimate strength of rock. The true triaxial test results conducted by Zhao et al. ( 2023 ) show the elastic strain energy of sandstone fluctuates slightly within a range of 0.0935 mJ·m − 3 with the number of loading cycles, while the dissipative strain energy stabilizes at 0.02–0.03 0.0935 mJ·m − 3 , with sand rock failure occurring at 1.214 mJ·m − 3 total strain energy ( 0.277 mJ·m − 3 cumulative damage energy of), the sand stone fails (Fig. 10 b). The introduction of resilient bolts reconfigures the energy distribution mechanism of discontinuous rock masses. Based on the calibration of test parameters (Fig. 7 ), the energy absorption/release density of a rock bolt in a single cycle is 0.10 mJ·m − 3 . The average value of the elastic strain energy of sandstone in a single cycle is taken as 0.924 mJ·m − 3 . The maximum disturbance strain energy that the rock-bolts system can withstand under 10 cycles of loading is 1.925 mJ·m − 3 , which is 1.6 times the failure threshold of the case without bolt, and the dissipative strain energy of the rock approaches zero (Xie et al. 2005 ) (Fig. 10 c). This indicates that the bolts could effectively suppress the propagation of microcrack through periodic energy release, transforming the damage mode of the rock mass from brittle fracture to controllable elastoplastic deformation. If the rock resistance is between the elastic and ultimate strengths of the rock mass ( \(\:{\sigma\:}_{e}\le\:{\sigma\:}_{b}<{\sigma\:}_{l}\) ), the effect of enhancing the system’s resilience is more significant. Taking the single-cycles dissipative strain energy of 0.01 mJ·m − 3 as an example, under the same number of cycles, the disturbance strain energy that the rock-resilient rock bolt system can withstand is 2.025 mJ·m − 3 , and the external input energy required to reach the cumulative damage threshold is as high as 5.4675 mJ·m − 3 , which is 4.5 times that of the rock mass without rock bolt (Fig. 10 d). The above thermodynamic mechanism provides a quantitative basis for the resilience control of rock mass engineering. For example, in response to high - frequency disturbances induced by mining activities, the energy - release cycle of the bolts can be adjusted to match the stress fluctuation frequency of the surrounding rock, thereby achieving dynamic energy balance. In the case of transient impacts such as earthquakes, the energy - absorption density parameter of the bolts can serve as a calibration benchmark for setting the disaster - warning thresholds of multi - source monitoring systems. This theoretical framework transforms experimental data into decision - making variables for engineering resilience management, promoting the transition of the "disturbance - damage - repair" cyclic model from the conceptual level to data - driven practice. 5.2 Limitation The concept of resilience represents a relatively nascent and burgeoning topic within the field of geotechnical engineering (Zheng et al., 2022 ). It pertains to the capacity of geotechnical systems to endure, recover from, and adapt to diverse disturbances and hazards, including earthquakes, landslides, floods, and climate variations. Resilience is intricately linked to sustainability, risk assessment, and reliability, while also possessing distinct attributes and challenges. In geotechnical practice, resilience is inherently interwoven with sustainability, risk assessment, and reliability across the entire lifecycle of infrastructure. Resilience-driven design strategies, such as redundant structural systems and adaptive materials, translate quantified risk assessments (e.g., geological hazard probabilities) into engineered safeguards, mitigating post-disaster recovery demands and reducing long-term resource consumption. This approach enhances sustainability by prolonging infrastructure lifespan and minimizing environmental impacts. Concurrently, real-time monitoring (e.g., deformation sensors, AI-driven early warning systems) and adaptive interventions (e.g., optimized support during construction or predictive maintenance) bolster system reliability, preventing incremental degradation and ensuring operational stability. Resilience operates through a systematic “prevention-adaptation-recovery” framework, harmonizing short-term costs with lifecycle benefits to optimize safety, efficiency, and resource stewardship. Ultimately, resilience integrates environmental, economic, and societal value streams, enabling infrastructure to withstand uncertainties while advancing sustainable development goals in engineering geology. A primary challenge in integrating resilience into geotechnical engineering systems from the lack of a universally accepted definition and standardized framework for assessing and enhancing resilience. Cross-disciplinary discrepancies in resilience conceptualization, ranging from material mechanics may emphasize physical resilience such as strength, stiffness, and ductility to engineering management’s prioritization of social and economic factors (e.g., functionality, maintainability, recovery time), further complicate its application (Lee et al., 2018; Liu et al., 2022 ). Additionally, resilience is inherently dynamic and context-dependent, influenced by disturbance characteristics (type, intensity), rock system properties, component interactions, environmental constraints. These complexities hinder quantitative comparisons of resilience across diverse geotechnical systems or scenarios (Zheng et al., 2022 ). A critical impediment to advancing resilience assessment lies in the scarcity of adequate data and knowledge gaps. Rock engineering systems are subject to multifaceted and variable disturbance factors, complicating accurate prediction and modeling (Wu et al., 2021 ). Intrinsic uncertainties, such as variability in rock properties, load conditions, design parameters, and construction methods, compound these challenges (Cai, 2011 ; Behnia et al., 2018; Elmo and Stead 2021 ). Consequently, acquiring reliable, representative data to evaluate the performance and recovery capacity of the system under diverse disturbances remains a formidable task. Advancing resilience in geotechnical engineering demands interdisciplinary innovation, integrating and practice through: (1) establishing unified definitions and metrics for resilience (such as recovery rate, robustness thresholds); (2) Developing multi-source monitoring and early warning systems to capture real-time performance data. (3) Proposing comprehensive evaluation frameworks that integrate multiple parameters (mechanical, environmental and socio-economic indicators). (4) Designing novel reinforcement materials and adaptive technologies to enhance system adaptability. (5) Optimizing resilience strategies to balance cost-effectiveness with ecological sustainability. 6. Conclusion This paper presents a comprehensive exploration of resilience in rock engineering, focusing on its conceptual foundations, evaluation methodologies, and enhancement technologies. The study defines rock engineering resilience through three core attributes: high pre-disaster reliability, low post-disaster consequences, and rapid functional recovery. A unified analytical integrates disturbance, rock engineering structure and functional efficiency, emphasizing the dynamic change of functional robustness and recovery as a key mechanism. By observing the physical-mechanical interactions within rock-support composites and leveraging rock mechanics principles, the framework reveals how resilience evolves under stress and deformation. A geotechnical disaster prevention model is proposed, combining multi-source monitoring and early warning system and resilience evolution analysis. This model spans three stages: pre-disaster risk evaluation, coordinated emergency response, and post-disaster recovery. Three resilience - enhancing technologies are introduced: grouting reinforcement technology, resilient anchor bolt support technology and high-pressure anchor grouting-spraying collaborative control technology, addressing large deformations in soft coal roadways via restressed support and stress redistribution. Theoretical advancements include a thermodynamic analysis of resilient anchor bolts, demonstrating their strain-energy dissipation mechanisms. The study concludes by advocating for resilience-driven design paradigms over traditional stability-centric approaches, emphasizing adaptive management and AI-enhanced predictive modeling to address evolving climatic and anthropogenic challenges in deep underground engineering. Future work should prioritize standardization of resilience metrics and validation of these technologies in extreme geomechanics environments. Declarations Acknowledgments The author sincerely acknowledges the support by the National Natural Science Foundation of China (42130706, 42207169); Key R & D Program of Xinjiang Uygur Autonomous Region (2021B03004-3), the Natural Science Foundation of Jiangsu Province (BK20221126); China Postdoctoral Science Foundation (2022M710177). Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Declaration of generative AI in scientific writing The authors declare that the AI tools had no role in the data analysis and interpretation in the research process, and were only applied to improve the language and readability of the text. References Anastasopoulos, I., Gazetas, G., Loli, M., et al. (2010). Soil failure can be used for seismic protection of structures. Bulletin of Earthquake Engineering, 8 (2), 309-326. Behnia, M., & Seifabad, M. C. (2018). Stability analysis and optimization of the support system of an underground powerhouse cavern considering rock mass variability. Environmental Earth Sciences, 77 (18), 645. https://doi.org/10.1007/s12665-018-7835-2 Brown, E. T. (2008). Estimating the mechanical properties of rock masses. In Y. Potvin, J. Carter, A. Dyskin, & R. Jeffrey (Eds.), Proceedings of the First Southern Hemisphere International Rock Mechanics Symposium (pp. 3-22). Australian Centre for Geomechanics. Bruneau, M., Chang, S. E., Eguchi, R. T., et al. (2003). A framework to quantitatively assess and enhance the seismic resilience of communities. Earthquake Spectra, 19 (4), 733-752. Bruneau, M., & Reinhorn, A. (2006). Overview of the resilience concept. In Proceedings of the 8th US National Conference on Earthquake Engineering . San Francisco: Curran Associates, Inc. Cai, M. (2011). Rock mass characterization and rock property variability considerations for tunnel and cavern design. Rock Mechanics and Rock Engineering, 44 (4), 379-399. https://doi.org/10.1007/s00603-011-0138-5 Cerfontaine, B., & Collin, F. (2018). Cyclic and fatigue behaviour of rock materials: Review, interpretation and research perspectives. Rock Mechanics and Rock Engineering, 51 , 391-414. https://doi.org/10.1007/s00603-017-1337-5 Zhou, C., Huang, C., Chen, Y., Zhang, W., & Wang, L. (2023). Performance of a novel resistant rock bolt with periodic energy absorption and release: Theory and experiment. Acta Geotechnica . El Tani, M. (2012). Grouting rock fractures with cement grout. Rock Mechanics and Rock Engineering, 45 , 547-561. https://doi.org/10.1007/s00603-012-0235-0 Elmo, D., & Stead, D. (2021). The role of behavioural factors and cognitive biases in rock engineering. Rock Mechanics and Rock Engineering, 54 (5), 2109-2128. https://doi.org/10.1007/s00603-021-02385-3 Fouda, Y. E., & ElKhazendar, D. M. (2023). Achievement of resilience in urbanism: A prototype for a simulative methodology. Alexandria Engineering Journal, 70 , 145-168. Global Commission on Adaptation. (2019). Adapt now: A global call for leadership on climate resilience. Gong, F. Q., Yan, J. Y., Li, X. B., et al. (2019). A peak-strength strain energy storage index for rock burst proneness of rock materials. International Journal of Rock Mechanics and Mining Sciences, 117 , 76-89. Gong, W. P., Khoshnevisan, S., & Juang, C. H. (2014). Gradient-based design robustness measure for robust geotechnical design. Canadian Geotechnical Journal, 51 (11), 1331-1342. Hasan, M., Shang, Y., Shao, P., Yi, X., & Meng, H. (2022). Evaluation of engineering rock mass quality via integration between geophysical and rock mechanical parameters. Journal of Rock Mechanics and Geotechnical Engineering, 15 (1), 1-24. He, M. C., Xie, H. P., Peng, S. P., et al. (2005). Study on rock mechanics in deep mining engineering. Chinese Journal of Rock Mechanics and Engineering, 24 (16), 2803-2813+11-12. Holling, C. S. (1973). Resilience and stability of ecological systems. Annual Review of Ecology and Systematics, 4 (1), 1-23. Hu, X. L., Zhou, C., Xu, C., et al. (2019). Model tests of the response of landslide-stabilizing piles to piles with different stiffness. Landslides, 16 , 2187-2200. Hua, W., Li, J., Dong, S., & Pan, X. (2019). Experimental study on mixed mode fracture behavior of sandstone under water–rock interactions. Processes, 7 (2), 70. https://doi.org/10.3390/pr7020070 Huang, H. W., & Zhang, D. M. (2016). Resilience analysis of shield tunnel lining under extreme surcharge: Characterization and field application. Tunnelling and Underground Space Technology, 51 , 301-312. Hudson, J., & Harrison, J. (1997). Engineering rock mechanics—an introduction to the principles (1st ed.). Elsevier, Amsterdam. Jin, L., & Sui, W. (2021). Experimental investigation on chemical grouting in rough 2D fracture network with flowing water. Bulletin of Engineering Geology and the Environment, 80 , 8519-8533. Joint TC205/TC304 Working Group. (2017). Discussion of statistical/reliability methods for Eurocodes final report. In Proceedings of the 5th International Symposium on Geotechnical Safety and Risk . Rotterdam: International Society for Soil Mechanics and Geotechnical Engineering. Juang, C. H., Wang, L., Liu, Z. F., et al. (2013). Robust geotechnical design of drilled shafts in sand: New design perspective. Journal of Geotechnical and Geoenvironmental Engineering, 139 (12), 2007-2019. Kang, H., Jiang, P., Huang, B., et al. (2020). Roadway strata control technology by means of bolting-modification-destressing in synergy in 1,000 m deep coal mines. Journal of China Coal Society, 45 (3), 845-864. https://doi.org/10.13225/j.cnki.jccs.SJ20.0204 Kang, H., Li, W., Gao, F., & Yang, J. (2022). Grouting theories and technologies for the reinforcement of fractured rocks surrounding deep roadways. Deep Underground Science and Engineering , 1-18. https://doi.org/10.1002/dug2.12026 Khoshnevisan, S., Gong, W. P., & Juang, C. H. (2015). Efficient robust geotechnical design of drilled shafts in clay using a spreadsheet. Journal of Geotechnical and Geoenvironmental Engineering, 141 (2), 04014092. Kong, D., Saroglou, C., Wu, F., Sha, P., & Li, B. (2021). Development and application of UAV-SfM photogrammetry for quantitative characterization of rock mass discontinuities. International Journal of Rock Mechanics and Mining Sciences, 141 , 104729. Kong, D., Wu, F., & Saroglou, C. (2020). Automatic identification and characterization of discontinuities in rock masses from 3D point clouds. Engineering Geology, 265 , 105442. Kuang, Z., Qiu, S., Li, S., Du, S., Huang, Y., & Chen, X. (2021). A new rock brittleness index based on the characteristics of complete stress–strain