Biomimetic energy-absorbing structure optimization method and system based on impact damage mode feedback

Abstract

The application discloses a kind of bionic energy-absorbing structure optimization method and system based on collision damage mode feedback, and relates to the technical field of collision protection and energy-absorbing structure design.The method comprises the following steps: constructing an initial bionic energy-absorbing structure model according to the collision protection requirements of the target structure; using an intelligent damage identification model to identify the damage data; encoding and representing the damage evolution characteristics generated during the structure collision process according to the damage characteristic parameters, analyzing the correlation between the structure parameters and the damage genes based on the damage gene system, identifying the key structure characteristics that affect the structure damage mode according to the contribution degree relationship model, and analyzing the structure damage mechanism; updating the initial bionic energy-absorbing structure model according to the structure optimization strategy to generate a new generation of bionic energy-absorbing structure model.The application can obtain a structure scheme with excellent collision protection performance and stable energy-absorbing characteristics through iterative optimization design of bionic energy-absorbing structure.

Description

Technical Field

[0001] This invention relates to the field of collision protection and energy absorption structure design technology, and in particular to a biomimetic energy absorption structure optimization method and system based on collision damage mode feedback. Background Technology

[0002] The statements in this section are merely background information related to the present invention and do not necessarily constitute prior art.

[0003] Energy-absorbing structures can absorb collision energy through their own deformation, reducing the impact of impact loads on the main structure. They are widely used in automotive collision avoidance systems, energy-absorbing devices for rail vehicles, aerospace buffer structures, battery pack protection systems, and engineering protective equipment. To improve the energy absorption efficiency and collision protection capabilities of structures, researchers have conducted extensive research on the design and optimization methods of energy-absorbing structures.

[0004] Existing optimization methods primarily focus on adjusting structural parameters and performance indicators, with an emphasis on changes in the final structural performance and limited utilization of damage evolution behavior during collisions. There is a lack of effective characterization of how structural features influence crack propagation, buckling propagation, progressive collapse, and energy dissipation, and an effective feedback mechanism has not yet been established between structural damage modes and structural design. Therefore, existing methods struggle to continuously optimize structures based on their actual damage behavior during collisions and fail to achieve synergistic improvements in energy absorption mechanisms and structural design. Summary of the Invention

[0005] To address the shortcomings of existing technologies, the present invention aims to provide a biomimetic energy-absorbing structure optimization method and system based on collision damage mode feedback. This method incorporates the damage behavior generated during structural collisions into the optimization process, establishes the correlation between damage modes and structural features, and obtains a structural scheme with excellent collision protection performance and stable energy absorption characteristics through iterative optimization design of the biomimetic energy-absorbing structure.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solution: The first aspect of this invention provides a biomimetic energy-absorbing structure optimization method based on collision damage mode feedback, comprising the following steps: An initial biomimetic energy-absorbing structure model was constructed based on the collision protection requirements of the target structure, and collision analysis was performed on the initial biomimetic energy-absorbing structure model to obtain damage data. The intelligent damage identification model is used to identify damage data, obtain information on structural damage behavior, and extract damage feature parameters. Based on the damage characteristic parameters, the damage evolution characteristics generated during the structural collision are uniformly encoded and characterized to construct a damage gene system. Based on the damage gene system, the correlation between structural parameters and damage genes is analyzed, a contribution relationship model is established, the key structural features affecting the structural damage mode are identified based on the contribution relationship model, and the structural damage mechanism is analyzed. Based on the damage mechanism analysis results, a structural optimization strategy is generated. The initial biomimetic energy-absorbing structural model is then updated according to the structural optimization strategy to generate a new generation of biomimetic energy-absorbing structural model.

