Symbiotic Mechanism for Passive Adaptive Shading: A Physical Intelligence Paradigm for Self-Stabilizing Systems

Symbiotic Mechanism for Passive Adaptive Shading: A Physical Intelligence Paradigm for Self-Stabilizing Systems | 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 Article Symbiotic Mechanism for Passive Adaptive Shading: A Physical Intelligence Paradigm for Self-Stabilizing Systems Bailiang Zhuang, Yuheng Gu, Yu Han This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9446527/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted You are reading this latest preprint version Abstract This paper presents a knowledge driven framework for a passively actuated adaptive shading system enabled by a symbiotic mechanism. The system leverages thermal expansion as its core actuation principle, utilizing a five-panel linkage with spherical joints to achieve multi-degree-of-freedom adjustability. A key innovation is the embedding of a gravity-based self-stabilization condition into the kinematic model, with the building facade serving as an external constraint. This resolves the kinematic indeterminacy inherent in multi degree of freedom mechanisms by distilling the minimum potential energy principle into a design rule, uniquely determining the physical posture (θ = 6.46°) from infinite geometric possibilities. Unlike conventional adaptive systems that merely utilize, depend on, or adapt to their environment, the proposed design symbiotically incorporates the environment as an integral part of its equilibrium mechanism—a previously unexplored paradigm we term “symbiotic physical intelligence.” To navigate the complex design space, a hybrid surrogate-assisted optimization strategy is employed. A quadratic polynomial regression model captures the quasi-linear behavior of summer shading performance, while a Gaussian Process (Kriging) model addresses the stronger non-linearity of the winter amplification ratio. This computationally efficient framework identified an optimal parameter set (β=23°,l=5.0m, etc.) and was further refined via a fine-tuning sensitivity analysis, revealing that a slight adjustment to the hinge coordinate (b=0.6094m) enhances the comprehensive performance score by 7.3% while guaranteeing stability. Annual simulations demonstrate the framework's predictive capability: at 20°N, the system increases comfort hours by 5.5% and reduces cooling energy by 6.1%, with robust performance under varied contact conditions. The work introduces a “fence-like” design paradigm, where the facade is treated as ground, enabling an “install-and-forget” solution. Distinct from existing mechano-intelligence paradigms that rely on complex nonlinear dynamics as computational substrates, this work achieves physical intelligence through gravitational self-stabilization—a deterministic, electronics-free decision-making mechanism. By systematically integrating physics-informed kinematics, data-driven surrogate modeling, and engineering performance validation, this framework provides a replicable methodological paradigm for the design of intelligent, passive building envelopes. Physical sciences/Engineering/Mechanical engineering Earth and environmental sciences/Environmental sciences/Environmental impact Physical sciences/Engineering/Civil engineering Physical sciences/Energy science and technology/Energy modelling Symbiotic mechanism Physical intelligence Knowledge-driven design Surrogate-assisted optimization Passive adaptive shading Thermal expansion actuation Physics-informed modeling Full Text Additional Declarations There is NO Competing Interest. Supplementary Files RawDataandPrograms.docx Raw Data and Programs Cite Share Download PDF Status: Under Review Version 1 posted 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. 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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-9446527","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":627453247,"identity":"07281433-9708-4bad-9196-667a665f4e48","order_by":0,"name":"Bailiang Zhuang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4klEQVRIie3PsQrCMBCA4QuBdgm6RqrtK0QEUSx9FxEydXByjgiddBfqQ/gIalE354JdXJx1EAoKmiqCU1o3wfxLcnDfcAA63S9GscieKlD5PzHXK0DQk5CMVKZ93vuOWOS0eo2qnHAo0CUAUg4nh73LFhjMaD1XETRbClyThCbbRsdnSQkI57GKYNoVuCIJxNywfHbEQElTSYw3cTLSYhESeYRIgs6SsIxAEUKr8hbYAaknG9weM94z8m5xwtECpQOw7X2A4vTmemUz2iiJzLwSuH9cl7P+DKVFtnQ6ne5/ewCkbkHJLE3c/gAAAABJRU5ErkJggg==","orcid":"","institution":"Jiangsu Branch of China Academy of Machinery Science and Technology Group Co., Ltd.","correspondingAuthor":true,"prefix":"","firstName":"Bailiang","middleName":"","lastName":"Zhuang","suffix":""},{"id":627453248,"identity":"dfbfd15e-efcc-436d-b6f9-0f0de3fc7e5d","order_by":1,"name":"Yuheng Gu","email":"","orcid":"","institution":"Jiangsu Branch of China Academy of Machinery Science and Technology Group Co., Ltd.","correspondingAuthor":false,"prefix":"","firstName":"Yuheng","middleName":"","lastName":"Gu","suffix":""},{"id":627453249,"identity":"24fa5611-7d23-4db2-a0ed-50f2328e6300","order_by":2,"name":"Yu Han","email":"","orcid":"","institution":"Jiangsu Branch of China Academy of Machinery Science and Technology Group Co., Ltd.","correspondingAuthor":false,"prefix":"","firstName":"Yu","middleName":"","lastName":"Han","suffix":""}],"badges":[],"createdAt":"2026-04-17 08:51:02","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9446527/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9446527/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108182938,"identity":"99d763fc-e837-4253-a9e5-ddbdb7d5a3e7","added_by":"auto","created_at":"2026-04-30 08:59:42","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1538759,"visible":true,"origin":"","legend":"","description":"","filename":"manu.