Stress simulation method and system for carbon fiber reinforced concrete member

Abstract

The present application relates to the technical field of physical property simulation monitoring, and in particular to a stress simulation method and system for carbon fiber reinforced concrete members. The method uses an adaptive inverse solving method. For each load, the interface constitutive parameter set under each monitoring section is obtained through an iterative optimization algorithm and a bond-slip relationship. According to the interface constitutive parameter set of the monitoring section under different loads, a parameter space is constructed, and then the change trajectory of the interface constitutive parameter set in the parameter space with the change of the load is obtained. The debonding load prediction value is a significant and distinctive characteristic convex peak on the change trajectory that is different from the previous load. The analysis process of the present application can effectively quantify the critical condition of the interface from the healthy bonding state to the macroscopic debonding failure, and improve the authenticity and reference of the material simulation output results.

Description

Technical Field

[0001] This invention relates to the field of physical property simulation and monitoring technology, specifically to a stress simulation method for carbon fiber reinforced concrete components. Background Technology

[0002] Carbon fiber reinforced polymer (CFRP) reinforcement technology is widely used in civil engineering due to its ability to effectively improve the load-bearing capacity and durability of concrete members. The success or failure of this technology is highly dependent on the mechanical properties of the bond interface between CFRP and concrete. Under actual loads, interfacial delamination is a common and significantly brittle failure mode. It often occurs without obvious macroscopic warning signs, and once it does, it leads to a sharp decline in the structural load-bearing capacity, posing a serious threat to structural safety.

[0003] To avoid overloading during the use of CFRP (Concrete Composite Reinforced Polymer), existing technologies require simulation testing to determine its critical peel load value, thus providing users with a reference. Existing simulation methods, whether theoretical calculations based on design specifications or conventional finite element numerical simulations, primarily aim to predict the ultimate bearing capacity and final failure mode of the structure. When dealing with interface peeling problems, these methods typically simplify the complex progressive damage process into an instantaneous judgment based on strength or fracture energy criteria; that is, the interface element abruptly changes from an "intact" state to a "failed" state at a certain moment. The limitation of this approach is that it cannot reveal and quantify the progressive evolution of the internal mechanical behavior and damage state of the interface from a healthy bonded state to macroscopic peeling failure. For complex nonlinear systems like CFRP-reinforced concrete structures, the final instability and failure often stems from a critical abrupt change in the system's internal state. Therefore, the simulation results in existing technologies usually have a significant lag compared to the true critical values, failing to obtain accurate and reliable critical peel load values. Summary of the Invention

[0004] To address the problem that existing simulation techniques produce outdated results and fail to provide accurate and reliable critical peel load values, this invention aims to provide a stress simulation method for carbon fiber reinforced concrete members. The specific technical solution adopted is as follows:

[0005] This invention proposes a stress simulation method for carbon fiber reinforced concrete members, the method comprising:

[0006] Multiple monitoring sections are divided on the simulated component, and multiple monitoring points are deployed in each monitoring section. During the simulation process, the actual longitudinal strain observation values ​​of the monitoring points under each load are obtained.

[0007] For each load after the preset initial load range, the upper limit of the interfacial bond strength of the monitoring section and the slip of the peak stress are used as the interface constitutive parameter set; the interface constitutive parameter set is obtained by an iterative optimization algorithm, and the minimum objective function of the iterative optimization algorithm is: the difference between the predicted longitudinal strain observation value and the actual longitudinal strain observation value obtained from the candidate interface constitutive parameter set.

[0008] For each monitoring point, a parameter space is constructed based on the interface constitutive parameter set of the monitoring section under different loads, and the change trajectory of the interface constitutive parameter set formed by the load change in the parameter space is obtained; the critical peel load prediction value is determined based on the convex position of the change trajectory.

[0009] Furthermore, the minimum objective function includes:

[0010] The sum of squared errors between the predicted longitudinal strain observations and the actual longitudinal strain observations at all monitoring points is taken as the minimum objective function.

[0011] Furthermore, the iterative optimization algorithm employs the LM algorithm.

[0012] Furthermore, the method for identifying the changed protruding position includes:

[0013] For each point in the changing trajectory, obtain the local curvature value of each point, compare the degree of change of the local curvature value of each point with the preset standard curvature value, and filter out the positions where the change is prominent.

