Rapid detection of embedded steel bars using scanning eddy current thermography

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Kodah, Chen Zhang, Md Mosfikur Rohan, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7182368/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract To rapidly visualize steel reinforcements in existing reinforced concrete (RC) structures is crucial prior to undertaking strengthening and repair operations. This study proposes a novel non-destructive evaluation (NDE) method, scanning eddy current thermography (ECT), for visualization of steel bars embedded in RC structures. A scanning ECT system was specifically developed, aiming at detecting steel bars with varying diameters, from 6 mm to 36 mm, in two RC specimens. The results demonstrated that the scanning ECT system is capable of visualizing steel bars with diameters exceeding 6 mm at a cover depth of 20 mm. The heating was conducted using a pre-defined path, with a duration of 1 minute. A multi-physics numerical simulation was performed, which agreed well with the experimental results of thermal response. This study highlights the potential of ECT as a NDE technique for the inspection of steel reinforcement in RC structures. reinforced concrete (RC) steel bars eddy current thermography (ECT) non-destructive evaluation (NDE) Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 1. Introduction Accurate detection of steel reinforcement within reinforced concrete (RC) structures is critical before operations of strengthening, repair, and maintenance ([ 1 ], [ 2 ]). As such, various non-destructive evaluation (NDE) methods have emerged as indispensable tools for locating and characterizing steel reinforcement in RC structures ([ 3 ]-[ 5 ]). While NDE techniques are not without limitations - such as restricted depth penetration, sensitivity to environmental conditions, and potential interference from adjacent reinforcement - they are often capable determining key parameters, including reinforcement diameter, cover depth, type, and condition of corrosion ([ 6 ]-[ 11 ]). By reducing the need for invasive procedures, NDE methods help preserve the structural integrity of RC elements ([ 7 ],[ 9 ]). Among the most widely used NDE techniques for locating reinforcement in RC structures are electromagnetic cover meters [ 12 ], which provide valuable information about the position, spacing, and approximate depth of reinforcement [ 13 ]. However, they are limited in their ability to generate detailed visual representations of reinforcement layouts. For instance, Yokota et al. [ 14 ] demonstrated the use of a probe coil to detect reinforcement bars and estimate their diameter and cover depth. Despite their utility, the lack of visualization capabilities in conventional cover meters have resulted in a scarcity of comprehensive experimental datasets, particularly those that include visual images of test specimens [ 15 ]. Recent technological advancements are broadening the scope of NDE methods by integrating complementary techniques such as eddy current thermography (ECT) ([ 16 ],[ 17 ]). ECT has shown significant promise for enhancing the diagnostic capabilities of NDE in RC structures. These anomalies create detectable temperature gradients, which can be captured using thermal cameras. ECT offers several advantages, including ease of implementation, and cost-effectiveness ([ 14 ],[ 18 ]). The resulting heat distribution allows for precise thermal analysis, enabling the identification of interfacial defects such as debonding, delamination, or voids that disrupt heat transfer across layers [ 19 ]. Unlike alternative heating methods, such as microwave or inductive heating, resistive heating ensures consistent thermal application across the target area, thereby improving diagnostic reliability [ 20 ]. However, based on the previous research on the detection of steel bars embedded in RC structures, there are currently two unsolved issues, namely, easy visualization and high accuracy. To address these issues, this experiment has further proven that ECT propose an effective and fast method to visualize steel bars embedded in concrete structures. However, this study has two main objectives, with each driven by one novelty as following: (i) two RC specimens will be constructed and tested under ECT, and a detailed multi-physics numerical simulation is proposed in this study. The heat generation and transferring mechanism will be revealed, and (ii) a scanning ECT system will be developed and used for rapid visualization of steel bars embedded in concrete. The remainder of this paper is structured as follows: Section 2 introduces methodology including principle, data, and materials; Section 3 presents the specimens fabrication, specimen detailed, thermographic analysis; Section 4 presents experimental results tested by scanning ECT system and prediction results given by numerical simulations; and Section 5 summarizes the new findings obtained from this study. 2. Principle of ECT The principle of ECT is based on detecting debonding gaps by analyzing anomalies in the temperature distribution of the steel bars [ 21 ]. Induced eddy currents uniformly heat the steel, but localized temperature variations can occur due to material defects, such as debonding gaps. These gaps disrupt the heat transfer from the steel bars to the surrounding concrete, creating high-temperature regions directly above the gaps [ 22 ]. The temperature distribution’s temporal and special variations are related to the thermal properties of material(s) and source of heat as determined by the equation as: $$\:\frac{\partial\:T}{\partial\:t}=\:\frac{\lambda\:}{\rho\:{C}_{p}}\:\left(\:\frac{{\partial\:}^{2}T}{\partial\:{x}^{2}}+\:\frac{{\partial\:}^{2}T}{\partial\:{y}^{2}}+\:\frac{{\partial\:}^{2}T}{\partial\:{Z}^{2}}\:\:\right)+\:\frac{1}{\rho\:{C}_{p}}\:q(x,y,z,t)$$ 1 where \(\:T\) means the temperature distribution; \(\:\lambda\:\) is the heat conductivity of the RC; \(\:\rho\:\) and \(\:{C}_{p}\) are the density and specific heat, respectively; and \(\:q\left(x,y,z,t\right)\:\) is the heat generated per unit material, which comes from the induced eddy current, see Fig. 1 . In the heating stage, with a certain excitation, the electrical conductivity and permeability of the conductive material determine the eddy current distribution, whereas the heat flow is affected not only by the eddy currents but also the thermal conductivity and emissivity of material. Hence, the heat dissipation of the steel bars completely depends on thermal conductivity and emissivity. To simplify the heat conduction model, transient excitation is utilized for shortening the heating stage. Table 1 shows the thermal properties of different parts in RC. In this study, RC specimens were subjected to a controlled flow of alternating current through a coil, generating a time - varying magnetic field, see Fig. 1 . When positioned near a conductive material, such as steel, this magnetic field induces circulating currents—commonly referred to as eddy currents - within the material. The heat produced by these currents increases the temperature of the steel bars, and a thermographic camera captures the surface temperature profile of the concrete. This thermal data helps reveal critical details about the embedded reinforcement. Studies have demonstrated ECT's accuracy in detecting reinforcement defects and material inconsistencies. Future sections