Method for detecting and evaluating chloride ion erosion degree of reinforced concrete structure in marine environment

Abstract

The invention discloses a method for detecting and evaluating the chloride ion erosion degree of a reinforced concrete structure in a marine environment, and the method comprises the steps: obtaining the current shape information of the reinforced concrete structure, comparing the current shape information with the original shape information, and determining the size of a shape missing part as first type information; establishing a design model based on the design information of the reinforced concrete structure, and adjusting the design model according to the first type of information to obtain a demonstration model; acquiring an internal erosion scanning graph of the reinforced concrete structure by using a non-contact electromagnetic field tomography technology; the demonstration model is adjusted based on the erosion scanning graph, a finite element analysis model is generated to conduct structural performance analysis on the reinforced concrete structure, and an analysis result is obtained; the chloride ion erosion degree of the reinforced concrete structure is evaluated according to the analysis result, and an evaluation result is obtained. According to the method, efficient and accurate detection and evaluation of the reinforced concrete structure in the marine environment can be realized, and the problems of destructive detection, inaccurate evaluation and the like in a traditional method are solved.

Description

Technical Field

[0001] The present invention belongs to the technical field of engineering assessment, and in particular relates to a method for detecting and assessing the degree of chloride ion corrosion of reinforced concrete structures in a marine environment. Background Art

[0002] During the service life of reinforced concrete structures, chloride ions from the external environment penetrate the reinforced concrete through the protective layer and produce electrochemical reactions, leading to steel corrosion. Rebar corrosion not only consumes the original steel but also forms rust products at the interface between the steel and concrete. As corrosion progresses, the accumulation of rust products eventually leads to concrete cracking. Cracks in the concrete facilitate chloride ion penetration, accelerating steel corrosion and severely impacting structural reliability. Chloride ion attack is one of the primary causes of reduced resistance and reliability in reinforced concrete structures. Therefore, research on the extent of structural damage caused by chloride ion attack is essential. Summary of the Invention

[0003] In view of this, the present invention proposes a method for detecting and evaluating the degree of chloride ion corrosion of reinforced concrete structures in a marine environment, which can realize efficient and accurate detection and evaluation of reinforced concrete structures in a marine environment, and solves the problems of destructive detection and inaccurate evaluation existing in traditional methods.

[0004] In order to achieve the above object, the present invention provides the following technical solutions: The present invention provides a method for detecting and evaluating the degree of chloride ion corrosion of reinforced concrete structures in a marine environment, comprising: Step S1: obtaining the current shape information of the reinforced concrete structure through 3D laser scanning, and comparing it with the original shape information to determine the volume of the missing part of the shape, and using it as the first type of information; Step S2: establishing a design model based on the pre-acquired design information of the reinforced concrete structure, determining design parameters corresponding to the design model, and adjusting the design model according to the first type of information to obtain a demonstration model of the reinforced concrete structure; Step S3, obtaining a scanning image of the internal corrosion of the reinforced concrete structure using non-contact electromagnetic field tomography technology; Step S4: adjusting the demonstration model based on the erosion scan image, and performing structural performance analysis on the reinforced concrete structure by generating a finite element analysis model to obtain analysis results; Step S45: Evaluate the degree of chloride ion corrosion of the reinforced concrete structure according to the analysis results to obtain an evaluation result.

[0005] Preferably, step S1 includes: Use pulsed or phase-controlled 3D laser scanners to collect billions of point cloud data from multiple sites on the target structure, and eliminate environmental noise through target sphere registration and statistical filtering; Convert the acquired billion-level point cloud data into a triangular mesh surface model with millimeter-level accuracy; The triangular mesh surface model and the original BIM / CAD design model are aligned with each other based on the best fitting of feature points. The three-dimensional Boolean operation is performed using the octree space segmentation and signed distance field (SDF) algorithm to calculate the geometric volume of the defective area on the structural surface.

[0006] Preferably, step S3 includes: An array of frequency-adjustable eddy current sensors is placed on the surface of the reinforced concrete structure corroded by chloride ions, which penetrates the protective layer of the reinforced concrete structure by emitting an alternating electromagnetic field. The alternating electromagnetic field induces chloride ion intrusion into the reinforced concrete structure to form a conductive channel. The local conductivity change causes the electromagnetic field phase lag and amplitude attenuation. The sensor array scans in a spiral path and synchronously collects surface complex impedance data. The frequency domain finite difference method (FDFD) is used to combine the complex impedance data with Maxwell's equations and solve them in three-dimensional discretization. The electromagnetic field distribution inside the reinforced concrete structure is obtained as the solution result. The Tikhonov regularization algorithm is used to deal with the ill-posed characteristics of the electromagnetic inverse problem in the solution, and the conductivity distribution map within a preset depth range inside the reinforced concrete is inverted through iterative optimization as the conductivity data. The conductivity data is coupled with the pre-calibrated chloride ion concentration-conductivity mapping relationship to generate a three-dimensional corrosion scan.

