Beam bridge structure optimization method based on BIM and finite element method

Abstract

The invention discloses a bridge structure optimization method based on BIM and a finite element method, and relates to the technical field of bridge structure optimization. According to the method, the finite element analysis model can be more accurately established, and the design precision is improved. Through finite element analysis and a digital simulation technology, structure response data is rapidly obtained, and design optimization is accelerated; the optimization of the final scheme is ensured by a multi-iteration optimization strategy, the extreme load response is predicted by introducing a machine learning algorithm, a high-risk area is identified in advance, and the overall performance is improved; based on a multi-scale analysis method, the durability and safety of the structure are comprehensively evaluated, weak links are identified, and long-term performance is guaranteed; meanwhile, the influence of environmental factors on material characteristics is considered, adjustment is performed according to climate data, the design scheme is closer to the actual environment, and durability is enhanced.

Description

Technical Field

[0001] This application belongs to the technical field of beam bridge structure optimization, and particularly relates to a beam bridge structure optimization method based on BIM and the finite element method. Background Art

[0002] In the field of bridge engineering, as a common bridge form, the structural design and optimization of beam bridges are crucial for ensuring the safety, durability, and economy of bridges. Traditional beam bridge design methods often rely on engineers' experience and judgment, lacking systematic analysis and optimization means, resulting in relatively large uncertainties and risks in the design results.

[0003] With the rapid development of Building Information Modeling (BIM) technology, its application in bridge design is becoming increasingly widespread. BIM technology can integrate information throughout the life cycle of bridge design, construction, and operation, providing strong support for the structural optimization of bridges. At the same time, as a numerical analysis method, the finite element method has unique advantages in the analysis of stress distribution and deformation of bridge structures; however, combining BIM technology with the finite element method for beam bridge structure optimization still faces some challenges.

[0004] Firstly, the geometric model provided by the BIM platform needs to be effectively docked with finite element analysis software to ensure the accuracy of the analysis results; secondly, for materials used in beam bridge structures, such as Ultra-High Performance Concrete (UHPC), its mechanical property parameters are affected by various factors, including environmental factors, etc., which need to be fully considered in the finite element analysis model; in addition, in the dynamic loading simulation of beam bridge structures, traditional simulation methods often can only analyze specific load conditions and cannot comprehensively predict the structural response under extreme load conditions; in the identification of weak links in beam bridge structures, traditional identification methods often rely on the results of macroscopic finite element analysis, but this method may not accurately reflect the stress state and damage mechanism inside the material; in the adjustment and optimization of beam bridge structure parameters, traditional trial-and-error methods are often inefficient and difficult to find the global optimal solution. Summary of the Invention

[0005] The purpose of this application is to provide a beam bridge structure optimization method based on BIM and the finite element method, which optimizes the beam bridge structure by combining BIM and the finite element method to meet the stress distribution and deformation requirements and improve the safety and durability of the beam bridge.

[0006] To achieve the above objective, an embodiment of this application provides a beam bridge structure optimization method based on BIM and the finite element method, including:

[0007] Obtain the geometric model of the beam bridge structure from the BIM platform, and establish a finite element analysis model of the beam bridge in combination with the mechanical property parameters of UHPC materials;

[0008] Use a finite element analysis software to conduct a stress distribution analysis on the finite element analysis model of the beam bridge, extract the stress values of key nodes, judge the stress concentration phenomenon, and obtain the stress distribution analysis results;

[0009] According to the stress distribution analysis results, judge the deformation condition of the beam bridge structure, calculate the displacement values of key sections, and compare them with the preset thresholds. If the displacement values exceed the preset thresholds, mark them as areas to be optimized; if the displacement values do not exceed the preset thresholds, do not mark them;

[0010] Adopt digital simulation technology to conduct dynamic loading simulation on the areas to be optimized, and obtain the structural response data under different load conditions;

[0011] Compare the structural response data with the stress distribution analysis results to identify the weak links of the beam bridge structure and obtain the weak link identification results;

[0012] According to the weak link identification results, adjust the structural parameters of the beam bridge and re-conduct finite element analysis and digital simulation; through multiple iterative optimizations until the stress distribution is uniform and the displacement values are less than the preset thresholds, obtain the beam bridge design scheme that meets the stress distribution and deformation requirements;

[0013] Import the beam bridge design scheme that meets the stress distribution and deformation requirements into the BIM platform to generate the final beam bridge structure model and complete the beam bridge structure optimization.