[0007] Furthermore, the specific steps for constructing the initial biomimetic energy-absorbing structure model based on the collision protection requirements of the target structure are as follows: Based on the application scenario, load type, impact direction, lightweight constraints, and expected damage mode of the target structure, the collision protection requirements of the target structure are determined, and a corresponding biological prototype is selected according to the collision protection requirements to establish a biomimetic energy-absorbing structure model. Parametric modeling of the biomimetic energy-absorbing structure model was performed to determine the structural geometric parameters, material parameters, and topological configuration parameters, forming an initial biomimetic energy-absorbing structure model for subsequent collision analysis and structural optimization.

[0008] Furthermore, the specific steps for collision analysis of the initial biomimetic energy-absorbing structure model are as follows: The collision condition parameters are determined based on the application scenario of the target structure. The application scenario includes one or more of the following: automotive anti-collision structure, rail vehicle energy absorption device, aerospace buffer structure, battery pack protection structure, and engineering protection equipment. The collision condition parameters include one or more of the following: impact velocity, impact mass, collision angle, constraint conditions, and load type. Collision analysis was performed on the initial biomimetic energy-absorbing structure model based on the collision condition parameters, and the dynamic response results of the structure during the collision process were obtained as damage data.

[0009] Furthermore, collision analysis is conducted using finite element numerical simulation, physical collision tests, or a combination of numerical simulation and physical tests. During the collision analysis, the deformation evolution process of the structure from the initial contact to the end of the collision is recorded to obtain information on the damage evolution and energy absorption response of the structure under impact load.

[0010] Furthermore, the damage characteristic parameters include one or more of the following: crack propagation characteristics, local buckling characteristics, progressive collapse characteristics, structural stability characteristics, and energy dissipation characteristics. The damage gene system is composed of damage genes, which correspond to the damage characteristic parameters, specifically including crack genes, buckling genes, collapse genes, stability genes, and energy dissipation genes.

[0011] Furthermore, the performance and damage of the new generation of biomimetic energy-absorbing structure model are evaluated to determine whether it meets the preset optimization target. When the new generation of biomimetic energy-absorbing structure model meets the preset optimization target, the iteration process is terminated and the final optimization result is output; when the preset optimization target is not met, the new generation of biomimetic energy-absorbing structure model is used as the initial structure for the next iteration.

[0012] A second aspect of the present invention provides a biomimetic energy-absorbing structure optimization system based on collision damage mode feedback, comprising: The initial model building module is configured to build an initial biomimetic energy-absorbing structure model based on the collision protection requirements of the target structure, and to perform collision analysis on the initial biomimetic energy-absorbing structure model to obtain damage data. The damage identification and parameter extraction module is configured to use an intelligent damage identification model to identify damage data, obtain structural damage behavior information and extract damage feature parameters. The damage correlation and mechanism analysis module is configured to uniformly encode and characterize the damage evolution characteristics generated during structural collision based on damage characteristic parameters, thereby constructing a damage gene system. Based on the damage gene system, the module analyzes the correlation between structural parameters and damage genes, establishes a contribution relationship model, identifies key structural features affecting structural damage patterns based on the contribution relationship model, and analyzes the structural damage mechanism. The structural optimization and model update module is configured to generate a structural optimization strategy based on the damage mechanism analysis results, and to update the initial biomimetic energy-absorbing structural model according to the structural optimization strategy to generate a new generation of biomimetic energy-absorbing structural model.

[0013] A third aspect of the present invention provides a computer-readable storage medium storing a computer program adapted for loading by a processor and executing the steps in the biomimetic energy-absorbing structure optimization method based on collision damage mode feedback as described in the first aspect of the present invention.

[0014] A fourth aspect of the present invention provides a computer device comprising: A processor, adapted to execute computer programs; A computer-readable storage medium storing a computer program, which, when executed by the processor, implements the biomimetic energy-absorbing structure optimization method based on collision damage mode feedback as described in the first aspect of the present invention.

[0015] A fifth aspect of the present invention provides a computer program product or computer program comprising computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the steps in the biomimetic energy-absorbing structure optimization method based on collision damage mode feedback as described in the first aspect of the present invention.