of this study will present the observed temperature variations and experimental results to further confirm the reliability and accuracy of ECT for RC analysis. Table 1 Thermal properties of different parts in RC structures. Materials \(\:k\) (W/m·K) \(\:c\) (J/kg·K) \(\:\rho\:\) (kg/m 3 ) Concrete 1.355 1091.91 2450 Steel 47.45 433.13 7850 3. Materials The concrete used was made in the laboratory with a good setting time, the concrete mixture used to construct the RC had a design compressive strength of 30 MPa, see Fig. 2a . The cement was a commercial product with a grade of C32.5 according to Chinese code GB/T17671-1999 [23], see Fig. 2b . The steel bars were made by Q235 steel, with a yield strength of 235 MPa. Coarse aggregates, see Fig. 2c was retained and collected from the 4.7 mm sieve compartment which was suitable for the concrete mix. 4. Methods 4.1. Design of specimens In this study, two specimens were prepared, see Fig. 3 . Specimen RC_1 was an RC block with steel bars diameter of 6 mm, 12 mm, and 18 mm, and Specimen RC_2 was a RC block with steel bars diameter of 22 mm, 28 mm, and 36 mm. Table 2 Design and parameters of specimen. Specimen ID \(\:\text{L}\text{e}\text{n}\text{g}\text{t}\text{h}\times\:\text{W}\text{i}\text{d}\text{t}\text{h}\times\:\text{H}\text{e}\text{i}\text{g}\text{h}\text{t}\) (mm) Diameter of steel bar (mm) Depth of reinforcement (mm) RC_1 400 \(\:\times\:\) 300 \(\:\times\:\) 100 6, 12, 18 20 RC_2 22, 28, 36 4.2. Fabrication of specimens The preparation of the specimens involved a systematic five-step process (Fig. 3 ): (a) the collection of six steel bars with varying diameters, as specified in Table 2 to meet the experimental requirements; (b) the precise arrangement of the steel bars within the mold to ensure proper alignment and spacing; (c) the preparation of the concrete mix, followed by pouring it into the mold containing the steel bars, and subsequently vibrating the mold to minimize voids and ensure uniform compaction of the RC blocks; Within both specimens, the vertical steel reinforcement consisted of deformed bars placed at regular intervals of 100 mm, measured from the center of one bar to the next, as illustrated in Fig. 3 a. A concrete cover of 100 mm was maintained on the tested side, as depicted in Fig. 3 b value consistent with common practices in the construction field, where concrete covers typically range from 10 mm to 50 mm depending on the exposure environment and structural requirements. (d) demolding the specimens after a curing period of seven days and cleaning the surrounding areas to remove any residual concrete or debris. 4.3. Thermographic analysis The thermal profiles for both specimens were analyzed, see Fig. 4 . Temperature contract (TC) is introduced to analyze the thermal profile, which are defined as: \(\:TC(x,y,t)=T(x,y,t)-T(x,y,0)\) (2) where \(\:TC(x,y,t)\) is the temperature contrast at time of \(\:t\) , \(\:T(x,y,t)\) is the measured temperature at time \(\:t\) , and \(\:\:T(x,y,0)\) is the temperature at \(\:t\:=0\) , i.e., the beginning of the heating of the specimen using ECT system. \(\:TC\) is used in lieu of \(\:T\) to eliminate the influence of different room temperatures for different specimens. 4.4. Setup of an ECT system An ECT system, comprising a cycler heating coil powered by an electrical current of 220 V, was employed to heat the RC specimens. The specimens were positioned on a lifting platform table, insulated with a thick foam plate to minimize heat loss to the surroundings. The testing procedure was divided into two distinct stages: (i) the first stage involved a heating phase lasting 1 minute, during which the specimens were subjected to controlled thermal excitation at a scanning path in Fig. 5 b, and (ii) the second stage consisted of a cooling phase lasting 2 minutes, allowing the specimens to gradually return to ambient conditions. A Fotric thermal camera with a resolution of 320 × 240 pixels, as shown in Fig. 5 , was utilized to monitor and record the changes in surface temperature on the concrete specimens. The infrared camera was positioned at a stand-off distance of 300 mm from the specimen to ensure optimal imaging accuracy and clarity. This experimental setup enabled precise observation and analysis of the thermal response of the RC specimens under controlled heating and cooling conditions. 5. Experimental results The thermogram images of all specimens at various time intervals are presented in Fig. 6. Analysis of these images reveals that, after a specific duration, the regions exhibiting high TC correspond accurately to the actual locations and geometries of the embedded steel bars within the specimens. For steel bars with thicknesses ranging from 6 mm to 36 mm, their geometric shapes, sizes, and positions are distinctly reflected in the high-temperature regions of the TC images. However, as the temperature of the steel bar on the detection surface decreases, the clarity of the corresponding regions in the thermogram diminishes, resulting in a relatively blurred response. Despite this reduction in clarity, the positions of the steel bars continue to align with the high TC areas in the images. This phenomenon suggests that the thermal contrast above the detected regions becomes more transparent as the thickness of the steel bar increases, leading to clearer and more pronounced imaging effects. Conversely, for thinner steel bars, the thermal contrast is less distinct, resulting in reduced clarity in the thermogram. These observations highlight the relationship between steel bar thickness and the effectiveness of thermal imaging in accurately identifying reinforcement characteristics within concrete structures. To clearly present the results in Fig. 7. in a two-dimensional format, the peak TC distribution was observed specifically over the regions corresponding to the steel bars within the specimens. In contrast, the remaining areas of the specimens, particularly the edges of the RC, exhibited significantly lower TC values. These areas demonstrated a steady thermal profile, characterized by a straight line with only minor fluctuations. This distinct contrast in TC distribution highlights the localized heating effect over the steel bars, while the surrounding concrete regions remained thermally stable, further emphasizing the effectiveness of thermal imaging in identifying reinforcement locations within the structure. For specimen RC_1, which contains steel bars with thicknesses of 6 mm, 12 mm, and 18 mm, a high TC area, indicative of the presence of steel bars, is observed within the detected region. In the solid concrete areas, the temperature trend remains stable at approximately 3.0 K, as illustrated in Fig. 7a . Similarly, for specimen RC_2, which includes steel bars with thicknesses of 22 mm, 28 mm, and 36 mm, a high TC area corresponding to the steel bars is also evident in the detected region. In this case, the temperature trend in the solid concrete areas stabilizes at approximately 6.0 K, as shown in Fig. 7b . From the edges of the RC, the temperature gradually increases toward the center of the detected area, reaching its maximum value and forming a sharp TC peak at the center point. Subsequently, the TC gradually decreases from this peak value of 3.0 K for RC_1 and 6.0 K for RC_2 (see Fig. 7 ) toward the opposite edge of the concrete. Upon reaching the concrete edge, the TC stabilizes once again. This consistent increase