Method and device for evaluating structural performance of cracked reinforced concrete beam

Abstract

The invention provides a cracked reinforced concrete beam structure performance evaluation method and device, and relates to the technical field of reinforced concrete beam performance evaluation.The method comprises the steps that a physical model of a reinforced concrete beam is built, a load test is conducted on the physical model, and actually-measured static response data of the reinforced concrete beam in the loading process is obtained; establishing a nonlinear finite element numerical model of the reinforced concrete beam; performing sensitivity analysis on the material performance parameters of the reinforced concrete beam to obtain optimized parameters of the nonlinear finite element numerical model; performing multi-target parameter optimization on the nonlinear finite element numerical model to obtain a coordinated optimal solution; and inputting the coordinated optimal solution into the nonlinear finite element numerical model to obtain a digital twinborn body of the reinforced concrete beam, and evaluating the structural performance of the cracked reinforced concrete beam through the digital twinborn body. The method solves the problem that the existing evaluation technology is not accurate enough to evaluate the structural performance of the cracked reinforced concrete beam structure in the whole life cycle.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of reinforced concrete beam performance evaluation, in particular to a method and device for evaluating the performance of a cracked reinforced concrete beam structure. BACKGROUND

[0002] Due to the increase in vehicle volume and traffic, medium and short span reinforced concrete bridges are very prone to cracking after serving in harsh environments for many years. The appearance of cracks will cause the accelerated entry of carbonation or chlorides into the concrete, leading to further expansion of the cracks, thereby reducing the ductility, durability and carrying capacity of the reinforced concrete beam. Therefore, it is necessary to evaluate the structural performance of the cracked reinforced concrete beam regularly to ensure its structural safety.

[0003] Currently, the evaluation of the structural performance and carrying capacity of the cracked reinforced concrete beam is mainly carried out by limiting the maximum width of the cracks or based on statistical analysis of crack characteristics. However, since there is no clear relationship between crack characteristics and the structural carrying capacity of the cracked reinforced concrete beam, these methods cannot satisfactorily reproduce the actual response of the cracked reinforced concrete beam structure. Nonlinear finite element analysis is another commonly used numerical method for evaluating the structural performance and carrying capacity of the cracked reinforced concrete beam. However, due to the complexity of crack behavior, there are many uncertainties in nonlinear simulation, which makes it difficult for nonlinear finite element analysis to accurately evaluate the performance of the cracked reinforced concrete beam structure. Therefore, finite element model updating methods are also used to reduce uncertainties. However, crack information as important detection data is rarely included in the finite element model updating process, thereby affecting the accuracy of the evaluation of the cracked reinforced concrete beam structure. SUMMARY

[0004] The present application aims to provide a method and device for evaluating the performance of a cracked reinforced concrete beam structure to improve the above problems. In order to achieve the above-mentioned purpose, the technical solutions adopted by the present application are as follows:

[0005] In a first aspect, the present application provides a method for evaluating the performance of a cracked reinforced concrete beam structure, comprising:

[0006] obtaining parameter information of the reinforced concrete beam;

[0007] constructing a physical model according to the parameter information of the reinforced concrete beam, and performing a load test on the physical model to obtain measured static response data of the reinforced concrete beam during loading, the measured static response data including measured deflection, measured strain and measured apparent damage;

[0008] establishing a nonlinear finite element numerical model of the reinforced concrete beam based on the parameter information;

[0009] Perform a sensitivity analysis on the material performance parameters of the reinforced concrete beam to obtain the optimization parameters of the nonlinear finite element numerical model;

[0010] Perform multi-objective parameter optimization on the nonlinear finite element numerical model through a multi-objective particle swarm optimization algorithm to obtain a coordinated optimal solution, wherein the objective function of the parameter optimization is obtained based on simulated static response data and the measured static response data, and the simulated static response data is calculated through the nonlinear finite element numerical model;

[0011] Input the coordinated optimal solution into the nonlinear finite element numerical model to obtain a digital twin of the reinforced concrete beam, and perform structural performance evaluation of the cracked reinforced concrete beam through the digital twin.