[0014] Furthermore, the degree of change is the absolute value of the difference between the local curvature value of each point and the local curvature value of the previous point; the standard curvature value is a preset multiple of the standard deviation of the local curvature values ​​of the preceding points of each point.

[0015] Furthermore, the method also includes:

[0016] Under each load, the shear stress transfer strength of each monitoring point is obtained based on the rate of change of the actual longitudinal strain observation value between the monitoring point and other monitoring points in space; the shear stress transfer strength variation characteristics of each monitoring point under the preset initial load range are analyzed to obtain the initial force transfer stiffness of each monitoring point; the initial force transfer stiffness is used as the simulation output result.

[0017] Furthermore, the method for obtaining the shear stress transfer strength includes:

[0018] Under a load, the strain distribution profile is obtained by taking the location of the monitoring point as the horizontal axis and the actual longitudinal strain observation value as the vertical axis. The slope of the tangent line corresponding to the monitoring point on the strain distribution profile is taken as the shear stress transfer intensity.

[0019] Furthermore, the method for obtaining the initial force transmission stiffness includes:

[0020] For each monitoring point, the shear stress transfer intensity corresponding to the preset initial load range is used to form a shear stress transfer intensity sequence. Linear regression analysis is performed on the shear stress transfer intensity sequence, and the obtained regression coefficients are used as the initial force transfer stiffness.

[0021] Furthermore, the strain distribution profile is obtained by fitting using a cubic spline interpolation spatial smoothing algorithm.

[0022] Furthermore, the method also includes:

[0023] The product of the upper limit of the interfacial bond strength, the slip of the peak stress, and the natural constant is used as the interfacial fracture capacity, and the interfacial fracture capacity is used as the simulation output result.

[0024] The present invention also proposes a stress simulation system for carbon fiber reinforced concrete members, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of any one of the stress simulation methods for carbon fiber reinforced concrete members.

[0025] The present invention has the following beneficial effects:

[0026] This invention first obtains the basic load simulation information at each monitoring point on the simulated component during the simulation process. Considering that the CFRP interface will produce nonlinear damage after the load exceeds the initial load range, and its mechanical behavior cannot be directly represented by changes in monitoring data, this invention adopts an adaptive inverse solution method. For each load, the interface constitutive parameter set under each monitoring segment is obtained through iterative optimization algorithms and bond-slip relationships. The interface constitutive parameter set can characterize the mechanical characteristics of the interface under the corresponding load in the monitoring segment. Therefore, for each monitoring point, a parameter space can be constructed according to the interface constitutive parameter set of the monitoring segment under different loads, and then the change trajectory of the interface constitutive parameter set formed by the load change in the parameter space can be obtained. The critical peel load prediction value is a significant characteristic peak on the change trajectory that is different from the previous load. It represents that when the material triggers a new and more severe failure mode under the critical peel load prediction value, such as the rapid penetration of a main crack from the propagation of diffuse microcracks, the mechanical behavior rules inside the interface will be fundamentally changed. This qualitative change in the internal mechanism will disrupt the evolutionary relationship between constitutive parameters, resulting in a sharp, nonlinear geometric shift. This invention, through iterative optimization algorithms and the bond-slip relationship, adaptively solves for the material's mechanical characteristics under larger loads in reverse, thereby obtaining predicted critical peel load values ​​corresponding to significantly varying interface constitutive parameter sets under different loads. The analysis process effectively quantifies the critical conditions between a healthy bonded state and macroscopic peel failure, improving the realism and reliability of the material simulation output. Attached Figure Description

[0027] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0028] Figure 1 This is a flowchart of a stress simulation method for carbon fiber reinforced concrete members, provided as an embodiment of the present invention. Detailed Implementation

[0029] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a stress simulation method for carbon fiber reinforced concrete components proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0030] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0031] The following describes in detail, with reference to the accompanying drawings, a specific scheme for a stress simulation method for carbon fiber reinforced concrete components provided by the present invention.

[0032] Please see Figure 1 The diagram illustrates a flowchart of a stress simulation method for carbon fiber reinforced concrete members according to an embodiment of the present invention. The method includes:

[0033] Step S1: Divide the simulation component into multiple monitoring sections, deploy multiple monitoring points in each monitoring section, and obtain the actual longitudinal strain observation values ​​of the monitoring points under each load during the simulation process.