in TC from the edges toward the center, followed by a symmetrical decrease, demonstrates that the temperature distribution along the x and y axes can be effectively used to determine the precise position of the steel bars. By analyzing the temperature profiles along these axes, it is evident that the location of the steel bars can be accurately identified through the TC distribution. This observation confirms that thermal imaging, combined with TC analysis, provides a reliable method for pinpointing the position of reinforcement within RC structures. The sharp TC peaks at the center of the detected areas, coupled with the symmetrical temperature gradients, further validate the effectiveness of this approach in non-destructively assessing the internal configuration of RC elements. The total testing duration for each specimen was three minutes, comprising one minute for heating the specimens and two minutes for cooling. During the cooling phase, which lasted for two minutes, the temperature distribution was monitored at specific points, as illustrated in Fig. 8 . At points A and E, located at the edges of the RC specimens, the absence of steel bars resulted in moderate temperature levels throughout the cooling period. In contrast, at points B, C, and D, which correspond to the locations of the steel bars, the TC reached its highest peak within one minute of heating due to the presence of the reinforcement. Following this peak, the time history of the TC gradually decreased over the two-minute cooling period, eventually stabilizing the temperature of the steel bars. This behavior highlights the distinct thermal response of areas with and without steel reinforcement, demonstrating the effectiveness of thermal imaging in identifying and characterizing embedded steel bars within concrete structures. 6. Comparison between numerical simulation and experimental results To reveal the mechanism of using ECT to visualize steel bars embedded in concrete, a numerical simulation was carried out using COMSOL Multiphysics software. Select specimen RC_1, see Fig. 9 shows a schematic diagram of the finite element model established with the material parameters of each part are the same as shown in Table 2 . The results, see Fig. 1 0 exhibit strong agreement between the numerical simulations and experimental data for the TC distributions at different time intervals. The numerical results demonstrate fewer noisy data points, providing a clearer and more consistent representation of the thermal behavior at the detected positions. Even at t = 60 s, the heat generated by the ECT is modeled as being uniformly applied to the surface of the RC for simplicity. This assumption aligns well with the experimental observations, further validating the accuracy of the numerical approach in capturing the thermal response of the RC specimens. The close correspondence between the numerical and experimental results underscores the reliability of the simulation model in predicting TC distributions and reinforces its utility for analyzing the thermal behavior of RC structures under ECT. The results demonstrate excellent agreement between the numerical simulations and experimental data regarding the distributions of TC along the x and y directions at the centerlines at t = 120 s, see Fig. 1 1 . While the experimental results exhibit noticeable fluctuations, likely due to measurement noise or environmental variability, the numerical simulations produce smooth and consistent curves. This smoothness in the numerical results can be attributed to the idealized conditions and controlled parameters used in the simulation model. Despite the differences in fluctuation levels, the overall trends and peak values of TC in both the numerical and experimental results align closely, validating the accuracy and reliability of the numerical approach in predicting the thermal behavior of the RC specimens. This strong correlation highlights the effectiveness of the simulation model in capturing the key thermal characteristics observed in the experimental study. Based on the numerical model, Fig. 12 illustrates the distribution of TC along the vertical direction at different time intervals for specimen RC_1 at t = 60 s. The results reveal the presence of a low-temperature region at the bottom of the RC, a phenomenon not captured in the experimental measurements. This discrepancy can be attributed to the lower thermal conductivity of the material beneath the RC, which limits heat transfer to the lower layers. As heat is continuously transferred downward from the upper surface of the RC, the thermal contrast gradually diminishes with increasing depth. This behavior aligns with the expected thermal diffusion characteristics of the material, highlighting the ability of the numerical model to capture subtle thermal gradients that may not be evident in experimental tests due to measurement limitations or environmental factors. 7. Conclusions This study introduces a novel NDE method, ECT, for visualization of steel bars embedded in RC structures. Through a combination of experimental tests and numerical simulations, the following key findings were established: ECT enables rapid and accurate visualization of steel reinforcement within concrete, providing a reliable alternative to traditional NDE techniques. ECT demonstrates superior performance in evaluating RC specimens compared to other NDE methods, offering enhanced precision and efficiency. For a concrete cover thickness of 100 mm, the optimal detection time was determined to be approximately 60 seconds, highlighting the influence of cover depth on the thermal response. Numerical simulations revealed that the TC gradually increases from the heating surface downward, with the temperature on the steel bars at the detected position being significantly higher than that at the concrete edges. This investigation represents a foundational step in the application of ECT for visualization of embedded steel bars. However, further research is necessary to address several challenges, including the reduction of noise in thermograms, the expansion of experimental datasets, and the development of more accurate methods for calculating defect areas under higher levels of measurement noise. These advancements will enhance the reliability and applicability of ECT in practical structural assessments. Declarations Availability of data The experimental and numerical TC responses of all the specimens are available by request from the corresponding author. Competing interests The authors declare that they have no competing interests. CRediT author statement Xingxing Zou: Conceptualization, Methodology, Funding support, Writing- Original draft preparation, Writing-Reviewing and Editing. Joseph N. Kodah Jr: Data acquisition, Writing- Original draft preparation. Chen Zhang: Data acquisition. Md Mosfikur Rohan: Data acquisition. Mingmin Ding: Conceptualization, Methodology. 