[0012] In a second aspect, the application further provides a device for evaluating the structural performance of a cracked reinforced concrete beam, comprising:

[0013] An acquisition module is configured to acquire parameter information of a reinforced concrete beam;

[0014] A test module is configured to construct a physical model according to the parameter information of the reinforced concrete beam, and perform a load test on the physical model to obtain measured static response data of the reinforced concrete beam during the loading process, wherein the measured static response data includes measured deflection, measured strain and measured apparent damage;

[0015] A construction module is configured to establish a nonlinear finite element numerical model of the reinforced concrete beam based on the parameter information;

[0016] An analysis module is configured to perform a sensitivity analysis on the material performance parameters of the reinforced concrete beam to obtain the optimization parameters of the nonlinear finite element numerical model;

[0017] An optimization module is configured to perform multi-objective parameter optimization on the nonlinear finite element numerical model through a multi-objective particle swarm optimization algorithm to obtain a coordinated optimal solution, wherein the objective function of the parameter optimization is obtained based on simulated static response data and the measured static response data, and the simulated static response data is calculated through the nonlinear finite element numerical model;

[0018] An evaluation module is configured to input the coordinated optimal solution into the nonlinear finite element numerical model to obtain a digital twin of the reinforced concrete beam, and perform structural performance evaluation of the cracked reinforced concrete beam through the digital twin.

[0019] The application has the following beneficial effects:

[0020] The application combines load test and nonlinear finite element analysis, and integrates structural health monitoring and detection data, can comprehensively evaluate the structural performance of the reinforced concrete beam from multiple responses, can accurately study the crack development process of the reinforced concrete by means of the digital twin, and can evaluate the structural performance and residual bearing capacity of the cracked reinforced concrete beam through multiple responses, overcome the uncertainty of numerical simulation in predicting the response of the reinforced concrete beam and the problem that the current method for evaluating the structural performance of the cracked reinforced concrete beam is not efficient and accurate. Meanwhile, the established digital twin can accurately predict the performance of components with the same material and similar stress form without a large number of complex repetitive tests.

[0021] Other features and advantages of the present application will be set forth in the following description, and in part will become apparent from the description, or can be learned by practice of the application as hereinafter described. BRIEF DESCRIPTION OF DRAWINGS

[0022] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the embodiments will be briefly introduced as follows, and it should be understood that the following drawings only show some embodiments of the present application, and therefore should not be regarded as a limitation on the scope, and for those skilled in the art, other related drawings can also be obtained without creative labor on the basis of these drawings.

[0023] Figure 1 A flow chart of the method for evaluating the structural performance of the cracked reinforced concrete beam described in the embodiments of the present application;

[0024] Figure 2 A schematic diagram of the Pareto frontier solution set described in the embodiments of the present application;

[0025] Figure 3 A structural schematic diagram of the device for evaluating the structural performance of the cracked reinforced concrete beam described in the embodiments of the present application.

[0026] In the figure, 901 is an acquisition module, 902 is a test module, 903 is a construction module, 904 is an analysis module, 905 is an optimization module, 906 is an evaluation module, 9041 is a test unit, 9042 is a first calculation unit, 9043 is a second calculation unit, 9044 is a first selection unit, 9051 is a first construction unit, 9052 is a second construction unit, 9053 is an acquisition unit, 9054 is a third calculation unit, 9055 is a third construction unit, 9056 is a definition unit, 9057 is an initial value determination unit, 9058 is an optimization unit, and 9059 is a second selection unit. DETAILED DESCRIPTION

[0027] In order to make the purposes, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, rather than all the embodiments. The components of the embodiments of the present application described and shown in the drawings can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the claimed present application, but only represents selected embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the scope of protection of the present application.

[0028] It should be noted that similar reference numerals and letters represent similar items in the following drawings, and therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. Meanwhile, in the description of the present application, the terms "first", "second", and the like are only used to distinguish the description, and cannot be understood as indicating or implying relative importance.

[0029] Embodiment 1

[0030] The present embodiment provides a method for evaluating the performance of a cracked reinforced concrete beam structure.

