Train collision energy absorption optimization method based on joint simulation

Abstract

The invention discloses a train collision energy absorption optimization method based on joint simulation, and the method comprises the steps: obtaining the compression force of a coupler and an anti-creeper, inputting the compression force of the coupler and the anti-creeper into a pre-constructed agent model, and obtaining an optimization result outputted by the agent model; the construction method of the proxy model comprises the steps that the marshalling condition of a target train is obtained, a simplified collision dynamics model is constructed, and a simulation configuration file output by the simplified collision dynamics model is obtained; the simulation configuration file is subjected to parameterization adding operation, then simulation is conducted, a simulation result file is obtained, and the parameterization adding operation comprises segmented parameterization of energy absorption curves of the anti-creeper and the car coupler, car body weight parameterization and initial speed parameterization; according to the method, the simplified collision dynamics model is established, the energy absorption curve is segmented and parameterized, optimization is carried out based on joint simulation, and the optimization efficiency is effectively improved.

Description

Technical Field

[0001] The present invention relates to a train collision energy absorption optimization method based on joint simulation, belonging to the technical field of collision optimization. Background Art

[0002] The design and optimization of train collision energy absorption devices mainly adopt the finite element method, use pre-processing software such as Hypermesh or ANSA to establish the whole vehicle collision model, use the LS-DYNA solver for calculation, and use LS-Prepost post-processing software for post-processing, extraction of calculation results and evaluation.

[0003] Existing methods for designing and optimizing collision energy absorption curves rely on manual selection to determine the configuration of the energy absorption device, making it difficult to obtain the optimal solution that meets project requirements. Furthermore, the acceleration response of each vehicle cannot be directly obtained during post-processing, requiring further manual processing, which is inefficient. It can be seen that in order to solve the above technical problems, a train collision energy absorption optimization method based on joint simulation is urgently needed. Summary of the Invention

[0004] The purpose of the present invention is to overcome the deficiencies in the prior art and provide a train collision energy absorption optimization method based on joint simulation. By establishing a simplified collision dynamics model, the energy absorption curve is parameterized in sections and optimized based on joint simulation, thereby effectively improving the optimization efficiency.

[0005] To achieve the above object, the present invention is implemented by adopting the following technical solutions: In a first aspect, the present invention provides a train collision energy absorption optimization method based on joint simulation, comprising: Obtaining the compression force of the coupler and the anti-climber, inputting the compression force of the coupler and the anti-climber into a pre-built proxy model, and obtaining an optimization result output by the proxy model; The method for constructing the proxy model includes: Obtain the marshaling of the target train, build a simplified collision dynamics model, and obtain a simulation configuration file output by the simplified collision dynamics model; After performing a parameter addition operation on the simulation configuration file, simulation is performed to obtain a simulation result file, wherein the parameter addition operation includes segmented parameterization of energy absorption curves of the anti-climber and the coupler, parameterization of the vehicle body weight, and parameterization of the initial speed; Perform post-processing on the simulation result file to obtain collision dynamics response data; Processing and analyzing the collision dynamics response data to obtain acceleration analysis result data; Through joint simulation, a mapping relationship is established between the input parameters in the simulation configuration file after parameterization and the collision dynamics response data and acceleration analysis result data. A sensitivity analysis is performed on the mapping relationship to obtain the design variables and generate sample points. The proxy model is constructed based on the sample points.

[0006] Furthermore, when constructing the simplified collision dynamics model, the vehicle body is modeled using a series connection of rigid materials and spring units, and the vehicle body's anti-climber and coupler energy-absorbing elements are modeled using discrete units.

[0007] Furthermore, the segmented parameterization of the energy absorption curves of the anti-climber and the coupler includes: The force and travel of the anti-climber are parameterized in single section; Fully automatic coupler is divided into buffer transient, buffer steady state, energy absorbing tube steady state, The 5 sections of shear stroke and idle stroke are parameterized and connected in series; The semi-automatic coupler is divided into three sections: buffer transient, buffer steady, and energy-absorbing tube steady. The force and stroke are parameterized and connected in series. The semi-permanent coupler is divided into three sections: buffer transient, buffer steady, and energy-absorbing tube steady. The force and stroke are parameterized and connected in series.