behaviors. Rock Mechanics and Rock Engineering, 54 (3), 1109-1128. Hasan, M., Shang, Y., Shao, P., Yi, X., & Meng, H. (2022). Evaluation of engineering rock mass quality via integration between geophysical and rock mechanical parameters. Journal of Rock Mechanics and Geotechnical Engineering, 15 (1), 1-24. Lee, M., & Basu, D. (2018). An integrated approach for resilience and sustainability in geotechnical engineering. Indian Geotechnical Journal, 48 (2), 207-234. https://doi.org/10.1007/s40098-018-0297-3 Li, X. M., Liu, C. Y., Syd, S. P., & Lu, Y. (2017). Fatigue deformation characteristics and damage model of sandstone subjected to uniaxial step cyclic loading. Journal of China University of Mining and Technology, 46 (1), 8-18. Liu, X. M., Li, D. Q., Ma, M. Q., Szymanski, B. K., Stanley, H. E., & Gao, J. X. (2022). Network resilience. Physics Reports, 971 , 1-108. Liu, X., & Yang, X. (2020). A numerical solution of a circular tunnel in a confining pressure-dependent strain-softening rock mass. Scientific Reports, 10 , 1369. https://doi.org/10.1038/s41598-020-58331-3 Liu, Y., Wang, Y., Zhong, Z., Li, Q., & Zuo, Y. (2023). Constitutive model for grouted rock mass by macro-meso damage. Materials, 16 (13), 4859. https://doi.org/10.3390/ma16134859 Lu, X., Chen, Y., & Mao, Y. (2011). New concept of structural seismic design: Earthquake resilient structures. Journal of Tongji University: Natural Science, 39 (7), 941-948. (in Chinese) Lv, X., Quan, L., & Jiang, H. (2017). Research trend of earthquake resilient structures seen from 16WCEE. Earthquake Engineering and Engineering Dynamics, 37 (3), 1-9. (in Chinese) Mohanty, A., Ramasamy, A. K., Verayiah, R., Bastia, S., Dash, S. S., Cuce, E., Khan, T. M. Y., & Soudagar, M. E. M. (2024). Power system resilience and strategies for a sustainable infrastructure: A review. Alexandria Engineering Journal, 105 , 261-279. Peer. (2010). Report of the seventh joint planning meeting of NEES/E-defense collaborative research on earthquake engineering. Berkeley: University of California. Peng, X., Li, D. Q., Cao, Z. J., et al. (2017). Reliability-based robust geotechnical design using Monte Carlo simulation. Bulletin of Engineering Geology and the Environment, 76 (3), 1217-1227. Pierce, M., Cundall, P., Potyondy, D., & Mas Ivars, D. (2011). The synthetic rock mass approach for jointed rock mass modelling. International Journal of Rock Mechanics and Mining Sciences, 48 (2), 219-244. Shadabfar, M., Mahsuli, M., Zhang, Y., et al. (2022). Resilience-based design of infrastructure: Review of models, methodologies, and computational tools. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 8 (1), 03121004. Sui, W. H. (2022a). Catastrophic mechanism of seepage deformation and failure of mining rock mass and its prevention & control I: Water-sand mixture inrush from seam roof. Journal of Earth Sciences and Environment, 4 (6), 000-000. Sui, W. H. (2022b). Active prevention and control of water-sand mixture inrush with high potential energy due to mining based on structural hydrogeology. Journal of Engineering Geology, 30 (1), 101-109. Sui, W. H. (2023). Evaluation method of resistance to seepage failure due to mining near unconsolidated aquifers I: Critical hydraulic gradient. Coal Geology & Exploration, 51 (2), 175-186. https://doi.org/10.12363/issn.1001-1986.22.11.0902 Tellman, B., Sullivan, J. A., Kuhn, C., et al. (2021). Satellite imaging reveals increased proportion of population exposed to floods. Nature, 596 , 80-86. https://doi.org/10.1038/s41586-021-03695-w Wang, G., Wang, Y., Yu, H., et al. (2021). Shaking table tests on seismic response of rocking frame structure considering foundation uplift. Chinese Journal of Geotechnical Engineering, 43 (11), 2064-2074. (in Chinese) Wang, M., Li, Z., Xia, E., Li, Z., Zou, Y., Wei, S., Wang, X., & Yang, D. (2022). Energy dissipation and supporting regulation effect of surrounding rock in deep roadway. Journal of Mining and Safety Engineering, 39 (4), 741-749. https://doi.org/10.13545/j.cnki.jmse.2021.0479 Wang, Y., Yang, P., Li, Z., Wu, S., & Zhao, Z. (2023). Study on fatigue failure characteristics and energy evolution mechanism of fractured rock under graded cyclic loading. KSCE Journal of Civil Engineering, 27 (4), 1157-1165. https://doi.org/10.1007/s12205-023-0657-0 Wang, F., Zhang, J., Qin, X., Yuan, C., Meng, X., & Zhang, H. (2024). Diffusion mechanism of fracture grouting in rock mass with flowing water. Alexandria Engineering Journal, 105 , 44-55. Ward, P., Jongman, B., Salamon, P., et al. (2015). Usefulness and limitations of global flood risk models. Nature Climate Change, 5 , 712-715. https://doi.org/10.1038/nclimate2742 Wu, B., & Ou, Y. (2014). Experimental study on tunnel lining joints temporarily strengthened by SMA bolts. Smart Materials and Structures, 23 (12), 125018. Wu, W. P., Feng, X. T., Zhang, C. Q., & Qiu, S. L. (2011). Classification of failure modes and controlling measures for surrounding rock of deep tunnel in hazard rock. Chinese Journal of Rock Mechanics and Engineering, 30 (9), 1872-1892. Wu, F., Wu, J., Bao, H., Li, B., Shan, Z., & Kong, D. (2021). Advances in statistical mechanics of rock masses and its engineering applications. Journal of Rock Mechanics and Geotechnical Engineering, 15 (1), 1-24. Xie, H. (2019). Research review of the state key research development program of China: Deep rock mechanics and mining theory. Journal of China Coal Society, 44 (5), 1283-1305. https://doi.org/10.13225/j.cnki.jccs.2019.6038 Xie, H. P., Ju, Y., & Li, L. Y. (2005). Criteria for strength and structural failure of rocks based on energy dissipation and energy release principles. Chinese Journal of Rock Mechanics and Engineering, 24 (17), 3003-3010. Yan, W. T., & Li, Z. H. (2023). Study on the resilience mechanism of urban spatial structure from the view of risk disturbance: Theoretical framework and empirical methodology. Urban Planning International, 28 (4), 1-12. Yao, J., Jiang, N., Yao, Y., Zhou, C., & Yang, Y. (2024). Instability mechanism of layered surrounding rock tunnels affected by layer thickness under dynamic and static loads. Alexandria Engineering Journal, 105 , 471-484. Ying, C., Hu, X., Zhou, C., et al. (2021). Analysis of chemo-mechanical behavior of silty soil under long-term immersion in saline reservoir water. Bulletin of Engineering Geology and the Environment, 80 (1), 627-640. Ying, C., Zhang, K., Wang, Z. N., et al. (2021). Analysis of the run-out processes of the Xinlu Village landslide using the generalized interpolation material point method. Landslides, 18 (4), 1519-1529. Zhang, D. M., Zhai, W. Z., Huang, H. W., et al. (2019). Robust retrofitting design for rehabilitation of segmental tunnel linings: Using the example of steel plates. Tunnelling and Underground Space Technology, 83 , 231-242. Zhang, G. (2022). Mechanism of deflection propagation for grouting in fractured rock mass with flowing water and mining effect on grouted curtain: A review. Journal of Engineering Geology, 30 (3), 987-997. https://doi.org/10.13544/j.cnki.jeg.2022-0091 Zhang, J., Shu, J., Ren, X., & Ren, H. (2013). Influence mechanism of grouting on mechanical characteristics of rock mass. Mathematical Problems in Engineering, 2013 , 281817. https://doi.org/10.1155/2013/281817 Zhao, K., Yu, X., Zhou, Y., et al. (2020). Energy evolution of brittle granite under different loading rates. International Journal of Rock Mechanics and Mining Sciences, 132 , 104392. Zhao, G., Liu, Z., Meng, X., Zhang, R., Gu, Q., & Qi, M. (2023). Energy evolution of sandstone under true triaxial cyclic principal stress. Rock and Soil Mechanics, 44 (7), 1875-1890. https://doi.org/10.16285/j.rsm.2023.1757 Zheng, G., Cheng, X. S., Zhou, H. Z., Zhang, T. Q., Yu, X. X., Diao, Y., Wang, R. Z., Yi, F., Zhang, W. B., & Guo, W. (2022). Resilient evaluation and control in geotechnical and underground engineering. China Civil Engineering Journal, 55 (7), 1-38. Zheng, G. (2022). Method and application of deformation control of excavations in soft ground. Chinese Journal of Geotechnical Engineering, 44 (1), 1-36. (in Chinese) Zheng, G. S., Sui, W. H., Zhang, G. L., Chen, J. X., & Zhang, D. Y. (2023). Propagation and sealing efficiency of chemical grouting in a two-dimensional fracture network with flowing water. International Journal of Mining Science and Technology, 33 (7), 903-917. Zhong, Z., Deng, R., Zhang, J., & Hu, X. (2020). Fracture properties of jointed rock infilled with mortar under uniaxial compression. Engineering Fracture Mechanics, 228 , 106822. https://doi.org/10.1016/j.engfracmech.2019.106822 Zhou, C., Hu, Y. J., Xiao, T., et al. (2023a). Analytical model for reinforcement effect and load transfer of pre-stressed anchor cable with bore deviation. Construction and Building Materials, 379 (5), 131219. https://doi.org/10.1016/j.conbuildmat.2023.131219 Zhou, C., Huang, C., Chen, Y. D., et al. (2023b). Development of a novel resilient anchor cable and its large shear deformation performance. International Journal of Rock Mechanics and Mining Sciences, 163 , 105293. Zhou, C., Ma, W. C., & Sui, W. H. (2022). Transparent soil model test of a landslide with umbrella-shaped anchors and different slope angles in response to rapid drawdown. Engineering Geology, 307 (4), 1-14. Zhu, G. (2011). A three-dimensional rock block system of complex rock mass based on hierarchical rock mass structure model. Chinese Journal of Rock Mechanics and Engineering, 30 (5), 895-906. Zhu, Z., Yang, S., Ranjith, P. G., Tian, W., Tian, H., Zheng, J., Jiang, G., & Dou, B. (2023). A comprehensive review on mechanical responses of granite in enhanced geothermal systems (EGSs). Journal of Cleaner Production, 383 , 135378. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 26 May, 2025 Read the published version in Geoenvironmental Disasters → Version 1 posted Editorial decision: Accepted 06 May, 2025 Reviews received at journal 04 May, 2025 Reviews received at journal 27 Apr, 2025 Reviewers agreed at journal 27 Apr, 2025 Reviewers agreed at journal 27 Apr, 2025 Reviewers agreed at journal 22 Apr, 2025 Reviewers invited by journal 22 Apr, 2025 Submission checks completed at journal 14 Apr, 2025 First submitted to journal 11 Apr, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5483583","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":446451103,"identity":"13b80862-1253-4d85-961e-19f2ab9d9536","order_by":0,"name":"Zhou Chang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4klEQVRIiWNgGAWjYDACCTB5gIGBvQEqcoBoLTwgpQkkaZFIIFIL/+zmZw+//LkjZ3Dz8TOpmz8Y5PhuJDB+LsBnyZ1j5sYyPM+MDW6nmUnnJDAYS95IYJaegUeLgUSCmbSExOHEDbdz2EBaEjfcSGBj5sGrJf2btIQBUMvNM2At9URoyTGT/JAA1HKDB6wlwYCQFokbOWXSDAcOG0ueSTO2zkmTMJx55mGzND4t/DPSt0n++HNYju/44Ye3c2xs5PmOJx/8jE8LCCA7AxRNjA0ENACV/CCoZBSMglEwCkY0AAAImkw7kZeJ/gAAAABJRU5ErkJggg==","orcid":"","institution":"China University of Mining and Technology","correspondingAuthor":true,"prefix":"","firstName":"Zhou","middleName":"","lastName":"Chang","suffix":""},{"id":446451104,"identity":"3f3ccdcc-b11e-4054-8aa0-051aeb149711","order_by":1,"name":"Han Chunni","email":"","orcid":"","institution":"China University of Mining and Technology","correspondingAuthor":false,"prefix":"","firstName":"Han","middleName":"","lastName":"Chunni","suffix":""},{"id":446451105,"identity":"2cdb5e5b-0a7f-45fb-9c2c-9e1cba7d023f","order_by":2,"name":"Sui Wanghua","email":"","orcid":"","institution":"China University of Mining and Technology","correspondingAuthor":false,"prefix":"","firstName":"Sui","middleName":"","lastName":"Wanghua","suffix":""}],"badges":[],"createdAt":"2024-11-19 12:38:25","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5483583/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5483583/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s40677-025-00325-9","type":"published","date":"2025-05-26T15:57:02+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":81202698,"identity":"67c0741d-0039-4ae9-8d24-cfb389886e8a","added_by":"auto","created_at":"2025-04-23 11:36:28","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":216354,"visible":true,"origin":"","legend":"\u003cp\u003eSummary of methodological approach and analysis of existing literature on resilience in geotechnical engineering\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-5483583/v1/cdbf9d3360d309ddd423175c.png"},{"id":81202661,"identity":"c6252990-d6fa-45d4-b0b8-85920fe5a423","added_by":"auto","created_at":"2025-04-23 11:36:19","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":259303,"visible":true,"origin":"","legend":"\u003cp\u003eCo-occurrence network of keyword\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-5483583/v1/1edbcc4b54b83dcc34f9515f.png"},{"id":81202667,"identity":"214619de-90ae-4d86-a97b-db3fb37e6e9e","added_by":"auto","created_at":"2025-04-23 11:36:19","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":356868,"visible":true,"origin":"","legend":"\u003cp\u003eAnalysis framework of rock engineering resilient mechanism\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-5483583/v1/13425b71dd6b09cf65602c39.png"},{"id":81202663,"identity":"88f24ed2-501f-4f50-be8a-1205af543651","added_by":"auto","created_at":"2025-04-23 11:36:19","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":605399,"visible":true,"origin":"","legend":"\u003cp\u003eComposite space network of grouting rock mass and structure system (Revised from Sui et al., 2023, Zhang et al., 2019, )\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-5483583/v1/2a1bd9c70caefb395edc7807.png"},{"id":81202665,"identity":"c0392a41-7a38-4ad3-8d8e-31d01a77fc15","added_by":"auto","created_at":"2025-04-23 11:36:19","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":337336,"visible":true,"origin":"","legend":"\u003cp\u003eDynamic evolution process of rock mass engineering under disturbance. UA zone: unaffected zone, SR zone: zone, PF zone: physical failure zone; PFT zone: Potential field transformation zone; RFM zone: related failure mechanisms. SG value: stress generation value.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-5483583/v1/08449cabb40a5593063a5d34.png"},{"id":81203486,"identity":"ac32baf2-e6b8-4fdd-8200-8bd007cc8883","added_by":"auto","created_at":"2025-04-23 11:44:20","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":492587,"visible":true,"origin":"","legend":"\u003cp\u003eResilience governance model of rock engineering\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-5483583/v1/425ea3426561d20e1d7dce60.png"},{"id":81203669,"identity":"1edbc1b5-cda0-4a9e-8a7d-4d9b103c712c","added_by":"auto","created_at":"2025-04-23 11:52:19","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":328706,"visible":true,"origin":"","legend":"\u003cp\u003eResilience performance level curve of rock engineering system. a) Deformation evolution curve of slope engineering system; b) Resilience reinforcement and traditional reinforcement design (Revised from Shadabfar et al., 2022); c) Performance level curve of rock engineering system after reinforcement repair during disturbance and after disaster recovery; d) shape-memory polymer grouts reinforcement increases recovery rates.