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9446527/v1_covered_d1eb2fab-cc9d-418d-9d96-458ed857bee6.pdf"},{"id":108168587,"identity":"45f4cc5e-6d14-4f49-b590-67707cc8b082","added_by":"auto","created_at":"2026-04-30 06:32:45","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1657643,"visible":true,"origin":"","legend":"Raw Data and Programs","description":"","filename":"RawDataandPrograms.docx","url":"https://assets-eu.researchsquare.com/files/rs-9446527/v1/e66a32a2b7bef63145208cc8.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Symbiotic Mechanism for Passive Adaptive Shading: A Physical Intelligence Paradigm for Self-Stabilizing Systems","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Symbiotic mechanism, Physical intelligence, Knowledge-driven design, Surrogate-assisted optimization, Passive adaptive shading, Thermal expansion actuation, Physics-informed modeling","lastPublishedDoi":"10.21203/rs.3.rs-9446527/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9446527/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis paper presents a knowledge driven framework for a passively actuated adaptive shading system enabled by a symbiotic mechanism. The system leverages thermal expansion as its core actuation principle, utilizing a five-panel linkage with spherical joints to achieve multi-degree-of-freedom adjustability. A key innovation is the embedding of a gravity-based self-stabilization condition into the kinematic model, with the building facade serving as an external constraint. This resolves the kinematic indeterminacy inherent in multi degree of freedom mechanisms by distilling the minimum potential energy principle into a design rule, uniquely determining the physical posture (θ = 6.46°) from infinite geometric possibilities. Unlike conventional adaptive systems that merely utilize, depend on, or adapt to their environment, the proposed design symbiotically incorporates the environment as an integral part of its equilibrium mechanism—a previously unexplored paradigm we term “symbiotic physical intelligence.” To navigate the complex design space, a hybrid surrogate-assisted optimization strategy is employed. A quadratic polynomial regression model captures the quasi-linear behavior of summer shading performance, while a Gaussian Process (Kriging) model addresses the stronger non-linearity of the winter amplification ratio. This computationally efficient framework identified an optimal parameter set (β=23°,l=5.0m, etc.) and was further refined via a fine-tuning sensitivity analysis, revealing that a slight adjustment to the hinge coordinate (b=0.6094m) enhances the comprehensive performance score by 7.3% while guaranteeing stability. Annual simulations demonstrate the framework's predictive capability: at 20°N, the system increases comfort hours by 5.5% and reduces cooling energy by 6.1%, with robust performance under varied contact conditions. The work introduces a “fence-like” design paradigm, where the facade is treated as ground, enabling an “install-and-forget” solution. Distinct from existing mechano-intelligence paradigms that rely on complex nonlinear dynamics as computational substrates, this work achieves physical intelligence through gravitational self-stabilization—a deterministic, electronics-free decision-making mechanism. By systematically integrating physics-informed kinematics, data-driven surrogate modeling, and engineering performance validation, this framework provides a replicable methodological paradigm for the design of intelligent, passive building envelopes.\u003c/p\u003e","manuscriptTitle":"Symbiotic Mechanism for Passive Adaptive Shading: A Physical Intelligence Paradigm for Self-Stabilizing Systems","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-30 06:32:41","doi":"10.21203/rs.3.rs-9446527/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"communications-engineering","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"commseng","sideBox":"Learn more about [Communications Engineering](http://link.springer.com/journal/44172)","snPcode":"44172","submissionUrl":"https://mts-commseng.nature.com/cgi-bin/main.plex","title":"Communications Engineering","twitterHandle":"@commseng","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"89d6983e-a64b-4309-939a-453b49b09ca0","owner":[],"postedDate":"April 30th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewerAgreed","content":"This content is not available.","date":"2026-04-29T14:15:21+00:00","index":3,"fulltext":"This content is not available."}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":66780616,"name":"Physical sciences/Engineering/Mechanical engineering"},{"id":66780617,"name":"Earth and environmental sciences/Environmental sciences/Environmental impact"},{"id":66780618,"name":"Physical sciences/Engineering/Civil engineering"},{"id":66780619,"name":"Physical sciences/Energy science and technology/Energy modelling"}],"tags":[],"updatedAt":"2026-04-30T06:32:41+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-30 06:32:41","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9446527","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9446527","identity":"rs-9446527","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}