[0008] Furthermore, the collision dynamics response data obtained by post-processing the simulation result file include: According to the simulation result file, a curve of the energy absorption, compression stroke and compression force value of the anti-climber and each coupler, the speed of each vehicle, and the acceleration of each vehicle over time is obtained through post-processing; The processing and analysis of the collision dynamics response data to obtain acceleration analysis result data includes: According to the curve of each vehicle's acceleration changing with time, data processing is performed to obtain the maximum average acceleration value of each vehicle at 30ms and 120ms.

[0009] Furthermore, a mapping relationship between the input parameters in the simulation configuration file after parameterization and the collision dynamics response data and acceleration analysis result data is established through joint simulation, including: Mapping design variables to input parameters in simulation configuration data, processing the simulation configuration data through finite element simulation tools, and generating detailed collision dynamics response data; Process the collision dynamics response data through post-processing tools and data processing programs to extract acceleration analysis result data; A mapping relationship is established based on the input parameters, collision dynamics response data, and acceleration analysis result data.

[0010] Furthermore, a sensitivity analysis is performed on the mapping relationship to obtain the design variables and generate sample points including: The sensitivity of input and output parameters is analyzed by parametric research method, and the factors with the greatest influence are selected as design variables; Through the optimal Latin hypercube sampling method, sample points are generated in the design domain of the determined design variables and calculated to obtain the output parameter value corresponding to each sample point.

[0011] Furthermore, a proxy model is constructed based on the sample points, including: All sample points and their corresponding output parameter values ​​are taken as data sets; Build a proxy model based on the dataset.

[0012] In a second aspect, the present invention provides a train collision energy absorption optimization device based on joint simulation, comprising: Optimization module: used to obtain the compression force of the coupler and the anti-climber, input the compression force of the coupler and the anti-climber into the pre-built proxy model, and obtain the optimization result output by the proxy model; The method for constructing the proxy model includes: Obtain the marshaling of the target train, build a simplified collision dynamics model, and obtain a simulation configuration file output by the simplified collision dynamics model; After performing a parameter addition operation on the simulation configuration file, simulation is performed to obtain a simulation result file, wherein the parameter addition operation includes segmented parameterization of energy absorption curves of the anti-climber and the coupler, parameterization of the vehicle body weight, and parameterization of the initial speed; Perform post-processing on the simulation result file to obtain collision dynamics response data; Processing and analyzing the collision dynamics response data to obtain acceleration analysis result data; Through joint simulation, a mapping relationship is established between the input parameters in the simulation configuration file after parameterization and the collision dynamics response data and acceleration analysis result data. A sensitivity analysis is performed on the mapping relationship to obtain the design variables and generate sample points. The proxy model is constructed based on the sample points.

[0013] In a third aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, which implements the steps of any of the aforementioned methods when executed by a processor.

[0014] In a fourth aspect, the present invention provides a computer device, comprising: Memory, used to store computer programs / instructions; A processor is configured to execute the computer program / instructions to implement the steps of any of the aforementioned methods.

[0015] In a fifth aspect, the present invention provides a computer program product, comprising a computer program / instruction, which implements the steps of any of the aforementioned methods when executed by a processor.

[0016] Compared with the prior art, the present invention has the following beneficial effects: The present invention provides a train collision energy absorption optimization method based on joint simulation. By establishing a simplified collision dynamics model, the energy absorption curve is parameterized in sections, and optimization is performed based on the joint simulation, thereby effectively improving the optimization efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 This is an application flow chart of a train collision energy absorption optimization method based on joint simulation provided by an embodiment of the present invention; Figure 2 yes Figure 1 Flowchart of data processing program; Figure 3 It is a schematic diagram of the integration of joint simulation software; Figure 4 This is a flow chart of a train collision energy absorption optimization method based on joint simulation provided by an embodiment of the present invention; Figure 5 yes Figure 4 Flowchart of the method for constructing the proxy model. DETAILED DESCRIPTION

[0018] The technical solution of the present invention is described in detail below through the accompanying drawings and specific embodiments. It should be understood that the embodiments of the present application and the specific features in the embodiments are detailed descriptions of the technical solution of the present application, rather than limitations on the technical solution of the present application. Unless there is a conflict, the embodiments of the present application and the technical features in the embodiments can be combined with each other.