[0007] Preferably, the frequency domain finite difference method (FDFD) is used to combine the complex impedance data with the Maxwell equations and perform a three-dimensional discretization solution, including: By moving a sensor array formed by 32 units in a spiral path on the reinforced concrete surface, each unit is activated in turn to emit electromagnetic waves; The complex impedance responses of adjacent sensors are measured synchronously to form a three-dimensional tensor representation ,in is the sensor number, is the frequency of electromagnetic waves; The complex impedance data is preprocessed, including temperature compensation and outlier removal. The temperature compensation is expressed as: Where, is the complex impedance after temperature compensation, is the measured complex impedance, is the ambient temperature; Outlier removal includes: detecting and replacing outliers in complex impedance data based on Mahalanobis distance; The reinforced concrete structure is divided into Yee grids of preset size and containing PML boundaries. The total number of grids is ; Based on the correspondence between the material properties of each part of the reinforced concrete structure in the demonstration model and each mesh, the material parameter tensor is defined for each voxel in the mesh: in, represents the conductivity tensor of the material; Discretize the frequency domain Maxwell: for the time-harmonic field Discretize the matrix equation and construct the FDFD forward operator: in represents a sparse complex matrix, is the coefficient matrix containing the discretized form of Maxwell's equations, is the excitation source vector is the electric field component, is the magnetic permeability, is the permittivity, is the angular frequency; Extract the surface field and index the matrix according to the sensor position Determine the 3D coordinates of each sensor and extract the surface electric field components from the global electric field solution : Generate a model for the calculation of complex impedance calculated by Poynting vector integration: in, is the simulated complex impedance, is the emission current, is the electric field at the ath sensor, is the conjugate magnetic field at the bth sensor, This is the sensitive area of ​​the sensor.

[0008] Preferably, the Tikhonov regularization algorithm is used to process the ill-conditioned characteristics of the electromagnetic inverse problem in the solution result, and the conductivity distribution map within the preset depth range inside the reinforced concrete is inverted through iterative optimization as the conductivity data, including: A regularized inversion system is constructed to deal with the ill-posed characteristics of the electromagnetic inverse problem in the solution results, including the definition of the objective function: in, represents the measured complex impedance, Represents the conductivity distribution based on The simulated complex impedance tensor, Indicates that the Frobenius norm is used to measure the overall difference of the matrix, is the regularization parameter used to balance the data fitting term and the regularization term. is the three-dimensional Laplace smoothing operator, represents the conductivity distribution to be solved; The adjoint field method is used to avoid explicit differentiation and calculate the Jacobian matrix: in, represents the partial derivative of the complex impedance with respect to conductivity in the Jacobian matrix, represents the forward electric field in the a-th sensor transmission mode, represents the accompanying field in the jth sensor receiving mode, represents the integration area of ​​the kth volume element, represents the volume differential of reinforced concrete structure; Through the joint iterative optimization of multi-frequency data, the conductivity distribution is gradually updated Until the convergence condition is reached, the conductivity distribution map is output as conductivity data.

[0009] Preferably, the step of optimizing through joint iteration of multi-frequency data includes: Step S11, setting the initial conductivity distribution; Step S12: Calculate the simulated complex impedance using the FDFD method based on the current conductivity distribution; Step S13, calculating the residual between the measured complex impedance and the simulated complex impedance; Step S14: updating the conductivity distribution by gradient descent or other optimization algorithms; Step S15: Check whether the residual meets the convergence condition. If so, stop the iteration; otherwise, return to step S12.

[0010] Preferably, step S4 includes: The demonstration model is adjusted based on the erosion scanning diagram to obtain a demonstration model with a chloride ion erosion state demonstration; Based on the material properties of concrete and steel materials under different concentrations of chloride ion corrosion, which were previously measured through experiments, the material properties of the corresponding positions in the demonstration model were reassigned to generate a finite element analysis model; According to the preset test strategy, loads are applied to the finite element analysis model, and structural performance simulation analysis of the reinforced concrete structure is performed to obtain analysis results.

[0011] Preferably, step S5 includes: Determine multiple structural performance parameters of reinforced concrete structures based on analysis results; Obtain the standard structural performance parameters of reinforced concrete structures during the design phase, and calculate the assessment score of the chloride ion corrosion degree of reinforced concrete structures using the following formula: in, represents the evaluation score, represents the participation weight of the preset i-th structural performance parameter, Represents the total number of structural performance parameters, represents the standard structural performance parameter of item i in the design stage, represents the structural performance parameter of the i-th reinforced concrete structure at the current stage; The evaluation results are obtained by simultaneously outputting the evaluation scores and the demonstration model under the chloride ion corrosion state demonstration.