[0016] The above one or more technical solutions have the following beneficial effects: This invention discloses a biomimetic energy-absorbing structure optimization method and system based on collision damage mode feedback. The method includes steps such as initial biomimetic energy-absorbing structure construction, collision analysis, damage data acquisition, intelligent damage identification, damage feature extraction, damage gene construction, damage mechanism analysis, structural optimization strategy generation, and iterative structural updates. By acquiring damage evolution information during structural collisions, damage behaviors such as crack propagation, local buckling, progressive collapse, and energy dissipation generated during collisions are identified and quantified, constructing a damage gene system characterizing the structural damage mechanism. Based on a contribution relationship model between structural parameters and damage genes, the structural damage mechanism is analyzed and corresponding structural optimization strategies are generated, enabling the structure to continuously evolve along favorable damage modes. This invention achieves closed-loop iterative optimization design of biomimetic energy-absorbing structures driven by damage evolution information, enabling the closed-loop iterative optimization design of biomimetic energy-absorbing structures and obtaining structural schemes with stable progressive collapse characteristics and excellent collision protection performance.

[0017] This invention introduces collision damage evolution information into the structural optimization process to achieve an effective correlation between structural damage behavior and structural features; by constructing a damage gene system, it achieves unified characterization and quantitative description of complex damage patterns, thereby improving the ability to analyze structural damage mechanisms; by establishing a closed-loop iterative optimization mechanism based on damage pattern feedback, it enables the structure to continuously evolve along the direction of favorable damage patterns, thereby obtaining a biomimetic energy-absorbing structure with excellent energy absorption performance and collision protection capabilities.

[0018] Advantages of additional aspects of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is a schematic diagram of the biomimetic energy-absorbing structure optimization method based on collision damage mode feedback in Embodiment 1 of the present invention; Figure 2 This is a schematic diagram of the closed-loop iterative optimization principle of the biomimetic energy-absorbing structure based on collision damage mode feedback in Embodiment 1 of the present invention; Figure 3 This is a schematic diagram illustrating the acquisition of collision damage evolution information and the construction of a damage evolution database in Embodiment 1 of the present invention; Figure 4 This is a schematic diagram of the intelligent damage recognition and damage feature extraction process in Embodiment 1 of the present invention; Figure 5 This is a schematic diagram of the damage gene system construction process in Embodiment 1 of the present invention; Figure 6 This is a schematic diagram of the correlation mapping and contribution analysis model of structural parameters, damage genes, and damage mechanisms in Embodiment 1 of the present invention; Figure 7 This is a schematic diagram of the structural iterative evolution mechanism driven by damage mode generation based on damage mechanism analysis results in Embodiment 1 of the present invention. Detailed Implementation

[0021] It should be noted that the following detailed descriptions are exemplary and intended to provide further illustration of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0022] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof. The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0023] With the development of automotive engineering, rail transportation, aerospace, new energy equipment, and protective engineering, increasingly higher demands are being placed on lightweight structures and collision safety performance. Energy-absorbing structures can absorb collision energy through their own deformation, reducing the impact of impact loads on the main structure. They are widely used in automotive collision avoidance systems, rail vehicle energy-absorbing devices, aerospace buffer structures, battery pack protection systems, and engineering protective equipment. To improve the energy absorption efficiency and collision protection capabilities of structures, researchers have conducted extensive research on the design and optimization methods of energy-absorbing structures.

[0024] In recent years, biomimetic design has been increasingly applied to the field of energy-absorbing structures. Researchers have drawn inspiration from natural biological structures such as bamboo, seashells, mantis shrimp, and fish scales, proposing a variety of biomimetic energy-absorbing structures. Simultaneously, methods such as parameter optimization, topology optimization, genetic algorithm optimization, and intelligent optimization have also been widely used in the design process of energy-absorbing structures. Existing optimization methods typically use indicators such as specific energy absorption, peak impact force, average impact force, and crushing force efficiency as evaluation criteria, adjusting parameters such as structural dimensions, material distribution, or topological configuration to obtain structurally superior solutions.