[0031] Referring to Figure 1 , the method includes steps S100, S200, S300, S400, S500 and S600.

[0032] Step S100: obtaining parameter information of the reinforced concrete beam;

[0033] Step S200: constructing a physical model according to the parameter information of the reinforced concrete beam, and performing a load test on the physical model to obtain measured static response data of the reinforced concrete beam in the loading process, wherein the measured static response data includes measured deflection, measured strain and measured apparent damage;

[0034] In the present embodiment, the measured static response data of the cracked reinforced concrete beam in the loading process is collected by using structural health monitoring and detection technology, including measured deflection, measured strain and measured apparent damage.

[0035] Among them, the measured deflection and measured strain response are both monitoring data, which are obtained by real-time monitoring of sensors, and the measured apparent damage is detected and quantified in the whole domain by machine vision technology, including the number of concrete cracks, crack development height, crack width and crack spacing, etc., so as to obtain the response results of the current service state of the reinforced concrete beam, and the apparent damage used in the present embodiment is crack width.

[0036] In this embodiment, the in-situ three-dimensional point cloud of the reinforced concrete beam is obtained by using three-dimensional laser scanning, and the thickness of the reinforced concrete protective layer, the arrangement of the reinforcement and other information are detected by using non-destructive testing equipment to obtain the actual geometric information of the reinforced concrete beam.

[0037] The step S200 comprises:

[0038] Step S201: constructing a physical model according to the parameter information of the reinforced concrete beam;

[0039] Step S202: selecting the mid-span cross-section position and the quarter-point position of the physical model, and arranging a deflection measurement sensor;

[0040] Step S203: selecting the mid-span cross-section position of the physical model and arranging a strain measurement sensor;

[0041] Step S204: conducting a load test on the physical model;

[0042] Step S205: obtaining the measured deflection of the reinforced concrete beam during the loading process by the deflection measurement sensor, and obtaining the measured strain of the reinforced concrete beam during the loading process by the strain measurement sensor;

[0043] Step S206: detecting and quantifying the loading process based on the machine vision method to obtain the measured apparent damage.

[0044] Step S300: establishing a nonlinear finite element numerical model of the reinforced concrete beam based on the parameter information;

[0045] The step S300 comprises:

[0046] Step S301: establishing a numerical model of the reinforced concrete beam based on the parameter information, wherein the parameter information comprises the in-situ three-dimensional point cloud and the actual geometric information of the reinforced concrete beam;

[0047] Step S302: selecting a crack model and a material constitutive curve of the numerical model;

[0048] Step S303: defining the boundary conditions of the numerical model, wherein the boundary conditions are consistent with the conditions of the load test;

[0049] Step S304: conducting a sensitivity analysis on the mesh of the numerical model, selecting the element size of the numerical model, and obtaining the nonlinear finite element numerical model of the reinforced concrete beam.

[0050] In the embodiment, a numerical model is generated by using the in-situ three-dimensional point cloud of the reinforced concrete beam, a crack model capable of simulating the crack behavior of concrete and a suitable material constitutive curve are selected, and boundary conditions and load tests of the numerical model are ensured to be consistent, then a mesh sensitivity analysis of the numerical model is performed, a suitable element size is selected to ensure the requirements of precision and efficiency, and a nonlinear finite element numerical model is obtained.

[0051] Step S400: sensitivity analysis is performed on the material performance parameters of the reinforced concrete beam to obtain the optimization parameters of the nonlinear finite element numerical model.

[0052] In the embodiment, since the actual geometric information is used to establish the numerical model, and the boundary conditions such as the contact conditions between the load, the support and the pad are considered, only the material performance parameters are considered as the updating parameters. After the parameter sensitivity analysis is performed, the material performance parameters with higher sensitivity are selected as the optimization parameters, and the parameter sensitivity can be obtained by directly calculating the partial derivative of the structure response to each material performance parameter. In order to reflect the global sensitivity in the updating parameter range, the Lagrange difference function is constructed from the discrete data, and then the normalized relative sensitivity of each material performance parameter is calculated.