[0012] The present invention has achieved at least the following beneficial effects: 1. This invention enables efficient and accurate detection and assessment of reinforced concrete structures in marine environments, resolving issues such as destructive detection and inaccurate assessments in traditional methods. It provides a scientific and reliable technical means for the maintenance and management of marine infrastructure, ensuring the safe operation of structures, reducing maintenance costs, and extending their service life.

[0013] 2. This technical solution enables efficient and accurate detection of surface defects in reinforced concrete structures, solving the problems of insufficient detection accuracy and complex data processing in traditional methods.

[0014] 3. This technical solution enables efficient and accurate detection of chloride ion corrosion inside reinforced concrete structures, solving the problems of insufficient detection accuracy and complex data processing in traditional methods.

[0015] Other advantages, objectives and features of the present invention will be described in the following description and will be apparent to those skilled in the art to some extent, or those skilled in the art can be taught from the practice of the present invention. The objectives and other advantages of the present invention can be realized and obtained through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to make the purpose, technical solutions and beneficial effects of the present invention more clear, the present invention provides the following drawings for illustration: Figure 1This is a flowchart of the steps of a method for detecting and evaluating the degree of chloride ion corrosion of reinforced concrete structures in a marine environment according to an embodiment of the present invention; Figure 2 A flowchart of the steps for generating the first type of information in an embodiment of the present invention; Figure 3 Flowchart of the steps of joint iterative optimization of multi-frequency data in an embodiment of the present invention. DETAILED DESCRIPTION

[0017] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0018] In order to achieve the above object, the present invention provides the following technical solutions: The present invention provides a method for detecting and evaluating the degree of chloride ion corrosion of reinforced concrete structures in marine environments, referring to Figure 1 ,include: Step S1: obtaining the current shape information of the reinforced concrete structure through 3D laser scanning, and comparing it with the original shape information to determine the volume of the missing part of the shape, and using it as the first type of information; Step S2: establishing a design model based on the pre-acquired design information of the reinforced concrete structure, determining design parameters corresponding to the design model, and adjusting the design model according to the first type of information to obtain a demonstration model of the reinforced concrete structure; Step S3, obtaining a scanning image of the internal corrosion of the reinforced concrete structure using non-contact electromagnetic field tomography technology; Step S4: adjusting the demonstration model based on the erosion scan image, and performing structural performance analysis on the reinforced concrete structure by generating a finite element analysis model to obtain analysis results; Step S45: Evaluate the degree of chloride ion corrosion of the reinforced concrete structure according to the analysis results to obtain an evaluation result.

[0019] The working principle and beneficial effects of the above technical solution are as follows: 3D laser scanning technology is used to obtain the current shape information of a reinforced concrete structure. This information is then compared with the original shape information to determine the volume of the missing shape portion, which serves as the first type of information, thereby enabling a quantitative assessment of the surface corrosion condition of the structure. In practical applications, for example, for a bridge exposed to a long-term marine environment, 3D laser scanning can quickly obtain high-precision shape data. After comparison with the original design shape, the volume of concrete spalling caused by chloride ion corrosion can be accurately calculated, providing an intuitive and quantitative basis for subsequent corrosion assessment. Based on the pre-acquired design information, a design model is established, design parameters are determined, and a demonstration model is generated based on the first type of information. This solves the problem of the model not matching the actual structural state in traditional methods. For example, for a reinforced concrete support column of an offshore platform, the design model includes detailed reinforcement layout and material strength parameters. By combining the missing shape data obtained in step S1 and adjusting the model, a demonstration model is generated that closely matches the actual structure, ensuring the accuracy of subsequent performance analysis. Internal corrosion scans are obtained using non-contact electromagnetic field tomography technology, enabling non-destructive testing of chloride ion corrosion conditions within reinforced concrete structures. In practical applications, such as inspecting the concrete lining of an undersea tunnel, this technology emits an alternating electromagnetic field and uses a sensor array positioned on the structure's surface to collect complex impedance data. This technology can penetrate the concrete cover and detect changes in conductivity caused by chloride ion corrosion. This generates intuitive corrosion scans, providing a basis for visually assessing the extent of corrosion. Based on the corrosion scans, a demonstration model is adjusted and a finite element analysis model is generated for structural performance analysis. The analysis results provide accurate predictions of structural performance. For example, using a concrete retaining wall in a marine environment, after obtaining the corrosion scans, the demonstration model is adjusted accordingly and a finite element analysis model is generated. Through simulation analysis, performance indicators such as load-bearing capacity and deformation can be predicted under varying degrees of corrosion. Based on the analysis results, the degree of chloride ion corrosion is assessed, resulting in a comprehensive and accurate assessment of the corrosion status of reinforced concrete structures. In practical applications, such as the assessment of offshore wind turbine foundations, performance data derived from finite element analysis is combined with specialized evaluation algorithms to quantify the impact of chloride ion corrosion on structural performance, including key indicators such as corrosion depth and remaining service life. Through the present invention, efficient and accurate detection and evaluation of reinforced concrete structures in marine environments can be achieved, solving the problems of destructive detection and inaccurate evaluation in traditional methods, providing scientific and reliable technical means for the maintenance and management of marine infrastructure, ensuring the safe operation of the structure, reducing maintenance costs, and extending the service life of the structure.