\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-5483583/v1/05e3d8f8dcc925d2841838c4.png"},{"id":81202674,"identity":"6703f5ef-a2d8-4d1e-a01f-935232e3cabb","added_by":"auto","created_at":"2025-04-23 11:36:19","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":317683,"visible":true,"origin":"","legend":"\u003cp\u003ea) Working principle of resilient rock bolt; b) axial force of the resilient rock bolt versus displacement; c) the axial force of the resilient rock bolt under shear large deformation. (Revised from Zhou et al., 2023)\u003c/p\u003e","description":"","filename":"floatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-5483583/v1/565cb2a81b4e909d82558ccb.png"},{"id":81202689,"identity":"a42fe4d6-52fb-4395-86be-85721e68db88","added_by":"auto","created_at":"2025-04-23 11:36:20","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":357290,"visible":true,"origin":"","legend":"\u003cp\u003ea) Tunnel grouting reinforcement for water burst (revised from Sui., 2022); b) Stress-strain curves of grouting rock mass with different grouting thickness; c) the curve of rock mass performance under grouting repair: with the increase of rock mass damage, the thickness of slurry will gradually increase, so \u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;E\u003csub\u003e1\u003c/sub\u003e\u0026gt;E\u003csub\u003e2\u003c/sub\u003e\u0026gt;E\u003csub\u003e3\u003c/sub\u003e\u0026gt;E\u003csub\u003e4\u003c/sub\u003e, and its deformation resistance is also increasing.\u003c/p\u003e","description":"","filename":"floatimage9.png","url":"https://assets-eu.researchsquare.com/files/rs-5483583/v1/4513e5e0fb97b4dbb480aeb8.png"},{"id":81202679,"identity":"a2b43470-4b3e-4d8e-aa78-c335fcb5b15a","added_by":"auto","created_at":"2025-04-23 11:36:20","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":406649,"visible":true,"origin":"","legend":"\u003cp\u003eEnergy evolution of the rock and rock with bolt during cyclic loading and unloading. a) rock with cyclic and uniaxial compression; b) energy of sandstone and c-d) sandstone with rock bolt versus cycles. The subgraph represents its constitutive model. The rock uses the generalized Kelvin model, and the constitutive model of the resilient anchor rod is adopted from Zhou et al., (2023c).\u003c/p\u003e","description":"","filename":"floatimage10.png","url":"https://assets-eu.researchsquare.com/files/rs-5483583/v1/2583d9a9d17d653346b5763b.png"},{"id":83782783,"identity":"6f5a2de6-a5ed-4532-9e35-820808f8cf8d","added_by":"auto","created_at":"2025-06-02 16:05:09","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4522251,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5483583/v1/a646aaa3-d679-48ff-abf8-f900856b2e05.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Resilience of Rock Engineering: Concept, Mechanism, Evaluation and Enhancement","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eRock engineering systems, characterized by complex rock -engineering structure interactions, face escalating challenges from the compounding effect of global climate change and the intensifying demands of deep engineering development (Xie et al., 2019; Tellman et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Ward et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; He et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). The inherent uncertainty and fragility of rock engineering systems are significantly exacerbated by Natural (e.g., earthquakes, climate change) and anthropogenic disturbances (e.g., mining, tunneling) amplify systemic fragility by inducing spatiotemporal alterations in rock mass structure, stress regimes, and hydraulic conditions. (Hu et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Ying et al., \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Sui et al., 2022b,2023; Zhou et al., \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). These disturbances induce a series of complex changes in rock mass. These include temporal, spatial, stress, hydrological changes to the rock\u0026rsquo;s structure and mechanical properties (Cerfontaine et al., 2018; Ying et al., \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Zhu et al., 2022). The far-reaching impact of these changes on engineering structure and their functional performance are substantial. For example, the time-dependent propagation of fractures in the rock mass causes the progressive deformation and failure of tunnel linings as well as large-scale deformation in roadways. Meanwhile, variation in hydrological conditions may result in water inrush and sand production, which can completely bury roadways (Sui et al., 2022a). These catastrophic events lead to severe consequences, including the loss of human life and significant property damage. Consequently, it is both urgent and essential to conduct a thorough evaluation of the resilience of rock engineering. This evaluation primarily focuses on the system\u0026rsquo;s capacity to maintain its functionality during disturbances or to rapidly recover it afterward. (Kuang et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Zhou et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe concept of resilience was firstly proposed by Holling in 1973 to characterize the adaptive capacity of ecosystems in response to external disturbances (Holling \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e1973\u003c/span\u003e; Liu et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Mohanty et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Fouda et al., 2023). Subsequently, this concept has been widely adopted in various fields, such as urban planning, transportation, water resources engineering. The aim is to accurately assess and improve the resistance and recovery capacity of these systems in the event of disasters (Bruneau et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2003\u003c/span\u003e, 2006; Yan et al., 2023). However, in the field of rock engineering, the practical application of the resilience concept is still in its infancy (Shadabfar et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). By integrating the concept of resilience, we can gain a more comprehensive and dynamic understanding of the challenges in discontinuous rock engineering. This view goes beyond to traditional focus on static stability and reliability, and also takes into account the crucial aspects of dynamic recoverability and adaptability.\u003c/p\u003e \u003cp\u003eThe resilience of rock engineering, characterized by the complex interactions between rock and engineering systems, has received relatively theoretical attention. Current research mainly revolves around two critical aspects: robust design and the post-disaster recoverability of rock engineering. Robust design involves optimizing the structural design of rock engineering system under parameter uncertainty. By minimizing their sensitivity to uncertain parameters, it substantially enhances the systems\u0026rsquo; adaptability to unforeseen events (Joint TC205/TC304 Working Group, 2017). There are diverse robust design methods, such as those based on failure probability standard deviation, gradient, functional function variability, Monte-Carlo weighting technique (Juang et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Gong et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Khoshnevisan et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Peng et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). This approach has been applied and validated in multiple fields, including retaining walls, shield tunnels, shallow foundations, bored pile (Zhang et al., \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). However, existing robust design methodologies primarily focus on preventing localized failures and optimizing structural design. Resilience-oriented design strategies have significant limitations in dealing with progressive damage accumulation and dynamic instability mechanism caused by long-term disturbances (Zheng et al., \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). For example, reservoir operations can lead to stepwise landslide deformation, and deep underground roadways may experience cyclic stress redistribution combined with dynamic load superposition under mining disturbances. These continuous perturbations push the structural systems towards gradual failure. This gap between theory and practice highlights the shortcomings of current methods in analyzing the long-term evolutionary processes of rock engineering systems, especially their inability to effectively control continuous instability processes or limit the propagation of failure zone. Post-disaster recoverability research focuses on using recoverable structures or advanced technologies to repair or replace the original rigid structures/connections in rock engineering. This goal is to restore the functionality of the rock engineering structure after a disaster (Anastasopoulos et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Commonly used recoverable structures include rocking structures, self-resetting structures, replaceable structures, and those made of shape memory alloy material (Lu et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Wang et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Wu et al., 2014; Zhou et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Considering the complex geological structures in rock engineering, especially in deep underground projects like tunnels and roadways, post-disaster repair is extremely challenging. Damage can include water inrush and sand production due to mining activities, roof failures, and tunnel deformations, settlements, faulting, and even collapse triggered by seismic events. Therefore, rapid recovery after significant deformations or catastrophic collapses is of utmost importance in rock engineering (Zhou et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2023\u003c/span\u003ea). Unfortunately, the current research in rock engineering lacks essential key technologies and theoretical guidance. Nevertheless, some successful cases exist. Huang et al. (2016) effectively used grouting techniques to quickly repair severely deformed tunnels, greatly improving the recovery rate and overall tunnel resilience. Moreover, Zheng (\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) proposed an innovative approach, the capsule mine leader active control technology to actively and promptly address tunnel deformations.\u003c/p\u003e \u003cp\u003eThe theory and methodology of rock engineering resilience represent an emerging and highly promising research field. This field aims to bolster the resistance and recovery capacities of rock engineering systems when confronted with various disturbances and disasters. It plays a crucial role in protecting human live, property, as well as promoting social and economic development. However, the current research on rock engineering resilience still grapples with numerous deficiencies and challenges. These include as the need for clearer conceptual clarification, the development of appropriate resilience indicators, the establishment of effective evaluation methods, the formulation of resilience-based design and optimization strategies, and the innovations of resilience-enhancing structures and technologies. According to the mechanical properties and failure modes of discontinuous rock mass, this paper undertakes a comprehensive review of resilience concepts applicable to geotechnical engineering. It synthesizes key concepts related to rock engineering resilience and constructs a comprehensive framework for mechanism analysis and governance model for rock engineering resilience, taking into account the dynamic evolution process. Moreover, this paper proposes reinforcement methods according to the characteristics of rock engineering at different stages-before, during and after disturbances. It also briefly introduces three key technologies for enhancing rock engineering resilience. Furthermore, it introduces the theory of rock engineering resilience support.\u003c/p\u003e"},{"header":"2. Literature review of resilience suitable for geotechnical engineering","content":"\u003cp\u003eThe resilience of geotechnical engineering is a novel and interdisciplinary topic that encompasses engineering, geology and system science. This review focuses on resilience studies within geotechnical engineering felid. To conduct the literature search, we utilized databases such as Web of Science (WoS), Scopus, and Google Scholar. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e provides a detailed account of the methodology employed for selecting relevant publications. In total, 93 publications, spanning from 1935 to 2024, were reviewed (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). We analyzed the temporal distribution of these literatures and keyword co-occurrence related to resilience in geotechnical engineering. The first relevant literature was published in 2011, with a significant increase in the number of publications starting from 2015. By 2024, the number of publications reached 18, and these publications had approximately 308 citations. Regarding the geographic distribution of these publications, 42.5% originated from Asia, Europe and Australia followed, each contributing 18\u0026ndash;19%.\u003c/p\u003e \u003cp\u003eThe five journals with the highest number of publications on this topic are the Soil Dynamic Earthquake Engineering, Journal of Geotechnical and Geoenvironmental Engineering, Bulletin of Earthquake Engineering, Natural Hazards, Engineering Geology, Frontiers in Earth Science. Among them, Soil Dynamic Earthquake Engineering has published 19 articles, accounting for 20.43% of the total, higher than other journals. These journals have a long-standing reputation and wield significant academic influence. An analysis of their topic and keywords of those publication finds that the proportion of papers with the theme of \"earthquake\" and \u0026ldquo;seismic\u0026rdquo; exceeded 40%, indicating that current publications mainly focus on earthquake-related research. It is further corroborated by keyword co-occurrence analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). In analysis, the nodes \"Earthquake,\" \"Landslides,\" and \"Simulation\" are closely interconnected, forming a distinct cluster. Meanwhile, \"Risk Management\" forms another cluster with \"Model,\" \"Performance,\" and \"Resilience,\" suggesting that model performance and system resilience are key topics in risk management studies.\u003c/p\u003e \u003cp\u003eThe keywords co-occurrence also reveals that current research topics are primarily concentrated on soil mechanisms (especially related to sand), engineering behavior, and geotechnical engineering. The strong association between \"Geotechnical Engineering\" and \"Risk Management\" suggests that risk management is a crucial research avenue within geotechnical engineering. Furthermore, the connection between \"Resilience\" and \"Sustainability\" points to a close relationship in research, possibly involving studies into system durability and environmental adaptability. The density of nodes and connection lines in the analysis reflects a strong focus on resilience and sustainability research in the environment and engineering fields in recent years. Thus, resilience in geotechnical engineering has emerged as a prominent research topic and is expected to continue attracting attention, especially in the context of extreme climate and the pursuit of sustainable development.