[0053] The step S400 comprises:

[0054] Step S401: material performance tests are performed on the reinforced concrete beam to obtain initial values of the material performance parameters of the reinforced concrete beam, the material performance parameters including the tensile strength of concrete, the compressive strength of concrete, the elastic modulus of concrete, the tensile fracture energy of concrete, the elastic modulus of steel and the yield strength of steel;

[0055] Step S402: the initial values are input into the nonlinear finite element numerical model to calculate the structure response;

[0056] Step S403: a Lagrange difference function is constructed based on the structure response, and the normalized relative sensitivity of each material performance parameter is calculated through the Lagrange difference function;

[0057] Step S404: the material performance parameter with the highest normalized relative sensitivity is selected as the optimization parameter of the nonlinear finite element numerical model.

[0058] In the embodiment, the calculation formula of the normalized relative sensitivity is:

[0059]

[0060] In the formula, S n (p) represents the normalized relative sensitivity of p, p represents the initial value of the material performance parameter, f(p) represents the structure response of p, and f a′a'th sample data point of structural response, p a , p b and p k respectively represent a'th, b'th and k'th sample data points of material performance parameters, n represents the number of increments, a = 0, 1…, n, b = 0, 1…, n, k = 0, 1…, n, a' = 0, 1…, n.

[0061] The structural response in the normalized relative sensitivity calculation formula is calculated by a nonlinear finite element numerical model. When the material performance parameter changes by an increment, the calculated structural response will also change accordingly.

[0062] When calculating the sensitivity of each material performance parameter, the material performance parameter needs to be changed by several increments based on the initial value of the material performance parameter. When analyzing the sensitivity of each material performance parameter p, n = 6 is set, and p3 is recorded as the initial value p of the material performance parameter, so that n + 1 sample points can be obtained. Suppose that three positive steps and three negative steps are taken based on the initial value p3. By performing finite element analysis, 7 sample data points can be obtained, i.e. (p0, f0), (p1, f1), (p2, f2), (p3, f3), (p4, f4), (p5, f5) and (p6, f6).

[0063] Step S500: performing multi-objective parameter optimization on the nonlinear finite element numerical model by a multi-objective particle swarm optimization algorithm to obtain a coordination optimal solution, wherein a target function of the parameter optimization is obtained based on simulated static response data and the measured static response data, and the simulated static response data is calculated by the nonlinear finite element numerical model;

[0064] In this embodiment, the target of the target function is to make the measured deflection, measured strain and actual crack width at a given measuring point under a certain load condition consistent with the calculated values of the numerical model.

[0065] The construction step of the target function is:

[0066] A100: constructing a residual function of deflection by simulating deflection and the measured deflection;

[0067] A200: constructing a residual function of strain by simulating strain and measured strain;

[0068] A300: based on the measured apparent damage, obtaining the actual average crack width and the actual maximum crack width at a preset cross-sectional height in a preset area on the reinforced concrete beam;

[0069] A400: calculating simulated average crack width and simulated maximum crack width at preset section height in the preset region based on simulated apparent damage, wherein the simulated deflection, the simulated strain and the simulated apparent damage are obtained from simulated static response data;

[0070] A500: constructing residual function of crack width based on the actual average crack width, the actual maximum crack width, the simulated average crack width and the simulated maximum crack width;

[0071] A600: defining target function through residual functions of deflection, strain and crack width.

[0072] In the embodiment, the expression of the target function is:

[0073] min J OF =min{f d (x),f s (y),f w (z)}

[0074]

[0075] In the formula, min J OF represents minimizing the target function, min represents taking the minimum value, f d (x) represents the residual function of deflection x, f s (y) represents the residual function of strain y, and f w (z) represents the residual function of crack width z, m d represents the number of load cases of deflection, n d represents the number of deflection measuring points, m s represents the number of load cases of strain, n s represents the number of strain measuring points, m w represents the number of load cases of crack width, d c,i,j represents simulated deflection of the i-th measuring point under the j-th load case, d e,i,j represents measured deflection of the i-th measuring point under the j-th load case, s c,i′j represents simulated strain of the i'-th measuring point under the j-th load case, s e,i′j represents measured strain of the i'-th measuring point under the j-th load case, w μ,c,j represents simulated average crack width at preset section height under the j-th load case in the preset region, w μ,e,j represents actual average crack width at preset section height under the j-th load case in the preset region, w max,c,j represents simulated maximum crack width at preset section height under the j-th load case in the preset region, w max,e,jrepresents the actual maximum crack width of the jth load case at the preset cross-section height in the preset area.