[0019] The term "and / or" in this document simply describes a relationship between related objects, indicating that three possible relationships exist. For example, "A and / or B" can mean: A exists alone, A and B exist simultaneously, or B exists alone. Additionally, the character " / " in this document generally indicates an "or" relationship between the related objects. Example

[0020] Figure 4 This is a flow chart of a train collision energy absorption optimization method based on joint simulation in the first embodiment of the present invention. The train collision energy absorption optimization method based on joint simulation provided in this embodiment can be applied to a terminal and can be executed by a train collision energy absorption optimization system based on joint simulation. The system can be implemented in software and / or hardware. The system can be integrated into a terminal, such as any smartphone, tablet computer or computer device with communication function. Figure 4, the method of this implementation specifically includes the following steps: Obtaining the compression force of the coupler and the anti-climber, inputting the compression force of the coupler and the anti-climber into a pre-built proxy model, and obtaining an optimization result output by the proxy model; like Figure 5 As shown, the method for constructing the proxy model includes: Obtain the marshaling of the target train, build a simplified collision dynamics model, and obtain a simulation configuration file output by the simplified collision dynamics model; After performing a parameter addition operation on the simulation configuration file, simulation is performed to obtain a simulation result file, wherein the parameter addition operation includes segmented parameterization of energy absorption curves of the anti-climber and the coupler, parameterization of the vehicle body weight, and parameterization of the initial speed; Perform post-processing on the simulation result file to obtain collision dynamics response data; Processing and analyzing the collision dynamics response data to obtain acceleration analysis result data; Through joint simulation, a mapping relationship is established between the input parameters in the simulation configuration file after parameterization and the collision dynamics response data and acceleration analysis result data. A sensitivity analysis is performed on the mapping relationship to obtain the design variables and generate sample points. The proxy model is constructed based on the sample points.

[0021] Furthermore, when constructing the simplified collision dynamics model, the vehicle body is modeled using a series connection of rigid materials and spring units, and the vehicle body's anti-climber and coupler energy-absorbing elements are modeled using discrete units.

[0022] Furthermore, the segmented parameterization of the energy absorption curves of the anti-climber and the coupler includes: The force and travel of the anti-climber are parameterized in single section; Fully automatic coupler is divided into buffer transient, buffer steady state, energy absorbing tube steady state, The 5 sections of shear stroke and idle stroke are parameterized and connected in series; The semi-automatic coupler is divided into three sections: buffer transient, buffer steady, and energy-absorbing tube steady. The force and stroke are parameterized and connected in series. The semi-permanent coupler is divided into three sections: buffer transient, buffer steady, and energy-absorbing tube steady. The force and stroke are parameterized and connected in series.

[0023] Furthermore, the collision dynamics response data obtained by post-processing the simulation result file include: According to the simulation result file, a curve of the energy absorption, compression stroke and compression force value of the anti-climber and each coupler, the speed of each vehicle, and the acceleration of each vehicle over time is obtained through post-processing; The processing and analysis of the collision dynamics response data to obtain acceleration analysis result data includes: According to the curve of each vehicle's acceleration changing with time, data processing is performed to obtain the maximum average acceleration value of each vehicle at 30ms and 120ms.

[0024] Furthermore, a mapping relationship between the input parameters in the simulation configuration file after parameterization and the collision dynamics response data and acceleration analysis result data is established through joint simulation, including: Mapping design variables to input parameters in simulation configuration data, processing the simulation configuration data through finite element simulation tools, and generating detailed collision dynamics response data; Process the collision dynamics response data through post-processing tools and data processing programs to extract acceleration analysis result data; A mapping relationship is established based on the input parameters, collision dynamics response data, and acceleration analysis result data.

[0025] Furthermore, a sensitivity analysis is performed on the mapping relationship to obtain the design variables and generate sample points including: The sensitivity of input and output parameters is analyzed by parametric research method, and the factors with the greatest influence are selected as design variables; Through the optimal Latin hypercube sampling method, sample points are generated in the design domain of the determined design variables and calculated to obtain the output parameter value corresponding to each sample point.

[0026] Furthermore, a proxy model is constructed based on the sample points, including: All sample points and their corresponding output parameter values ​​are taken as data sets; Build a proxy model based on the dataset.