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"3. Resilience of rock engineering","content":"\u003cp\u003eTo ensure the long-term safety and stability of engineering projects, it is essential to effectively reinforce fractured rock mass, which form the foundation of rock engineering. Commonly used reinforcement methods, such as rock bolts/cables, anti-slide piles, concrete structures, and grouting transformation methods, are classic approaches for dealing with rock mass failure. However, under complex geological dynamic conditions, these methods may encounter difficulties in effectively preventing or recovering rock mass failure. This is particularly true when the rock mass experiences great deformations or catastrophic collapses due to severe disturbances. Therefore, there is an urgent need to develop innovative methods and technologies to further enhance the resilience of rock engineering. In this paper, Resilience is defined as the system\u0026rsquo;s capacity to either maintain its function or quickly recover it after being subjected to disturbances.\u003c/p\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Resilience concept of rock engineering\u003c/h2\u003e \u003cp\u003eBruneau et al. (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2003\u003c/span\u003e) was the first to introduce the concept of recoverability into civil engineering. They proposed a conceptual framework of seismic resilience and pioneered the application of resilience enhancement theory in this field. With the development of engineering technology and economy, this resilience focused approach has gradually made its way into geotechnical engineering.\u003c/p\u003e \u003cp\u003eAs underground engineering ventures deeper, the complexity of the geological, ecological and engineering environment has increased significantly. Consequently, rock engineering is confronted with higher requirements and daunting challenges. The concept of resilience in rock engineering can be derived from seismic resilience theory. This theory defines resilience in four dimensions, characterized by four evaluation indicators and three critical features. In the context of rock engineering, resilience refers to the system\u0026rsquo;s innate capacity of the system to adjust its function before, during, or after various disturbances. This adaptability enables the system to maintain its engineering performance under both expected and unexpected disturbance conditions. Robustness is used to evaluate the system\u0026rsquo;s reliability prior to a disaster. Resourcefulness and redundancy are crucial for assessing the system\u0026rsquo;s post-disaster recover ability. Rapidity measures the efficiency of post-disaster recovery. The theory of enhancing rock engineering resilience measures to adjust the system\u0026rsquo;s function at different stages of disturbances. These measures greatly improve the system\u0026rsquo;s capacity to maintain engineering performance even in the face of challenging disturbance scenarios (Peer \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; lv et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Resilience mechanism analysis framework of rock engineering\u003c/h2\u003e \u003cp\u003eIn the rock engineering system, rock engineering structures, disturbance and engineering performance are three elements that are intricately interrelated, interdependent and mutually constrained. Together, they form the dynamic evolution process of rock engineering system. Therefore, to enhance the resilience and sustainability of the rock engineering system, research must comprehensively consider the interaction mechanism among rock engineering structure, disturbance and engineering performance from a holistic perspective throughout the entire life cycle of the system. This paper integrates three elements: disturbance, rock engineering structure and engineering performance, into a comprehensive analysis framework. It clarifies the interaction mechanism among disturbance, rock mass and engineering structure. Specially, it examines the dynamic change in functional robustness. By analyzing the evolution of geological structure and its strength, engineering support resistance, and deformation under disturbance, the paper identifies the inherent dynamic changes and threshold in rock engineering, and reveals the resilience evolution mechanism of rock engineering.\u003c/p\u003e \u003cp\u003e(1) The impact of disturbance on the rock engineering system\u003c/p\u003e \u003cp\u003eThe spatial framework of rock engineering consists of geological structures, stratum lithology, stress, hydrological features, and others. The functional integrity of this system is controlled by the coordination effect between the geological structural plane network and engineering structures (such as anchor bolts, grouting bodies). Disturbance loads, from engineering activities, disasters impact, geological time-varying effect, change the state of rock mass. According to their mechanisms for rock function degradation, these disturbances can be classified into three types: elastic action (disturbance load\u0026thinsp;\u0026lt;\u0026thinsp;elastic limit load, the rock deforms reversibly without any loss of functional), plastic action (elastic limit load\u0026thinsp;\u0026lt;\u0026thinsp;disturbance load\u0026thinsp;\u0026lt;\u0026thinsp;yield limit load, the irreversible deformation of the rock causes functional degradation), and critical action (disturbance load\u0026thinsp;\u0026gt;\u0026thinsp;yield limit, local functional loss triggers rock failure). Considering the effect of the rock structural planes, rock mass failure under disturbances can be divided into three types: 1) Physical failure, where the disturbance directly causes physical damage on the rock (equivalent to critical action). This results in the loss of function of system nodes, which are the points where components of the rock mass engineering interact. However, it does not affect the overall system function. 2) Related failure, because of the interactions within the system\u0026rsquo;s networks, the loss or improvement of the function of local network and nodes can impact the function of other parts of the network (Yan et al., 2023). For example, an anchor bolt failure can lead to the instability of the rock block it supports. 3) Potential field transformation, where the disturbances can modify the original stress-strain field of the rock mass. This transformation leads to significant changes in the interaction relationships between networks. For example, a disturbance that causes side-wall failure in a roadway leads to the formation of a new stress arch in the surrounding rock, creating a new stable system. In other words, local physical damage causes stress and energy transfer. These three action mechanisms are involved in an interactive dynamic process. They transforms the rock engineering system, and affects its structural and mechanical properties (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e(2) Dynamic evolution of rock engineering spatial structure under disturbance\u003c/p\u003e \u003cp\u003eRock engineering is a complex system with a spatial structure defined by stratum lithology, geological structures, and engineering components. Stratum lithology is fundamental as it determines the physical properties and spatial distribution of rock masses, forming the cornerstone of the rock engineering spatial structure. The geological structure, conversely, acts as the controlling elements. They mirror the complex processes of rock mass formation, deformation, and failure, which introduce heterogeneity and discontinuity into the rock mass. These characteristics increase the complexity and uncertainty of the rock engineering system. Engineering structures involve critical operations such as excavation, support, and reinforcement of rock masses. These activities are integral to the complex rock engineering system. As these engineering interventions are carried out, they dynamically modify the structure and stress state of the rock mass. The interplay among stratum lithology, geological structure, and engineering interventions shapes the overall structure and stress distribution of rock engineering projects, ultimately exerting significant influences on their stability and safety. Zhu (\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) proposed the hierarchical rock mass structure model. This three-dimensional modeling approach classifies the structural planes within the rock mass into deterministic structural planes (e.g., faults, stratum interfaces, and ground surfaces) and random structural planes. Using a hierarchical modeling method, this model constructs a three-dimensional representation that captures the internal structural features of the rock mass, providing a geometric basis for stability analysis. Then, we have developed a three-dimensional spatial system for complex rock engineering. Firstly, based on stratum lithology, the stratum is abstracted as a spatial set \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{R}_{S}=\\left\\{{R}_{1},{R}_{2},\\cdots\\:,{R}_{n}\\right\\}\\)\u003c/span\u003e\u003c/span\u003e. Definite interface such as structural planes, engineering interfaces, ground surfaces and other definite interfaces abstracted as a three-dimensional planar set\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{P}_{S}=\\left\\{{P}_{1},{P}_{2},\\cdots\\:,{P}_{n}\\right\\}\\)\u003c/span\u003e\u003c/span\u003e. The anchor bolt structure is abstracted as a line set \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{L}_{S}=\\left\\{{L}_{1},{L}_{2},\\cdots\\:,{L}_{n}\\right\\}\\)\u003c/span\u003e\u003c/span\u003e, and the underground hydrological system is abstracted as a spatial set \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{W}_{S}=\\left\\{{W}_{1},{W}_{2},\\cdots\\:,{W}_{n}\\right\\}\\)\u003c/span\u003e\u003c/span\u003e. Grouting reinforcement involves injecting grouting material into the structural plane spaces such as structural fissures, layers, effectively filling the interface. This is abstracted as \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{{P}_{S}}^{\\prime }=\\left\\{{{P}_{1}}^{\\prime },{{P}_{2}}^{\\prime },\\cdots\\:,{{P}_{n}}^{\\prime }\\right\\}\\)\u003c/span\u003e\u003c/span\u003e. The degree of overlap between the interface \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{P}_{i}\\)\u003c/span\u003e\u003c/span\u003e and the grouting reinforcement \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{{P}_{i}}^{\\prime }\\)\u003c/span\u003e\u003c/span\u003e is used as the integrity weight of the grouting rock mass, and an integrity matrix \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\left\\{{l}_{i}\\right\\}\\)\u003c/span\u003e\u003c/span\u003e is constructed. These networks are superimposed to form a composite spatial network of the grouting rock mass-structure system \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\text{G}=({R}_{S}\\cup\\:{P}_{S}\\cup\\:{L}_{1}\\cup\\:{{P}_{1}}^{\\prime })\\)\u003c/span\u003e\u003c/span\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Stratum information, rock mass structure and grouting effect can be obtained through field tests such as drilling and water injection.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe input of energy as a disturbance to the rock mass triggers changes in its internal stress and strain. These changes propagate and transform in the form of energy, stress, and strain. To better understand this complex behavior, we conceptualize the engineering unit rock mass (labeled A-F) and the engineering structure (labeled a-c) as nodes. The pathways through which energy, stress, and strain propagate within the rock mass and structure are regarded as edges, thus forming an intricate interaction spatial network in rock engineering (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). As the input energy escalates, the rock groups and structures gradually undergo physical damage, resulting in the release of energy. Meanwhile, due to the related failure mechanisms and potential field transformations (Yan et al., 2023), there are synchronous changes in accessibility and stress at each node. These changes have a great impact the load-bearing capacity and overall stability of the rock engineering system. The continuous increase in the number of physically damaged nodes progressively damages the integrity of rock engineering. As proportion of affected nodes expands, it may ultimately lead to severe instability and functional impairment of the entire rock engineering system. By analyzing the proportion of stable block and the risk index associated with each disaster scenario, we can construct curves depicting the variation of these characteristic indicators with respect to the disturbance intensity. These curves reveal the resilience characteristics of the rock engineering spatial structure. When a disturbance occurs, it promotes the expansion and penetration of internal joints and fissures in the rock mass, thereby increasing risk indicators such as the failure probability of water inrush and sand production. As the system deformation intensifies, the rock bolt b begins to Sustain initial physical damage. This leads to a rapid drop in the stress within the related rock block A, followed by gradual physical damage and slippage. Subsequently, the stress gradually transfers to other parts of the rock mass, giving rise to an ear of increased stress (associated with potential energy transformation) (C/D). When the rock bolt A also gets damage, the related rock mass E and F experience related failure, which significantly impacts the overall performance of the entire rock engineering system.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Resilience evaluation index and method\u003c/h2\u003e \u003cp\u003eThe resilience index Q(t) is a metric that quantifies the system\u0026rsquo;s ability to recover from disturbances over time (Bruneau et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). To standardize the dimensions, we define the resilience indicator Q(t) as the ratio of the actual resilience R(t) to the maximum possible resilience R\u003csub\u003emax\u003c/sub\u003e. Here, R(t) denotes the distance between the system\u0026rsquo;s current state and its equilibrium or reference state, while R\u003csub\u003emax\u003c/sub\u003e represents the maximum distance the system can withstand before undergoing a state transition or collapse. The value of the resilience indicator Q(t) ranges from 0 to 1. A value of 0 indicates that the system has no resilience, whereas a value of 1 represents full resilience. When evaluating the resilience indicator Q for a discontinuous rock mass structure, the appropriate performance indicator R(t) must be carefully selected according to the specific engineering types and objectives. For certain important or critical projects, such as nuclear waste disposal projects and underground gas storage projects, long-term stability or sealing performance should be prioritized as the chosen R(t). In conventional or general projects, such as tunnels, foundation pits, slopes, displacement or stress can serve as suitable performance indicator R(t). For some special or complex projects, such as underground reservoirs, underground power stations, a combination of relevant or complementary performance indicators R(t) can be selected, with each assigned different weight.