Corrugated steel web composite beam bridge simulation method, system, equipment and medium

Abstract

The invention relates to a corrugated steel web composite beam bridge simulation method, system and equipment and a medium. The method comprises the following steps: acquiring a three-dimensional structure finite element model of the corrugated steel web composite beam bridge; calculating a static characteristic vector of a structural member in the three-dimensional structural finite element model of the corrugated steel web composite girder bridge; obtaining a dynamic load vector, and obtaining a distributed load field vector and a bridge flexural rigidity vector based on the dynamic load vector and the corrugated steel web composite beam bridge three-dimensional structure finite element model; inputting the bridge static characteristic vector, the dynamic load vector, the distributed load field vector and the bridge flexural rigidity vector into a bridge dynamic neural network model to obtain a corrugated steel web composite beam bridge displacement field vector; and constructing a three-dimensional dynamic finite element model of the corrugated steel web composite girder bridge based on the dynamic load vector, the displacement field vector of the corrugated steel web composite girder bridge and the three-dimensional structure finite element model of the corrugated steel web composite girder bridge. By adopting the method, the dynamic load simulation of the corrugated steel web composite beam bridge can be realized.

Description

Technical Field

[0001] The present invention belongs to the technical field of three-dimensional finite element modeling and numerical simulation of bridges, and in particular relates to a simulation method, system, equipment and medium for a composite beam bridge with corrugated steel webs. Background Art

[0002] In recent years, composite beam bridges with corrugated steel webs have become an important trend in bridge design due to their good structural performance, high material utilization and low construction cost. The core advantage of composite beam bridges with corrugated steel webs is that through the innovative design of corrugated steel webs, it can not only reduce deadweight and improve rigidity, but also significantly reduce the amount of materials used and the difficulty of construction, which is especially suitable for bridge structures with large spans and high load requirements.

[0003] However, despite the significant advantages of composite beam bridges with corrugated steel webs, how to quickly and accurately design them while meeting diverse design requirements is still a major challenge facing the current bridge design field. Traditional design methods often fail to fully consider the various constraints of bridges. At the same time, the structural response of composite beam bridges with corrugated steel webs under dynamic loads often exhibits nonlinear characteristics. It is difficult to effectively simulate and analyze the impact of dynamic loads on composite beam bridges with corrugated steel webs through artificial means, which is not conducive to further optimizing the structure of composite beam bridges with corrugated steel webs. Summary of the invention

[0004] Based on this, it is necessary to provide a simulation method, system, equipment and medium for a corrugated steel web composite beam bridge to address the above technical problems.

[0005] In a first aspect, the present application provides a simulation method for a corrugated steel web composite beam bridge, comprising: A three-dimensional structural finite element model of a composite beam bridge with corrugated steel webs is obtained, and the three-dimensional structural finite element model of a composite beam bridge with corrugated steel webs is used to characterize the static structural characteristics of the composite beam bridge with corrugated steel webs; Calculate the static characteristic values ​​of the structural components in the three-dimensional finite element model of the corrugated steel web composite beam bridge, and construct the bridge static characteristic vector, which is used to characterize the mechanical properties of the corrugated steel web composite beam bridge under static load; Obtain a dynamic load vector, and obtain a distributed load field vector and a bridge bending stiffness vector based on the dynamic load vector and a three-dimensional structural finite element model of a composite beam bridge with corrugated steel webs; The bridge static characteristic vector, dynamic load vector, distributed load field vector and bridge bending stiffness vector are input into the bridge dynamic neural network model to obtain the displacement field vector of the corrugated steel web composite beam bridge; Based on the dynamic load vector, the displacement field vector of the corrugated steel web composite beam bridge and the three-dimensional structural finite element model of the corrugated steel web composite beam bridge, a three-dimensional dynamic finite element model of the corrugated steel web composite beam bridge is constructed. The three-dimensional dynamic finite element model is used to simulate the mechanical properties of the corrugated steel web composite beam bridge under dynamic loads.

[0006] In one embodiment, obtaining a three-dimensional structural finite element model of a corrugated steel web composite beam bridge includes: Obtaining a corrugated steel web composite beam bridge route and initializing a corrugated steel web composite beam bridge model to obtain a static initial model of the corrugated steel web composite beam bridge; Obtaining structural parameters of the corrugated steel web composite beam bridge, and building a three-dimensional structural finite element model of the corrugated steel web composite beam bridge based on the structural parameters of the corrugated steel web composite beam bridge and the static initial model of the corrugated steel web composite beam bridge; The expression of the structural parameters of the composite beam bridge with corrugated steel web is:

[0007] In the formula, is the structural parameter vector of the composite beam bridge with corrugated steel webs, is the bridge span component, is the bridge deck width component, is the bridge beam height component, is the bridge beam bottom curve component, is the thickness component of the corrugated steel web, is the height component of the corrugated steel web.

[0008] In one embodiment, obtaining structural parameters of a corrugated steel web composite beam bridge includes: Obtaining initial vectors of structural parameters of a composite beam bridge with corrugated steel webs, and calculating comprehensive performance indicators of the bridge based on the initial vectors of structural parameters of the bridge; If the comprehensive performance index of the bridge is higher than the threshold to be optimized, the initial vector of the structural parameters of the corrugated steel web composite beam bridge is set as the structural parameters of the corrugated steel web composite beam bridge. The threshold to be optimized is used to represent the boundary value of the comprehensive performance index of the bridge that needs to adjust the initial vector of the structural parameters of the corrugated steel web composite beam bridge to improve the comprehensive performance of the bridge; If the comprehensive performance index of the bridge is lower than the threshold to be optimized, the initial vector of the structural parameters of the corrugated steel web composite beam bridge is optimized based on the BP neural network, and the optimized initial vector of the structural parameters of the corrugated steel web composite beam bridge is set as the structural parameters of the corrugated steel web composite beam bridge.