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Actuators A: Phys. 309 , 111999 (2020). https://doi.org/10.1016/j.sna.2020.111999 Ding, S., Tian, G., Zhu, J., Chen, X., Wang, Y., Chen, Y.: Characterisation and evaluation of paint-coated marine corrosion in carbon steel using eddy current pulsed thermography. NDT E Int. 130 , 102678 (2022). https://doi.org/10.1016/j.ndteint.2022.102678 Standardization Administration of China: Method of testing cements - Determination of strength. GB/T 17671 – 1999 (1999) Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted 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-7182368","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":554290603,"identity":"1ad1ef85-d1b1-4cc4-9337-b799a82c0870","order_by":0,"name":"Xingxing Zou","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAtklEQVRIie3PsQrCMBCA4SsHmQJ1jIPvEBE65U1cLgjZfIMOhYIdu/oYQsE55UDHvkIeoe4dbEcHadwc8i233M9xAEnyjxDAh3nmiH2IT2ie20acdPylJdGDLDZR23kj954mYzuGAqA0x9VEsdSepLN3Bhfg4c7VWqJRkCfFS/LUWcWxiWbb1dlFRSboPRHbG6KISxQviXeHKwvUFPNL3vb1OE5m17bDK4ylWU8+0W/rSZIkyTdvjc4+ysepRKsAAAAASUVORK5CYII=","orcid":"","institution":"Nanjing Forestry University","correspondingAuthor":true,"prefix":"","firstName":"Xingxing","middleName":"","lastName":"Zou","suffix":""},{"id":554290604,"identity":"a385491f-400a-4a05-84bf-9c0ced06e2dd","order_by":1,"name":"Joseph N. 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1","display":"","copyAsset":false,"role":"figure","size":51967,"visible":true,"origin":"","legend":"\u003cp\u003eIllustration of ECT to visualize steel bars embedded in concrete.\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7182368/v1/5ef10737b06cd10676885f21.jpg"},{"id":97446860,"identity":"7291c92d-cfae-45c1-9634-b5c215ff04a1","added_by":"auto","created_at":"2025-12-04 12:56:14","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":48950,"visible":true,"origin":"","legend":"\u003cp\u003eMaterials: (a) steel bars, (b) cement, (c) coarse aggregates, (d) sand.\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7182368/v1/e5eaf1b68ab1b7a67eb541e6.jpg"},{"id":97446859,"identity":"829214b8-5fc5-45de-a205-97e7872f6c82","added_by":"auto","created_at":"2025-12-04 12:56:14","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":38184,"visible":true,"origin":"","legend":"\u003cp\u003eConstruction of specimens: (a) RC_1, and (b) RC_2.\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7182368/v1/e6b373c0a86d415b9b89d9d3.jpg"},{"id":97446862,"identity":"3cae1a94-38c2-451a-bc69-b02fa11151da","added_by":"auto","created_at":"2025-12-04 12:56:14","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":24505,"visible":true,"origin":"","legend":"\u003cp\u003eThermographic analysis method of thermogram series.\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7182368/v1/f7daaa34961b51786d7dc478.jpg"},{"id":97446865,"identity":"ba40611e-9046-4c69-a05f-1f3130408b52","added_by":"auto","created_at":"2025-12-04 12:56:14","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":53715,"visible":true,"origin":"","legend":"\u003cp\u003eSetup of an ECT system: (a) actual photo, and (b) ECT movement pattern above a specimen.\u003c/p\u003e","description":"","filename":"5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7182368/v1/ebe2350f86761e29b13b1eb4.jpg"},{"id":97667610,"identity":"980ce1fd-b740-458f-b5f1-6394d3c298c7","added_by":"auto","created_at":"2025-12-08 09:23:53","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":51499,"visible":true,"origin":"","legend":"\u003cp\u003eHeating time intervolve of both specimens: (a) thermogram images capturing the time intervolve of specimen RC_1, and (b) thermogram images capturing the time intervolve of specimen RC_2.\u003c/p\u003e","description":"","filename":"6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7182368/v1/0b59abd63fcf8ffdf17fd00e.jpg"},{"id":97667793,"identity":"3052cb9d-59b3-4f7e-aafd-d2e086476868","added_by":"auto","created_at":"2025-12-08 09:24:16","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":84203,"visible":true,"origin":"","legend":"\u003cp\u003eComparison between RC_1 and RC_2 and the TC fields at different moments: (a) RC\u003cem\u003e_\u003c/em\u003e1, and (b) RC\u003cem\u003e_\u003c/em\u003e2.\u003c/p\u003e","description":"","filename":"7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7182368/v1/dafd837205461b95b09f1c77.jpg"},{"id":97446868,"identity":"430e5023-b716-416c-8c54-401f3fcc02a7","added_by":"auto","created_at":"2025-12-04 12:56:14","extension":"jpg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":88644,"visible":true,"origin":"","legend":"\u003cp\u003eTime history response of temperature contrast (TC) for all the specimens: (a) RC\u003cem\u003e_\u003c/em\u003e1, and (b) RC\u003cem\u003e_\u003c/em\u003e2.\u003c/p\u003e","description":"","filename":"8.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7182368/v1/58f2ac25de97c61be942a44a.jpg"},{"id":97446871,"identity":"1297dc7e-7d49-4ab3-9c0e-6ef7aadba147","added_by":"auto","created_at":"2025-12-04 12:56:14","extension":"jpg","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":75004,"visible":true,"origin":"","legend":"\u003cp\u003eNumerical simulation of the RC (a) geometric model for the RC, and (b) Top and side view.\u003c/p\u003e","description":"","filename":"9.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7182368/v1/42b87a38505396d8acd000ab.jpg"},{"id":97667843,"identity":"04954891-9669-4e84-ae87-2c4dec7d8552","added_by":"auto","created_at":"2025-12-08 09:24:21","extension":"jpg","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":92507,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of tested and simulated results on the time intervolve of both RC specimen: (a) RC_1, and (b) RC_2.\u003c/p\u003e","description":"","filename":"10.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7182368/v1/9bc8ba3a59c830c724e7f6f4.jpg"},{"id":97668448,"identity":"5120d04f-9812-4723-9c8d-32d428edda19","added_by":"auto","created_at":"2025-12-08 09:25:34","extension":"jpg","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":107049,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of experiment and simulated TC fields at different moments of both RC specimens: (a) RC_1, and (b) RC_2.\u003c/p\u003e","description":"","filename":"11.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7182368/v1/6348b37f213280d85f58028c.jpg"},{"id":97668905,"identity":"17b6e8f6-2add-4b0e-bc4b-ca3bba27606f","added_by":"auto","created_at":"2025-12-08 09:26:33","extension":"jpg","order_by":12,"title":"Figure 12","display":"","copyAsset":false,"role":"figure","size":87713,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of experiment and simulated TC time history of both RC specimen: (a) RC\u003cem\u003e_\u003c/em\u003e1, and (b) RC\u003cem\u003e_\u003c/em\u003e2.\u003c/p\u003e","description":"","filename":"12.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7182368/v1/54140e8c3713fcdc40150d5f.jpg"},{"id":102296204,"identity":"8075f9a7-70db-499e-89d7-4c5eca4485c2","added_by":"auto","created_at":"2026-02-10 10:18:06","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1450901,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7182368/v1/861e4d6f-16de-47a9-81c3-22df5e3d9a01.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Rapid detection of embedded steel bars using scanning eddy current thermography","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eAccurate detection of steel reinforcement within reinforced concrete (RC) structures is critical before operations of strengthening, repair, and maintenance ([\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e], [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]). As such, various non-destructive evaluation (NDE) methods have emerged as indispensable tools for locating and characterizing steel reinforcement in RC structures ([\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]-[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]). While NDE techniques are not without limitations - such as restricted depth penetration, sensitivity to environmental conditions, and potential interference from adjacent reinforcement - they are often capable determining key parameters, including reinforcement diameter, cover depth, type, and condition of corrosion ([\u003cspan additionalcitationids=\"CR7 CR8 CR9 CR10\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]-[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]). By reducing the need for invasive procedures, NDE methods help preserve the structural integrity of RC elements ([\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e],[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]).