\u003c/p\u003e \u003cp\u003eBruneau et al. (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2003\u003c/span\u003e) proposed four evaluation indicators of resilience in seismic engineering: robustness, rapidity, resourcefulness, and redundancy, which are used to assess engineering performance before and after a disaster respectively. When evaluating the robustness of the system, multiple geological factors need to be considered simultaneously. For example, the rock mass structural plane network controls the stress-failure path and affects the deformation resistance of the system. The crustal stress could cause the loss of the prestress in the supporting structure, reducing its restraint efficiency. Support structures enhance the robustness of rock engineering through synergistic mechanisms. Rock bolts prevent structural slippage; grouting homogenizes stress to form a composite arch; yielding bolts release energy at a constant resistance, slowing strain accumulation; multi-layer cables redistribute stress when they fail, maintaining integrity through redundancy and resistance to cascading failure. These factors have a significantly impacts on the overall robustness of the system. Therefore, when evaluating the robustness of discontinuous rock mass structure, it is advisable to use numerical methods that can accurately capture the discontinuity characteristics, such as the discrete element method and the continuous-discontinuous method. Moreover, the coupling effect between the rock mass and the support structure should be considered during the assessment process.\u003c/p\u003e \u003cp\u003eWhen assessing the rapidity and resourcefulness of a rock engineering system, it is crucial to take into account secondary disasters that may occur during the recovery process of rock engineering after disturbances. These secondary disasters include slips, collapses, water inrushes. These additional challenges greatly extend the recovery time and thus reduce the rapidity and resourcefulness of the rock mass structure. To effectively evaluate these aspects, numerical methods capable of capturing dynamic change and nonlinear effect should be used, such as the finite difference method, the finite element method.\u003c/p\u003e \u003cp\u003eRedundancy in a rock engineering system is influenced by the presence of structural planes, like fissures and joints. These structural planes introduce dispersion and changes in the force transmission path, thereby impacting the overall redundancy of the rock mass structure. When evaluating the redundancy of a rock engineering system, numerical methods that can account for changes in the force transmission path, such as the discrete element method and the continuous-discontinuous method, should be employed. Additionally, the influence of discontinuous planes on force transmission paths must be carefully considered.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Resilience governance model of rock engineering\u003c/h2\u003e \u003cp\u003eGeotechnical engineering design methods have transitioned from traditional single safety factor approaches towards a multi-tiered framework integrating reliability, robustness, and recoverability designs (Zheng et al., \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). While lifecycle management has gradually been incorporated into geotechnical design (e.g., Behnia et al., 2018), existing approaches predominantly focus on structural durability and cost control, often neglecting the dynamic degradation of geological conditions (e.g., rock mass strength attenuation, fracture network evolution). Moreover, current practices often neglect cross-phase integration across the lifecycle of rock engineering projects. This necessitates a paradigm shift toward a lifecycle-oriented resilience governance framework that prioritizes not only static stability and probabilistic reliability, but also dynamic resilience mechanisms. Our framework addresses this gap by integrating real-time monitoring of geological deterioration (e.g., microseismic events, hydraulic conductivity changes) with adaptive interventions (e.g., staged grouting, resilient anchor adjustments), thereby enabling proactive lifecycle resilience governance. By advancing systematic resilience modeling of geological systems evolution, such a framework could \\transition disaster mitigation from reactive to proactive strategies through integrated, informatized, and automated management system. These systems unify disturbance scenarios, such as excavation, groundwater fluctuations, and seismic activity, with real-time risk assessment, monitoring, emergency response coordination, and rapid recovery protocols. Finally, advance a unified paradigm for engineering geological disaster prevention and sustainable resilience governance in critical infrastructure projects (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). Central to this framework is a dynamic resilience evaluation model:\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:Q\\left(t\\right)=\\alpha\\:S\\left(t\\right)+\\beta\\:D\\left(t\\right)+\\gamma\\:E\\left(t\\right)$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere S denotes stress state coefficient, D represents deformation rate, and E quantifies energy dissipation. Coupled with multi-source monitoring data, this framework could enable real-time quantitative diagnosis and AI-driven prediction of instability probabilities under varying disturbance conditions. A three-dimensional decision matrix (risk intensity \u0026times; exposure \u0026times; vulnerability) dynamically optimizes hierarchical warning thresholds. During emergencies, an intelligent decision-making system, built on digital twin platforms, performs multi-objective optimization by aligning resilience evolution trajectories with resource allocation and structural redundancy, generating tailored contingency plans (e.g., personnel evacuation, emergency drainage, grout-based water inrush mitigation).\u003c/p\u003e \u003cp\u003ePost-disaster recovery leverages adaptive materials such as self-compensating prestressed anchors and shape-memory polymer grouts, with reconstruction efficacy quantified via the resilience gain coefficient (ΔQ). This establishes a closed-loop control mechanism spanning disturbance identification \u0026rarr; resilience degradation \u0026rarr; functional reconstruction, culminating in a novel resilience governance paradigm characterized by proactive defense, intelligent coordination, and resilient recovery.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo advance the rock engineering resilience, a comprehensive multi-field monitoring framework is required to quantify real-time stress state coefficients (S), development rates (D), and energy dissipation factor (E). This framework integrates advanced sensing modalities such as acoustic emissions, microseismic events, and electromagnetic signals. Coupling this data with AI-driven predictive algorithms enables the identification time-dependent disturbance models, ranging from sudden seismic events (requiring rapid-response strategies like controlled blasting, temporary supports) to gradual creep and excavation effects. The latter are addressed via adaptive reinforcement using resilience-enhanced materials and technologies (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), including tunnel lining spring structures, self-compensating prestressed anchors, and anchor-grouting integrated systems. Moreover, three-dimensional risk matrices (risk intensity\u0026times; exposure\u0026times; vulnerability) optimize warning thresholds and guide intelligent digital twin platforms in matching resilience evolution trajectories with multi-objective emergency protocols (e.g., grouting, drainage). Post-recovery structural durability and functionality are ensured through long-term monitoring, inspection, and maintenance that validate resilience gain coefficients (ΔQ) and enhance system adaptability via modular redundancy (Figs.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ea, b). This closed-loop \"disturbance-damage-repair-recovery\" paradigm embeds resilience principles (robustness, resourcefulness, redundancy) into reconstruction phases (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ec), employing shape-memory polymer grouts and staged reinforcement to mitigate progressive damage, reduce disaster consequences, and elevate recovery rates (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ed). Thereby, the passive mitigation is transitioned to proactive governance through systematic diagnostics of rock mass damage space, failure mode prognostics, and sustainability-driven lifecycle management of critical infrastructure.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResilient reinforcement method for rock mass engineering based on evolution process analysis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReinforcement/design methods\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReinforcement mechanism\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMethods\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePre-disaster\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRobust design, restorable design\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eImprove the robustness, resource and redundancy of rock mass engineering system and recovery after disaster\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1. Recoverable structure\u003c/p\u003e \u003cp\u003e2. Resilient anchoring technology\u003c/p\u003e \u003cp\u003e3. Anchor grouting technology\u003c/p\u003e \u003cp\u003e4. Relieve pressure\u003c/p\u003e \u003cp\u003e5. Steel structure, anchoring and spraying\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIn-disaster\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBased on the monitoring system, the rock engineering damage is predicted and the repair damage space is adaptive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEvolution of system performance into a cyclical pattern, i.e. \"Disturbance - damage - repair - recovery\"\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1. Temporary structure\u003c/p\u003e \u003cp\u003e2. Adaptive management: compensation for prestress, grouting, channel blocking\u003c/p\u003e \u003cp\u003e3. Controlled blasting technology\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePost-disaster\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAssess system damage and vulnerability to quickly repair critical parts/functions of rock mass and systems\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eImprove system recovery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1. Grouting\u003c/p\u003e \u003cp\u003e2. Controlled blasting technology\u003c/p\u003e \u003cp\u003e3. Recoverable structure\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Resilient reinforcement techniques for rock mass engineering","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Resilient bolt support technology\u003c/h2\u003e \u003cp\u003eResilient anchor bolts represent an innovative advancement in rock bolt support technology, characterized by high support resistance and dynamic adaptability to address the limitations of conventional and energy-absorbing bolts in complex geodynamic environments. Unlike traditional bolts optimized for static loads and minimal deformation, resilient bolts integrate a dual-threshold mechanism (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003ec): the maximum anchoring force ensures structural stability under peak disturbances (e.g., seismic events), while the minimum anchoring force maintains functionality during resilience degradation, enabling phased recovery through periodic energy release (0.10 mJ\u0026middot;m⁻\u0026sup3; per cycle) (Zhou et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2023\u003c/span\u003eb,c). This technology dynamically modulates support resistance to accommodate large shear deformation and time-dependent creep (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eb), suppressing stress concentration and crack propagation by redistributing energy via controlled yield-reset cycles. For instance, in deep coal roadways, resilient bolts reduced shear displacement by 40% compared to conventional bolts, demonstrating superior adaptability to cyclic mining-induced stress redistribution (Zhou et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2023\u003c/span\u003ec). By converting brittle fractures into elastoplastic progressive damage, resilient bolts synergize with AI-driven monitoring systems to translate experimental data (e.g., axial force fluctuations\u0026thinsp;\u0026gt;\u0026thinsp;20%) into actionable repair protocols, bridging the \"disturbance-damage-repair\" cycle from conceptual models to data-driven resilience management.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Grouting reinforcement\u003c/h2\u003e \u003cp\u003eRock, as a naturally brittle material, exhibits rigid contact between constituent blocks, rendering it susceptible to fracturing and fragmentation under external forces. This behavior precipitates abrupt reductions in strength and stiffness, limiting its capacity to effectively withstand deformation and impact (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003ea). Grouting reinforcement is redefined through a multi-stage lifecycle strategy that transitions from passive repair to proactive resilience management (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003eb). In the pre-disturbance phase, high-pressure pre-grouting fills deterministic structural planes (such as faults, bedding interfaces) with high-fluidity slurries, reducing permeability (\u0026lt;\u0026thinsp;10⁻⁷ m/s) and blocking seepage paths. This preemptive reinforcement improves the overall stability of the rock mass and the system's robustness by decreasing hydraulic-mechanical coupling risks prior to external disturbance (Zhang \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Kang et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Wang et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). During active disturbances, real - time microseismic monitoring acts as an important trigger for adaptive grouting. When event rate exceeds redefined threshold, indicating evolving fracture networks, gradient grouting using elastoplastic materials (epoxy resins) is initiated. This approach dynamically seals propagating fractures while redistributing stress concentrations, thereby preserving structural integrity and system functionality (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003ec). The grouting parameters (e.g., pressure, material rheology) are systematically adjusted in response to resilience performance metrics, ensuring engineering efficiency remains above minimum safety thresholds even under multi-phase disturbances (Jin et al., 2021; Zheng et al., \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Post-disaster, self-healing shape-memory polymer (SMP) grouts enable autonomous repair of critical damage zones. These advanced materials achieve rapid crack closure through hydration-activated expansion, restoring structural continuity while maximizing the resilience gain coefficient (ΔQ). Collectively, this strategy transitions rock failure modes from brittle to ductile via two synergistic mechanisms: 1) Stress homogenization through grouted composite arches that redistribute loads across reinforced zones (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003ea); 2) Energy dissipation via localized plastic deformation within elastoplastic grouted matrices, effectively buffering dynamic impacts (Tani, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). It aligns with the requirements of a lifecycle - oriented resilience governance framework, enabling the rock engineering system to better withstand various disturbances throughout its life cycle (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003ec).