[0009] In one embodiment, the initial vector of structural parameters of a corrugated steel web composite beam bridge is optimized based on a BP neural network, including: The initial vector of the structural parameters of the composite beam bridge with corrugated steel web is input into the 6-dimensional BP neural network to obtain the optimized initial vector of the structural parameters of the composite beam bridge with corrugated steel web; The objective function of the BP neural network is constructed based on the comprehensive performance index of the bridge; The expression of the comprehensive performance index of the bridge is: In the formula, A is the comprehensive performance index of the bridge, is the strength index coefficient, is the deflection index coefficient, is the economic indicator coefficient, is the maximum stress of the whole bridge under the ultimate load, is the ultimate strength of the bridge material, is the deflection in the middle of the main span under the ultimate load, is the upper limit of the mid-span deflection of the main span, M is the theoretical mass of the bridge, is the bridge quality cost coefficient, and P is the estimated cost of the bridge.

[0010] In one embodiment, the bridge dynamic neural network model is a convolutional neural network model, and the bridge dynamic neural network model includes a convolutional layer and a fully connected layer; The expression of the objective function of the bridge dynamic neural network model is: In the formula, is the objective function of the bridge dynamic neural network model, is the dynamic load vector value, is the dynamic load vector, is the bridge bending stiffness vector value under dynamic load, is the displacement field vector value of the composite beam bridge with corrugated steel web under dynamic load, is the distributed load field vector value under dynamic load.

[0011] In one embodiment, the bridge static characteristic vector includes a bridge elastic buckling critical shear stress field vector; The calculation formula of the critical shear stress field vector of bridge elastic buckling is: In the formula, is the critical shear stress field vector value of bridge elastic buckling, is the local elastic buckling shear stress, is the overall elastic buckling shear stress, is the local shear buckling coefficient, E is Young's modulus, is Poisson's ratio, is the thickness of the corrugated steel web, is the maximum folded width of the corrugated steel web, is the overall shear buckling coefficient, is the longitudinal bending stiffness per unit length of the corrugated steel web, Transverse bending stiffness per unit length of corrugated steel web, is the height of corrugated steel web.

[0012] In one embodiment, the static characteristic vector of the bridge includes an external beam cumulative damage value component, a shear stud cumulative damage value component, and a bridge overall life prediction component.

[0013] In a second aspect, the present application also provides a corrugated steel web composite beam bridge simulation system, comprising: A structural model acquisition module is used to acquire a three-dimensional structural finite element model of a composite beam bridge with corrugated steel webs. The three-dimensional structural finite element model of a composite beam bridge with corrugated steel webs is used to characterize the static structural characteristics of the composite beam bridge with corrugated steel webs. Static characteristic analysis module, used to calculate the static characteristic values ​​of the structural components in the three-dimensional structural finite element model of the corrugated steel web composite beam bridge, and construct the bridge static characteristic vector, which is used to characterize the mechanical properties of the corrugated steel web composite beam bridge under static load; A dynamic data acquisition module is used to acquire a dynamic load vector, and acquire a distributed load field vector and a bridge bending stiffness vector based on the dynamic load vector and a three-dimensional structural finite element model of a composite beam bridge with corrugated steel webs; Dynamic displacement analysis module, used to input bridge static characteristic vector, dynamic load vector, distributed load field vector and bridge bending stiffness vector into the bridge dynamic neural network model to obtain the displacement field vector of the corrugated steel web composite beam bridge; The dynamic model acquisition module is used to build a three-dimensional dynamic finite element model of the corrugated steel web composite beam bridge based on the dynamic load vector, the displacement field vector of the corrugated steel web composite beam bridge and the three-dimensional structural finite element model of the corrugated steel web composite beam bridge.

[0014] In a third aspect, the present application further provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented: A three-dimensional structural finite element model of a composite beam bridge with corrugated steel webs is obtained, and the three-dimensional structural finite element model of a composite beam bridge with corrugated steel webs is used to characterize the static structural characteristics of the composite beam bridge with corrugated steel webs; Calculate the static characteristic values ​​of the structural components in the three-dimensional finite element model of the corrugated steel web composite beam bridge, and construct the bridge static characteristic vector, which is used to characterize the mechanical properties of the corrugated steel web composite beam bridge under static load; Obtain a dynamic load vector, and obtain a distributed load field vector and a bridge bending stiffness vector based on the dynamic load vector and a three-dimensional structural finite element model of a composite beam bridge with corrugated steel webs; The bridge static characteristic vector, dynamic load vector, distributed load field vector and bridge bending stiffness vector are input into the bridge dynamic neural network model to obtain the displacement field vector of the corrugated steel web composite beam bridge; Based on the dynamic load vector, the displacement field vector of the corrugated steel web composite beam bridge and the three-dimensional structural finite element model of the corrugated steel web composite beam bridge, a three-dimensional dynamic finite element model of the corrugated steel web composite beam bridge is constructed. The three-dimensional dynamic finite element model is used to simulate the mechanical properties of the corrugated steel web composite beam bridge under dynamic loads.