\u003c/p\u003e\u003cp\u003eAmong the most widely used NDE techniques for locating reinforcement in RC structures are electromagnetic cover meters [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], which provide valuable information about the position, spacing, and approximate depth of reinforcement [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. However, they are limited in their ability to generate detailed visual representations of reinforcement layouts. For instance, Yokota et al. [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] demonstrated the use of a probe coil to detect reinforcement bars and estimate their diameter and cover depth. Despite their utility, the lack of visualization capabilities in conventional cover meters have resulted in a scarcity of comprehensive experimental datasets, particularly those that include visual images of test specimens [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Recent technological advancements are broadening the scope of NDE methods by integrating complementary techniques such as eddy current thermography (ECT) ([\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e],[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]). ECT has shown significant promise for enhancing the diagnostic capabilities of NDE in RC structures. These anomalies create detectable temperature gradients, which can be captured using thermal cameras. ECT offers several advantages, including ease of implementation, and cost-effectiveness ([\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e],[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]). The resulting heat distribution allows for precise thermal analysis, enabling the identification of interfacial defects such as debonding, delamination, or voids that disrupt heat transfer across layers [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Unlike alternative heating methods, such as microwave or inductive heating, resistive heating ensures consistent thermal application across the target area, thereby improving diagnostic reliability [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eHowever, based on the previous research on the detection of steel bars embedded in RC structures, there are currently two unsolved issues, namely, easy visualization and high accuracy. To address these issues, this experiment has further proven that ECT propose an effective and fast method to visualize steel bars embedded in concrete structures. However, this study has two main objectives, with each driven by one novelty as following: (i) two RC specimens will be constructed and tested under ECT, and a detailed multi-physics numerical simulation is proposed in this study. The heat generation and transferring mechanism will be revealed, and (ii) a scanning ECT system will be developed and used for rapid visualization of steel bars embedded in concrete.\u003c/p\u003e\u003cp\u003eThe remainder of this paper is structured as follows: Section \u003cspan refid=\"Sec2\" class=\"InternalRef\"\u003e2\u003c/span\u003e introduces methodology including principle, data, and materials; Section \u003cspan refid=\"Sec3\" class=\"InternalRef\"\u003e3\u003c/span\u003e presents the specimens fabrication, specimen detailed, thermographic analysis; Section \u003cspan refid=\"Sec4\" class=\"InternalRef\"\u003e4\u003c/span\u003e presents experimental results tested by scanning ECT system and prediction results given by numerical simulations; and Section \u003cspan refid=\"Sec9\" class=\"InternalRef\"\u003e5\u003c/span\u003e summarizes the new findings obtained from this study.\u003c/p\u003e"},{"header":"2. Principle of ECT","content":"\u003cp\u003eThe principle of ECT is based on detecting debonding gaps by analyzing anomalies in the temperature distribution of the steel bars [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Induced eddy currents uniformly heat the steel, but localized temperature variations can occur due to material defects, such as debonding gaps. These gaps disrupt the heat transfer from the steel bars to the surrounding concrete, creating high-temperature regions directly above the gaps [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. The temperature distribution\u0026rsquo;s temporal and special variations are related to the thermal properties of material(s) and source of heat as determined by the equation as:\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$$\\:\\frac{\\partial\\:T}{\\partial\\:t}=\\:\\frac{\\lambda\\:}{\\rho\\:{C}_{p}}\\:\\left(\\:\\frac{{\\partial\\:}^{2}T}{\\partial\\:{x}^{2}}+\\:\\frac{{\\partial\\:}^{2}T}{\\partial\\:{y}^{2}}+\\:\\frac{{\\partial\\:}^{2}T}{\\partial\\:{Z}^{2}}\\:\\:\\right)+\\:\\frac{1}{\\rho\\:{C}_{p}}\\:q(x,y,z,t)$$\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\\(\\:T\\)\u003c/span\u003e\u003c/span\u003e means the temperature distribution; \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\lambda\\:\\)\u003c/span\u003e\u003c/span\u003e is the heat conductivity of the RC; \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\rho\\:\\)\u003c/span\u003e\u003c/span\u003e and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{C}_{p}\\)\u003c/span\u003e\u003c/span\u003e are the density and specific heat, respectively; and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:q\\left(x,y,z,t\\right)\\:\\)\u003c/span\u003e\u003c/span\u003eis the heat generated per unit material, which comes from the induced eddy current, see Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. In the heating stage, with a certain excitation, the electrical conductivity and permeability of the conductive material determine the eddy current distribution, whereas the heat flow is affected not only by the eddy currents but also the thermal conductivity and emissivity of material. Hence, the heat dissipation of the steel bars completely depends on thermal conductivity and emissivity. To simplify the heat conduction model, transient excitation is utilized for shortening the heating stage. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the thermal properties of different parts in RC.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eIn this study, RC specimens were subjected to a controlled flow of alternating current through a coil, generating a time - varying magnetic field, see Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. When positioned near a conductive material, such as steel, this magnetic field induces circulating currents\u0026mdash;commonly referred to as eddy currents - within the material. The heat produced by these currents increases the temperature of the steel bars, and a thermographic camera captures the surface temperature profile of the concrete. This thermal data helps reveal critical details about the embedded reinforcement.