[0014] According to the above method of the embodiments of the present application, the following additional technical features may also be provided:

[0015] Further, obtain the geometric model of the beam bridge structure from the BIM platform, and establish a finite element analysis model of the beam bridge in combination with the mechanical property parameters of the UHPC material, including:

[0016] When establishing the finite element analysis model of the beam bridge, introduce the influence of environmental factors on the mechanical property parameters of the UHPC material, and adjust the elastic modulus, tensile strength and compressive strength of the UHPC material according to the climate data of the location of the beam bridge.

[0017] Further, adopt digital simulation technology to conduct dynamic loading simulation on the areas to be optimized, and obtain the structural response data under different load conditions, including introducing machine learning algorithms to predict the structural response of the beam bridge under extreme load conditions.

[0018] Further, introduce machine learning algorithms to predict the structural response of the beam bridge under extreme load conditions, including:

[0019] Collect historical load data and corresponding structural response data, train a machine learning model to identify the relationship between load and structural response; use the trained model to predict the structural response under extreme load conditions and identify potential high-risk areas in advance.

[0020] Further, compare the structural response data with the stress distribution analysis results to identify the weak links of the beam bridge structure and obtain the weak link identification results, including:

[0021] Based on the multi-scale analysis method, determine the stress distribution and displacement of the overall structure of the beam bridge through macroscopic finite element analysis. For the identified potential weak links, use a microscopic finite element model for simulation, analyze the stress state and damage mechanism inside the material, and evaluate the durability and safety of the beam bridge structure.

[0022] Further, according to the weak link identification results, adjust the beam bridge structure parameters, and re-conduct finite element analysis and digital simulation; through multiple iterative optimizations until the stress distribution is uniform and the displacement value is less than the preset threshold, obtain a beam bridge design scheme that meets the stress distribution and deformation requirements, including:

[0023] Use a genetic algorithm to search for the optimal combination of beam bridge structure parameters, define a gene encoding that includes the beam bridge structure size and material properties, and set a fitness function to evaluate the structural performance under different parameter combinations; through genetic operations of selection, crossover, and mutation, gradually iteratively evolve a beam bridge design scheme that meets the requirements of uniform stress distribution and a displacement value less than the preset threshold.

[0024] Using the beam bridge structure optimization method based on BIM and the finite element method provided in the embodiments of the present application, compared with the prior art, it has the following beneficial technical effects:

[0025] In the embodiments of the present application, by combining the beam bridge structure geometric model obtained from the BIM platform and the mechanical property parameters of UHPC materials, a more accurate finite element analysis model can be established, providing a solid foundation for subsequent analysis and optimization; the application of finite element analysis software makes the stress distribution analysis more accurate, can quickly extract the stress values of key nodes and judge the stress concentration phenomenon, thereby improving the design accuracy; the introduction of digital simulation technology enables the rapid acquisition of structural response data under different load conditions, further accelerating the design optimization process.

[0026] In the embodiments of the present application, through multiple iterative optimization strategies, continuously adjust the beam bridge structure parameters and re-conduct finite element analysis and digital simulation until the stress distribution is uniform and the displacement value is less than the preset threshold, ensuring the optimization of the final design scheme; introducing a machine learning algorithm to predict the beam bridge structure response under extreme load conditions can identify potential high-risk areas in advance, so as to conduct targeted optimization in the design stage and improve the overall performance of the structure.

[0027] Based on the multi-scale analysis method, the embodiments of the present application can more comprehensively evaluate the durability and safety of the beam bridge structure through the combination of macroscopic finite element analysis and microscopic finite element models; this not only helps to identify the weak links of the structure, but also provides strong guarantee for the long-term performance of the structure.