[0015] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the following steps are implemented: A three-dimensional structural finite element model of a composite beam bridge with corrugated steel webs is obtained, and the three-dimensional structural finite element model of a composite beam bridge with corrugated steel webs is used to characterize the static structural characteristics of the composite beam bridge with corrugated steel webs; Calculate the static characteristic values ​​of the structural components in the three-dimensional finite element model of the corrugated steel web composite beam bridge, and construct the bridge static characteristic vector, which is used to characterize the mechanical properties of the corrugated steel web composite beam bridge under static load; Obtain a dynamic load vector, and obtain a distributed load field vector and a bridge bending stiffness vector based on the dynamic load vector and a three-dimensional structural finite element model of a composite beam bridge with corrugated steel webs; The bridge static characteristic vector, dynamic load vector, distributed load field vector and bridge bending stiffness vector are input into the bridge dynamic neural network model to obtain the displacement field vector of the corrugated steel web composite beam bridge; Based on the dynamic load vector, the displacement field vector of the corrugated steel web composite beam bridge and the three-dimensional structural finite element model of the corrugated steel web composite beam bridge, a three-dimensional dynamic finite element model of the corrugated steel web composite beam bridge is constructed. The three-dimensional dynamic finite element model is used to simulate the mechanical properties of the corrugated steel web composite beam bridge under dynamic loads.

[0016] The above-mentioned simulation method and system of the corrugated steel web composite beam bridge can accurately evaluate the mechanical properties of the corrugated steel web composite beam bridge under static load by constructing a three-dimensional structural finite element model, calculating static characteristic values ​​and constructing static characteristic vectors, thereby providing a strong basis for the initial design and static load safety of the bridge.

[0017] Furthermore, the acquisition of dynamic load vectors is improved, and the distributed load field vectors and bridge bending stiffness vectors are further calculated, as well as the displacement field vectors are obtained by combining the dynamic neural network model. The dynamic load conditions faced by the bridge in actual use are fully considered, making the analysis of bridge performance closer to actual working conditions, and thus better understanding the mechanical behavior of the bridge under different load conditions to ensure the safety of transportation. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the related technologies, the drawings required for use in the embodiments or the related technical descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0019] Figure 1 A schematic flow chart of a method for simulating a corrugated steel web composite beam bridge provided in one embodiment of the present application; Figure 2 A schematic flow chart of a method for obtaining structural parameters of a corrugated steel web composite beam bridge provided in one embodiment of the present application; Figure 3 A schematic diagram of the structure of a 6-dimensional BP neural network provided in one embodiment of the present application; Figure 4 A schematic diagram of the structure of a bridge dynamic neural network model provided by one embodiment of the present application; Figure 5 A schematic flow chart of another method for simulating a composite beam bridge with corrugated steel webs provided in one embodiment of the present application; Figure 6 A schematic structural diagram of a corrugated steel web composite beam bridge simulation system provided for one embodiment of the present application. DETAILED DESCRIPTION

[0020] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0021] In one embodiment, Figure 1 As shown, a simulation method for a composite beam bridge with corrugated steel webs is provided. This embodiment uses the method applied to a terminal as an example for illustration. It can be understood that the method can also be applied to a server, and can also be applied to a system including a terminal and a server, and is implemented through the interaction between the terminal and the server. In this embodiment, the method includes the following steps: Step S101, obtaining a three-dimensional structural finite element model of a corrugated steel web composite beam bridge.

[0022] Specifically, the terminal can obtain a three-dimensional structural finite element model of a corrugated steel web composite beam bridge. The three-dimensional structural finite element model of a corrugated steel web composite beam bridge can be a preset three-dimensional structural finite element model or a three-dimensional structural finite element model constructed based on basic information of the corrugated steel web composite beam bridge through an application installed on the terminal.

[0023] Schematically, the three-dimensional structural finite element model of the composite beam bridge with corrugated steel web can be used to characterize the static structural characteristics of the composite beam bridge with corrugated steel web. The three-dimensional structural finite element model of the composite beam bridge with corrugated steel web can be used to analyze the key performance indicators such as structural strength and stiffness of the composite beam bridge with corrugated steel web under static load.

[0024] Step S102, calculating the static characteristic values ​​of the structural members in the three-dimensional structural finite element model of the corrugated steel web composite beam bridge, and constructing a static characteristic vector of the bridge.

[0025] Specifically, the terminal can perform finite element characteristic analysis and calculation based on the three-dimensional structural finite element model of the corrugated steel web composite beam bridge to obtain the static characteristic values ​​of the structural members in the three-dimensional structural finite element model of the corrugated steel web composite beam bridge. And the static characteristic vector of the bridge can be constructed based on the obtained static characteristic values.

[0026] Schematically, the bridge static characteristic vector can be used to characterize the mechanical properties of the corrugated steel web composite beam bridge under static load. The bridge static characteristic vector can be used to evaluate the static bearing capacity, stability and connection relationship between the various parts of the bridge structure.

[0027] Step S103, obtaining a dynamic load vector, and obtaining a distributed load field vector and a bridge bending stiffness vector based on the dynamic load vector and the three-dimensional structural finite element model of the corrugated steel web composite beam bridge.

[0028] Specifically, the terminal can obtain a dynamic load vector, which can be a preset dynamic load vector stored in a database, or a real-time dynamic load vector constructed by an application installed on the terminal based on the basic parameter information of the actual dynamic load of the corrugated steel web composite beam bridge. The terminal can apply the dynamic load vector to the three-dimensional structural finite element model of the corrugated steel web composite beam bridge, and calculate the load distribution of each part of the corrugated steel web composite beam bridge under the action of the dynamic load through the finite element analysis software to obtain the distributed load field vector. Among them, the three-dimensional structural finite element model of the corrugated steel web composite beam bridge can be, but not limited to, characterizing the geometric characteristics of the corrugated steel web, the material properties of the corrugated steel web composite beam bridge, and the connection method between the corrugated steel web and the concrete wing plate; the finite element analysis software can be, but not limited to, ABAQUS, ANSYS and LS-DYNA. The terminal can calculate the initial bridge bending stiffness vector based on the knowledge of material mechanics and structural mechanics combined with the three-dimensional structural finite element model of the corrugated steel web composite beam bridge, and use the three-dimensional structural finite element model of the corrugated steel web composite beam bridge to simulate the deformation and stress distribution of the corrugated steel web composite beam bridge under dynamic loads. The terminal can also verify and adjust the initial bridge bending stiffness vector based on the simulation results of the deformation and stress distribution to obtain the bridge bending stiffness vector.