[0020] In a specific embodiment, referring to Figure 2 , step S1 includes: Use pulsed or phase-controlled 3D laser scanners to collect billions of point cloud data from multiple sites on the target structure, and eliminate environmental noise through target sphere registration and statistical filtering; Convert the acquired billion-level point cloud data into a triangular mesh surface model with millimeter-level accuracy; The triangular mesh surface model and the original BIM / CAD design model are aligned with each other based on the best fitting of feature points. The three-dimensional Boolean operation is performed using the octree space segmentation and signed distance field (SDF) algorithm to calculate the geometric volume of the defective area on the structural surface.

[0021] The working principle and beneficial effects of the above-mentioned technical solution are as follows: A pulsed or phase-shifted 3D laser scanner is used to collect billions of point cloud data from multiple locations of the target structure. Target sphere registration and statistical filtering are used to eliminate ambient noise, thereby achieving high-precision and comprehensive acquisition of the structure's shape information. In practical applications, such as the inspection of large bridges, pulsed laser scanning can quickly cover large areas of the structure, while phase-shifted laser scanning provides higher precision. Target sphere registration ensures data consistency across multiple locations, and statistical filtering effectively removes random noise during the scanning process, ensuring data purity. By converting the acquired billions of point cloud data into a triangulated surface model with millimeter-level accuracy, efficient conversion from raw point cloud to usable 3D models is achieved. In practical applications, such as detailed inspections of concrete structures, the point cloud data is filtered and denoised, and then specialized 3D reconstruction software is used to convert the discrete point cloud data into a continuous triangulated surface model. This process not only preserves the structure's geometric details but also ensures high consistency between the model and the actual structure with millimeter-level accuracy. By performing a best-fit alignment of the triangular mesh surface model with the original BIM / CAD design model based on feature points, and using octree spatial segmentation and the signed distance field (SDF) algorithm to perform three-dimensional Boolean operations, the geometric volume of the defective area on the structural surface is calculated, thereby achieving accurate quantification of the structural defect. In practical applications, such as the inspection of bridge piers, the alignment of the triangular mesh surface model with the original design model can accurately identify structural deformation and defects. Octree spatial segmentation decomposes complex models into manageable sub-regions, and the signed distance field (SDF) algorithm efficiently calculates the difference between the defective area and the complete model, ultimately obtaining the defect volume, which provides key data support for subsequent erosion assessment. This technical solution enables efficient and accurate detection of surface defects in reinforced concrete structures, solving the problems of insufficient detection accuracy and complex data processing in traditional methods. This solution is particularly suitable for the regular inspection and maintenance of large marine structures, and can significantly improve detection efficiency, reduce detection costs, and provide reliable data support for structural safety assessments.

[0022] In a specific embodiment, step S3 includes: An array of frequency-adjustable eddy current sensors is placed on the surface of the reinforced concrete structure corroded by chloride ions, which penetrates the protective layer of the reinforced concrete structure by emitting an alternating electromagnetic field. The alternating electromagnetic field induces chloride ion intrusion into the reinforced concrete structure to form a conductive channel. The local conductivity change causes the electromagnetic field phase lag and amplitude attenuation. The sensor array scans in a spiral path and synchronously collects surface complex impedance data. The frequency domain finite difference method (FDFD) is used to combine the complex impedance data with Maxwell's equations and solve them in three-dimensional discretization. The electromagnetic field distribution inside the reinforced concrete structure is obtained as the solution result. The Tikhonov regularization algorithm is used to deal with the ill-posed characteristics of the electromagnetic inverse problem in the solution, and the conductivity distribution map within a preset depth range inside the reinforced concrete is inverted through iterative optimization as the conductivity data. The conductivity data is coupled with the pre-calibrated chloride ion concentration-conductivity mapping relationship to generate a three-dimensional corrosion scan.