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e4.3 High-pressure anchor grouting-spraying collaborative control technology\u003c/h2\u003e \u003cp\u003eHigh-pressure anchor grouting-spraying collaborative control technology, developed by Prof. Kang\u0026rsquo;s research group, addresses large deformation challenges in kilometer-deep soft coal roadway The approach integrates high-strength, high-pressure composite grouting anchor bolts, high-pressure grouting anchor cables, high-prestress anchor bolts. It also combines support with high-pressure splitting grouting modification and surface spraying. When implemented together, this significantly enhances the structure, integrity, and strength of roadway coal sides. As a result, it effectively controls large deformations in soft coal side roadways (Kang et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The mechanism of the high-pressure anchor grouting-spraying collaborative control technology encompasses the following main aspects (Kang et al., 2023): (1) High-prestress anchor bolts and anchor cables support can increase the initial stress level in the roadway\u0026rsquo;s surrounding rock. This action enhances the stability and anti-deformation capacity of the rock mass. (2) High-pressure splitting grouting modification forms a continuous grouting crack network within the roadway surrounding rock. This not only improves the integrity and strength of the rock, but also releases a portion of the ground stress, thereby reducing the overall stress level; (3) Surface spraying creates a uniform, dense and durable protective layer on the roadway\u0026rsquo;s surface. This layer prevents weathering and rock detachment, thereby improving the overall durability and stability of the roadway. The technology substantially improves the anti-deformation and anti-failure capacity of the roadway. It enables the roadway to endure larger deformations and higher stress levels without experiencing instability or failure. Additionally, the self-healing and self-adaptive capabilities of the roadway are enhanced. When the roadway is deformed or damaged, the grouting crack network allows for repair and adjustment, restoring or maintaining the rock mass structure and its function. Moreover, the technology enhances the redundancy and diversity of the roadway surrounding rock. In cases where certain parts or functions fail, other components can compensate or replace them. This ensures overall safety and operational efficiency.\u003c/p\u003e \u003c/div\u003e"},{"header":"5. Discussion","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e5.1 Reinforcement theory of resilient rock bolt\u003c/h2\u003e \u003cp\u003eResilient bolt support technology, a critical advancement in enhancing the engineering resilience of discontinuous rock masses, fundamentally transforms conventional rigid confinement through thermodynamic energy regulation mechanisms, enabling dynamic adaptability and controlled damage in rock engineering under disturbances by periodically releasing support resistance to dissipate accumulated strain energy\u0026mdash;thereby converting brittle fractures into elastoplastic progressive damage and suppressing microcrack propagation\u0026mdash;while exhibiting intrinsic compatibility with the cyclic \"disturbance-damage-recovery\" evolution of discontinuous rock systems, with optimized parameters (constant-resistance thresholds and energy-release intervals) tailored to structural discontinuities and disturbance types (e.g., stress-redistribution matching in mining-induced high-stress zones versus shock-absorption coordination for seismic shear mitigation), synergistically integrating with grouting reinforcement and high-pressure anchoring to establish multi-scale resilience through macro-stabilization via energy regulation and micro-continuity improvement via fracture filling, thereby advancing the quantification of robustness (energy-absorption density) and redundancy (recovery-rate potential) in resilience metrics while providing a technical framework for autonomous disturbance-adaptive recovery throughout engineering lifecycles.\u003c/p\u003e \u003cp\u003eThe disturbance energy imposed on rock is divided in to elastic strain energy and irreversible dissipative strain energy (Xie, 2005; Wang et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$$\\:U={U}_{e}+{U}_{d}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e1\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:U\\)\u003c/span\u003e\u003c/span\u003e is disturbance energy. \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{U}_{e}\\)\u003c/span\u003e\u003c/span\u003e is the elastic strain energy release of the unit. \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{U}_{d}\\)\u003c/span\u003e\u003c/span\u003e is the dissipated strain energy of the unit。\u003c/p\u003e \u003cp\u003eDuring compression tests, the releasable elastic strain energy (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{U}_{e}\\)\u003c/span\u003e\u003c/span\u003e) within rock gradually increases as the rock enters the elastic deformation stage. As internal microcracks propagate in uniaxial compression or the material approaches failure (under cyclic loading), the internal damage increases rapidly. Consequently, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{U}_{e}\\)\u003c/span\u003e\u003c/span\u003e decreases rapidly, while the dissipative strain energy (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{U}_{d}\\)\u003c/span\u003e\u003c/span\u003e) per unit increases sharply (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003ea) (Zhao et al., \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2020\u003c/span\u003e, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Gong et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Li et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe coordinate deformation of the resilient anchor bolt-rock system alters the energy evolution in rock mass (Wang et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Zhou et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2023\u003c/span\u003ea). The disturbance energy could be divided into three parts: (1) elastic strain energy in rock mass, (2) dissipative strain energy through irreversible damage mechanism, and (3) cyclic energy release via bolt yield-adaptation (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003ec) (Zhou et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2023\u003c/span\u003ec). There are three distinct conditions: (1) when bolt resistance remains below the rock's elastic limit, system resilience is enhanced through bolt-dominated energy absorption that elevates disturbance resistance thresholds; (2) at bolt resistance levels between elastic limit and peak strength, delayed damage accumulation through scheduled energy release enables elevated energy capacity thresholds; and (3) when bolt resistance exceeds ultimate failure strength, energy redistribution prioritizes bolt-mediated dissipation pathways. Each condition dictates distinct energy partitioning ratios between rock damage processes and bolt-controlled energy regulation mechanisms.\u003cdiv id=\"Equ2\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ2\" name=\"EquationSource\"\u003e\n$$\\:U=\\left\\{\\begin{array}{c}{U}_{e}+{U}_{b}\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:{\\sigma\\:}_{b}\\le\\:{\\sigma\\:}_{e}\\\\\\:{U}_{e}+{U}_{b}+{U}_{d}\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:{\\sigma\\:}_{e}\\le\\:{\\sigma\\:}_{b}\u0026lt;{\\sigma\\:}_{l}\\\\\\:{U}_{d}\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:{\\sigma\\:}_{l}\\le\\:{\\sigma\\:}_{b}\\end{array}\\right.$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e2\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:U\\)\u003c/span\u003e\u003c/span\u003e is the total strain energy generated by the disturbance. \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{U}_{b}\\)\u003c/span\u003e\u003c/span\u003e is the dissipated strain energy of resilient bolt resistance with periodic variation. \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\sigma\\:}_{b}\\)\u003c/span\u003e\u003c/span\u003e is the maximum support resistance of resilient bolt. \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\sigma\\:}_{e}\\)\u003c/span\u003e\u003c/span\u003e is the elastic limit load of the rock. \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\sigma\\:}_{l}\\)\u003c/span\u003e\u003c/span\u003e is the ultimate strength of rock.\u003c/p\u003e \u003cp\u003eThe true triaxial test results conducted by Zhao et al. (\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) show the elastic strain energy of sandstone fluctuates slightly within a range of 0.0935 mJ\u0026middot;m\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e with the number of loading cycles, while the dissipative strain energy stabilizes at 0.02\u0026ndash;0.03 0.0935 mJ\u0026middot;m\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e, with sand rock failure occurring at 1.214 mJ\u0026middot;m\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e total strain energy ( 0.277 mJ\u0026middot;m\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e cumulative damage energy of), the sand stone fails (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003eb). The introduction of resilient bolts reconfigures the energy distribution mechanism of discontinuous rock masses. Based on the calibration of test parameters (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e), the energy absorption/release density of a rock bolt in a single cycle is 0.10 mJ\u0026middot;m\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e. The average value of the elastic strain energy of sandstone in a single cycle is taken as 0.924 mJ\u0026middot;m\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe maximum disturbance strain energy that the rock-bolts system can withstand under 10 cycles of loading is 1.925 mJ\u0026middot;m\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e, which is 1.6 times the failure threshold of the case without bolt, and the dissipative strain energy of the rock approaches zero (Xie et al. \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2005\u003c/span\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003ec). This indicates that the bolts could effectively suppress the propagation of microcrack through periodic energy release, transforming the damage mode of the rock mass from brittle fracture to controllable elastoplastic deformation. If the rock resistance is between the elastic and ultimate strengths of the rock mass (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\sigma\\:}_{e}\\le\\:{\\sigma\\:}_{b}\u0026lt;{\\sigma\\:}_{l}\\)\u003c/span\u003e\u003c/span\u003e), the effect of enhancing the system\u0026rsquo;s resilience is more significant. Taking the single-cycles dissipative strain energy of 0.01 mJ\u0026middot;m\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e as an example, under the same number of cycles, the disturbance strain energy that the rock-resilient rock bolt system can withstand is 2.025 mJ\u0026middot;m\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e, and the external input energy required to reach the cumulative damage threshold is as high as 5.4675 mJ\u0026middot;m\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e, which is 4.5 times that of the rock mass without rock bolt (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003ed).\u003c/p\u003e \u003cp\u003eThe above thermodynamic mechanism provides a quantitative basis for the resilience control of rock mass engineering. For example, in response to high - frequency disturbances induced by mining activities, the energy - release cycle of the bolts can be adjusted to match the stress fluctuation frequency of the surrounding rock, thereby achieving dynamic energy balance. In the case of transient impacts such as earthquakes, the energy - absorption density parameter of the bolts can serve as a calibration benchmark for setting the disaster - warning thresholds of multi - source monitoring systems. This theoretical framework transforms experimental data into decision - making variables for engineering resilience management, promoting the transition of the \"disturbance - damage - repair\" cyclic model from the conceptual level to data - driven practice.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e5.2 Limitation\u003c/h2\u003e \u003cp\u003eThe concept of resilience represents a relatively nascent and burgeoning topic within the field of geotechnical engineering (Zheng et al., \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). It pertains to the capacity of geotechnical systems to endure, recover from, and adapt to diverse disturbances and hazards, including earthquakes, landslides, floods, and climate variations. Resilience is intricately linked to sustainability, risk assessment, and reliability, while also possessing distinct attributes and challenges. In geotechnical practice, resilience is inherently interwoven with sustainability, risk assessment, and reliability across the entire lifecycle of infrastructure. Resilience-driven design strategies, such as redundant structural systems and adaptive materials, translate quantified risk assessments (e.g., geological hazard probabilities) into engineered safeguards, mitigating post-disaster recovery demands and reducing long-term resource consumption. This approach enhances sustainability by prolonging infrastructure lifespan and minimizing environmental impacts. Concurrently, real-time monitoring (e.g., deformation sensors, AI-driven early warning systems) and adaptive interventions (e.g., optimized support during construction or predictive maintenance) bolster system reliability, preventing incremental degradation and ensuring operational stability. Resilience operates through a systematic \u0026ldquo;prevention-adaptation-recovery\u0026rdquo; framework, harmonizing short-term costs with lifecycle benefits to optimize safety, efficiency, and resource stewardship. Ultimately, resilience integrates environmental, economic, and societal value streams, enabling infrastructure to withstand uncertainties while advancing sustainable development goals in engineering geology.