[0029] Optionally, the dynamic load vector may include but is not limited to a dynamic meteorological load vector and a dynamic traffic load vector. The dynamic meteorological load vector may include but is not limited to a temperature dynamic load vector, a water flow dynamic load vector, an air flow dynamic load vector and an earthquake dynamic load vector. The dynamic traffic load vector may include but is not limited to a train dynamic load vector, a motor vehicle dynamic load vector and an accident dynamic load vector.

[0030] Schematically, the distributed load field vector can be used to describe the distribution of dynamic loads on the corrugated steel web composite beam bridge structure. The distributed load field vector may include but is not limited to the magnitude and direction of the loads borne at different positions of the corrugated steel web composite beam bridge. The bridge bending stiffness vector can be used to reflect the bending deformation resistance of the corrugated steel web composite beam bridge. The bridge bending stiffness vector can evaluate the mechanical properties and structural stability of the bridge by comprehensively considering the material properties and geometric shape of the bridge structure.

[0031] Step S104, inputting the bridge static characteristic vector, dynamic load vector, distributed load field vector and bridge bending stiffness vector into the bridge dynamic neural network model to obtain the displacement field vector of the corrugated steel web composite beam bridge.

[0032] Specifically, the terminal can input the bridge static characteristic vector, dynamic load vector, distributed load field vector and bridge bending stiffness vector into the bridge dynamic neural network model to obtain the displacement field vector of the corrugated steel web composite beam bridge. The bridge dynamic neural network model can be carried on the terminal or on the server.

[0033] Optionally, the terminal may use the bridge static characteristic vector as a training supervision label for the bridge dynamic neural network model.

[0034] Step S105, constructing a three-dimensional dynamic finite element model of the composite beam bridge with corrugated steel webs based on the dynamic load vector, the displacement field vector of the composite beam bridge with corrugated steel webs and the three-dimensional structural finite element model of the composite beam bridge with corrugated steel webs.

[0035] Specifically, the terminal can generate a three-dimensional dynamic model of dynamic load based on the dynamic load vector, and can apply the displacement field vector of the corrugated steel web composite beam bridge to the three-dimensional structural finite element model of the corrugated steel web composite beam bridge to generate a three-dimensional dynamic structural deformation finite element model of the corrugated steel web composite beam bridge. Among them, the three-dimensional dynamic structural deformation finite element model of the corrugated steel web composite beam bridge can make the node displacement of the three-dimensional dynamic finite element model of the corrugated steel web composite beam bridge conform to the actual dynamic response during the dynamic analysis process. The terminal can perform time matching and position matching of the three-dimensional dynamic model of dynamic load and the three-dimensional dynamic structural deformation finite element model of the corrugated steel web composite beam bridge to construct a three-dimensional dynamic finite element model of the corrugated steel web composite beam bridge. Among them, the three-dimensional dynamic finite element model can be used to simulate the mechanical properties of the corrugated steel web composite beam bridge under the action of dynamic loads.

[0036] Optionally, the three-dimensional dynamic finite element model may include, but is not limited to, a dynamic load sub-model corresponding to a dynamic load vector, a three-dimensional dynamic finite element sub-model of a corrugated steel web composite beam bridge, and a time degradation sub-model of a corrugated steel web composite beam bridge.

[0037] In the above-mentioned simulation method of the composite beam bridge with corrugated steel web, by constructing a three-dimensional finite element model of the composite beam bridge with corrugated steel web, the geometric shape, material properties and boundary conditions of the composite beam bridge with corrugated steel web can be accurately characterized. By calculating the static characteristic values ​​of the structural parts, the mechanical properties of the bridge under static loads can be quantified, and the static characteristic values ​​can be constructed in vector form to facilitate subsequent analysis and optimization.

[0038] Furthermore, through the dynamic load vector, the dynamic loads borne by the composite beam bridge with corrugated steel web in actual use can be accurately simulated, and by using the neural network model, the displacement field of the bridge under dynamic load can be quickly predicted to reduce the calculation time. Through the three-dimensional dynamic finite element model, combined with the static and dynamic analysis results, the mechanical properties of the bridge under actual load can be accurately simulated, the structural performance of the bridge can be comprehensively evaluated, and the design efficiency, safety and reliability of the composite beam bridge with corrugated steel web can be significantly improved.

[0039] In one of the optional embodiments, obtaining a three-dimensional structural finite element model of a corrugated steel web composite beam bridge includes: Specifically, a corrugated steel web composite beam bridge line is obtained and a corrugated steel web composite beam bridge model is initialized to obtain a static initial model of the corrugated steel web composite beam bridge.

[0040] Indicatively, a route of a composite beam bridge with corrugated steel web may be generated based on a route planning file, map data, and surveying data of the composite beam bridge with corrugated steel web.

[0041] Optionally, a matching initial model of a composite beam bridge with corrugated steel web may be obtained from a database of initial models of composite beam bridge with corrugated steel web based on the composite beam bridge line with corrugated steel web as a static initial model of the composite beam bridge with corrugated steel web.

[0042] Specifically, the structural parameters of the corrugated steel web composite beam bridge are obtained, and a three-dimensional structural finite element model of the corrugated steel web composite beam bridge is constructed based on the structural parameters of the corrugated steel web composite beam bridge and the static initial model of the corrugated steel web composite beam bridge.

[0043] Optionally, a three-dimensional structural finite element model of the corrugated steel web composite beam bridge may be constructed based on preset structural parameters of the corrugated steel web composite beam bridge and combined with a static initial model of the corrugated steel web composite beam bridge.