[0023] The working principle and beneficial effects of the above technical solution are as follows: An array of frequency-adjustable eddy current sensors is deployed on the surface of a reinforced concrete structure corroded by chloride ions. The sensors emit an alternating electromagnetic field that penetrates the protective layer, thereby enabling nondestructive testing of the structure's interior. The alternating electromagnetic field interacts with the conductive channels formed by the chloride ion intrusion, causing local conductivity changes, which in turn leads to phase lag and amplitude attenuation of the electromagnetic field. The sensor array scans along a spiral path, synchronously collecting surface complex impedance data to comprehensively capture the changes in electromagnetic characteristics within the structure. The frequency-domain finite-difference method (FDFD) is used to combine the complex impedance data with Maxwell's equations and solve them in three dimensions, revealing the electromagnetic field distribution within the reinforced concrete structure. The FDFD method discretizes the continuous Maxwell equations into difference equations, enabling efficient computational solutions for complex electromagnetic field problems. This approach not only accurately simulates the propagation characteristics of the electromagnetic field in concrete but also effectively incorporates the complex impedance data into the computational model, thereby improving the accuracy of the simulation results. The Tikhonov regularization algorithm is used to address the electromagnetic inverse problem in the solution, resolving instabilities caused by ill-conditioned characteristics. Through iterative optimization, the conductivity distribution map within a preset depth range inside the reinforced concrete is inverted. This process ensures the stability and reliability of the inversion results, and a reasonable conductivity distribution can be obtained even when the data is noisy or incomplete. Finally, the conductivity data is coupled with the pre-calibrated chloride ion concentration-conductivity mapping relationship to generate a three-dimensional corrosion scan map. This mapping relationship is based on a large amount of experimental data and theoretical analysis, and can accurately convert the change in conductivity into the distribution of chloride ion concentration, thereby realizing the visualization and quantitative evaluation of the corrosion status inside the reinforced concrete structure. Through this technical solution, efficient and accurate detection of the chloride ion corrosion status inside the reinforced concrete structure can be achieved, solving the problems of insufficient detection accuracy and complex data processing in traditional methods. This solution is particularly suitable for structural detection in complex environments, such as marine engineering, bridges and tunnels, etc. It can significantly improve detection efficiency, reduce detection costs, and provide a scientific basis for structural safety assessment and maintenance decisions.

[0024] In a specific embodiment, the frequency domain finite difference method (FDFD) is used to combine complex impedance data with Maxwell's equations and perform a three-dimensional discretization solution, including: By moving a sensor array formed by 32 units in a spiral path on the reinforced concrete surface, each unit is activated in turn to emit electromagnetic waves; The complex impedance responses of adjacent sensors are measured synchronously to form a three-dimensional tensor representation ,in is the sensor number, is the frequency of electromagnetic waves; The complex impedance data is preprocessed, including temperature compensation and outlier removal. The temperature compensation is expressed as: Where, is the complex impedance after temperature compensation, is the measured complex impedance, is the ambient temperature; Outlier removal includes: detecting and replacing outliers in complex impedance data based on Mahalanobis distance; The reinforced concrete structure is divided into Yee grids of preset size and containing PML boundaries. The total number of grids is ; Based on the correspondence between the material properties of each part of the reinforced concrete structure in the demonstration model and each mesh, the material parameter tensor is defined for each voxel in the mesh: in, represents the conductivity tensor of the material; Discretize the frequency domain Maxwell: for the time-harmonic field Discretize the matrix equation and construct the FDFD forward operator: in represents a sparse complex matrix, is the coefficient matrix containing the discretized form of Maxwell's equations, is the excitation source vector is the electric field component, is the magnetic permeability, is the permittivity, is the angular frequency; Extract the surface field and index the matrix according to the sensor position Determine the 3D coordinates of each sensor and extract the surface electric field components from the global electric field solution : Generate a model for the calculation of complex impedance calculated by Poynting vector integration: in, is the simulated complex impedance, is the emission current, is the electric field at the ath sensor, is the conjugate magnetic field at the bth sensor, This is the sensitive area of ​​the sensor.

[0025] In a specific embodiment, the Tikhonov regularization algorithm is used to process the ill-conditioned characteristics of the electromagnetic inverse problem in the solution result, and the conductivity distribution map within a preset depth range inside the reinforced concrete is inverted through iterative optimization as the conductivity data including: A regularized inversion system is constructed to deal with the ill-posed characteristics of the electromagnetic inverse problem in the solution results, including the definition of the objective function: in, represents the measured complex impedance, Represents the conductivity distribution based on The simulated complex impedance tensor, Indicates that the Frobenius norm is used to measure the overall difference of the matrix, is the regularization parameter used to balance the data fitting term and the regularization term. is the three-dimensional Laplace smoothing operator, represents the conductivity distribution to be solved; The adjoint field method is used to avoid explicit differentiation and calculate the Jacobian matrix: in, represents the partial derivative of the complex impedance with respect to conductivity in the Jacobian matrix, represents the forward electric field in the a-th sensor transmission mode, represents the accompanying field in the jth sensor receiving mode, represents the integration area of ​​the kth volume element, represents the volume differential of reinforced concrete structure; Through the joint iterative optimization of multi-frequency data, the conductivity distribution is gradually updated Until the convergence condition is reached, the conductivity distribution map is output as conductivity data.