[0028] The embodiments of the present application also consider the influence of environmental factors on the mechanical characteristic parameters of UHPC materials and make adjustments according to the climate data of the location where the beam bridge is located, so that the design scheme is closer to the actual use environment and further enhances the durability of the structure. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 The flow diagram showing the beam bridge structure optimization method based on BIM and finite element method according to the embodiments of the present application is shown. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0030] In order to make the above objects, features and advantages of the present application more obvious and understandable, the following will describe in detail the specific embodiments of the present application with reference to the drawings. It can be understood that the specific embodiments described herein are only for explaining the present application, rather than limiting the present application. In addition, it should be noted that for the convenience of description, only some parts related to the present application rather than all the structures are shown in the drawings. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the scope of protection of the present application.

[0031] The terms "including" and "having" and any variations thereof in the present application are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but may optionally further include steps or units not listed, or may optionally further include other steps or units inherent to these processes, methods, products or devices.

[0032] Referring to "embodiments" in the present application means that the specific features, structures or characteristics described in connection with the embodiments can be included in at least one embodiment of the present application. The phrase appears in various places in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. Those skilled in the art explicitly and implicitly understand that the embodiments described in the present application can be combined with other embodiments.

[0033] As Figure 1 shown, the embodiments of the present application provide a beam bridge structure optimization method based on BIM and finite element method, including the following steps:

[0034] Step 101: Obtain the geometric model of the beam bridge structure from the BIM platform, and establish a finite element analysis model of the beam bridge in combination with the mechanical property parameters of UHPC material.

[0035] Step 101 is to obtain the geometric model of the beam bridge structure from the BIM (Building Information Modeling) platform and establish a finite element analysis model of the beam bridge in combination with the mechanical property parameters of UHPC (Ultra-High Performance Concrete) material. This is the starting point of the entire beam bridge structure optimization method and provides the basis for subsequent analysis and optimization.

[0036] The BIM platform is a digital platform that integrates information in multiple stages such as building design, construction, and operation. Obtaining the geometric model of the beam bridge from this platform can ensure the accuracy and integrity of the model, and facilitate subsequent analysis and optimization.

[0037] UHPC is a new type of concrete material with high strength, high toughness, and good durability. When establishing the finite element analysis model, it is necessary to fully consider the mechanical property parameters of UHPC, such as elastic modulus, tensile strength, and compressive strength, to ensure the accuracy of the model.

[0038] Environmental factors such as temperature, humidity, and salt spray will all affect the mechanical properties of UHPC material. When establishing the finite element analysis model, it is necessary to adjust the mechanical property parameters of UHPC material according to the climate data of the location where the beam bridge is located. This can ensure that the model is closer to the actual situation and improve the accuracy of the analysis.

[0039] Adjust the elastic modulus, tensile strength, and compressive strength of the material according to the influence of environmental factors on the mechanical properties of UHPC material. These adjusted parameters will be used in the finite element analysis model to simulate the stress conditions of the beam bridge in the actual environment.

[0040] Through Step 101 in the embodiments of this application, a more accurate and actual situation-based finite element analysis model of the beam bridge can be established. This model provides the basis for subsequent steps such as stress distribution analysis, structural deformation discrimination, and digital simulation, helps to discover the weak links of the beam bridge structure and optimize them. Introducing the influence of environmental factors on the mechanical property parameters of UHPC material can further improve the accuracy of the analysis and provide more reliable technical support for the design, construction, and maintenance of the beam bridge.

[0041] Step 102: Conduct stress distribution analysis on the finite element analysis model of the beam bridge through finite element analysis software, extract the stress values of key nodes, judge the stress concentration phenomenon, and obtain the stress distribution analysis results.

[0042] The main purpose of step 102 is to conduct an accurate stress distribution analysis on the established finite element analysis model of the beam bridge through finite element analysis software, which helps to understand the stress distribution of the beam bridge structure under the stress state, so as to identify potential stress concentration areas.