[0034] Step S1 in this embodiment of the invention is a processing step in a conventional simulation process, aimed at obtaining basic simulation information. In this embodiment, multiple monitoring points are uniformly deployed along the longitudinal direction of the CFRP reinforcement layer. After each load is applied and static equilibrium is reached, the actual longitudinal strain observation values ​​at the monitoring point locations are obtained. It should be noted that in this embodiment, the load is gradually increased from small to large during the simulation process, resulting in multiple sets of actual longitudinal strain observation values, each representing feedback data under a specific load. The specific data acquisition method is a well-known technique and will not be elaborated here.

[0035] It should be noted that, in order to achieve accurate monitoring of local locations during the simulation process of this embodiment of the invention, multiple monitoring segments are divided on the component interface, that is, each monitoring segment consists of multiple monitoring points. Similarly, it is also possible not to divide the monitoring segments and analyze all monitoring points to obtain overall information about the component interface. The specific division method and deployment of monitoring points can be set according to the actual simulation requirements, and will not be elaborated here.

[0036] Step S2: For each load after the preset initial load range, the upper limit of the interfacial bond strength of the monitoring section and the slip of the peak stress are used as the interface constitutive parameter set; the interface constitutive parameter set is obtained by an iterative optimization algorithm, and the minimum objective function of the iterative optimization algorithm is: the difference between the predicted longitudinal strain observation value and the actual longitudinal strain observation value obtained from the selected interface constitutive parameter set.

[0037] For CFRP, under lower loads, it exhibits linear mechanical properties characteristic of its undamaged state, with a stable linear relationship between interfacial load strength and external load. This linear relationship facilitates analysis and prediction. However, under higher loads, the component begins to develop nonlinear damage, and its mechanical behavior no longer follows the linear relationship under lower loads. The uncertain mechanical behavior caused by this nonlinear damage is difficult to observe, and current technologies cannot effectively quantify the true mechanical state at this stage.

[0038] To quantify the nonlinear behavior of a component interface from health to failure, this invention employs a feature set that accurately characterizes its mechanical properties: the interface constitutive parameter set. This set comprises the upper limit of the interface bond strength and the slip at peak stress for each load exceeding the initial load range in the monitored section. The upper limit of the interface bond strength represents the maximum shear stress that the interface can transmit, directly reflecting its bonding capacity. The slip at peak stress represents the relative slip required for the shear stress to reach the upper limit of the interface bond strength, reflecting the initial stiffness and toughness of the interface. Therefore, the interface constitutive parameter set effectively characterizes the nonlinear mechanical state under load. It should be noted that the bond-slip constitutive relationship is existing technology for those skilled in the art. This invention selects an exponential bond-slip constitutive model, widely validated in engineering and capable of capturing key physical characteristics. The model expression is:

[0039]

[0040] in, It is an exponential bond-slip constitutive model. For interfacial bond strength, This represents the upper limit of interfacial bond strength. For slip, Let be the slip at peak stress, and exp be an exponential function with the natural constant as the base. It should be noted that this model is a technique well-known to those skilled in the art, and its specific meaning and logic will not be elaborated further.

[0041] Regarding the method for obtaining the interface constitutive parameter set, this embodiment of the invention considers the significant difficulty in detecting and calculating such parameters under nonlinear damage in CFRP. Therefore, this embodiment employs an adaptive inverse solution method to determine the most suitable interface constitutive parameter set for the monitoring section under the current load. This inverse solution method is an iterative optimization algorithm. Starting from an initially set interface constitutive parameter set, it iteratively changes the set. During the iteration, a minimum objective function is calculated to determine whether the candidate interface constitutive parameter set is the optimal set for the current state. Then, the optimal interface constitutive parameter set is determined from multiple candidate sets. In this embodiment, the minimum objective function of the iterative optimization algorithm is the difference between the predicted longitudinal strain observation value obtained from the candidate interface constitutive parameter set and the actual longitudinal strain observation value. The smaller the difference, the more likely the candidate interface constitutive parameter set is to be the optimal result. Different candidate interface constitutive parameter sets are iteratively selected until the difference is minimized, at which point the optimal result is determined.

[0042] Preferably, in this embodiment of the invention, the minimum objective function includes:

[0043] The sum of squared errors between the predicted and actual longitudinal strain observations at all monitoring points is used as the minimum objective function. It should be noted that, because this embodiment of the invention analyzes the data in units of monitoring sections, for any candidate interface constitutive parameter, there is a sequence of predicted longitudinal strain observations and a sequence of actual longitudinal strain observations. The position of each element in the sequence represents the monitoring point number. This embodiment of the invention obtains the squared errors between monitoring point numbers with the same number, and then sums them to obtain the minimum objective function.