[0026] In a specific embodiment, referring to Figure 3 , the steps of joint iterative optimization through multi-frequency data include: Step S11, setting the initial conductivity distribution; Step S12: Calculate the simulated complex impedance using the FDFD method based on the current conductivity distribution; Step S13, calculating the residual between the measured complex impedance and the simulated complex impedance; Step S14: updating the conductivity distribution by gradient descent or other optimization algorithms; Step S15: Check whether the residual meets the convergence condition. If so, stop the iteration; otherwise, return to step S12.

[0027] In a specific embodiment, step S4 includes: The demonstration model is adjusted based on the erosion scanning diagram to obtain a demonstration model with a chloride ion erosion state demonstration; Based on the material properties of concrete and steel materials under different concentrations of chloride ion corrosion, which were previously measured through experiments, the material properties of the corresponding positions in the demonstration model were reassigned to generate a finite element analysis model; According to the preset test strategy, loads are applied to the finite element analysis model, and structural performance simulation analysis of the reinforced concrete structure is performed to obtain analysis results.

[0028] The working principle and beneficial effects of the above technical solution are as follows: the demonstration model is adjusted based on the erosion scan image to obtain a demonstration model with a chloride ion erosion state, thereby achieving an accurate simulation of the current actual state of the structure. The erosion scan image provides detailed distribution information of chloride ion erosion within the reinforced concrete structure. This information is used to correct the erosion areas in the demonstration model so that the model can accurately reflect the geometry and physical state of the structure after chloride ion erosion. Based on the material properties of concrete and steel materials under different chloride ion erosion concentrations determined in advance through experiments, the material properties are reassigned to the corresponding positions in the demonstration model to generate a finite element analysis model. This step ensures that the material parameters of the finite element model match the material properties of the actual structure by combining experimental data with the model, thereby improving the accuracy and reliability of the model. According to the preset test strategy, the finite element analysis model is loaded, and the structural performance simulation analysis of the reinforced concrete structure is carried out to obtain the analysis results. Through simulation analysis, the performance of the structure under different load conditions, such as bearing capacity and deformation, can be predicted, providing a scientific basis for structural safety assessment. Through this technical solution, efficient and accurate simulation analysis of the performance of reinforced concrete structures after chloride ion erosion can be achieved. This process not only improves the accuracy of detection and evaluation, but also provides detailed data support for the maintenance and repair of the structure, which helps to formulate reasonable maintenance strategies, extend the service life of the structure, and ensure the safe operation of the structure.

[0029] In a specific embodiment, the process of performing structural performance simulation analysis on a reinforced concrete structure specifically includes: Step 1: Digital Twin Erosion State Mapping Input data: 3D chloride ion corrosion map (spatial resolution 1 mm³, maximum concentration 0.68%), steel bar corrosion distribution map (calculated based on Faraday's law, cross-sectional area loss rate 3.2% to 8.7%); Model adjustment method: import the BIM model into ANSYS SpaceClaim and adjust the model according to the erosion depth. Perform geometric cutting: ( is the initial radius, z is the height coordinate) Dynamic reduction of steel bar diameter: ( , HRB400 grade steel bars) Step 2: Multi-scale material property assignment Concrete material library (based on ASTM C1202 test calibration): Using the Concrete Damaged Plasticity model: Rebar material correction, yield strength degradation: Ultimate elongation decay: The interface bond-slip model uses the exponential decay formula in the CEB-FIP Model Code 2010: ( , is the slip amount) Step 3: Apply and solve multiple load cases Load case settings: Finite element modeling details: Unit type: C3D8R reduced integration unit is used for concrete, and T3D2 truss unit is used for steel bar Contact Definition: Rebar-Concrete Embedded Region Grid size: 10mm in erosion area and 25mm in non-erosion area Solution settings: Dynamic explicit analysis (time step 1e-6s, total duration 2.0s) Step 4: Nonlinear solution and result extraction Solution process monitoring: Iterative convergence criterion: residual force < 0.5% of total internal force. The calculation took 18 hours (192-core CPU cluster). Key output results: Damage evolution analysis: (The red area indicates damage factor d_c>0.95, which means that the material has completely failed) Step 5: Safety Assessment and Life Prediction Time-varying reliability analysis, establishing the limit state equation: The reliability index β is calculated using Monte Carlo simulation (sample number 1e5 times): Remaining life determination: When β < 2.0 (corresponding to a failure probability of 4.5%), an early warning is triggered. In this example, the remaining life is 12.3 years (95% confidence interval 11.6-13.1 years). Engineering verification case: Testing of steel tube concrete columns at a deep-water wharf Input data: Maximum Cl⁻ concentration 0.54%, steel bar cross-sectional loss 6.8% Actual bearing capacity test value: 8920kN Simulation results: Conclusion: The simulation model accurately captures the mechanical behavior of the eroded structure, and the bearing capacity prediction error is less than 5%, meeting the engineering accuracy requirements.