[0044] Specifically, the feasible expressions for the structural parameters of the corrugated steel web composite beam bridge are:

[0045] In the formula, is the structural parameter vector of the composite beam bridge with corrugated steel webs, is the bridge span component, is the bridge deck width component, is the bridge beam height component, is the bridge beam bottom curve component, is the thickness component of the corrugated steel web, is the height component of the corrugated steel web.

[0046] Schematically, the structural parameter vector of the composite beam bridge with corrugated steel webs The bridge span component Can be used to characterize the overall stiffness of the bridge, the width component of the bridge deck It can be used to characterize the lateral stability of bridges and the high component of bridge beams Can be used to characterize the mechanical performance of bridges and the curve component of the bottom of bridge beams Can be used to characterize the stress distribution of bridges, the thickness component of corrugated steel webs and corrugated steel web height component It can be used to characterize the mechanical properties of corrugated steel webs.

[0047] In the above-mentioned simulation method of the corrugated steel web composite beam bridge, the geometric shape and topological structure of the corrugated steel web composite beam bridge can be accurately described through line data and structural parameters, and based on the structural parameter vector, a three-dimensional finite element model can be quickly generated to provide a basis for subsequent static and dynamic analysis and ensure the reliability of the analysis results.

[0048] In one of the optional embodiments, Figure 2As shown in the figure, the structural parameters of the corrugated steel web composite beam bridge are obtained, including: Step S201, obtaining an initial vector of structural parameters of a composite beam bridge with corrugated steel webs, and calculating a comprehensive performance index of the bridge based on the initial vector of structural parameters of the bridge.

[0049] Optionally, the comprehensive performance index of the bridge may include a strength component, a deflection component and an economic component.

[0050] Step S202: if the comprehensive performance index of the bridge is higher than the threshold to be optimized, the initial vector of the structural parameters of the corrugated steel web composite beam bridge is set as the structural parameters of the corrugated steel web composite beam bridge.

[0051] Specifically, if the comprehensive performance index of the bridge is higher than the threshold to be optimized, the initial vector of the structural parameters of the corrugated steel web composite beam bridge is set to the structural parameters of the corrugated steel web composite beam bridge, and the threshold to be optimized is used to represent the boundary value of the comprehensive performance index of the bridge that needs to adjust the initial vector of the structural parameters of the corrugated steel web composite beam bridge to improve the comprehensive performance of the bridge.

[0052] Step S203, if the comprehensive performance index of the bridge is lower than the threshold to be optimized, the initial vector of the structural parameters of the corrugated steel web composite beam bridge is optimized based on the BP neural network, and the optimized initial vector of the structural parameters of the corrugated steel web composite beam bridge is set as the structural parameters of the corrugated steel web composite beam bridge.

[0053] Optionally, the dimension of the BP neural network may be the same as the dimension of the initial vector of the structural parameters of the corrugated steel web composite beam bridge.

[0054] In the above-mentioned simulation method of the composite beam bridge with corrugated steel web, the bridge performance can be quantified by calculating the comprehensive performance indicators, and the design scheme can be quickly evaluated, thereby significantly improving the design efficiency, performance and economy of the composite beam bridge with corrugated steel web.

[0055] In one of the optional embodiments, please refer to Figure 3 , optimize the initial vector of structural parameters of corrugated steel web composite beam bridge, including: Specifically, the initial vector of the structural parameters of the composite beam bridge with corrugated steel web is input into the 6-dimensional BP neural network to obtain the optimized initial vector of the structural parameters of the composite beam bridge with corrugated steel web; Schematically, the BP neural network may include an input layer, a hidden layer, and an output layer. The initial vector of the structural parameters of the corrugated steel web composite beam bridge to be optimized may be input into the trained BP neural network through the input layer for optimization processing, and the optimized initial vector of the structural parameters of the corrugated steel web composite beam bridge may be output in the output layer.

[0056] Optionally, before inputting the initial vector of the structural parameter of the corrugated steel web composite beam bridge into the 6-dimensional BP neural network, the data of the initial vector of the structural parameter of the corrugated steel web composite beam bridge can be subjected to sample data normalization processing. A feasible formula for sample data normalization processing is:

[0057] In the formula, X is the value before normalization, and Y is the value after normalization. is the lower limit parameter of normalization processing, is the upper limit parameter of normalization processing, is the maximum value of each dimension data, The minimum value of each dimension data.

[0058] Specifically, the objective function of the BP neural network can be constructed based on the comprehensive performance index of the bridge.

[0059] Specifically, the feasible expression of the comprehensive performance index of the bridge is: Where A is the comprehensive performance index of the bridge, is the strength index coefficient, is the deflection index coefficient, is the economic indicator coefficient, is the maximum stress of the whole bridge under the ultimate load, is the ultimate strength of the bridge material, is the deflection in the middle of the main span under the ultimate load, is the upper limit of the mid-span deflection of the main span, M is the theoretical mass of the bridge, is the bridge quality cost coefficient, and P is the estimated cost of the bridge.

[0060] In the above simulation method of corrugated steel web composite beam bridge, the nonlinear mapping ability of BP neural network can be used to quickly search for the optimal structural parameters; based on the objective function of comprehensive performance indicators, the optimization direction can be clarified and multi-objective optimization can be achieved. By introducing BP neural network, the design efficiency, performance and economy of corrugated steel web composite beam bridge can be significantly improved.

[0061] In one of the optional embodiments, please refer to Figure 4 ,The bridge dynamic neural network model is a convolutional neural network model, and the bridge dynamic neural network model can include a convolutional layer and a fully connected layer.

[0062] Specifically, the feasible expression of the objective function of the bridge dynamic neural network model is: In the formula, is the objective function of the bridge dynamic neural network model, is the dynamic load vector value, is the dynamic load vector, is the bridge bending stiffness vector value under dynamic load, is the displacement field vector value of the composite beam bridge with corrugated steel web under dynamic load, is the distributed load field vector value under dynamic load.