[0043] First, import the established finite element analysis model of the beam bridge into the finite element analysis software. This model usually contains key information such as the geometric shape, material properties, boundary conditions, and loading conditions of the beam bridge. Set the analysis parameters in the software, such as the solver type, convergence criterion, number of iterations, etc. The selection of these parameters will directly affect the accuracy and efficiency of the analysis results.

[0044] Start the finite element analysis software and begin the stress distribution analysis. The software will automatically calculate the stress values at each node and element of the beam bridge structure according to the input model information and set parameters. After the analysis is completed, export the stress value data of the key nodes from the software. These data are usually presented in the form of tables or graphs for subsequent analysis and processing.

[0045] Based on the extracted stress value data, determine whether there is stress concentration in the beam bridge structure. Stress concentration usually manifests as the stress values of certain nodes or elements being significantly higher than the surrounding areas, which may cause the structure to fail at these positions. Output the stress distribution analysis results in the form of a report or graph for use in subsequent steps. These results usually include stress distribution diagrams, lists of stress values of key nodes, and identifications of stress concentration areas.

[0046] Through accurate stress distribution analysis, step 102 can timely detect and handle potential stress concentration problems, thus avoiding the structure from being damaged during operation. In addition, the stress distribution analysis results can also provide important reference bases for subsequent steps such as deformation discrimination of the beam bridge structure, digital simulation, and parameter adjustment.

[0047] In step 103, according to the stress distribution analysis results, determine the deformation situation of the beam bridge structure, calculate the displacement values of the key sections, and compare them with the preset thresholds. If the displacement value exceeds the preset threshold, mark it as the area to be optimized; if the displacement value does not exceed the preset threshold, do not mark it.

[0048] Step 103 mainly focuses on the deformation situation of the beam bridge structure. First, based on the stress distribution analysis results, conduct deformation discrimination on the overall or local structure of the beam bridge. The core of this step is to calculate the displacement values of the key sections and compare these displacement values with the preset thresholds.

[0049] The stress distribution analysis results are the basis for step 103. By using finite element analysis software to conduct stress distribution analysis on the finite element analysis model of the beam bridge, the stress values of key nodes and the locations of stress concentration phenomena can be obtained. These analysis results provide a preliminary judgment on the stress state of the beam bridge structure.

[0050] After obtaining the stress distribution analysis results, the displacement values of key sections need to be calculated next. These key sections are usually the parts of the beam bridge structure that are subjected to greater stress or are more sensitive to deformation. By calculating the displacement values of these sections, the deformation conditions of the beam bridge structure can be more intuitively understood.

[0051] The calculated displacement values need to be compared with a preset threshold value. This preset threshold value is usually determined by comprehensively considering factors such as the design requirements of the beam bridge, material properties, and safety standards. If the displacement value exceeds this threshold, it means that the beam bridge structure may have excessive deformation under the stress state and needs to be optimized.

[0052] For the key sections where the displacement values exceed the preset threshold, they need to be marked as areas to be optimized. These areas are the focus of subsequent optimization work and need to improve their stress-bearing performance and deformation conditions by adjusting structural parameters, strengthening the structure, etc. If the displacement value does not exceed the preset threshold, it means that the deformation conditions of the beam bridge structure under the current stress state are within an acceptable range and no additional marking or optimization is required.

[0053] Step 103 provides an important basis for subsequent optimization work by judging the deformation conditions of the beam bridge structure and calculating the displacement values of key sections. Through this step, the problem areas that may exist in the beam bridge structure can be accurately identified and targeted measures can be taken for improvement, thereby improving the overall performance and safety of the beam bridge.

[0054] In step 104, digital simulation technology is used to conduct dynamic loading simulation on the areas to be optimized to obtain structural response data under different load conditions.

[0055] Step 104 involves using digital simulation technology to conduct dynamic loading simulation on the areas to be optimized to obtain structural response data under different load conditions. This step can not only deeply understand the behavior of the areas to be optimized under different load conditions but also provide strong data support for subsequent optimization design.