[0030] In a specific embodiment, step S5 includes: Determine multiple structural performance parameters of reinforced concrete structures based on analysis results; Obtain the standard structural performance parameters of reinforced concrete structures during the design phase, and calculate the assessment score of the chloride ion corrosion degree of reinforced concrete structures using the following formula: in, represents the evaluation score, represents the participation weight of the preset i-th structural performance parameter, Represents the total number of structural performance parameters, represents the standard structural performance parameter of item i in the design stage, represents the structural performance parameter of the i-th reinforced concrete structure at the current stage; The evaluation results are obtained by simultaneously outputting the evaluation scores and the demonstration model under the chloride ion corrosion state demonstration.

[0031] The working principle and beneficial effects of this technical solution are as follows: Evaluation results are simultaneously output based on the evaluation score and a demonstration model demonstrating chloride ion corrosion. These results quantify and visually demonstrate the degree of performance degradation of reinforced concrete structures under chloride ion corrosion, providing a scientific basis for structural maintenance decisions. For example, a higher evaluation score indicates a more severe structural performance degradation and requires more urgent maintenance measures. This quantitative assessment can effectively identify structural weaknesses, rationally allocate maintenance resources, and ensure the safety and durability of the structure.

[0032] Finally, it should be noted that the above preferred embodiments are only used to illustrate the technical solutions of the present invention and are not limiting. Although the present invention has been described in detail through the above preferred embodiments, those skilled in the art should understand that various changes can be made in form and details without departing from the scope defined by the claims of the present invention.

Claims

1. A method for detecting and evaluating the degree of chloride ion corrosion of reinforced concrete structures in a marine environment, characterized in that: include: Step S1: obtaining the current shape information of the reinforced concrete structure through 3D laser scanning, and comparing it with the original shape information to determine the volume of the missing part of the shape, and using it as the first type of information; Step S2: establishing a design model based on the pre-acquired design information of the reinforced concrete structure, determining design parameters corresponding to the design model, and adjusting the design model according to the first type of information to obtain a demonstration model of the reinforced concrete structure; Step S3, obtaining a scanning image of the internal corrosion of the reinforced concrete structure using non-contact electromagnetic field tomography technology; Step S4: adjusting the demonstration model based on the erosion scan image, and performing structural performance analysis on the reinforced concrete structure by generating a finite element analysis model to obtain analysis results; Step S45: Evaluate the degree of chloride ion corrosion of the reinforced concrete structure according to the analysis results to obtain an evaluation result.

2. The method for detecting and evaluating the degree of chloride ion corrosion of reinforced concrete structures in a marine environment according to claim 1, characterized in that: Step S1 includes: Use pulsed or phase-controlled 3D laser scanners to collect billions of point cloud data from multiple sites on the target structure, and eliminate environmental noise through target sphere registration and statistical filtering; Convert the acquired billion-level point cloud data into a triangular mesh surface model with millimeter-level accuracy; The triangular mesh surface model and the original BIM / CAD design model are aligned with each other based on the best fitting of feature points. The three-dimensional Boolean operation is performed using the octree space segmentation and signed distance field (SDF) algorithm to calculate the geometric volume of the defective area on the structural surface.

3. The method for detecting and evaluating the degree of chloride ion corrosion of reinforced concrete structures in a marine environment according to claim 1, characterized in that: Step S3 includes: An array of frequency-adjustable eddy current sensors is placed on the surface of the reinforced concrete structure corroded by chloride ions, which penetrates the protective layer of the reinforced concrete structure by emitting an alternating electromagnetic field. The alternating electromagnetic field induces chloride ion intrusion into the reinforced concrete structure to form a conductive channel. The local conductivity change causes the electromagnetic field phase lag and amplitude attenuation. The sensor array scans in a spiral path and synchronously collects surface complex impedance data. The frequency domain finite difference method (FDFD) is used to combine the complex impedance data with Maxwell's equations and solve them in three-dimensional discretization. The electromagnetic field distribution inside the reinforced concrete structure is obtained as the solution result. The Tikhonov regularization algorithm is used to deal with the ill-posed characteristics of the electromagnetic inverse problem in the solution, and the conductivity distribution map within a preset depth range inside the reinforced concrete is inverted through iterative optimization as the conductivity data. The conductivity data is coupled with the pre-calibrated chloride ion concentration-conductivity mapping relationship to generate a three-dimensional corrosion scan.