[0025] Energy-absorbing structures exhibit damage behaviors such as crack propagation, local buckling, progressive collapse, stress concentration, and energy dissipation during collisions. Collision tests or numerical simulations can provide information on crack propagation paths, buckling locations, collapse sequences, stress distribution, and energy absorption processes. This information reflects the deformation process and failure characteristics of the structure under impact loads, providing crucial reference for analyzing the energy absorption mechanism. Currently, most studies primarily evaluate structural quality using post-collision performance indicators, while damage evolution information generated during the collision is typically observed and analyzed as a post-processing result, without being involved in subsequent structural optimization processes.

[0026] To address the aforementioned shortcomings of existing technologies, this invention provides a biomimetic energy-absorbing structure optimization method and system based on collision damage mode feedback. This method uses damage evolution information generated during collisions as the basis for structural optimization feedback. Through damage identification, feature extraction, damage gene construction, damage mechanism analysis, and structural optimization decision-making, it achieves closed-loop iterative optimization design of the biomimetic energy-absorbing structure. Details are provided in the following embodiments.

[0027] Example 1: To overcome the problem that existing energy-absorbing structure optimization methods mainly rely on performance indicators such as specific energy absorption, peak impact force, and average impact force for evaluation and optimization, the large amount of damage evolution information generated during the collision process is not effectively involved in the structural optimization process. This results in a lack of effective correlation between structural features and damage mechanisms, and the optimization process fails to reflect the actual failure behavior of the structure. Embodiment 1 of this invention provides a biomimetic energy-absorbing structure optimization method based on collision damage mode feedback. Figure 1 As shown, it includes: S1. Construct an initial biomimetic energy-absorbing structure model.

[0028] S2. Perform collision analysis on the initial biomimetic energy-absorbing structure model.

[0029] S3. Acquire damage data generated during the collision.

[0030] S4. Based on the damage data, perform intelligent damage identification to obtain structural damage behavior information.

[0031] S5. Extract damage feature parameters based on the structural damage behavior information.

[0032] S6. Construct a damage gene system based on the damage characteristic parameters.

[0033] S7. The structural damage mechanism is analyzed based on the aforementioned damage gene system.

[0034] S8. Generate structural optimization strategies based on the damage mechanism analysis results.

[0035] S9. Generate a new generation of biomimetic energy-absorbing structure model based on the structure optimization strategy.

[0036] S10. Determine whether the preset termination condition is met; if it is met, output the optimization result; if it is not met, return to step S2 to continue the next round of iteration optimization.

[0037] This method uses the damage evolution information generated during structural collision as the basis for optimization feedback. By identifying and analyzing damage behaviors such as crack propagation, local buckling, progressive collapse, stress concentration and energy dissipation generated during the collision, a damage gene system characterizing the structural damage mechanism is constructed. Based on the damage mechanism analysis results, corresponding structural optimization strategies are generated to achieve iterative optimization design of biomimetic energy-absorbing structures.

[0038] Specifically, the following steps are included: Step 1: Construct an initial biomimetic energy-absorbing structure model based on the collision protection requirements of the target structure, and perform collision analysis on the initial biomimetic energy-absorbing structure model to obtain damage data.

[0039] Step 1.1: Construct an initial biomimetic energy-absorbing structure model based on the collision protection requirements of the target structure.

[0040] Step 1.1.1: Based on the application scenario, load type, impact direction, lightweight constraints and expected damage mode of the target structure, determine the collision protection requirements of the target structure, and select the corresponding biological prototype according to the collision protection requirements to establish a biomimetic energy-absorbing structure model.