\u003c/p\u003e\u003cp\u003eStudies have demonstrated ECT's accuracy in detecting reinforcement defects and material inconsistencies. Future sections of this study will present the observed temperature variations and experimental results to further confirm the reliability and accuracy of ECT for RC analysis.\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\u003eThermal properties of different parts in RC structures.\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=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMaterials\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:k\\)\u003c/span\u003e\u003c/span\u003e (W/m\u0026middot;K)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:c\\)\u003c/span\u003e\u003c/span\u003e (J/kg\u0026middot;K)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\rho\\:\\)\u003c/span\u003e\u003c/span\u003e (kg/m\u003csup\u003e3\u003c/sup\u003e)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eConcrete\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.355\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1091.91\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2450\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSteel\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e47.45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e433.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e7850\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"3. Materials","content":"\u003cp\u003eThe concrete used was made in the laboratory with a good setting time, the concrete mixture used to construct the RC had a design compressive strength of 30 MPa, see \u003cstrong\u003eFig. 2a\u003c/strong\u003e. The cement was a commercial product with a grade of C32.5 according to Chinese code GB/T17671-1999 [23], see \u003cstrong\u003eFig. 2b\u003c/strong\u003e. The steel bars were made by Q235 steel, with a yield strength of 235 MPa. Coarse aggregates, see \u003cstrong\u003eFig. 2c\u003c/strong\u003e was retained and collected from the 4.7 mm sieve compartment which was suitable for the concrete mix.\u0026nbsp;\u003c/p\u003e"},{"header":"4. Methods","content":"\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\n \u003ch2\u003e4.1. Design of specimens\u003c/h2\u003e\n \u003cp\u003eIn this study, two specimens were prepared, see Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e. Specimen RC_1 was an RC block with steel bars diameter of 6 mm, 12 mm, and 18 mm, and Specimen RC_2 was a RC block with steel bars diameter of 22 mm, 28 mm, and 36 mm.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eDesign and parameters of specimen.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSpecimen ID\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\text{L}\\text{e}\\text{n}\\text{g}\\text{t}\\text{h}\\times\\:\\text{W}\\text{i}\\text{d}\\text{t}\\text{h}\\times\\:\\text{H}\\text{e}\\text{i}\\text{g}\\text{h}\\text{t}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003cp\u003e(mm)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDiameter of steel bar\u003c/p\u003e\n \u003cp\u003e(mm)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDepth of reinforcement\u003c/p\u003e\n \u003cp\u003e(mm)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRC_1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e400\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\times\\:\\)\u003c/span\u003e\u003c/span\u003e300\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\times\\:\\)\u003c/span\u003e\u003c/span\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6, 12, 18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"2\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRC_2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22, 28, 36\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\n \u003ch2\u003e4.2. Fabrication of specimens\u003c/h2\u003e\n \u003cp\u003eThe preparation of the specimens involved a systematic five-step process (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e): (a) the collection of six steel bars with varying diameters, as specified in Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e to meet the experimental requirements; (b) the precise arrangement of the steel bars within the mold to ensure proper alignment and spacing; (c) the preparation of the concrete mix, followed by pouring it into the mold containing the steel bars, and subsequently vibrating the mold to minimize voids and ensure uniform compaction of the RC blocks; Within both specimens, the vertical steel reinforcement consisted of deformed bars placed at regular intervals of 100 mm, measured from the center of one bar to the next, as illustrated in Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ea. A concrete cover of 100 mm was maintained on the tested side, as depicted in Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eb value consistent with common practices in the construction field, where concrete covers typically range from 10 mm to 50 mm depending on the exposure environment and structural requirements. (d) demolding the specimens after a curing period of seven days and cleaning the surrounding areas to remove any residual concrete or debris.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\n \u003ch2\u003e4.3. Thermographic analysis\u003c/h2\u003e\n \u003cp\u003eThe thermal profiles for both specimens were analyzed, see Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e. Temperature contract (TC) is introduced to analyze the thermal profile, which are defined as:\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003ctable id=\"Tabc\" border=\"1\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:TC(x,y,t)=T(x,y,t)-T(x,y,0)\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003ewhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:TC(x,y,t)\\)\u003c/span\u003e\u003c/span\u003e is the temperature contrast at time of \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:t\\)\u003c/span\u003e\u003c/span\u003e, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:T(x,y,t)\\)\u003c/span\u003e\u003c/span\u003e is the measured temperature at time \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:t\\)\u003c/span\u003e\u003c/span\u003e, and\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\:T(x,y,0)\\)\u003c/span\u003e\u003c/span\u003e is the temperature at \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:t\\:=0\\)\u003c/span\u003e\u003c/span\u003e, i.e., the beginning of the heating of the specimen using ECT system. \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:TC\\)\u003c/span\u003e\u003c/span\u003e is used in lieu of \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:T\\)\u003c/span\u003e\u003c/span\u003e to eliminate the influence of different room temperatures for different specimens.