4. The method for detecting and evaluating the degree of chloride ion corrosion of reinforced concrete structures in a marine environment according to claim 3, characterized in that: The frequency domain finite difference method (FDFD) is used to combine complex impedance data with Maxwell's equations and perform a three-dimensional discretization solution, including: By moving a sensor array formed by 32 units in a spiral path on the reinforced concrete surface, each unit is activated in turn to emit electromagnetic waves; The complex impedance responses of adjacent sensors are measured synchronously to form a three-dimensional tensor representation ,in is the sensor number, is the frequency of electromagnetic waves; The complex impedance data is preprocessed, including temperature compensation and outlier removal. The temperature compensation is expressed as: Where, is the complex impedance after temperature compensation, is the measured complex impedance, is the ambient temperature; Outlier removal includes: detecting and replacing outliers in complex impedance data based on Mahalanobis distance; The reinforced concrete structure is divided into Yee grids of preset size and containing PML boundaries. The total number of grids is ; Based on the correspondence between the material properties of each part of the reinforced concrete structure in the demonstration model and each mesh, the material parameter tensor is defined for each voxel in the mesh: in, represents the conductivity tensor of the material; Discretize the frequency domain Maxwell: for the time-harmonic field Discretize the matrix equation and construct the FDFD forward operator: in represents a sparse complex matrix, is the coefficient matrix containing the discretized form of Maxwell's equations, is the excitation source vector is the electric field component, is the magnetic permeability, is the permittivity, is the angular frequency; Extract the surface field and index the matrix according to the sensor position Determine the 3D coordinates of each sensor and extract the surface electric field components from the global electric field solution : Generate a model for the calculation of complex impedance calculated by Poynting vector integration: in, is the simulated complex impedance, is the emission current, is the electric field at the ath sensor, is the conjugate magnetic field at the bth sensor, This is the sensitive area of ​​the sensor.

5. The method for detecting and evaluating the degree of chloride ion corrosion of reinforced concrete structures in a marine environment according to claim 4, characterized in that: The Tikhonov regularization algorithm is used to deal with the ill-conditioned characteristics of the electromagnetic inverse problem in the solution. Through iterative optimization, the conductivity distribution map within the preset depth range inside the reinforced concrete is inverted as the conductivity data, including: A regularized inversion system is constructed to deal with the ill-posed characteristics of the electromagnetic inverse problem in the solution results, including the definition of the objective function: in, represents the measured complex impedance, Represents the conductivity distribution based on The simulated complex impedance tensor, Indicates that the Frobenius norm is used to measure the overall difference of the matrix, is the regularization parameter used to balance the data fitting term and the regularization term. is the three-dimensional Laplace smoothing operator, represents the conductivity distribution to be solved; The adjoint field method is used to avoid explicit differentiation and calculate the Jacobian matrix: in, represents the partial derivative of the complex impedance with respect to conductivity in the Jacobian matrix, represents the forward electric field in the a-th sensor transmission mode, represents the accompanying field in the jth sensor receiving mode, represents the integration area of ​​the kth volume element, represents the volume differential of reinforced concrete structure; Through the joint iterative optimization of multi-frequency data, the conductivity distribution is gradually updated Until the convergence condition is reached, the conductivity distribution map is output as conductivity data.

6. The method for detecting and evaluating the degree of chloride ion corrosion of reinforced concrete structures in a marine environment according to claim 5, characterized in that: The steps of joint iterative optimization through multi-frequency data include: Step S11, setting the initial conductivity distribution; Step S12: Calculate the simulated complex impedance using the FDFD method based on the current conductivity distribution; Step S13, calculating the residual between the measured complex impedance and the simulated complex impedance; Step S14: updating the conductivity distribution by gradient descent or other optimization algorithms; Step S15: Check whether the residual meets the convergence condition. If so, stop the iteration; otherwise, return to step S12.

7. The method for detecting and evaluating the degree of chloride ion corrosion of reinforced concrete structures in a marine environment according to claim 1, characterized in that: Step S4 includes: The demonstration model is adjusted based on the erosion scanning diagram to obtain a demonstration model with a chloride ion erosion state demonstration; Based on the material properties of concrete and steel materials under different concentrations of chloride ion corrosion, which were previously measured through experiments, the material properties of the corresponding positions in the demonstration model were reassigned to generate a finite element analysis model; According to the preset test strategy, loads are applied to the finite element analysis model, and structural performance simulation analysis of the reinforced concrete structure is performed to obtain analysis results.

8. The method for detecting and evaluating the degree of chloride ion corrosion of reinforced concrete structures in a marine environment according to claim 1, characterized in that: Step S5 includes: Determine multiple structural performance parameters of reinforced concrete structures based on analysis results; Obtain the standard structural performance parameters of reinforced concrete structures during the design phase, and calculate the assessment score of the chloride ion corrosion degree of reinforced concrete structures using the following formula: in, represents the evaluation score, represents the participation weight of the preset i-th structural performance parameter, Represents the total number of structural performance parameters, represents the standard structural performance parameter of item i in the design stage, represents the structural performance parameter of the i-th reinforced concrete structure at the current stage; The evaluation results are obtained by simultaneously outputting the evaluation scores and the demonstration model under the chloride ion corrosion state demonstration.

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