[0063] In the above-mentioned simulation method of the corrugated steel web composite beam bridge, the convolutional neural network can be used to effectively extract the local features of the input data, reduce the amount of calculation, and improve the calculation efficiency, thereby significantly improving the dynamic analysis efficiency, prediction accuracy and design level of the corrugated steel web composite beam bridge.

[0064] In one optional embodiment, the static characteristic vector of the bridge includes a critical shear stress field vector of elastic buckling of the bridge.

[0065] Specifically, the calculation formula for the critical shear stress field vector of bridge elastic buckling is:

[0066] In the formula, is the critical shear stress field vector value of bridge elastic buckling, is the local elastic buckling shear stress, is the overall elastic buckling shear stress, is the local shear buckling coefficient, E is Young's modulus, is Poisson's ratio, is the thickness of the corrugated steel web, is the maximum folded width of the corrugated steel web, is the overall shear buckling coefficient, is the longitudinal bending stiffness per unit length of the corrugated steel web, Transverse bending stiffness per unit length of corrugated steel web, is the height of corrugated steel web.

[0067] Optionally, when the geometric shape of the corrugated steel web is relatively simple, such as when the corrugated steel web is symmetrical or periodically regular corrugated, and in the preliminary design of the bridge structure, the feasible calculation formulas for the longitudinal bending stiffness per unit length of the corrugated steel web and the transverse bending stiffness per unit length of the corrugated steel web are:

[0068] In the formula, is the corrugation shape correction factor.

[0069] Furthermore, when the geometric shape of the corrugated steel web is more complex, such as: the corrugation is asymmetric, variable cross-section or locally strengthened; when the corrugated steel web is subjected to dynamic loads and multi-directional load coupling; and in the detailed design stage of the bridge structure, the feasible calculation formulas for the longitudinal bending stiffness per unit length of the corrugated steel web and the transverse bending stiffness per unit length of the corrugated steel web are:

[0070] Wherein, b is the length of the straight section between two adjacent crests or troughs on the corrugated steel web, d is the horizontal projection length of the inclined section between adjacent crests or troughs on the corrugated steel web, and c is the length of the inclined section between adjacent crests or troughs on the corrugated steel web. is the moment of inertia of the corrugated steel web about the y-axis, It is the vertical projection length of the inclined section of adjacent wave crests or wave troughs on the corrugated steel web. It is the inclination angle of the inclined section of adjacent wave crests or wave troughs on the corrugated steel web.

[0071] Schematically, the critical shear stress field vector of bridge elastic buckling can be used as a training supervision label for the bridge dynamic neural network model, and the critical shear stress field vector of bridge elastic buckling can be used to characterize the critical shear stress when the bridge structure reaches the elastic buckling state under the action of shear load.

[0072] In one feasible embodiment, the static characteristic vector of the bridge includes an external beam cumulative damage value component, a shear stud cumulative damage value component and a bridge overall life prediction component.

[0073] Alternatively, a feasible expression for the cumulative damage value component is: Where D is the cumulative damage value, For the The number of cycles under the same stress amplitude, For the Fatigue life corresponding to different stress amplitudes.

[0074] In one possible embodiment, Figure 5 As shown in the figure, another simulation method of corrugated steel web composite beam bridge is provided, including: Step S501, obtaining a corrugated steel web composite beam bridge line and initializing a corrugated steel web composite beam bridge model to obtain a static initial model of the corrugated steel web composite beam bridge.

[0075] Step S502, obtaining the initial vector of the structural parameters of the corrugated steel web composite beam bridge, and calculating the comprehensive performance index of the bridge based on the initial vector of the bridge structural parameters.

[0076] Step S511, if the comprehensive performance index of the bridge is higher than the threshold to be optimized, the initial vector of the structural parameters of the corrugated steel web composite beam bridge is set as the structural parameters of the corrugated steel web composite beam bridge.

[0077] Step S521, if the comprehensive performance index of the bridge is lower than the threshold to be optimized, the initial vector of the structural parameters of the corrugated steel web composite beam bridge is input into the 6-dimensional BP neural network to obtain the optimized initial vector of the structural parameters of the corrugated steel web composite beam bridge.

[0078] Step S522, setting the optimized initial vector of the structural parameters of the composite beam bridge with corrugated steel web as the structural parameters of the composite beam bridge with corrugated steel web.

[0079] Step S503: constructing a three-dimensional structural finite element model of the composite beam bridge with corrugated steel webs based on the structural parameters of the composite beam bridge with corrugated steel webs and the static initial model of the composite beam bridge with corrugated steel webs.

[0080] Step S504, calculating the static characteristic values ​​of the structural members in the three-dimensional structural finite element model of the corrugated steel web composite beam bridge, and constructing a static characteristic vector of the bridge.

[0081] Step S505, obtaining a dynamic load vector, and obtaining a distributed load field vector and a bridge bending stiffness vector based on the dynamic load vector and the three-dimensional structural finite element model of the corrugated steel web composite beam bridge.

[0082] Step S506, inputting the bridge static characteristic vector, dynamic load vector, distributed load field vector and bridge bending stiffness vector into the bridge dynamic neural network model to obtain the displacement field vector of the corrugated steel web composite beam bridge.

[0083] Step S507, constructing a three-dimensional dynamic finite element model of the composite beam bridge with corrugated steel webs based on the dynamic load vector, the displacement field vector of the composite beam bridge with corrugated steel webs and the three-dimensional structural finite element model of the composite beam bridge with corrugated steel webs.