\u003c/p\u003e \u003cp\u003eA primary challenge in integrating resilience into geotechnical engineering systems from the lack of a universally accepted definition and standardized framework for assessing and enhancing resilience. Cross-disciplinary discrepancies in resilience conceptualization, ranging from material mechanics may emphasize physical resilience such as strength, stiffness, and ductility to engineering management\u0026rsquo;s prioritization of social and economic factors (e.g., functionality, maintainability, recovery time), further complicate its application (Lee et al., 2018; Liu et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Additionally, resilience is inherently dynamic and context-dependent, influenced by disturbance characteristics (type, intensity), rock system properties, component interactions, environmental constraints. These complexities hinder quantitative comparisons of resilience across diverse geotechnical systems or scenarios (Zheng et al., \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eA critical impediment to advancing resilience assessment lies in the scarcity of adequate data and knowledge gaps. Rock engineering systems are subject to multifaceted and variable disturbance factors, complicating accurate prediction and modeling (Wu et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Intrinsic uncertainties, such as variability in rock properties, load conditions, design parameters, and construction methods, compound these challenges (Cai, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Behnia et al., 2018; Elmo and Stead \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Consequently, acquiring reliable, representative data to evaluate the performance and recovery capacity of the system under diverse disturbances remains a formidable task. Advancing resilience in geotechnical engineering demands interdisciplinary innovation, integrating and practice through: (1) establishing unified definitions and metrics for resilience (such as recovery rate, robustness thresholds); (2) Developing multi-source monitoring and early warning systems to capture real-time performance data. (3) Proposing comprehensive evaluation frameworks that integrate multiple parameters (mechanical, environmental and socio-economic indicators). (4) Designing novel reinforcement materials and adaptive technologies to enhance system adaptability. (5) Optimizing resilience strategies to balance cost-effectiveness with ecological sustainability.\u003c/p\u003e \u003c/div\u003e"},{"header":"6. Conclusion","content":"\u003cp\u003eThis paper presents a comprehensive exploration of resilience in rock engineering, focusing on its conceptual foundations, evaluation methodologies, and enhancement technologies. The study defines rock engineering resilience through three core attributes: high pre-disaster reliability, low post-disaster consequences, and rapid functional recovery. A unified analytical integrates disturbance, rock engineering structure and functional efficiency, emphasizing the dynamic change of functional robustness and recovery as a key mechanism. By observing the physical-mechanical interactions within rock-support composites and leveraging rock mechanics principles, the framework reveals how resilience evolves under stress and deformation.\u003c/p\u003e \u003cp\u003eA geotechnical disaster prevention model is proposed, combining multi-source monitoring and early warning system and resilience evolution analysis. This model spans three stages: pre-disaster risk evaluation, coordinated emergency response, and post-disaster recovery. Three resilience - enhancing technologies are introduced: grouting reinforcement technology, resilient anchor bolt support technology and high-pressure anchor grouting-spraying collaborative control technology, addressing large deformations in soft coal roadways via restressed support and stress redistribution. Theoretical advancements include a thermodynamic analysis of resilient anchor bolts, demonstrating their strain-energy dissipation mechanisms. The study concludes by advocating for resilience-driven design paradigms over traditional stability-centric approaches, emphasizing adaptive management and AI-enhanced predictive modeling to address evolving climatic and anthropogenic challenges in deep underground engineering. Future work should prioritize standardization of resilience metrics and validation of these technologies in extreme geomechanics environments.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAcknowledgments\u003c/h2\u003e\n\u003cp\u003eThe author sincerely acknowledges the support by the National Natural Science Foundation of China (42130706, 42207169); Key R \u0026amp; D Program of Xinjiang Uygur Autonomous Region (2021B03004-3), the Natural Science Foundation of Jiangsu Province (BK20221126); China Postdoctoral Science Foundation (2022M710177).\u003c/p\u003e\n\u003ch2\u003eDeclaration of competing interest\u003c/h2\u003e\n\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\n\u003ch2\u003eDeclaration of generative AI in scientific writing\u003c/h2\u003e\n\u003cp\u003eThe authors declare that the AI tools had no role in the data analysis and interpretation in the research process, and were only applied to improve the language and readability of the text.\u0026nbsp;\u003c/p\u003e\n"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAnastasopoulos, I., Gazetas, G., Loli, M., et al. (2010). Soil failure can be used for seismic protection of structures. \u003cem\u003eBulletin of Earthquake Engineering, 8\u003c/em\u003e(2), 309-326.\u003c/li\u003e\n\u003cli\u003eBehnia, M., \u0026amp; Seifabad, M. C. (2018). Stability analysis and optimization of the support system of an underground powerhouse cavern considering rock mass variability. \u003cem\u003eEnvironmental Earth Sciences, 77\u003c/em\u003e(18), 645. https://doi.org/10.1007/s12665-018-7835-2\u003c/li\u003e\n\u003cli\u003eBrown, E. T. (2008). Estimating the mechanical properties of rock masses. In Y. Potvin, J. Carter, A. Dyskin, \u0026amp; R. Jeffrey (Eds.), \u003cem\u003eProceedings of the First Southern Hemisphere International Rock Mechanics Symposium\u003c/em\u003e (pp. 3-22). Australian Centre for Geomechanics.\u003c/li\u003e\n\u003cli\u003eBruneau, M., Chang, S. E., Eguchi, R. T., et al. (2003). A framework to quantitatively assess and enhance the seismic resilience of communities. \u003cem\u003eEarthquake Spectra, 19\u003c/em\u003e(4), 733-752.\u003c/li\u003e\n\u003cli\u003eBruneau, M., \u0026amp; Reinhorn, A. (2006). Overview of the resilience concept. In \u003cem\u003eProceedings of the 8th US National Conference on Earthquake Engineering\u003c/em\u003e. San Francisco: Curran Associates, Inc.\u003c/li\u003e\n\u003cli\u003eCai, M. (2011). Rock mass characterization and rock property variability considerations for tunnel and cavern design. \u003cem\u003eRock Mechanics and Rock Engineering, 44\u003c/em\u003e(4), 379-399. https://doi.org/10.1007/s00603-011-0138-5\u003c/li\u003e\n\u003cli\u003eCerfontaine, B., \u0026amp; Collin, F. (2018). Cyclic and fatigue behaviour of rock materials: Review, interpretation and research perspectives. \u003cem\u003eRock Mechanics and Rock Engineering, 51\u003c/em\u003e, 391-414. https://doi.org/10.1007/s00603-017-1337-5\u003c/li\u003e\n\u003cli\u003eZhou, C., Huang, C., Chen, Y., Zhang, W., \u0026amp; Wang, L. (2023). Performance of a novel resistant rock bolt with periodic energy absorption and release: Theory and experiment. \u003cem\u003eActa Geotechnica\u003c/em\u003e.\u003c/li\u003e\n\u003cli\u003eEl Tani, M. (2012). Grouting rock fractures with cement grout. \u003cem\u003eRock Mechanics and Rock Engineering, 45\u003c/em\u003e, 547-561. https://doi.org/10.1007/s00603-012-0235-0\u003c/li\u003e\n\u003cli\u003eElmo, D., \u0026amp; Stead, D. (2021). The role of behavioural factors and cognitive biases in rock engineering. \u003cem\u003eRock Mechanics and Rock Engineering, 54\u003c/em\u003e(5), 2109-2128. https://doi.org/10.1007/s00603-021-02385-3\u003c/li\u003e\n\u003cli\u003eFouda, Y. E., \u0026amp; ElKhazendar, D. M. (2023). Achievement of resilience in urbanism: A prototype for a simulative methodology. \u003cem\u003eAlexandria Engineering Journal, 70\u003c/em\u003e, 145-168.\u003c/li\u003e\n\u003cli\u003eGlobal Commission on Adaptation. (2019). Adapt now: A global call for leadership on climate resilience.\u003c/li\u003e\n\u003cli\u003eGong, F. Q., Yan, J. Y., Li, X. B., et al. (2019). A peak-strength strain energy storage index for rock burst proneness of rock materials. \u003cem\u003eInternational Journal of Rock Mechanics and Mining Sciences, 117\u003c/em\u003e, 76-89.\u003c/li\u003e\n\u003cli\u003eGong, W. P., Khoshnevisan, S., \u0026amp; Juang, C. H. (2014). Gradient-based design robustness measure for robust geotechnical design. \u003cem\u003eCanadian Geotechnical Journal, 51\u003c/em\u003e(11), 1331-1342.\u003c/li\u003e\n\u003cli\u003eHasan, M., Shang, Y., Shao, P., Yi, X., \u0026amp; Meng, H. (2022). Evaluation of engineering rock mass quality via integration between geophysical and rock mechanical parameters. \u003cem\u003eJournal of Rock Mechanics and Geotechnical Engineering, 15\u003c/em\u003e(1), 1-24.\u003c/li\u003e\n\u003cli\u003eHe, M. C., Xie, H. P., Peng, S. P., et al. (2005). Study on rock mechanics in deep mining engineering. \u003cem\u003eChinese Journal of Rock Mechanics and Engineering, 24\u003c/em\u003e(16), 2803-2813+11-12.\u003c/li\u003e\n\u003cli\u003eHolling, C. S. (1973). Resilience and stability of ecological systems. \u003cem\u003eAnnual Review of Ecology and Systematics, 4\u003c/em\u003e(1), 1-23.\u003c/li\u003e\n\u003cli\u003eHu, X. L., Zhou, C., Xu, C., et al. (2019). Model tests of the response of landslide-stabilizing piles to piles with different stiffness. \u003cem\u003eLandslides, 16\u003c/em\u003e, 2187-2200.\u003c/li\u003e\n\u003cli\u003eHua, W., Li, J., Dong, S., \u0026amp; Pan, X. (2019). Experimental study on mixed mode fracture behavior of sandstone under water\u0026ndash;rock interactions. \u003cem\u003eProcesses, 7\u003c/em\u003e(2), 70. https://doi.org/10.3390/pr7020070\u003c/li\u003e\n\u003cli\u003eHuang, H. W., \u0026amp; Zhang, D. M. (2016). Resilience analysis of shield tunnel lining under extreme surcharge: Characterization and field application. \u003cem\u003eTunnelling and Underground Space Technology, 51\u003c/em\u003e, 301-312.\u003c/li\u003e\n\u003cli\u003eHudson, J., \u0026amp; Harrison, J. (1997). \u003cem\u003eEngineering rock mechanics\u0026mdash;an introduction to the principles\u003c/em\u003e (1st ed.). Elsevier, Amsterdam.\u003c/li\u003e\n\u003cli\u003eJin, L., \u0026amp; Sui, W. (2021). Experimental investigation on chemical grouting in rough 2D fracture network with flowing water. \u003cem\u003eBulletin of Engineering Geology and the Environment, 80\u003c/em\u003e, 8519-8533.\u003c/li\u003e\n\u003cli\u003eJoint TC205/TC304 Working Group. (2017). Discussion of statistical/reliability methods for Eurocodes final report. In \u003cem\u003eProceedings of the 5th International Symposium on Geotechnical Safety and Risk\u003c/em\u003e. Rotterdam: International Society for Soil Mechanics and Geotechnical Engineering.\u003c/li\u003e\n\u003cli\u003eJuang, C. H., Wang, L., Liu, Z. F., et al. (2013). Robust geotechnical design of drilled shafts in sand: New design perspective. \u003cem\u003eJournal of Geotechnical and Geoenvironmental Engineering, 139\u003c/em\u003e(12), 2007-2019.\u003c/li\u003e\n\u003cli\u003eKang, H., Jiang, P., Huang, B., et al. (2020). Roadway strata control technology by means of bolting-modification-destressing in synergy in 1,000 m deep coal mines. \u003cem\u003eJournal of China Coal Society, 45\u003c/em\u003e(3), 845-864. https://doi.org/10.13225/j.cnki.jccs.SJ20.0204\u003c/li\u003e\n\u003cli\u003eKang, H., Li, W., Gao, F., \u0026amp; Yang, J. (2022). Grouting theories and technologies for the reinforcement of fractured rocks surrounding deep roadways. \u003cem\u003eDeep Underground Science and Engineering\u003c/em\u003e, 1-18. https://doi.org/10.1002/dug2.12026\u003c/li\u003e\n\u003cli\u003eKhoshnevisan, S., Gong, W. P., \u0026amp; Juang, C. H. (2015). Efficient robust geotechnical design of drilled shafts in clay using a spreadsheet. \u003cem\u003eJournal of Geotechnical and Geoenvironmental Engineering, 141\u003c/em\u003e(2), 04014092.\u003c/li\u003e\n\u003cli\u003eKong, D., Saroglou, C., Wu, F., Sha, P., \u0026amp; Li, B. (2021). Development and application of UAV-SfM photogrammetry for quantitative characterization of rock mass discontinuities. \u003cem\u003eInternational Journal of Rock Mechanics and Mining Sciences, 141\u003c/em\u003e, 104729.\u003c/li\u003e\n\u003cli\u003eKong, D., Wu, F., \u0026amp; Saroglou, C. (2020). Automatic identification and characterization of discontinuities in rock masses from 3D point clouds. \u003cem\u003eEngineering Geology, 265\u003c/em\u003e, 105442.\u003c/li\u003e\n\u003cli\u003eKuang, Z., Qiu, S., Li, S., Du, S., Huang, Y., \u0026amp; Chen, X. (2021). A new rock brittleness index based on the characteristics of complete stress\u0026ndash;strain behaviors. \u003cem\u003eRock Mechanics and Rock Engineering, 54\u003c/em\u003e(3), 1109-1128.\u003c/li\u003e\n\u003cli\u003eHasan, M., Shang, Y., Shao, P., Yi, X., \u0026amp; Meng, H. (2022). Evaluation of engineering rock mass quality via integration between geophysical and rock mechanical parameters. \u003cem\u003eJournal of Rock Mechanics and Geotechnical Engineering, 15\u003c/em\u003e(1), 1-24.\u003c/li\u003e\n\u003cli\u003eLee, M., \u0026amp; Basu, D. (2018). An integrated approach for resilience and sustainability in geotechnical engineering. \u003cem\u003eIndian Geotechnical Journal, 48\u003c/em\u003e(2), 207-234. https://doi.org/10.1007/s40098-018-0297-3\u003c/li\u003e\n\u003cli\u003eLi, X. M., Liu, C. Y., Syd, S. P., \u0026amp; Lu, Y. (2017). Fatigue deformation characteristics and damage model of sandstone subjected to uniaxial step cyclic loading. \u003cem\u003eJournal of China University of Mining and Technology, 46\u003c/em\u003e(1), 8-18.\u003c/li\u003e\n\u003cli\u003eLiu, X. M., Li, D. Q., Ma, M. Q., Szymanski, B. K., Stanley, H. E., \u0026amp; Gao, J. X. (2022). Network resilience. \u003cem\u003ePhysics Reports, 971\u003c/em\u003e, 1-108.\u003c/li\u003e\n\u003cli\u003eLiu, X., \u0026amp; Yang, X. (2020). A numerical solution of a circular tunnel in a confining pressure-dependent strain-softening rock mass. \u003cem\u003eScientific Reports, 10\u003c/em\u003e, 1369. https://doi.org/10.1038/s41598-020-58331-3\u003c/li\u003e\n\u003cli\u003eLiu, Y., Wang, Y., Zhong, Z., Li, Q., \u0026amp; Zuo, Y. (2023). Constitutive model for grouted rock mass by macro-meso damage. \u003cem\u003eMaterials, 16\u003c/em\u003e(13), 4859. https://doi.org/10.3390/ma16134859\u003c/li\u003e\n\u003cli\u003eLu, X., Chen, Y., \u0026amp; Mao, Y. (2011). New concept of structural seismic design: Earthquake resilient structures. \u003cem\u003eJournal of Tongji University: Natural Science, 39\u003c/em\u003e(7), 941-948. (in Chinese)\u003c/li\u003e\n\u003cli\u003eLv, X., Quan, L., \u0026amp; Jiang, H. (2017). Research trend of earthquake resilient structures seen from 16WCEE. \u003cem\u003eEarthquake Engineering and Engineering Dynamics, 37\u003c/em\u003e(3), 1-9. (in Chinese)\u003c/li\u003e\n\u003cli\u003eMohanty, A., Ramasamy, A. K., Verayiah, R., Bastia, S., Dash, S. S., Cuce, E., Khan, T. M. Y., \u0026amp; Soudagar, M. E. M. (2024). Power system resilience and strategies for a sustainable infrastructure: A review. \u003cem\u003eAlexandria Engineering Journal, 105\u003c/em\u003e, 261-279.