[0076] In this embodiment, the preset area for crack width measurement is the position of the center of gravity of the tensile reinforcement in the pure bending region under four-point bending load.

[0077] The step S500 comprises:

[0078] Step S501: taking the initial value of the material performance parameter as the initial value of the nonlinear finite element numerical model;

[0079] Step S502: setting the parameters of the multi-objective particle swarm optimization algorithm to optimize the nonlinear finite element numerical model, until the objective function converges or reaches the preset iteration number, to obtain a Pareto front solution set;

[0080] Step S503: selecting a coordinated optimal solution based on the Pareto front solution set.

[0081] In this embodiment, the optimization algorithm is selected according to the number of optimization parameters and optimization objectives. Since there are three objective functions in this embodiment, in order to avoid the subjectivity of function combination weight values, a multi-objective particle swarm optimization algorithm is used for multi-objective optimization.

[0082] At the beginning of the update of the nonlinear finite element numerical model, the material performance parameters of concrete and reinforcement obtained by material performance tests and specification formula calculation are first assigned to the nonlinear finite element numerical model as initial values. After setting appropriate parameters of the multi-objective particle swarm optimization algorithm, the update is performed until the maximum iteration number is reached or the objective function converges, a Pareto front solution set is obtained, and a coordinated optimal solution is selected to establish the digital twin of the reinforced concrete beam. The Pareto front solution set is used to solve the problem of multiple objectives, and describes the trade-off and compromise between multiple objectives.

[0083] As shown in Figure 2 The Pareto front solution of this embodiment is shown in the figure. Since there are three objective functions, the solutions in the Pareto front solution set need to be balanced among the three objectives in three-dimensional space, and at least one value in one direction is larger than the rest. Among them, Crack width represents crack width, Deflection represents deflection, and Strain represents strain.

[0084] The coordinated optimal solution can select the solution closest to the origin, which means that the values of the three objective functions are relatively small. At the same time, the selection will be made according to the importance of the objectives. In this embodiment, the crack width is actually a macroscopic manifestation of strain, so a solution with smaller deflection and crack width will be selected, and then a solution with the smallest strain will be selected from this group of solutions.

[0085] Step S600: Input the optimal solution of coordination into the nonlinear finite element numerical model to obtain a digital twin of the reinforced concrete beam, and evaluate the structural performance of the cracked reinforced concrete beam through the digital twin.

[0086] In this embodiment, additional measurement data is used to verify the established digital twin. Here, additional measurement data refers to measurement data that was not used during the model update process and was measured experimentally.

[0087] Once the digital twin of a reinforced concrete beam is established and verified, the uncertainties in simulating the actual stress behavior of a reinforced concrete beam using a nonlinear finite element numerical model can be considered eliminated. Therefore, the digital twin can be used to predict the performance of components made from the same batch of materials and with similar stress patterns (such as components with different spans and reinforcement ratios). Furthermore, because the digital twin can vividly and accurately reproduce the complex cracking behavior of concrete, and because multiple response information is used in the process of establishing the digital twin, the crack development process of reinforced concrete can be accurately studied using the digital twin, and the structural performance and residual bearing capacity of reinforced concrete beams can be comprehensively evaluated through multiple responses.

[0088] Example 2:

[0089] like Figure 3 As shown in the figure, this embodiment provides a device for evaluating the performance of cracked reinforced concrete beam structures. The device includes:

[0090] The acquisition module is used to obtain parameter information of reinforced concrete beams;

[0091] The test module is used to construct a physical model based on the parameter information of the reinforced concrete beam, and to conduct load tests on the physical model to obtain the measured static response data of the reinforced concrete beam during the loading process. The measured static response data includes measured deflection, measured strain and measured apparent damage.