[0041] In one specific implementation, when the target structure is mainly subjected to high risks of local high-speed impact, puncture impact, or rapid crack propagation, biological prototypes with crack deflection, interlayer crack resistance, and impact resistance characteristics are preferred, such as mantis shrimp rappelling impactors and shell layered structures; when the target structure is mainly subjected to axial crushing, continuous compression, or needs to achieve stable progressive collapse, biological prototypes with segmented, hierarchical, or periodic cell features are preferred, such as bamboo structures and honeycomb structures; when the target structure is mainly subjected to multi-directional impact, bending impact, or needs to balance compliant deformation and load transfer, biological prototypes with multi-layered connections, gradient distribution, or controllable deformation characteristics are preferred, such as beetle elytra structures and fish scale structures.

[0042] In this embodiment, different biological prototypes correspond to different initial structural features and parameterized design variables. The selection of the biological prototype affects the cell form, hierarchical configuration, gradient distribution, wall thickness distribution, connection mode, and material distribution of the subsequent biomimetic energy-absorbing structure model, and further influences damage behaviors such as crack propagation, local buckling, progressive collapse, structural stability, and energy dissipation during collision. Therefore, the selection of the biological prototype is not only used to establish the initial biomimetic energy-absorbing structure model, but also to determine the basic structural features for subsequent damage gene construction, damage mechanism analysis, and structural optimization strategy generation.

[0043] It should be noted that when there are multiple collision protection requirements, one biological prototype can be selected as the dominant biomimetic prototype, or two or more biological prototypes can be selected for combined design to form a composite biomimetic energy-absorbing structure model that simultaneously has crack suppression, stable collapse, load dispersion and high-efficiency energy dissipation characteristics.

[0044] Step 1.1.2: Perform parametric modeling on the biomimetic energy-absorbing structure model, determine the structural geometric parameters, material parameters, and topological configuration parameters, and form an initial biomimetic energy-absorbing structure model for subsequent collision analysis and structural optimization.

[0045] In one specific implementation, a biomimetic energy-absorbing structure model is established based on the extracted biological structural features, and the structure undergoes parametric modeling. The parametric modeling includes the definition of structural geometric parameters, material parameters, and topological configuration parameters. The structural geometric parameters include one or more of the following: wall thickness, cell size, height, interlayer angle, gradient parameters, and number of layers; the material parameters include parameters such as elastic modulus, yield strength, and density; and the topological configuration parameters include parameters such as cell connection method, gradient distribution form, and hierarchical configuration characteristics. Through parametric modeling, an iteratively updatable initial biomimetic energy-absorbing structure model is formed, providing a foundational model for subsequent collision analysis, damage evolution information acquisition, and structural optimization.

[0046] Step 1.2: Perform collision analysis on the initial biomimetic energy-absorbing structure model.

[0047] Step 1.2.1: Determine the collision condition parameters based on the application scenario of the target structure. The collision condition parameters include one or more of the following: impact velocity, impact mass, collision angle, constraint conditions, and load type.

[0048] In one specific implementation, the target structure is used in one or more of the following scenarios: automotive anti-collision structures, rail vehicle energy absorption devices, aerospace buffer structures, battery pack protection structures, and engineering protective equipment. Different application scenarios correspond to different collision characteristics, and therefore require different collision condition parameters.

[0049] For example, when the target structure is used for automotive anti-collision structures, the collision characteristics are mainly manifested as frontal collisions, side collisions, offset collisions, or pole collisions. In this case, the collision condition parameters can be determined based on the vehicle's collision speed, equivalent collision mass, collision angle, vehicle body connection constraints, and axial crushing or bending crushing load forms. When the target structure is used for energy absorption devices in rail vehicles, the collision characteristics are mainly manifested as large impact mass, long energy absorption stroke, and the requirement for stable progressive collapse. In this case, the collision condition parameters can be determined based on the train's equivalent impact mass, collision speed, end-of-vehicle constraints, and axial compression load forms. When the target structure is used for battery pack protection structures, the collision characteristics are mainly manifested as bottom collisions, lateral compression, or partial intrusion collisions. In this case, the collision condition parameters can be determined based on the shape of the impact body, impact speed, impact location, collision angle, and battery pack installation constraints.