[0027] like Figures 1 to 3 As shown, the processing method provided in this embodiment specifically involves the following steps: S1. Use Hypermesh to build a simplified train collision dynamics model and obtain the train collision finite element model k-file; S2. Using the k-file obtained in S1, use Hypermesh to add *PARAMETER and *PARAMETER_EXPRESSION keywords to implement segmented parameterization of the energy absorption curve, vehicle weight parameterization, and initial velocity parameterization. S3. Import the parameterized model k file created in S2 into LS-DYNA for solution to obtain the op2 result file; S4. Use LS-Prepost to load the op2 file obtained in S3. Post-process it to obtain curves showing the energy absorption, compression stroke and force of the anti-climber and each coupler, the speed of each car, and the acceleration of each car over time. Export these results to a text file and record a macro file (cfile) containing the command stream for the operations performed to obtain these post-processing results. S5. Use Python to write a vehicle acceleration processing program, avgAcc.exe. This program will recognize the time-varying acceleration data file for each vehicle obtained in S4, automatically read the file, process the data, and output the result file. It will obtain the maximum average acceleration value of each vehicle over 30ms and 120ms, and output it to the acceleration.csv file. S6: Integrate the three programs LS-DYNA, LS-Prepost, and avgAcc.exe into the optimization software. The Simcode component named "run_lsdyna" in the optimization software implements the following functions: ① Automatically perform input parameter mapping on the energy absorption curve parameters, mass, initial velocity and other parameters in the parameterized file obtained in S2; ② Automatically call LS-DYNA software to calculate the parameterized k file to obtain the op2 file in S3.

[0028] The Simcode component named “run_lsprepost” in the optimization software implements the following functions: LS-Prepost and the macro file cfile are automatically called to obtain the text file containing the results obtained in S4.

[0029] The Data Exchanger component named "stroke&energy" in the optimization software automatically reads the text file generated by "run_lsprepost" (containing the energy absorption, compression stroke and compression force data of the anti-climber and each coupler), automatically identifies the maximum compression stroke and compression force, and performs output parameter mapping for sensitivity analysis.

[0030] The Simcode component named "avgAcc" in the optimization software automatically calls the avgacc.exe program to process the acceleration data of each vehicle generated in "run_lsprepost", obtain the maximum average acceleration of 30ms and 120ms, write it to the acceleration.csv file, and then map the maximum average acceleration to the output parameter.

[0031] S7: Use the DOE method provided by the optimization software to perform a sensitivity analysis to study the impact of the input mapping parameters in steps S1 to S7 on the output mapping parameters. The main input mapping parameters with the greatest impact include the curve parameters of the fully automatic coupler, semi-automatic coupler, and semi-permanent coupler in S2, and the main output mapping parameters include the compression force and compression stroke parameters in S4-S5, and generate a sufficient number of sample points; S8: Using the approximate model provided by the optimization software, a proxy model of the input mapping parameters and the output mapping parameters is constructed based on the sample points generated in S7, and the accuracy of the proxy model is verified using the finite element calculation results; S9: Based on the proxy model generated in S8, the coupler energy absorption curve is optimized. The design variables are the compression force and compression stroke of the coupler and anti-climber. The constraints are the compression stroke limits of each interface and the maximum average acceleration of each vehicle at 30ms and 120ms. The design goal is to minimize the interface energy absorption / average acceleration / remaining compression stroke, etc.

[0032] The following describes the contents involved in the above embodiment in conjunction with a preferred embodiment.

[0033] S1. Use Hypermesh to build a simplified collision dynamics model of the train: (1) A collision dynamics model is established based on the train formation, where the car body is modeled using a series of rigid materials and spring units to simulate the car body mass and stiffness; (2) The anti-climber and coupler energy absorption elements are modeled using discrete elements; S2. Use Hypermesh energy absorption curve for segmented parameterization: (1) Use *PARAMETER and *PARAMETER_EXPRESSION keywords to parameterize the energy absorption curves of the anti-climber and coupler in sections; (2) Single-segment parameterization of force and travel of the anti-climber; (3) Fully automatic couplers are divided into buffer transient, buffer steady state, energy absorbing tube steady state, The 5 sections of shear stroke and idle stroke are parameterized and connected in series; (4) The semi-automatic coupler is divided into three sections: buffer transient, buffer steady, and energy-absorbing tube steady. The force and stroke are parameterized and connected in series. (5) The semi-permanent coupler is divided into three sections: buffer transient, buffer steady, and energy-absorbing tube steady. The force and stroke are parameterized and connected in series. S3. Solve using LS-DYNA software and obtain the op2 result file: (1) Use LS-DYNA to solve the k file generated in the above steps and generate the op2 binary file and glstat text file.