[0056] Digital simulation technology is a computer simulation-based technology that can accurately simulate and analyze beam bridge structures. In dynamic loading simulation, different load conditions are set, such as static load, dynamic load, impact load, etc., to simulate various load situations that a beam bridge may encounter during actual operation. Through simulation analysis, response data such as displacement, stress, and strain of the area to be optimized under these load conditions can be obtained, so as to comprehensively evaluate its structural performance.

[0057] To further improve the accuracy and efficiency of dynamic loading simulation, machine learning algorithms are introduced to predict the response of beam bridge structures under extreme load conditions. Machine learning is a computational method that can automatically learn and improve, and it can extract useful information and patterns from a large amount of data. In the process of beam bridge structure optimization, machine learning algorithms can be used to train models to identify the relationship between loads and structural responses.

[0058] Specifically, a large amount of historical load data and corresponding structural response data need to be collected first. These data can come from actual beam bridge operation monitoring, laboratory model tests, or other reliable sources. Then, these data are used to train a machine learning model so that it can accurately identify the complex relationship between loads and structural responses. Once the model training is completed, it can be used to predict the response of the beam bridge structure under extreme load conditions. This predictive ability is of great significance for identifying potential high-risk areas, optimizing structural design, and improving the safety of beam bridges.

[0059] By introducing machine learning algorithms, the application of digital simulation technology in beam bridge structure optimization has been further expanded and improved. It can not only improve the accuracy and efficiency of dynamic loading simulation, but also provide a more comprehensive and in-depth structural performance evaluation.

[0060] Step 105: Compare the structural response data with the stress distribution analysis results to identify the weak links of the beam bridge structure and obtain the weak link identification result.

[0061] Step 105 involves comparing the structural response data with the stress distribution analysis results to identify the weak links of the beam bridge structure. The detailed process of this step is as follows:

[0062] First, through macroscopic finite element analysis, determine the stress distribution and displacement of the overall structure of the beam bridge. Macroscopic finite element analysis is a commonly used structural analysis method that simulates the overall behavior of the structure by dividing the structure into multiple small elements and considering the interaction between elements. This method can provide the stress distribution and displacement of the beam bridge under specific loads, so as to initially understand the overall performance of the structure.

[0063] However, macroscopic finite element analysis may not be able to capture the local details in the structure, especially when there are potential weak links in the structure. Therefore, in order to more accurately identify these weak links, a microscopic finite element model needs to be used for simulation. The microscopic finite element model can describe the internal structure and properties of the material more precisely, so as to analyze the stress state and damage mechanism inside the material.

[0064] When using the microscopic finite element model for simulation, modeling and analysis will be carried out for the identified potential weak links. By simulating the material behavior under different load conditions, the stress state and damage mechanism of these weak links can be deeply understood, so as to evaluate the durability and safety of the beam bridge structure.

[0065] Finally, based on the results of macroscopic and microscopic finite element analyses, the identification results of the weak links of the beam bridge structure can be obtained. These results will provide important information about the structural performance and help formulate targeted optimization measures. For example, the structural parameters of the beam bridge can be adjusted according to the identified weak links, such as adding stiffeners, changing material properties, etc., to improve the overall performance and durability of the structure.

[0066] In summary, step 105 can accurately identify the weak links of the beam bridge structure and provide strong support for subsequent optimization measures by comparing the structural response data with the stress distribution analysis results and using the multi-scale analysis method for simulation and analysis.

[0067] In step 106, according to the weak link identification results, adjust the beam bridge structural parameters and re-perform finite element analysis and digital simulation; through multiple iterative optimizations until the stress distribution is uniform and the displacement value is less than the preset threshold, a beam bridge design scheme that meets the stress distribution and deformation requirements is obtained.

[0068] In step 105, the weak links of the beam bridge structure have been identified by comparing the structural response data with the stress distribution analysis results. Next, the structural parameters of the beam bridge need to be adjusted according to these identification results. These parameters may include the span, height, width of the beam bridge, material properties (such as elastic modulus, tensile strength, compressive strength, etc.) and the configuration of stiffeners, etc. The purpose of adjusting these parameters is to improve the stress distribution and deformation of the structure, so as to enhance the durability and safety of the beam bridge.