[0092] A construction module is used to establish a nonlinear finite element numerical model of the reinforced concrete beam based on the parameter information;

[0093] The analysis module is used to perform sensitivity analysis on the material property parameters of the reinforced concrete beam to obtain the optimized parameters of the nonlinear finite element numerical model.

[0094] The optimization module is used to perform multi-objective parameter optimization on the nonlinear finite element numerical model using a multi-objective particle swarm optimization algorithm to obtain a coordinated optimal solution. The objective function of the parameter optimization is obtained based on the simulated static response data and the measured static response data. The simulated static response data is calculated through the nonlinear finite element numerical model.

[0095] An evaluation module configured to input the coordination optimal solution into the nonlinear finite element numerical model to obtain a digital twin of the reinforced concrete beam, and perform a cracking reinforced concrete beam structure performance evaluation through the digital twin.

[0096] The analysis module comprises:

[0097] A test unit configured to perform a material performance test on the reinforced concrete beam to obtain initial values of material performance parameters of the reinforced concrete beam, the material performance parameters comprising a concrete tensile strength, a concrete compressive strength, a concrete elastic modulus, a concrete tensile fracture energy, a steel elastic modulus, and a steel yield strength;

[0098] A first calculation unit configured to input the initial values into the nonlinear finite element numerical model to calculate a structure response;

[0099] A second calculation unit configured to construct a Lagrange difference function based on the structure response, and calculate a normalized relative sensitivity of each material performance parameter through the Lagrange difference function;

[0100] A first selection unit configured to select a material performance parameter with the highest normalized relative sensitivity as an optimization parameter of the nonlinear finite element numerical model.

[0101] The optimization module comprises:

[0102] A first construction unit configured to construct a residual function of deflection through the simulated deflection and the measured deflection;

[0103] A second construction unit configured to construct a residual function of strain through the simulated strain and the measured strain;

[0104] An acquisition unit configured to acquire actual average crack widths and actual maximum crack widths at preset sectional heights in a preset region of the reinforced concrete beam based on the measured apparent damage;

[0105] A third calculation unit configured to calculate simulated average crack widths and simulated maximum crack widths at the preset sectional heights in the preset region based on simulated apparent damage, wherein the simulated deflection, the simulated strain, and the simulated apparent damage are obtained from simulated static response data;

[0106] A third construction unit configured to construct a residual function of crack width based on the actual average crack widths, the actual maximum crack widths, the simulated average crack widths, and the simulated maximum crack widths;

[0107] A definition unit configured to define a target function through the residual functions of deflection, strain, and crack width.

[0108] The optimization module further comprises:

[0109] An initial value determining unit is configured to determine an initial value of the material performance parameter as an initial value of the nonlinear finite element numerical model.

[0110] An optimization unit is configured to perform multi-objective parameter optimization on the nonlinear finite element numerical model after setting parameters of the multi-objective particle swarm optimization algorithm until a target function converges or a preset iteration number is reached, and obtain a Pareto front solution set.

[0111] A second selection unit is configured to select a coordination optimal solution based on the Pareto front solution set.

[0112] It should be noted that, as for the device in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment related to the method, and will not be described in detail here.

[0113] The above only describes the preferred embodiments of the present application and is not intended to limit the present application. For those skilled in the art, the present application can have various modifications and changes. Any modification, equivalent replacement, improvement, etc. within the spirit and principles of the present application shall be included in the protection scope of the present application.