[0034] S4. Use LS-Prepost to load the op2 file and record the macro file: (1) Use the op2 file to load and output the energy curves and maximum values ​​of all anti-climbers and couplers to the energy text file, and the compression curves and maximum values ​​to the stroke text file; (2) Output the acceleration time history curve data of each vehicle body to the acceleration.csv file; (3) Record the operation process into a cfile macro file.

[0035] S5. Use Python software to write the vehicle acceleration processing program avgAcc.exe: (1) This program processes the acceleration.csv format data extracted from LS-Prepost, calculates the maximum average acceleration data within 30ms and 120ms of each car, and saves the result data as max_acc.csv file.

[0036] (2) The program can automatically identify the number of groups, the total time of the acceleration time history and the time step.

[0037] S6: Integrate LS-DYNA, LS-Prepost and avgAcc.exe into the optimization software: (1) The integrated optimization design platform includes the LS-DYNA collision calculation module, the LS-Prepost post-processing module, and the avgAcc.exe acceleration data processing program, which realizes the automatic update of collision model curve parameters, the automatic submission of calculations, and the automatic extraction of back-end results; (2) Write the run_lsdyna.bat batch file and use the Simcode component in the optimization software to call the batch file to realize the automatic execution of the LS-DYNA software, and map the speed, vehicle mass, total energy, kinetic energy, internal energy, energy absorption of the energy absorption element, and compression stroke in the k file as input parameters; (3) Write the run_lsprepost.bat batch file and use the Simcode component in the optimization software to call the batch file to automatically execute the macro file recorded in step S4 of the LS-prepost software and map the energy absorption and compression stroke of each energy absorbing element in stroke and energy as output parameters; (4) Use the Simcode component in the optimization software to call the avgAcc.exe program and map the maximum average acceleration value within 30ms and 60ms of each car in the generated acceleration.csv to the output variable; S7: Use DOE method to study the effect of parameters on collision response: (1) In the DOE module, identify the input parameters generated in the above steps (including buffer stroke, fully automatic coupler crushing pipe stroke, shear stroke, idle stroke, anti-climbing device stroke, semi-permanent coupler crushing pipe stroke, semi-automatic coupler crushing pipe stroke, buffer force, overload protection force, anti-climbing device compression force, fully automatic coupler crushing pipe compression force, semi-permanent coupler crushing pipe compression force, semi-automatic coupler crushing pipe compression force, vehicle weight, etc.), and output parameters (including the maximum average acceleration within 30ms and 120ms of each car, anti-climbing device compression stroke, fully automatic coupler compression stroke, semi-automatic coupler compression stroke, semi-permanent coupler compression stroke, etc.). (2) The parameter study method is used to study the sensitivity of input parameters to output parameters, and the factors with the greatest influence (anti-climber force, anti-climber stroke, fully automatic coupler crushing tube force, semi-automatic coupler crushing tube force, semi-permanent coupler crushing tube force, buffer stroke, and buffer force) are selected as design variables for subsequent optimization design; (3) Using the Optimal Latin Hypercube method, 200 sample points are generated and calculated within the design domain of the design variables.

[0038] S8: Build a proxy model and verify its accuracy: (1) Proxy model selection: test each model based on the built-in models of the optimization software and select the model with the highest accuracy; (2) Constructing a proxy model between design variables and responses; (3) Use finite element simulation data to verify the accuracy of the proxy model.

[0039] S9: Optimization design of coupler energy absorption curve based on surrogate model: (1) Design variables: the optimized design variables determined in step S7; (2) Design constraints: The maximum average acceleration of each car within 30ms does not exceed 10g, the maximum average acceleration within 120ms does not exceed 5g, and the compression stroke of each interface does not exceed the allowable stroke of the energy absorption element; (3) Optimization objective: Based on the project requirements, the energy absorption of a certain interface can be maximized, the acceleration of a certain vehicle section can be minimized, or the compression of a certain interface can be minimized. In this embodiment, the optimization objective of the model is to minimize the acceleration of the vehicle at the collision interface. The specific content of the model is as follows: 1. Optimize variables: frc_fpq Anti-climber compression force frc_gou1 Coupler 1 Compression Force frc_gou2 Coupler 2 Compression Force frc_gou3 coupler 3 compression force 2. Response: Car1_120ms, Car1_30ms, average acceleration of car 1 during 120ms and 30ms Car2_120ms, Car2_30ms, average acceleration of car 2 during 120ms and 30ms Car3_120ms, Car3_30ms, average acceleration of car 3 at 120ms and 30ms Car4_120ms, Car4_30ms, average acceleration of the fourth car at 120ms and 30ms Car5_120ms, Car5_30ms, average acceleration of car 5 at 120ms and 30ms Car6_120ms, Car6_30ms, average acceleration of car 6 at 120ms and 30ms energy1, energy12, energy3, energy4, energy5, energy6, anti-climber, energy absorption of coupler 2 to coupler 6 strk1,strk2,strk3,strk4,strk5,strk6,anti-climber,compression stroke of coupler 2 to coupler 6 3. Example of optimization model elements Optimization goal: ; Constraints: , where i ranges from 1 to 6, indicating the i-th car from the 1st to the 6th car, and LIMIT is the travel limit Optimization variables:

[0040] This part adopts the response surface model, in which the model input is the compression force of the coupler and anti-climber, the model constraints are the vehicle acceleration, the compression stroke of the coupler and anti-climber, and the optimization goal is to minimize the average acceleration of the vehicle at the collision interface at 120ms and 30ms.

[0041] Embodiment 2: This embodiment provides a processing device, including: Optimization module: used to obtain the compression force of the coupler and the anti-climber, input the compression force of the coupler and the anti-climber into the pre-built proxy model, and obtain the optimization result output by the proxy model; The method for constructing the proxy model includes: Obtain the marshaling of the target train, build a simplified collision dynamics model, and obtain a simulation configuration file output by the simplified collision dynamics model; After performing a parameter addition operation on the simulation configuration file, simulation is performed to obtain a simulation result file, wherein the parameter addition operation includes segmented parameterization of energy absorption curves of the anti-climber and the coupler, parameterization of the vehicle body weight, and parameterization of the initial speed; Perform post-processing on the simulation result file to obtain collision dynamics response data; Processing and analyzing the collision dynamics response data to obtain acceleration analysis result data; Through joint simulation, a mapping relationship is established between the input parameters in the simulation configuration file after parameterization and the collision dynamics response data and acceleration analysis result data. A sensitivity analysis is performed on the mapping relationship to obtain the design variables and generate sample points. The proxy model is constructed based on the sample points.

[0042] The specific functional implementation of each of the above modules can be found in the relevant content of the method in Example 1 and will not be elaborated on here.

[0043] Example 3: This embodiment provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the steps of any one of the methods described in Example 1 are implemented.

[0044] Embodiment 4: This embodiment provides a computer device, including: Memory, used to store computer programs / instructions; A processor, configured to execute the computer program / instructions to implement the steps of any one of the methods described in Example 1.

[0045] Example 5: This embodiment provides a computer program product, including a computer program / instruction, which implements the steps of any method described in Example 1 when executed by a processor.

[0046] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

[0047] Those skilled in the art will appreciate that embodiments of the present disclosure may be provided as methods, systems, or computer program products. Thus, the present disclosure may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present disclosure may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROMs, optical storage, etc.) containing computer-usable program code.

[0048] The present disclosure is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present disclosure. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0049] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0050] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0051] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present disclosure and are not intended to limit its scope of protection. Although the present disclosure has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that after reading the present disclosure, those skilled in the art can still make various changes, modifications or equivalent substitutions to the specific implementation methods of the invention, but these changes, modifications or equivalent substitutions are all within the scope of protection of the disclosed claims to be approved.

Claims

1. A train collision energy absorption optimization method based on joint simulation, characterized by: include: Obtaining the compression force of the coupler and the anti-climber, inputting the compression force of the coupler and the anti-climber into a pre-built proxy model, and obtaining an optimization result output by the proxy model; The method for constructing the proxy model includes: Obtain the marshaling of the target train, build a simplified collision dynamics model, and obtain a simulation configuration file output by the simplified collision dynamics model; After performing a parameter addition operation on the simulation configuration file, simulation is performed to obtain a simulation result file, wherein the parameter addition operation includes segmented parameterization of energy absorption curves of the anti-climber and the coupler, parameterization of the vehicle body weight, and parameterization of the initial speed; Perform post-processing on the simulation result file to obtain collision dynamics response data; Processing and analyzing the collision dynamics response data to obtain acceleration analysis result data; Through joint simulation, a mapping relationship is established between the input parameters in the simulation configuration file after parameterization and the collision dynamics response data and acceleration analysis result data. A sensitivity analysis is performed on the mapping relationship to obtain the design variables and generate sample points. The proxy model is constructed based on the sample points.