[0069] After adjusting the structural parameters of the beam bridge, it is necessary to re - conduct finite - element analysis and digital simulation. Finite - element analysis is a commonly used structural analysis method. It simulates the overall behavior of the structure by dividing the structure into multiple small elements and considering the interactions between elements. Digital simulation is a method that uses computer technology to simulate the dynamic loading of the structure, and it can obtain the structural response data under different load conditions. By re - conducting these two types of analyses, it is possible to evaluate whether the adjusted beam - bridge structure meets the stress - distribution and deformation requirements.

[0070] Due to the complexity of the beam - bridge structure, a single adjustment may not fully meet the stress - distribution and deformation requirements. Therefore, it is necessary to gradually approach the optimal solution through multiple iterative optimizations. In each iteration, the structural parameters are adjusted according to the analysis results, and finite - element analysis and digital simulation are re - conducted. Through continuous iteration, the stress distribution and deformation of the structure can be gradually improved until a beam - bridge design scheme that meets the requirements of uniform stress distribution and a displacement value less than the preset threshold is obtained.

[0071] In the process of multiple iterative optimizations, a genetic algorithm can be used to search for the optimal combination of beam - bridge structural parameters. The genetic algorithm is an optimization algorithm that simulates the natural - selection and genetic mechanisms. It gradually iteratively evolves to find the optimal solution through genetic operations such as selection, crossover, and mutation. In the optimization of the beam - bridge structure, parameters such as the structural dimensions and material properties of the beam bridge can be defined as gene codes, and a fitness function can be set to evaluate the structural performance under different parameter combinations. Through the iterative evolution of the genetic algorithm, a beam - bridge design scheme that meets the requirements of uniform stress distribution and a displacement value less than the preset threshold can be found.

[0072] In summary, step 106 involves adjusting the structural parameters of the beam bridge according to the weak - link identification results, and obtaining the final design scheme that meets the stress - distribution and deformation requirements through multiple iterative optimizations and genetic - algorithm search. The implementation of this step will help improve the durability and safety of the beam bridge.

[0073] In step 107, the beam - bridge design scheme that meets the stress - distribution and deformation requirements is imported into the BIM platform to generate the final beam - bridge structural model, completing the optimization of the beam - bridge structure.

[0074] In the previous steps, through a series of complex analysis and optimization processes, a beam - bridge design scheme that meets the stress - distribution and deformation requirements has been obtained. This scheme has withstood the tests of finite - element analysis, digital simulation, weak - link identification, and multiple iterative optimizations, ensuring its stability and safety under various load conditions.

[0075] Importing the optimized beam bridge design scheme into the BIM platform is the primary task of this step. In the BIM platform, the provided modeling tools and functions can be used to generate the final beam bridge structural model according to the optimized design scheme. This model not only includes the geometric shape and dimensional information of the beam bridge, but also rich information such as material properties, connection methods, and construction sequences. This information will provide important references and bases for subsequent construction and operation and maintenance.

[0076] With the generation of the final beam bridge structural model, the entire process of beam bridge structure optimization is also declared completed. This optimized beam bridge design scheme not only meets the requirements of stress distribution and deformation, but also realizes the sharing and efficient utilization of information through the integration and collaboration of the BIM platform. This will bring great convenience and benefits to subsequent construction and operation and maintenance.

[0077] In summary, step 107 marks the end of the entire optimization process and the generation of the final result. By importing the optimized design scheme into the BIM platform and generating the final structural model, it can provide strong support for subsequent construction and operation and maintenance, and provide useful references and examples for the optimization and design of similar projects.

[0078] It should be noted that in this application, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or also includes elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "including a..." does not exclude the existence of additional identical elements in the process, method, article or device including that element. In addition, it should be pointed out that the scope of the methods and devices in the embodiments of this application is not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in a reverse order according to the functions involved. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Additionally, the features described with reference to certain examples may be combined in other examples.