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003e4.4. Setup of an ECT system\u003c/h2\u003e\n \u003cp\u003eAn ECT system, comprising a cycler heating coil powered by an electrical current of 220 V, was employed to heat the RC specimens. The specimens were positioned on a lifting platform table, insulated with a thick foam plate to minimize heat loss to the surroundings. The testing procedure was divided into two distinct stages: (i) the first stage involved a heating phase lasting 1 minute, during which the specimens were subjected to controlled thermal excitation at a scanning path in Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003eb, and (ii) the second stage consisted of a cooling phase lasting 2 minutes, allowing the specimens to gradually return to ambient conditions. A Fotric thermal camera with a resolution of 320 \u0026times; 240 pixels, as shown in Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e, was utilized to monitor and record the changes in surface temperature on the concrete specimens. The infrared camera was positioned at a stand-off distance of 300 mm from the specimen to ensure optimal imaging accuracy and clarity. This experimental setup enabled precise observation and analysis of the thermal response of the RC specimens under controlled heating and cooling conditions.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"5. Experimental results","content":"\u003cp\u003eThe thermogram images of all specimens at various time intervals are presented in \u003cstrong\u003eFig. 6.\u003c/strong\u003e Analysis of these images reveals that, after a specific duration, the regions exhibiting high TC correspond accurately to the actual locations and geometries of the embedded steel bars within the specimens. For steel bars with thicknesses ranging from 6 mm to 36 mm, their geometric shapes, sizes, and positions are distinctly reflected in the high-temperature regions of the TC images. However, as the temperature of the steel bar on the detection surface decreases, the clarity of the corresponding regions in the thermogram diminishes, resulting in a relatively blurred response. Despite this reduction in clarity, the positions of the steel bars continue to align with the high TC areas in the images.\u003c/p\u003e\n\u003cp\u003eThis phenomenon suggests that the thermal contrast above the detected regions becomes more transparent as the thickness of the steel bar increases, leading to clearer and more pronounced imaging effects. Conversely, for thinner steel bars, the thermal contrast is less distinct, resulting in reduced clarity in the thermogram. These observations highlight the relationship between steel bar thickness and the effectiveness of thermal imaging in accurately identifying reinforcement characteristics within concrete structures.\u003c/p\u003e\n\u003cp\u003eTo clearly present the results in \u003cstrong\u003eFig. 7.\u003c/strong\u003e in a two-dimensional format, the peak TC distribution was observed specifically over the regions corresponding to the steel bars within the specimens. In contrast, the remaining areas of the specimens, particularly the edges of the RC, exhibited significantly lower TC values. These areas demonstrated a steady thermal profile, characterized by a straight line with only minor fluctuations. This distinct contrast in TC distribution highlights the localized heating effect over the steel bars, while the surrounding concrete regions remained thermally stable, further emphasizing the effectiveness of thermal imaging in identifying reinforcement locations within the structure.\u003c/p\u003e\n\u003cp\u003eFor specimen RC_1, which contains steel bars with thicknesses of 6 mm, 12 mm, and 18 mm, a high TC area, indicative of the presence of steel bars, is observed within the detected region. In the solid concrete areas, the temperature trend remains stable at approximately 3.0 K, as illustrated in \u003cstrong\u003eFig. 7a\u003c/strong\u003e. Similarly, for specimen RC_2, which includes steel bars with thicknesses of 22 mm, 28 mm, and 36 mm, a high TC area corresponding to the steel bars is also evident in the detected region. In this case, the temperature trend in the solid concrete areas stabilizes at approximately 6.0 K, as shown in \u003cstrong\u003eFig. 7b\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003eFrom the edges of the RC, the temperature gradually increases toward the center of the detected area, reaching its maximum value and forming a sharp TC peak at the center point. Subsequently, the TC gradually decreases from this peak value of 3.0 K for RC_1 and 6.0 K for RC_2 (see \u003cstrong\u003eFig. 7\u003c/strong\u003e) toward the opposite edge of the concrete. Upon reaching the concrete edge, the TC stabilizes once again. This consistent increase in TC from the edges toward the center, followed by a symmetrical decrease, demonstrates that the temperature distribution along the x and y axes can be effectively used to determine the precise position of the steel bars.\u003c/p\u003e\n\u003cp\u003eBy analyzing the temperature profiles along these axes, it is evident that the location of the steel bars can be accurately identified through the TC distribution. This observation confirms that thermal imaging, combined with TC analysis, provides a reliable method for pinpointing the position of reinforcement within RC structures. The sharp TC peaks at the center of the detected areas, coupled with the symmetrical temperature gradients, further validate the effectiveness of this approach in non-destructively assessing the internal configuration of RC elements.\u003c/p\u003e\n\u003cp\u003eThe total testing duration for each specimen was three minutes, comprising one minute for heating the specimens and two minutes for cooling. During the cooling phase, which lasted for two minutes, the temperature distribution was monitored at specific points, as illustrated in \u003cstrong\u003eFig. 8\u003c/strong\u003e. At points A and E, located at the edges of the RC specimens, the absence of steel bars resulted in moderate temperature levels throughout the cooling period. In contrast, at points B, C, and D, which correspond to the locations of the steel bars, the TC reached its highest peak within one minute of heating due to the presence of the reinforcement. Following this peak, the time history of the TC gradually decreased over the two-minute cooling period, eventually stabilizing the temperature of the steel bars. This behavior highlights the distinct thermal response of areas with and without steel reinforcement, demonstrating the effectiveness of thermal imaging in identifying and characterizing embedded steel bars within concrete structures.\u003c/p\u003e"},{"header":"6. Comparison between numerical simulation and experimental results","content":"\u003cp\u003eTo reveal the mechanism of using ECT to visualize steel bars embedded in concrete, a numerical simulation was carried out using COMSOL Multiphysics software. Select specimen RC_1, see \u003cstrong\u003eFig.\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e9\u003c/strong\u003e shows a schematic diagram of the finite element model established with the material parameters of each part are the same as shown in \u003cstrong\u003eTable \u003cem\u003e2\u003c/em\u003e\u003c/strong\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe results, see \u003cstrong\u003eFig.\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003cstrong\u003e0\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eexhibit strong agreement between the numerical simulations and experimental data for the TC distributions at different time intervals. The numerical results demonstrate fewer noisy data points, providing a clearer and more consistent representation of the thermal behavior at the detected positions. Even at t = 60 s, the heat generated by the ECT is modeled as being uniformly applied to the surface of the RC for simplicity. This assumption aligns well with the experimental observations, further validating the accuracy of the numerical approach in capturing the thermal response of the RC specimens. The close correspondence between the numerical and experimental results underscores the reliability of the simulation model in predicting TC distributions and reinforces its utility for analyzing the thermal behavior of RC structures under ECT.