[0050] Therefore, collision condition parameters are determined based on the collision characteristics of different application scenarios, so that the damage data obtained from subsequent collision analysis can reflect the damage evolution behavior of the target structure under the corresponding service conditions.

[0051] Step 1.2.2: Perform collision analysis on the initial biomimetic energy-absorbing structure model based on the collision condition parameters to obtain the dynamic response results of the structure during the collision process as damage data.

[0052] In one specific implementation, such as Figure 3 As shown, collision analysis is carried out using finite element numerical simulation, physical collision test, or a combination of numerical simulation and physical test. During the collision analysis, the deformation evolution process of the structure from the initial contact to the end of the collision is recorded to obtain the damage evolution information and energy absorption response information of the structure under impact load.

[0053] Specifically, during a collision, a structure can undergo damage evolution states such as local buckling, progressive collapse, crack propagation, local instability, and eventual crushing. These damage evolution states can exhibit different sequences and coupling patterns depending on the structure type, collision conditions, and material parameters. By tracking and recording the structural deformation behavior at each stage, damage evolution information during the structural collision process can be obtained.

[0054] The obtained collision analysis results were collected and processed to acquire deformation image sequences, stress field data, strain field data, displacement field data, and energy response data during the structural collision process, and a collision damage database was constructed. Specifically, the deformation image sequences were used to record the geometric changes of the structure at different collision moments; the stress field data were used to characterize the internal stress distribution characteristics of the structure; the strain field data were used to characterize the degree of local deformation of the structure; the displacement field data were used to describe the overall and local motion laws of the structure; and the energy response data were used to reflect the energy absorption and dissipation characteristics during the structural collision process.

[0055] The collision damage database is used to record damage evolution information during structural collisions. By constructing the collision damage evolution database, unified storage and management of damage evolution information throughout the entire structural collision process can be achieved, providing a data foundation for subsequent intelligent damage identification, damage feature extraction, and damage gene construction.

[0056] Step 2: Use the intelligent damage identification model to identify damage data, obtain structural damage behavior information, and extract damage feature parameters.

[0057] In one specific implementation, such as Figure 4 As shown, based on a collision damage database, the damage evolution characteristics generated during structural collisions are intelligently identified to obtain information on structural damage behavior. Specifically, this includes the following steps: Step 2.1: First, perform data preprocessing on the collision damage evolution database.

[0058] Specifically, data preprocessing includes data denoising, filtering, normalization, and data augmentation to improve the accuracy and stability of subsequent damage identification.

[0059] Step 2.2: Input the preprocessed deformation image data, stress field data, strain field data, displacement field data, and energy response data into the intelligent damage identification model to automatically identify and classify the damage evolution behavior during the structural collision process.

[0060] Specifically, intelligent damage recognition models can be implemented using convolutional neural networks, graph neural networks, deep learning models, or other intelligent recognition algorithms. By jointly analyzing multimodal collision damage data, they can achieve structural damage region localization, damage type identification, and damage evolution behavior classification.

[0061] Step 2.3: Obtain damage behavior information during the structural collision process and extract damage feature parameters through intelligent damage identification.

[0062] Specifically, damage behavior information includes one or more of the following: crack propagation behavior, local buckling behavior, progressive collapse behavior, instability behavior, and energy dissipation behavior.

[0063] After obtaining damage behavior information, features are further extracted from various damage behaviors to construct a structured damage feature parameter system. Specifically, for crack propagation behavior, feature parameters such as crack initiation location, crack propagation path, crack length, and crack propagation rate are extracted; for local buckling behavior, feature parameters such as buckling initiation location, buckling range, buckling amplitude, and buckling occurrence time are extracted; for progressive collapse behavior, feature parameters such as number of collapse layers, collapse sequence, collapse range, and collapse rate are extracted; for instability behavior, feature parameters such as instability location, instability mode, instability degree, and instability development rate are extracted; and for energy dissipation behavior, parameters such as absorbed energy, energy dissipation efficiency, and mechanical response characteristics are extracted.