[0044] It should be noted that the predicted longitudinal strain observation values ​​can be obtained by substituting the constitutive parameters of the selected interface into the finite element or finite difference mechanical model of the corresponding monitoring section, and calculating the predicted longitudinal strain observation values ​​at all monitoring points in the section under the current load and with the given parameters. In other words, the predicted longitudinal strain observation value can be considered as a predicted estimation result. The finite element or finite difference mechanical model is a mechanical model obtained by fitting empirical data obtained during the simulation process; this is a technique well-known to those skilled in the art and will not be elaborated further.

[0045] Preferably, the iterative optimization algorithm in this embodiment of the invention is the LM algorithm. This algorithm is chosen because it combines the advantages of gradient descent (which guarantees stable convergence when far from the optimal solution) and the Gauss-Newton method (which achieves fast convergence when close to the optimal solution). The specific iterative process is as follows: Under the target load, for the target monitoring section, a preset initial interface constitutive parameter set is started. This initial interface constitutive parameter set is set as the interface constitutive parameter set already determined for the target monitoring section under the previous load. In each iteration, the LM algorithm determines the parameter update direction and step size by calculating the Jacobian matrix of the minimum objective function relative to the constitutive parameters of the candidate interface, until the residual between the predicted strain and the actual strain converges to a preset minimum threshold, or the maximum number of iterations is reached. The specific LM algorithm is a well-known technique to those skilled in the art and will not be described in detail here.

[0046] Step S3: For each monitoring point, construct a parameter space based on the interface constitutive parameter set of the monitoring section under different loads, and obtain the change trajectory of the interface constitutive parameter set formed by the load change in the parameter space; determine the critical stripping load prediction value based on the convex position of the change trajectory.

[0047] For a target monitoring section, after optimization in step S2, each load exceeding the preset initial load range corresponds to an interface constitutive parameter set. This can be considered as each monitoring point corresponding to an interface constitutive parameter set under each load. For any monitoring point on the component interface, its interface constitutive parameter set will continuously change. Since the interface constitutive parameter set is two-dimensional data, a two-dimensional parameter space can be constructed. The interface constitutive parameter set of the monitoring point under each load will obtain corresponding data points in this parameter space. As the load changes, these data points will generate a discrete path. Connecting the discrete points on the path yields the trajectory of the interface constitutive parameter set changing with the load in the parameter space. In other words, each monitoring point corresponds to a trajectory, which records the entire degradation history of the interface performance at that point in a highly condensed and physically intuitive way.

[0048] In the stable damage stage, the degradation mechanism of the interface is singular and continuous, such as the slow propagation of microcracks. This leads to a relatively stable proportional relationship in the evolution of the interface constitutive parameters, resulting in a smooth, almost linear trajectory. However, when damage accumulates to a critical point, triggering a new and more severe failure mode—for example, the rapid propagation of a main crack instead of diffuse microcracks—the mechanical behavior rules within the interface undergo a fundamental change. This qualitative change in the internal mechanism disrupts the evolutionary relationship between constitutive parameters, causing a sharp, nonlinear inflection point in the parameter evolution trajectory. Therefore, the predicted critical peel load value is a prominent point on the trajectory.

[0049] Preferably, in this embodiment of the invention, the method for identifying the changing protrusion position includes:

[0050] For each point in the changing trajectory, obtain the local curvature value of each point, compare the degree of change of the local curvature value of each point with the preset standard curvature value, and filter out the positions where the change is prominent.

[0051] In this embodiment of the invention, the method for obtaining the local curvature value is as follows: for any data point in the changing trajectory, select the coordinates of the preceding and following data points, and calculate the local curvature value of the target data point using the standard discrete curvature calculation formula. The standard discrete curvature formula can be the reciprocal of the radius of the circumcircle of the triangle formed by the three data points. The specific method for obtaining this formula is well-known to those skilled in the art and will not be elaborated upon here.