[0084] The above-mentioned simulation method of the corrugated steel web composite beam bridge can form a complete simulation system from the construction of the corrugated steel web composite beam bridge model, parameter determination to static and dynamic performance analysis, which is helpful to improve the design quality of the corrugated steel web composite beam bridge, the design efficiency, safety and reliability of the corrugated steel web composite beam bridge, thereby ensuring the operational safety of the corrugated steel web composite beam bridge and optimizing the maintenance strategy of the corrugated steel web composite beam bridge.

[0085] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0086] Based on the same inventive concept, the embodiment of the present application also provides a corrugated steel web composite beam bridge simulation system for implementing the corrugated steel web composite beam bridge simulation method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more corrugated steel web composite beam bridge simulation system embodiments provided below can refer to the limitations of the corrugated steel web composite beam bridge simulation method above, and will not be repeated here.

[0087] In an exemplary embodiment, Figure 6 As shown, a corrugated steel web composite beam bridge simulation system 600 is provided, comprising: The structural model acquisition module 601 can be used to acquire a three-dimensional structural finite element model of a composite beam bridge with corrugated steel webs. The three-dimensional structural finite element model of a composite beam bridge with corrugated steel webs is used to characterize the static structural characteristics of the composite beam bridge with corrugated steel webs.

[0088] The static characteristic analysis module 602 can be used to calculate the static characteristic values ​​of the structural members in the three-dimensional structural finite element model of the corrugated steel web composite beam bridge and construct the bridge static characteristic vector, which is used to characterize the mechanical properties of the corrugated steel web composite beam bridge under static load.

[0089] The dynamic data acquisition module 603 can be used to acquire the dynamic load vector, and acquire the distributed load field vector and the bridge bending stiffness vector based on the dynamic load vector and the three-dimensional structural finite element model of the corrugated steel web composite beam bridge.

[0090] The dynamic displacement analysis module 604 can be used to input the bridge static characteristic vector, dynamic load vector, distributed load field vector and bridge bending stiffness vector into the bridge dynamic neural network model to obtain the displacement field vector of the corrugated steel web composite beam bridge.

[0091] The dynamic model acquisition module 605 can be used to construct a three-dimensional dynamic finite element model of the corrugated steel web composite beam bridge based on the dynamic load vector, the displacement field vector of the corrugated steel web composite beam bridge and the three-dimensional structural finite element model of the corrugated steel web composite beam bridge.

[0092] In an optional embodiment, the structural model acquisition module 601 can also be used to obtain the corrugated steel web composite beam bridge line and initialize the corrugated steel web composite beam bridge model to obtain the static initial model of the corrugated steel web composite beam bridge; obtain the structural parameters of the corrugated steel web composite beam bridge, and construct a three-dimensional structural finite element model of the corrugated steel web composite beam bridge based on the structural parameters of the corrugated steel web composite beam bridge and the static initial model of the corrugated steel web composite beam bridge.

[0093] In an optional embodiment, the structural model acquisition module 601 can also be used to obtain the initial vector of the structural parameters of the corrugated steel web composite beam bridge, and calculate the comprehensive performance index of the bridge based on the initial vector of the bridge structural parameters; if the comprehensive performance index of the bridge is higher than the threshold to be optimized, the initial vector of the structural parameters of the corrugated steel web composite beam bridge is set as the structural parameters of the corrugated steel web composite beam bridge; if the comprehensive performance index of the bridge is lower than the threshold to be optimized, the initial vector of the structural parameters of the corrugated steel web composite beam bridge is optimized based on the BP neural network, and the optimized initial vector of the structural parameters of the corrugated steel web composite beam bridge is set as the structural parameters of the corrugated steel web composite beam bridge.

[0094] In an optional embodiment, the structural model acquisition module 601 can also be used to input the initial vector of the structural parameters of the corrugated steel web composite beam bridge into a 6-dimensional BP neural network to obtain an optimized initial vector of the structural parameters of the corrugated steel web composite beam bridge.

[0095] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of a power supply safety management method as described above when executing the computer program.

[0096] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0097] For the device embodiments, since they basically correspond to the method embodiments, the relevant parts can refer to the partial description of the method embodiments. The device embodiments described above are only schematic, wherein the components described as separate parts may or may not be physically separated, and the parts displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the disclosed solution. A person of ordinary skill in the art can understand and implement it without paying any creative work.

[0098] The above-mentioned embodiments only express several implementation methods of the embodiments of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the patent of the embodiments of the present application. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the embodiments of the present application, and these all belong to the protection scope of the embodiments of the present application.

Claims

1. A simulation method for a composite beam bridge with corrugated steel webs, characterized in that: The method comprises: Obtaining a three-dimensional structural finite element model of a corrugated steel web composite beam bridge, wherein the three-dimensional structural finite element model of the corrugated steel web composite beam bridge is used to characterize the static structural characteristics of the corrugated steel web composite beam bridge; Calculating the static characteristic values ​​of the structural members in the three-dimensional structural finite element model of the corrugated steel web composite beam bridge, and constructing a bridge static characteristic vector, wherein the bridge static characteristic vector is used to characterize the mechanical properties of the corrugated steel web composite beam bridge under static load; Obtaining a dynamic load vector, and obtaining a distributed load field vector and a bridge bending stiffness vector based on the dynamic load vector and the three-dimensional structural finite element model of the corrugated steel web composite beam bridge; Inputting the bridge static characteristic vector, the dynamic load vector, the distributed load field vector and the bridge bending stiffness vector into a bridge dynamic neural network model to obtain a displacement field vector of a corrugated steel web composite beam bridge; Based on the dynamic load vector, the displacement field vector of the corrugated steel web composite beam bridge and the three-dimensional structural finite element model of the corrugated steel web composite beam bridge, a three-dimensional dynamic finite element model of the corrugated steel web composite beam bridge is constructed. The three-dimensional dynamic finite element model is used to simulate the mechanical properties of the corrugated steel web composite beam bridge under the action of dynamic load.