[0079] The embodiments of this application have been described above in conjunction with the accompanying drawings. However, this application is not limited to the above specific embodiments. The above specific embodiments are merely illustrative and not restrictive. Under the inspiration of this application, those of ordinary skill in the art can also make many forms without departing from the purpose of this application and the scope protected by the claims, and all of them fall within the protection scope of this application.

Claims

1. A beam bridge structure optimization method based on BIM and finite element method, characterized in that: The method comprises: Obtain the geometric model of the beam bridge structure from the BIM platform, and establish a finite element analysis model of the beam bridge based on the mechanical property parameters of the UHPC material; Use finite element analysis software to analyze the stress distribution of the beam bridge finite element analysis model, extract the stress values ​​of key nodes, determine the stress concentration phenomenon, and obtain the stress distribution analysis results; According to the stress distribution analysis results, the deformation of the beam bridge structure is judged, the displacement value of the key section is calculated, and compared with the preset threshold. If the displacement value exceeds the preset threshold, it is marked as an area to be optimized; if the displacement value does not exceed the preset threshold, it is not marked; Use digital simulation technology to simulate dynamic loading of the area to be optimized and obtain structural response data under different load conditions; Comparing the structural response data with the stress distribution analysis results, identifying weak links of the beam bridge structure, and obtaining weak link identification results; According to the weak link identification results, the structural parameters of the beam bridge are adjusted, and the finite element analysis and digital simulation are re-performed; through multiple iterations of optimization, the stress distribution is uniform and the displacement value is less than the preset threshold, and the beam bridge design that meets the stress distribution and deformation requirements is obtained; The beam bridge design scheme that meets the stress distribution and deformation requirements is imported into the BIM platform to generate the final beam bridge structure model and complete the beam bridge structure optimization.

2. The beam bridge structure optimization method according to claim 1, characterized in that: The method of obtaining the geometric model of the beam bridge structure from the BIM platform and establishing the finite element analysis model of the beam bridge in combination with the mechanical property parameters of the UHPC material includes: When establishing the finite element analysis model of the beam bridge, the influence of environmental factors on the mechanical properties of UHPC materials was introduced, and the elastic modulus, tensile strength and compressive strength of the UHPC material were adjusted according to the climate data of the location of the beam bridge.

3. The beam bridge structure optimization method according to claim 1, characterized in that: The digital simulation technology is used to simulate dynamic loading of the area to be optimized, and obtain structural response data under different load conditions, including the introduction of machine learning algorithms to predict the structural response of beam bridges under extreme load conditions.

4. The beam bridge structure optimization method according to claim 3, characterized in that: The introduction of machine learning algorithms to predict the structural response of beam bridges under extreme load conditions includes: Collect historical load data and corresponding structural response data, train machine learning models to identify the relationship between load and structural response; use the trained model to predict the structural response under extreme load conditions and identify potential high-risk areas in advance.

5. The beam bridge structure optimization method according to claim 1, characterized in that: The step of comparing the structural response data with the stress distribution analysis result to identify the weak links of the beam bridge structure and obtain the weak link identification result includes: Based on the multi-scale analysis method, the stress distribution and displacement of the overall structure of the beam bridge are determined through macroscopic finite element analysis. For the identified potential weak links, the microscopic finite element model is used to simulate and analyze the stress state and damage mechanism inside the material, and to evaluate the durability and safety of the beam bridge structure.

6. The beam bridge structure optimization method according to claim 1, characterized in that: According to the weak link identification results, the structural parameters of the beam bridge are adjusted, and the finite element analysis and digital simulation are re-performed; Through multiple iterations of optimization, until the stress distribution is uniform and the displacement value is less than the preset threshold, a beam bridge design scheme that meets the stress distribution and deformation requirements is obtained, including: A genetic algorithm is used to search for the optimal combination of beam bridge structural parameters, and the genetic code including the structural dimensions and material properties of the beam bridge is defined. The fitness function is set to evaluate the structural performance under different parameter combinations. Through genetic operations of selection, crossover and mutation, a beam bridge design scheme that satisfies uniform stress distribution and displacement value less than the preset threshold is gradually iterated and evolved.

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