[0114] The above only describes the preferred embodiments of the present application and is not intended to limit the present application. For those skilled in the art, the present application can have various modifications and changes. Any modification, equivalent replacement, improvement, etc. within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A method of evaluating the performance of a cracked reinforced concrete beam structure, characterized by, The method comprises the following steps: obtaining parameter information of a reinforced concrete beam; constructing a physical model according to the parameter information of the reinforced concrete beam, and performing a load test on the physical model to obtain measured static response data of the reinforced concrete beam during loading, wherein the measured static response data includes measured deflection, measured strain and measured apparent damage; establishing a nonlinear finite element numerical model of the reinforced concrete beam based on the parameter information; performing sensitivity analysis on material performance parameters of the reinforced concrete beam to obtain optimized parameters of the nonlinear finite element numerical model; performing multi-objective parameter optimization on the nonlinear finite element numerical model through a multi-objective particle swarm optimization algorithm to obtain a coordinated optimal solution, wherein the objective function of the parameter optimization is obtained based on simulated static response data and the measured static response data, and the simulated static response data is calculated through the nonlinear finite element numerical model; inputting the coordinated optimal solution into the nonlinear finite element numerical model to obtain a digital twin of the reinforced concrete beam, and performing structural performance evaluation on the cracked reinforced concrete beam through the digital twin.

2. The cracked reinforced concrete beam structural performance evaluation method according to claim 1, characterized by The method comprises the following steps: constructing a physical model according to the parameter information of the reinforced concrete beam, and performing a load test on the physical model to obtain measured static response data of the reinforced concrete beam during loading, wherein the measured static response data includes: constructing a physical model according to the parameter information of the reinforced concrete beam; selecting a mid-span cross-section position and a quarter-point position of the physical model, and arranging a deflection measurement sensor; selecting a mid-span cross-section position of the physical model and arranging a strain measurement sensor; performing a load test on the physical model; obtaining measured deflection of the reinforced concrete beam during loading through the deflection measurement sensor, and obtaining measured strain of the reinforced concrete beam during loading through the strain measurement sensor; 3. The method of claim 1, wherein detecting and quantifying the loading process based on a machine vision method to obtain measured apparent damage. The method comprises the following steps: establishing a nonlinear finite element numerical model of the reinforced concrete beam based on the parameter information, wherein the method comprises the following steps: establishing a numerical model of the reinforced concrete beam based on the parameter information, wherein the parameter information includes in-situ three-dimensional point cloud and actual geometric information of the reinforced concrete beam; selecting a crack model and a material constitutive curve of the numerical model; 4. The cracked reinforced concrete beam structural performance evaluation method according to claim 1, characterized by defining boundary conditions of the numerical model, wherein the boundary conditions are consistent with the conditions of the load test; performing sensitivity analysis on the grid of the numerical model, and selecting an element size of the numerical model to obtain the nonlinear finite element numerical model of the reinforced concrete beam. The method comprises the following steps: performing sensitivity analysis on material performance parameters of the reinforced concrete beam to obtain optimized parameters of the nonlinear finite element numerical model, wherein the method comprises the following steps: performing a material performance test on the reinforced concrete beam to obtain initial values of the material performance parameters of the reinforced concrete beam, wherein the material performance parameters include tensile strength of concrete, compressive strength of concrete, elastic modulus of concrete, tensile fracture energy of concrete, elastic modulus of steel and yield strength of steel; inputting the initial values into the nonlinear finite element numerical model to calculate structural response. constructing a Lagrange difference function based on the structural response, calculating a normalized relative sensitivity of each material performance parameter through the Lagrange difference function; selecting a material performance parameter with the highest normalized relative sensitivity as an optimization parameter of the nonlinear finite element numerical model.

5. The cracked reinforced concrete beam structural performance evaluation method according to claim 1, characterized by The construction of the objective function comprises: constructing a residual function of deflection through the simulated deflection and the measured deflection; constructing a residual function of strain through the simulated strain and the measured strain; based on the measured apparent damage, obtaining actual average crack width and actual maximum crack width at a preset cross-sectional height in a preset region on the reinforced concrete beam; based on the simulated apparent damage, calculating simulated average crack width and simulated maximum crack width at the preset cross-sectional height in the preset region, wherein the simulated deflection, the simulated strain and the simulated apparent damage are obtained from simulated static response data; based on the actual average crack width, the actual maximum crack width, the simulated average crack width and the simulated maximum crack width, constructing a residual function of crack width; defining a target function through the residual functions of deflection, strain and crack width.