\u003c/p\u003e\n\u003cp\u003eThe results demonstrate excellent agreement between the numerical simulations and experimental data regarding the distributions of TC along the x and y directions at the centerlines at t = 120 s, see \u003cstrong\u003eFig. 1\u003c/strong\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003cstrong\u003e.\u003c/strong\u003e While the experimental results exhibit noticeable fluctuations, likely due to measurement noise or environmental variability, the numerical simulations produce smooth and consistent curves. This smoothness in the numerical results can be attributed to the idealized conditions and controlled parameters used in the simulation model. Despite the differences in fluctuation levels, the overall trends and peak values of TC in both the numerical and experimental results align closely, validating the accuracy and reliability of the numerical approach in predicting the thermal behavior of the RC specimens. This strong correlation highlights the effectiveness of the simulation model in capturing the key thermal characteristics observed in the experimental study.\u003c/p\u003e\n\u003cp\u003eBased on the numerical model, \u003cstrong\u003eFig. 12\u003c/strong\u003e illustrates the distribution of TC along the vertical direction at different time intervals for specimen RC_1 at t = 60 s. The results reveal the presence of a low-temperature region at the bottom of the RC, a phenomenon not captured in the experimental measurements. This discrepancy can be attributed to the lower thermal conductivity of the material beneath the RC, which limits heat transfer to the lower layers. As heat is continuously transferred downward from the upper surface of the RC, the thermal contrast gradually diminishes with increasing depth. This behavior aligns with the expected thermal diffusion characteristics of the material, highlighting the ability of the numerical model to capture subtle thermal gradients that may not be evident in experimental tests due to measurement limitations or environmental factors.\u003c/p\u003e"},{"header":"7. Conclusions","content":"\u003cp\u003eThis study introduces a novel NDE method, ECT, for visualization of steel bars embedded in RC structures. Through a combination of experimental tests and numerical simulations, the following key findings were established:\u003c/p\u003e\n\u003col style=\"list-style-type: lower-roman;\"\u003e\n \u003cli\u003eECT enables rapid and accurate visualization of steel reinforcement within concrete, providing a reliable alternative to traditional NDE techniques.\u003c/li\u003e\n \u003cli\u003eECT demonstrates superior performance in evaluating RC specimens compared to other NDE methods, offering enhanced precision and efficiency.\u003c/li\u003e\n \u003cli\u003eFor a concrete cover thickness of 100 mm, the optimal detection time was determined to be approximately 60 seconds, highlighting the influence of cover depth on the thermal response.\u003c/li\u003e\n \u003cli\u003eNumerical simulations revealed that the TC gradually increases from the heating surface downward, with the temperature on the steel bars at the detected position being significantly higher than that at the concrete edges.\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eThis investigation represents a foundational step in the application of ECT for visualization of embedded steel bars. However, further research is necessary to address several challenges, including the reduction of noise in thermograms, the expansion of experimental datasets, and the development of more accurate methods for calculating defect areas under higher levels of measurement noise. These advancements will enhance the reliability and applicability of ECT in practical structural assessments.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003e\u003cstrong\u003eAvailability of data\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThe experimental and numerical TC responses of all the specimens are available by request from the corresponding author.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCRediT author statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eXingxing Zou:\u003c/strong\u003e Conceptualization, Methodology, Funding support, Writing- Original draft preparation, Writing-Reviewing and Editing. \u003cstrong\u003eJoseph N. Kodah Jr:\u0026nbsp;\u003c/strong\u003eData acquisition, Writing- Original draft preparation.\u003cstrong\u003e\u0026nbsp;Chen Zhang:\u0026nbsp;\u003c/strong\u003eData acquisition. \u003cstrong\u003eMd Mosfikur Rohan:\u0026nbsp;\u003c/strong\u003eData acquisition. \u003cstrong\u003eMingmin Ding:\u003c/strong\u003e Conceptualization, Methodology.\u0026nbsp;\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThis study was funded by National Natural Science Foundation of China (No. 52208256).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMalhotra, V.M., Carino, N.J.: Handbook on nondestructive testing of concrete. CRC (2003)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBungey, J.H., Grantham, M.G.: Testing of concrete in structures. 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GB/T 17671\u0026thinsp;\u0026ndash;\u0026thinsp;1999 (1999)\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"reinforced concrete (RC), steel bars, eddy current thermography (ECT), non-destructive evaluation (NDE)","lastPublishedDoi":"10.21203/rs.3.rs-7182368/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7182368/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eTo rapidly visualize steel reinforcements in existing reinforced concrete (RC) structures is crucial prior to undertaking strengthening and repair operations. This study proposes a novel non-destructive evaluation (NDE) method, scanning eddy current thermography (ECT), for visualization of steel bars embedded in RC structures. A scanning ECT system was specifically developed, aiming at detecting steel bars with varying diameters, from 6 mm to 36 mm, in two RC specimens. The results demonstrated that the scanning ECT system is capable of visualizing steel bars with diameters exceeding 6 mm at a cover depth of 20 mm. The heating was conducted using a pre-defined path, with a duration of 1 minute. A multi-physics numerical simulation was performed, which agreed well with the experimental results of thermal response. This study highlights the potential of ECT as a NDE technique for the inspection of steel reinforcement in RC structures.\u003c/p\u003e","manuscriptTitle":"Rapid detection of embedded steel bars using scanning eddy current thermography","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-04 12:56:09","doi":"10.21203/rs.3.rs-7182368/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"163a4e27-e285-4ce6-92b0-22b17239e8c0","owner":[],"postedDate":"December 4th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-02-07T12:41:27+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-04 12:56:09","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7182368","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7182368","identity":"rs-7182368","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}