\u003c/li\u003e\n\u003cli\u003ePeer. (2010). Report of the seventh joint planning meeting of NEES/E-defense collaborative research on earthquake engineering. Berkeley: University of California.\u003c/li\u003e\n\u003cli\u003ePeng, X., Li, D. Q., Cao, Z. J., et al. (2017). Reliability-based robust geotechnical design using Monte Carlo simulation. \u003cem\u003eBulletin of Engineering Geology and the Environment, 76\u003c/em\u003e(3), 1217-1227.\u003c/li\u003e\n\u003cli\u003ePierce, M., Cundall, P., Potyondy, D., \u0026amp; Mas Ivars, D. (2011). The synthetic rock mass approach for jointed rock mass modelling. \u003cem\u003eInternational Journal of Rock Mechanics and Mining Sciences, 48\u003c/em\u003e(2), 219-244.\u003c/li\u003e\n\u003cli\u003eShadabfar, M., Mahsuli, M., Zhang, Y., et al. (2022). Resilience-based design of infrastructure: Review of models, methodologies, and computational tools. \u003cem\u003eASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 8\u003c/em\u003e(1), 03121004.\u003c/li\u003e\n\u003cli\u003eSui, W. H. (2022a). Catastrophic mechanism of seepage deformation and failure of mining rock mass and its prevention \u0026amp; control I: Water-sand mixture inrush from seam roof. \u003cem\u003eJournal of Earth Sciences and Environment, 4\u003c/em\u003e(6), 000-000.\u003c/li\u003e\n\u003cli\u003eSui, W. H. (2022b). Active prevention and control of water-sand mixture inrush with high potential energy due to mining based on structural hydrogeology. \u003cem\u003eJournal of Engineering Geology, 30\u003c/em\u003e(1), 101-109.\u003c/li\u003e\n\u003cli\u003eSui, W. H. (2023). Evaluation method of resistance to seepage failure due to mining near unconsolidated aquifers I: Critical hydraulic gradient. \u003cem\u003eCoal Geology \u0026amp; Exploration, 51\u003c/em\u003e(2), 175-186. https://doi.org/10.12363/issn.1001-1986.22.11.0902\u003c/li\u003e\n\u003cli\u003eTellman, B., Sullivan, J. A., Kuhn, C., et al. (2021). Satellite imaging reveals increased proportion of population exposed to floods. \u003cem\u003eNature, 596\u003c/em\u003e, 80-86. https://doi.org/10.1038/s41586-021-03695-w\u003c/li\u003e\n\u003cli\u003eWang, G., Wang, Y., Yu, H., et al. (2021). Shaking table tests on seismic response of rocking frame structure considering foundation uplift. \u003cem\u003eChinese Journal of Geotechnical Engineering, 43\u003c/em\u003e(11), 2064-2074. (in Chinese)\u003c/li\u003e\n\u003cli\u003eWang, M., Li, Z., Xia, E., Li, Z., Zou, Y., Wei, S., Wang, X., \u0026amp; Yang, D. (2022). Energy dissipation and supporting regulation effect of surrounding rock in deep roadway. \u003cem\u003eJournal of Mining and Safety Engineering, 39\u003c/em\u003e(4), 741-749. https://doi.org/10.13545/j.cnki.jmse.2021.0479\u003c/li\u003e\n\u003cli\u003eWang, Y., Yang, P., Li, Z., Wu, S., \u0026amp; Zhao, Z. (2023). Study on fatigue failure characteristics and energy evolution mechanism of fractured rock under graded cyclic loading. \u003cem\u003eKSCE Journal of Civil Engineering, 27\u003c/em\u003e(4), 1157-1165. https://doi.org/10.1007/s12205-023-0657-0\u003c/li\u003e\n\u003cli\u003eWang, F., Zhang, J., Qin, X., Yuan, C., Meng, X., \u0026amp; Zhang, H. (2024). Diffusion mechanism of fracture grouting in rock mass with flowing water. \u003cem\u003eAlexandria Engineering Journal, 105\u003c/em\u003e, 44-55.\u003c/li\u003e\n\u003cli\u003eWard, P., Jongman, B., Salamon, P., et al. (2015). Usefulness and limitations of global flood risk models. \u003cem\u003eNature Climate Change, 5\u003c/em\u003e, 712-715. https://doi.org/10.1038/nclimate2742\u003c/li\u003e\n\u003cli\u003eWu, B., \u0026amp; Ou, Y. (2014). Experimental study on tunnel lining joints temporarily strengthened by SMA bolts. \u003cem\u003eSmart Materials and Structures, 23\u003c/em\u003e(12), 125018.\u003c/li\u003e\n\u003cli\u003eWu, W. P., Feng, X. T., Zhang, C. Q., \u0026amp; Qiu, S. L. (2011). Classification of failure modes and controlling measures for surrounding rock of deep tunnel in hazard rock. \u003cem\u003eChinese Journal of Rock Mechanics and Engineering, 30\u003c/em\u003e(9), 1872-1892.\u003c/li\u003e\n\u003cli\u003eWu, F., Wu, J., Bao, H., Li, B., Shan, Z., \u0026amp; Kong, D. (2021). Advances in statistical mechanics of rock masses and its engineering applications. \u003cem\u003eJournal of Rock Mechanics and Geotechnical Engineering, 15\u003c/em\u003e(1), 1-24.\u003c/li\u003e\n\u003cli\u003eXie, H. (2019). Research review of the state key research development program of China: Deep rock mechanics and mining theory. \u003cem\u003eJournal of China Coal Society, 44\u003c/em\u003e(5), 1283-1305. https://doi.org/10.13225/j.cnki.jccs.2019.6038\u003c/li\u003e\n\u003cli\u003eXie, H. P., Ju, Y., \u0026amp; Li, L. Y. (2005). Criteria for strength and structural failure of rocks based on energy dissipation and energy release principles. \u003cem\u003eChinese Journal of Rock Mechanics and Engineering, 24\u003c/em\u003e(17), 3003-3010.\u003c/li\u003e\n\u003cli\u003eYan, W. T., \u0026amp; Li, Z. H. (2023). Study on the resilience mechanism of urban spatial structure from the view of risk disturbance: Theoretical framework and empirical methodology. \u003cem\u003eUrban Planning International, 28\u003c/em\u003e(4), 1-12.\u003c/li\u003e\n\u003cli\u003eYao, J., Jiang, N., Yao, Y., Zhou, C., \u0026amp; Yang, Y. (2024). Instability mechanism of layered surrounding rock tunnels affected by layer thickness under dynamic and static loads. \u003cem\u003eAlexandria Engineering Journal, 105\u003c/em\u003e, 471-484.\u003c/li\u003e\n\u003cli\u003eYing, C., Hu, X., Zhou, C., et al. (2021). Analysis of chemo-mechanical behavior of silty soil under long-term immersion in saline reservoir water. \u003cem\u003eBulletin of Engineering Geology and the Environment, 80\u003c/em\u003e(1), 627-640.\u003c/li\u003e\n\u003cli\u003eYing, C., Zhang, K., Wang, Z. N., et al. (2021). Analysis of the run-out processes of the Xinlu Village landslide using the generalized interpolation material point method. \u003cem\u003eLandslides, 18\u003c/em\u003e(4), 1519-1529.\u003c/li\u003e\n\u003cli\u003eZhang, D. M., Zhai, W. Z., Huang, H. W., et al. (2019). Robust retrofitting design for rehabilitation of segmental tunnel linings: Using the example of steel plates. \u003cem\u003eTunnelling and Underground Space Technology, 83\u003c/em\u003e, 231-242.\u003c/li\u003e\n\u003cli\u003eZhang, G. (2022). Mechanism of deflection propagation for grouting in fractured rock mass with flowing water and mining effect on grouted curtain: A review. \u003cem\u003eJournal of Engineering Geology, 30\u003c/em\u003e(3), 987-997. https://doi.org/10.13544/j.cnki.jeg.2022-0091\u003c/li\u003e\n\u003cli\u003eZhang, J., Shu, J., Ren, X., \u0026amp; Ren, H. (2013). Influence mechanism of grouting on mechanical characteristics of rock mass. \u003cem\u003eMathematical Problems in Engineering, 2013\u003c/em\u003e, 281817. https://doi.org/10.1155/2013/281817\u003c/li\u003e\n\u003cli\u003eZhao, K., Yu, X., Zhou, Y., et al. (2020). Energy evolution of brittle granite under different loading rates. \u003cem\u003eInternational Journal of Rock Mechanics and Mining Sciences, 132\u003c/em\u003e, 104392.\u003c/li\u003e\n\u003cli\u003eZhao, G., Liu, Z., Meng, X., Zhang, R., Gu, Q., \u0026amp; Qi, M. (2023). Energy evolution of sandstone under true triaxial cyclic principal stress. \u003cem\u003eRock and Soil Mechanics, 44\u003c/em\u003e(7), 1875-1890. https://doi.org/10.16285/j.rsm.2023.1757\u003c/li\u003e\n\u003cli\u003eZheng, G., Cheng, X. S., Zhou, H. Z., Zhang, T. Q., Yu, X. X., Diao, Y., Wang, R. Z., Yi, F., Zhang, W. B., \u0026amp; Guo, W. (2022). Resilient evaluation and control in geotechnical and underground engineering. \u003cem\u003eChina Civil Engineering Journal, 55\u003c/em\u003e(7), 1-38.\u003c/li\u003e\n\u003cli\u003eZheng, G. (2022). Method and application of deformation control of excavations in soft ground. \u003cem\u003eChinese Journal of Geotechnical Engineering, 44\u003c/em\u003e(1), 1-36. (in Chinese)\u003c/li\u003e\n\u003cli\u003eZheng, G. S., Sui, W. H., Zhang, G. L., Chen, J. X., \u0026amp; Zhang, D. Y. (2023). Propagation and sealing efficiency of chemical grouting in a two-dimensional fracture network with flowing water. \u003cem\u003eInternational Journal of Mining Science and Technology, 33\u003c/em\u003e(7), 903-917.\u003c/li\u003e\n\u003cli\u003eZhong, Z., Deng, R., Zhang, J., \u0026amp; Hu, X. (2020). Fracture properties of jointed rock infilled with mortar under uniaxial compression. \u003cem\u003eEngineering Fracture Mechanics, 228\u003c/em\u003e, 106822. https://doi.org/10.1016/j.engfracmech.2019.106822\u003c/li\u003e\n\u003cli\u003eZhou, C., Hu, Y. J., Xiao, T., et al. (2023a). Analytical model for reinforcement effect and load transfer of pre-stressed anchor cable with bore deviation. \u003cem\u003eConstruction and Building Materials, 379\u003c/em\u003e(5), 131219. https://doi.org/10.1016/j.conbuildmat.2023.131219\u003c/li\u003e\n\u003cli\u003eZhou, C., Huang, C., Chen, Y. D., et al. (2023b). Development of a novel resilient anchor cable and its large shear deformation performance. \u003cem\u003eInternational Journal of Rock Mechanics and Mining Sciences, 163\u003c/em\u003e, 105293.\u003c/li\u003e\n\u003cli\u003eZhou, C., Ma, W. C., \u0026amp; Sui, W. H. (2022). Transparent soil model test of a landslide with umbrella-shaped anchors and different slope angles in response to rapid drawdown. \u003cem\u003eEngineering Geology, 307\u003c/em\u003e(4), 1-14.\u003c/li\u003e\n\u003cli\u003eZhu, G. (2011). A three-dimensional rock block system of complex rock mass based on hierarchical rock mass structure model. \u003cem\u003eChinese Journal of Rock\u003c/em\u003e\u003cem\u003e Mechanics and Engineering, 30\u003c/em\u003e(5), 895-906.\u003c/li\u003e\n\u003cli\u003eZhu, Z., Yang, S., Ranjith, P. G., Tian, W., Tian, H., Zheng, J., Jiang, G., \u0026amp; Dou, B. (2023). A comprehensive review on mechanical responses of granite in enhanced geothermal systems (EGSs). \u003cem\u003eJournal of Cleaner Production, 383\u003c/em\u003e, 135378.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"geoenvironmental-disasters","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"gedi","sideBox":"Learn more about [Geoenvironmental Disasters](http://geoenvironmental-disasters.springeropen.com)","snPcode":"40677","submissionUrl":"https://submission.nature.com/new-submission/40677/3","title":"Geoenvironmental Disasters","twitterHandle":"@SpringerOpen","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Rock Engineering Resilience, Dynamic Evolution Process, Complex System Science, Resilience Evaluation, Bolt-Grouting System","lastPublishedDoi":"10.21203/rs.3.rs-5483583/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5483583/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eRock engineering systems face escalating threats from extreme climatic events and the complexities of deep engineering, necessitating robust resilience to withstand multi-hazard disturbances. Traditional methods, based on static equilibrium analysis, prove unsuited to address the dynamic, nonlinear interactions inherent in these systems. This study proposes a resilience-oriented framework for rock engineering, emphasizing the system's capacity to maintain or rapidly recover functionality following disturbances. The study proposes a conceptual model, evaluation method, and enhancement techniques to improve rock engineering resilience, based on the complex system science. A unified disaster resilience management system is proposed, synergizing multi-field monitoring, risk assessment, and rapid recovery strategies. Three resilience-enhancing techniques are presented, including grouting reinforcement, resilient anchor support, and high-pressure anchor injection-spraying collaborative control, optimize stress redistribution and fracture resistance in rock masses. The research provides theoretical foundations and actionable strategies to reconcile the safety-sustainability dichotomy in rock engineering, particularly for deep tunneling and slope stabilization projects. By redefining resilience as a quantifiable system property rather than a qualitative goal, the framework enables data-driven lifecycle management of geotechnical infrastructure.\u003c/p\u003e","manuscriptTitle":"Resilience of Rock Engineering: Concept, Mechanism, Evaluation and Enhancement","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-23 11:36:14","doi":"10.21203/rs.3.rs-5483583/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Accepted","date":"2025-05-06T08:58:39+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-04T10:06:06+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-27T17:01:16+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"75891049801102412316405567960136059418","date":"2025-04-27T16:51:22+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"198603254192955400451628131261356703170","date":"2025-04-27T14:29:13+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"213213015032311913744391690582182539805","date":"2025-04-22T15:16:31+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-04-22T14:06:37+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-14T09:04:22+00:00","index":"","fulltext":""},{"type":"submitted","content":"Geoenvironmental Disasters","date":"2025-04-11T05:02:39+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"geoenvironmental-disasters","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"gedi","sideBox":"Learn more about [Geoenvironmental Disasters](http://geoenvironmental-disasters.springeropen.com)","snPcode":"40677","submissionUrl":"https://submission.nature.com/new-submission/40677/3","title":"Geoenvironmental Disasters","twitterHandle":"@SpringerOpen","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1eda950f-26cc-4a85-a0ce-c0acf01c8500","owner":[],"postedDate":"April 23rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-06-02T15:58:59+00:00","versionOfRecord":{"articleIdentity":"rs-5483583","link":"https://doi.org/10.1186/s40677-025-00325-9","journal":{"identity":"geoenvironmental-disasters","isVorOnly":false,"title":"Geoenvironmental Disasters"},"publishedOn":"2025-05-26 15:57:02","publishedOnDateReadable":"May 26th, 2025"},"versionCreatedAt":"2025-04-23 11:36:14","video":"","vorDoi":"10.1186/s40677-025-00325-9","vorDoiUrl":"https://doi.org/10.1186/s40677-025-00325-9","workflowStages":[]},"version":"v1","identity":"rs-5483583","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5483583","identity":"rs-5483583","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}