6. The cracked reinforced concrete beam structural performance evaluation method according to claim 4, characterized by The multi-objective parameter optimization of the nonlinear finite element numerical model through the multi-objective particle swarm optimization algorithm comprises: taking initial values of the material performance parameters as initial values of the nonlinear finite element numerical model; setting parameters of the multi-objective particle swarm optimization algorithm to perform multi-objective parameter optimization on the nonlinear finite element numerical model until the target function converges or a preset number of iterations is reached, to obtain a Pareto front solution set; selecting a coordination optimal solution based on the Pareto front solution set.

7. A cracking reinforced concrete beam structural performance evaluation device, characterized by, The method comprises: an acquisition module configured to acquire parameter information of a reinforced concrete beam; a test module configured to construct a physical model according to the parameter information of the reinforced concrete beam, and perform a load test on the physical model to obtain measured static response data of the reinforced concrete beam in a loading process, the measured static response data comprising measured deflection, measured strain and measured apparent damage; a construction module configured to establish a nonlinear finite element numerical model of the reinforced concrete beam based on the parameter information; an analysis module configured to perform sensitivity analysis on material performance parameters of the reinforced concrete beam to obtain optimization parameters of the nonlinear finite element numerical model; an optimization module configured to perform multi-objective parameter optimization on the nonlinear finite element numerical model through a multi-objective particle swarm optimization algorithm to obtain a coordination optimal solution, a target function of the parameter optimization being obtained based on simulated static response data and the measured static response data, the simulated static response data being calculated through the nonlinear finite element numerical model; an evaluation module configured to input the coordination optimal solution into the nonlinear finite element numerical model to obtain a digital twin of the reinforced concrete beam, and perform structural performance evaluation on the cracked reinforced concrete beam through the digital twin.

8. The cracked reinforced concrete beam structural performance evaluation apparatus according to claim 7, characterized by, The analysis module comprises: The test unit is configured to perform a material performance test on the reinforced concrete beam to obtain initial values of material performance parameters of the reinforced concrete beam, the material performance parameters including a tensile strength of concrete, a compressive strength of concrete, an elastic modulus of concrete, a tensile fracture energy of concrete, an elastic modulus of steel, and a yield strength of steel. The first calculation unit is configured to input the initial values into the nonlinear finite element numerical model to calculate a structural response. The second calculation unit is configured to construct a Lagrange difference function based on the structural response, and calculate a normalized relative sensitivity of each material performance parameter through the Lagrange difference function. The first selection unit is configured to select a material performance parameter with the highest normalized relative sensitivity as an optimization parameter of the nonlinear finite element numerical model.

9. The cracked reinforced concrete beam structural performance evaluation apparatus according to claim 7, characterized by, The optimization module includes: The first construction unit is configured to construct a residual function of deflection by using the simulated deflection and the measured deflection. The second construction unit is configured to construct a residual function of strain by using the simulated strain and the measured strain. The acquisition unit is configured to acquire actual average crack widths and actual maximum crack widths at preset sectional heights in a preset region of the reinforced concrete beam based on the measured apparent damage. The third calculation unit is configured to calculate simulated average crack widths and simulated maximum crack widths at the preset sectional heights in the preset region based on simulated apparent damage, wherein the simulated deflection, the simulated strain, and the simulated apparent damage are obtained from simulated static response data. The third construction unit is configured to construct a residual function of crack width based on the actual average crack widths, the actual maximum crack widths, the simulated average crack widths, and the simulated maximum crack widths. The definition unit is configured to define a target function by using the residual functions of deflection, strain, and crack width.

10. The cracked reinforced concrete beam structural performance evaluation apparatus according to claim 8, characterized by, The optimization module further includes: The initial value determination unit is configured to use the initial values of the material performance parameters as initial values of the nonlinear finite element numerical model. The optimization unit is configured to perform multi-objective parameter optimization on the nonlinear finite element numerical model by setting parameters of a multi-objective particle swarm optimization algorithm until the target function converges or a preset number of iterations is reached, to obtain a Pareto front solution set. The second selection unit is configured to select a coordination optimal solution based on the Pareto front solution set.

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