2. The train collision energy absorption optimization method based on joint simulation according to claim 1 is characterized in that: When constructing the simplified collision dynamics model, the car body is modeled in series using rigid materials and spring units, and the car body's anti-climber and coupler energy-absorbing elements are modeled using discrete units.

3. The train collision energy absorption optimization method based on joint simulation according to claim 1 is characterized in that: The segmented parameterization of the energy absorption curve of the anti-climber and the coupler includes: The force and travel of the anti-climber are parameterized in single section; The fully automatic coupler is divided into five sections: buffer transient state, buffer steady state, energy absorbing tube steady state, shear stroke, and idle stroke, which are parameterized and connected in series. The semi-automatic coupler is divided into three sections: buffer transient, buffer steady, and energy-absorbing tube steady. The force and stroke are parameterized and connected in series. The semi-permanent coupler is divided into three sections: buffer transient, buffer steady, and energy-absorbing tube steady. The force and stroke are parameterized and connected in series.

4. The train collision energy absorption optimization method based on joint simulation according to claim 1 is characterized in that: Post-processing is performed based on the simulation result file to obtain collision dynamics response data including: According to the simulation result file, a curve of the energy absorption, compression stroke and compression force value of the anti-climber and each coupler, the speed of each vehicle, and the acceleration of each vehicle over time is obtained through post-processing; The processing and analysis of the collision dynamics response data to obtain acceleration analysis result data includes: According to the curve of each vehicle's acceleration changing with time, data processing is performed to obtain the maximum average acceleration value of each vehicle at 30ms and 120ms.

5. The train collision energy absorption optimization method based on joint simulation according to claim 1, characterized in that: Through joint simulation, a mapping relationship is established between the input parameters in the simulation configuration file after parameterization and the collision dynamics response data and acceleration analysis result data, including: Mapping design variables to input parameters in simulation configuration data, processing the simulation configuration data through finite element simulation tools, and generating detailed collision dynamics response data; Process the collision dynamics response data through post-processing tools and data processing programs to extract acceleration analysis result data; A mapping relationship is established based on the input parameters, collision dynamics response data, and acceleration analysis result data.

6. The train collision energy absorption optimization method based on joint simulation according to claim 1, characterized in that: Perform sensitivity analysis on the mapping relationship to obtain design variables and generate sample points including: The sensitivity of input and output parameters is analyzed by parametric research method, and the factors with the greatest influence are selected as design variables; Through the optimal Latin hypercube sampling method, sample points are generated in the design domain of the determined design variables and calculated to obtain the output parameter value corresponding to each sample point.

7. The train collision energy absorption optimization method based on joint simulation according to claim 1 is characterized in that: Construct a proxy model based on sample points, including: All sample points and their corresponding output parameter values ​​are taken as data sets; Build a proxy model based on the dataset.

8. A train collision energy absorption optimization device based on joint simulation, characterized in that: include: Optimization module: used to obtain the compression force of the coupler and the anti-climber, input the compression force of the coupler and the anti-climber into the pre-built proxy model, and obtain the optimization result output by the proxy model; The method for constructing the proxy model includes: Obtain the marshaling of the target train, build a simplified collision dynamics model, and obtain a simulation configuration file output by the simplified collision dynamics model; After performing a parameter addition operation on the simulation configuration file, simulation is performed to obtain a simulation result file, wherein the parameter addition operation includes segmented parameterization of energy absorption curves of the anti-climber and the coupler, parameterization of the vehicle body weight, and parameterization of the initial speed; Perform post-processing on the simulation result file to obtain collision dynamics response data; Processing and analyzing the collision dynamics response data to obtain acceleration analysis result data; Through joint simulation, a mapping relationship is established between the input parameters in the simulation configuration file after parameterization and the collision dynamics response data and acceleration analysis result data. A sensitivity analysis is performed on the mapping relationship to obtain the design variables and generate sample points. The proxy model is constructed based on the sample points.

9. A computer-readable storage medium having a computer program stored thereon, wherein when the program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer device comprising: Memory, used to store computer programs / instructions; A processor configured to execute the computer program / instructions to implement the steps of the method according to any one of claims 1 to 7.

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