2. The method according to claim 1, characterized in that The method of obtaining a three-dimensional structural finite element model of a corrugated steel web composite beam bridge comprises: Obtaining a corrugated steel web composite beam bridge route and initializing a corrugated steel web composite beam bridge model to obtain a static initial model of the corrugated steel web composite beam bridge; Acquire structural parameters of a corrugated steel web composite beam bridge, and construct a three-dimensional structural finite element model of the corrugated steel web composite beam bridge based on the structural parameters of the corrugated steel web composite beam bridge and a static initial model of the corrugated steel web composite beam bridge; The expression of the structural parameters of the corrugated steel web composite beam bridge is: In the formula, is the structural parameter vector of the composite beam bridge with corrugated steel webs, is the bridge span component, is the bridge deck width component, is the bridge beam height component, is the bridge beam bottom curve component, is the thickness component of the corrugated steel web, is the height component of the corrugated steel web.

3. The method according to claim 2, characterized in that The obtaining of structural parameters of a corrugated steel web composite beam bridge comprises: Obtaining an initial vector of structural parameters of a corrugated steel web composite beam bridge, and calculating a comprehensive performance index of the bridge based on the initial vector of the structural parameters of the bridge; If the comprehensive performance index of the bridge is higher than the threshold to be optimized, the initial vector of the structural parameters of the corrugated steel web composite beam bridge is set to the structural parameters of the corrugated steel web composite beam bridge, and the threshold to be optimized is used to represent the boundary value of the comprehensive performance index of the bridge that needs to adjust the initial vector of the structural parameters of the corrugated steel web composite beam bridge to improve the comprehensive performance of the bridge; If the comprehensive performance index of the bridge is lower than the threshold to be optimized, the initial vector of the structural parameters of the corrugated steel web composite beam bridge is optimized based on the BP neural network, and the optimized initial vector of the structural parameters of the corrugated steel web composite beam bridge is set as the structural parameters of the corrugated steel web composite beam bridge.

4. The method according to claim 3, characterized in that The optimization of the initial vector of the structural parameters of the corrugated steel web composite beam bridge based on the BP neural network includes: Inputting the initial vector of the structural parameters of the corrugated steel web composite beam bridge into the 6-dimensional BP neural network to obtain the optimized initial vector of the structural parameters of the corrugated steel web composite beam bridge; The objective function of the BP neural network is constructed based on the comprehensive performance index of the bridge; The expression of the comprehensive performance index of the bridge is: Where A is the comprehensive performance index of the bridge, is the strength index coefficient, is the deflection index coefficient, is the economic indicator coefficient, is the maximum stress of the whole bridge under the ultimate load, is the ultimate strength of the bridge material, is the deflection in the middle of the main span under the ultimate load, is the upper limit of the mid-span deflection of the main span, M is the theoretical mass of the bridge, is the bridge quality cost coefficient, and P is the estimated cost of the bridge.

5. The method according to claim 1, characterized in that The bridge dynamic neural network model is a convolutional neural network model, and the bridge dynamic neural network model includes a convolutional layer and a fully connected layer; The objective function of the bridge dynamic neural network model is expressed as: In the formula, is the objective function of the bridge dynamic neural network model, is the dynamic load vector value, is the dynamic load vector, is the bridge bending stiffness vector value under dynamic load, is the displacement field vector value of the composite beam bridge with corrugated steel web under dynamic load, is the distributed load field vector value under dynamic load.

6. The method according to any one of claims 1 to 5, characterized in that: The bridge static characteristic vector includes the bridge elastic buckling critical shear stress field vector; The calculation formula of the critical shear stress field vector of bridge elastic buckling is: In the formula, is the critical shear stress field vector value of bridge elastic buckling, is the local elastic buckling shear stress, is the overall elastic buckling shear stress, is the local shear buckling coefficient, E is Young's modulus, is Poisson's ratio, is the thickness of the corrugated steel web, is the maximum folded width of the corrugated steel web, is the overall shear buckling coefficient, is the longitudinal bending stiffness per unit length of the corrugated steel web, Transverse bending stiffness per unit length of corrugated steel web, is the height of corrugated steel web.

7. The method according to any one of claims 1 to 5, characterized in that: The bridge static characteristic vector includes an external beam cumulative damage value component, a shear stud cumulative damage value component and a bridge overall life prediction component.

8. A simulation system for a composite beam bridge with corrugated steel webs, characterized in that: The system comprises: A structural model acquisition module, used to acquire a three-dimensional structural finite element model of a composite beam bridge with corrugated steel webs, wherein the three-dimensional structural finite element model of a composite beam bridge with corrugated steel webs is used to characterize the static structural characteristics of the composite beam bridge with corrugated steel webs; A static characteristic analysis module, used to calculate the static characteristic values ​​of the structural members in the three-dimensional structural finite element model of the corrugated steel web composite beam bridge, and to construct a bridge static characteristic vector, wherein the bridge static characteristic vector is used to characterize the mechanical properties of the corrugated steel web composite beam bridge under static load; A dynamic data acquisition module, used to acquire a dynamic load vector, and acquire a distributed load field vector and a bridge bending stiffness vector based on the dynamic load vector and the three-dimensional structural finite element model of the corrugated steel web composite beam bridge; A dynamic displacement analysis module, used for inputting the bridge static characteristic vector, the dynamic load vector, the distributed load field vector and the bridge bending stiffness vector into a bridge dynamic neural network model to obtain a displacement field vector of a corrugated steel web composite beam bridge; A dynamic model acquisition module is used to construct a three-dimensional dynamic finite element model of the corrugated steel web composite beam bridge based on the dynamic load vector, the displacement field vector of the corrugated steel web composite beam bridge and the three-dimensional structural finite element model of the corrugated steel web composite beam bridge.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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