[0052] Furthermore, this embodiment of the invention considers that during the stable progressive damage stage, the parameter evolution trajectory is smooth, and its local curvature value will fluctuate steadily in a small range near zero, forming a baseline background. When the interface enters a critical instability state and the trajectory undergoes a sharp turn, its local curvature value will inevitably show a significant, isolated peak that is distinct from the historical background fluctuations. Therefore, the degree of change is the absolute value of the difference between the local curvature value of each point and the local curvature value of the previous point; the standard curvature value is a preset multiple of the standard deviation of the local curvature values ​​of the preceding points of each point. That is, when the degree of change is greater than the standard curvature value, it indicates that the data point is at a point of convex change. This embodiment of the invention traverses each point in the change trajectory in ascending order of load. When a point of convex change is detected, the system outputs a warning signal, records the corresponding load as the predicted value of the critical stripping load, and highlights the location of the curvature peak on the visualization model of the component, thereby intuitively indicating the critical situation.

[0053] Preferably, in this embodiment of the invention, in order to improve the reference value of the simulation process for workers, the simulation method of this embodiment of the invention, in addition to outputting the predicted value of the critical stripping load, also includes:

[0054] Under each load, the shear stress transfer strength of each monitoring point is obtained based on the rate of change of the actual longitudinal strain observation values ​​between the monitoring point and other monitoring points in space. The variation characteristics of the shear stress transfer strength of each monitoring point under the preset initial load range are analyzed to obtain the initial force transfer stiffness of each monitoring point; this initial force transfer stiffness is used as the simulation output result. The initial force transfer stiffness represents the response sensitivity of the interface force transfer strength at the monitoring point location to a unit external load under ideal elastic conditions, i.e., low load conditions. The initial force transfer stiffness at all monitoring point locations can form a set, which serves as the initial force transfer characteristic benchmark for the component. This benchmark, in the form of a stiffness function distributed along the component length, completely encapsulates the inherent force transfer mode of the specific component in its healthiest state. It provides a unique and personalized criterion for determining whether and to what extent the mechanical behavior has deteriorated after the load increases and the component enters the nonlinear damage stage.

[0055] In this embodiment of the invention, the initial load range is set to the first 20% of all load ranges, which falls within the elastic range of the component. During this stage, the increase in the interface force transmission strength has a stable linear relationship with the applied external load.

[0056] The methods for obtaining shear stress transfer strength include:

[0057] This embodiment of the invention takes into account that the direct physical quantity driving the delamination of the CFRP-concrete interface is the interfacial shear stress, and according to the principle of mechanical equilibrium, this shear stress is numerically proportional to the strain gradient of the CFRP layer along the length of the member. Therefore, this embodiment of the invention obtains a strain distribution profile under one load, with the monitoring point location as the horizontal axis and the actual longitudinal strain observation value as the vertical axis. The slope of the tangent line corresponding to the monitoring point on the strain distribution profile is taken as the shear stress transfer intensity.

[0058] Furthermore, in this embodiment of the invention, the strain distribution profile is obtained by fitting using a cubic spline interpolation spatial smoothing algorithm. The specific techniques are well-known to those skilled in the art and will not be elaborated further.

[0059] Furthermore, methods for obtaining the initial force transmission stiffness include:

[0060] For each monitoring point, the shear stress transfer intensity corresponding to the preset initial load range is used to construct a shear stress transfer intensity sequence. Linear regression analysis is performed on this sequence, and the obtained regression coefficients are used as the initial force transfer stiffness. The regression coefficients characterize the influence of the independent variable on the dependent variable. Therefore, for the shear stress transfer intensity sequence, the dependent variable is the load, and the independent variable is the shear stress transfer intensity. Thus, the regression coefficients can characterize the sensitivity of the relationship between the two, thereby determining the response sensitivity of the interface force transfer intensity at the monitoring point to a unit external load under ideal elastic conditions. It should be noted that the method for obtaining the regression coefficients is a well-known technique to those skilled in the art and will not be elaborated upon here.

[0061] Preferably, the simulation method proposed in this embodiment of the invention further includes:

[0062] The product of the upper limit of the interfacial bond strength, the slip of the peak stress, and the natural constant is used as the interfacial fracture capacity, which is then used as the simulation output. The interfacial fracture capacity represents the energy dissipated to cause complete failure of the interface per unit area. It should be noted that the interfacial fracture capacity is the integral result across the entire range in the actual exponential bond-slip constitutive model; that is, the energy of this continuous function of the exponential bond-slip constitutive model obtained by numerical integration in this embodiment of the invention is a technique well-known to those skilled in the art and will not be elaborated further.

[0063] In summary, this invention adaptively solves the material mechanical characteristics under large loads by using iterative optimization algorithms and bond-slip relationships. This allows for the prediction of critical peel loads corresponding to significantly varying interface constitutive parameter sets under different loads. The analysis process effectively quantifies the critical conditions between a healthy bonded state and macroscopic peel failure, improving the realism and reference value of the material simulation output results.

[0064] The present invention also proposes a stress simulation system for carbon fiber reinforced concrete members, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of any one of the stress simulation methods for carbon fiber reinforced concrete members.

[0065] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0066] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

Claims

1. A stress simulation method for carbon fiber reinforced concrete members, characterized in that, The method includes: Multiple monitoring sections are divided on the simulated component, and multiple monitoring points are deployed in each monitoring section. During the simulation process, the actual longitudinal strain observation values ​​of the monitoring points under each load are obtained. For each load after the preset initial load range, the upper limit of the interfacial bond strength of the monitoring section and the slip of the peak stress are used as the interface constitutive parameter set; the interface constitutive parameter set is obtained by an iterative optimization algorithm, and the minimum objective function of the iterative optimization algorithm is: the difference between the predicted longitudinal strain observation value and the actual longitudinal strain observation value obtained from the candidate interface constitutive parameter set. For each monitoring point, a parameter space is constructed based on the interface constitutive parameter set of the monitoring section under different loads, and the change trajectory of the interface constitutive parameter set formed by the load change in the parameter space is obtained; the critical peel load prediction value is determined based on the convex position of the change trajectory.

2. The stress simulation method for carbon fiber reinforced concrete members according to claim 1, characterized in that, The minimum objective function includes: The sum of squared errors between the predicted longitudinal strain observations and the actual longitudinal strain observations at all monitoring points is taken as the minimum objective function.

3. The stress simulation method for carbon fiber reinforced concrete members according to claim 1, characterized in that, The iterative optimization algorithm used is the LM algorithm.

4. The stress simulation method for carbon fiber reinforced concrete members according to claim 1, characterized in that, The method for identifying the changing protruding position includes: For each point in the changing trajectory, obtain the local curvature value of each point, compare the degree of change of the local curvature value of each point with the preset standard curvature value, and filter out the positions where the change is prominent.

5. The stress simulation method for carbon fiber reinforced concrete members according to claim 4, characterized in that, The degree of change is the absolute value of the difference between the local curvature value of each point and the local curvature value of the previous point; the standard curvature value is a preset multiple of the standard deviation of the local curvature values ​​of the preceding points of each point.

6. The stress simulation method for carbon fiber reinforced concrete members according to claim 1, characterized in that, The method further includes: Under each load, the shear stress transfer strength of each monitoring point is obtained based on the rate of change of the actual longitudinal strain observation value between the monitoring point and other monitoring points in space; the shear stress transfer strength variation characteristics of each monitoring point under the preset initial load range are analyzed to obtain the initial force transfer stiffness of each monitoring point; the initial force transfer stiffness is used as the simulation output result.

7. The stress simulation method for carbon fiber reinforced concrete members according to claim 6, characterized in that, The method for obtaining the shear stress transfer strength includes: Under a load, the strain distribution profile is obtained by taking the location of the monitoring point as the horizontal axis and the actual longitudinal strain observation value as the vertical axis. The slope of the tangent line corresponding to the monitoring point on the strain distribution profile is taken as the shear stress transfer intensity.

8. The stress simulation method for carbon fiber reinforced concrete members according to claim 6, characterized in that, The method for obtaining the initial force transmission stiffness includes: For each monitoring point, the shear stress transfer intensity corresponding to the preset initial load range is used to form a shear stress transfer intensity sequence. Linear regression analysis is performed on the shear stress transfer intensity sequence, and the obtained regression coefficients are used as the initial force transfer stiffness.

9. The stress simulation method for carbon fiber reinforced concrete members according to claim 1, characterized in that, The method further includes: The product of the upper limit of the interfacial bond strength, the slip of the peak stress, and the natural constant is used as the interfacial fracture capacity, and the interfacial fracture capacity is used as the simulation output result.

10. A stress simulation system for carbon fiber reinforced concrete members, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the stress simulation method for carbon fiber reinforced concrete components as described in any one of claims 1 to 9.

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