[0064] Step 3: Based on the damage characteristic parameters, the damage evolution characteristics generated during the structural collision are uniformly encoded and characterized to construct a damage gene system. Based on the damage gene system, the correlation between structural parameters and damage genes is analyzed, a contribution relationship model is established, the key structural features affecting the structural damage mode are identified according to the contribution relationship model, and the structural damage mechanism is analyzed.

[0065] Step 3.1: Based on the damage characteristic parameters, the damage evolution characteristics generated during the structural collision are uniformly encoded and characterized to construct a damage gene system.

[0066] In one specific implementation, a structural damage feature vector is constructed based on damage feature parameters to provide foundational data for subsequent damage gene construction. The damage feature parameters include one or more of the following: crack propagation features, local buckling features, progressive collapse features, structural stability features, and energy dissipation features. The damage gene system consists of damage genes, which correspond to the damage feature parameters and include crack genes, buckling genes, collapse genes, stability genes, and energy dissipation genes. Specifically, crack genes characterize structural crack propagation behavior; buckling genes characterize structural local buckling behavior; collapse genes characterize structural progressive collapse behavior; stability genes characterize structural instability behavior; and energy dissipation genes characterize structural energy absorption and dissipation behavior.

[0067] The damage evolution characteristics generated during structural collisions are uniformly encoded and represented to achieve a digital description of structural damage modes, failure behaviors, and energy dissipation mechanisms.

[0068] like Figure 5 As shown, multimodal damage evolution information includes crack propagation-related information, local buckling-related information, asymptotic collapse-related information, instability behavior-related information, and energy dissipation-related information, which correspond to damage characteristic parameters such as crack propagation characteristics, local buckling characteristics, asymptotic collapse characteristics, structural stability characteristics, and energy dissipation characteristics, respectively. These various damage characteristic parameters are organized and expressed in a unified format to form a structural damage characteristic parameter vector, which is represented as follows: .

[0069] in, Represents the structural damage feature parameter vector. Indicates the first Each damage characteristic parameter, Indicates the number of damage characteristic parameters. Indicates the sequence number of the damage characteristic parameter.

[0070] In this embodiment, damage gene vectors are used to characterize the damage evolution and failure mechanisms of structures during collisions. Different structures correspond to different combinations of damage genes. By comparing the differences in damage genes among different structures, a quantitative description of structural damage patterns can be achieved. By constructing the damage gene system, the complex damage behavior during collisions is transformed into computable, comparable, and iteratively optimizeable feature information, providing a basis for subsequent damage mechanism analysis and structural optimization strategy generation.

[0071] Since different damage characteristic parameters have different dimensions and value ranges, each damage characteristic parameter is normalized. The normalized damage characteristic parameters are expressed as follows: .

[0072] in, Represents the normalized damage characteristic parameters; and These represent the maximum and minimum values ​​of the corresponding damage characteristic parameters, respectively.

[0073] Each type of damage gene is obtained by weighting multiple normalized damage feature parameters under the corresponding damage behavior category. Let the first... The damage genes corresponding to damage-like behaviors are , No. Damage-like behaviors include Then the damage characteristic parameter, the first Damage-like genes are represented as: .

[0074] in, Indicates the first Damage genes corresponding to damage-like behaviors; Indicates the first The first type of injury behavior A normalized damage characteristic parameter; Indicates the first The first type of injury behavior The weight coefficients corresponding to each normalized damage feature parameter; Indicates the first The number of damage characteristic parameters included in a class of damage behaviors; Indicates the category of damaging behavior. This indicates the sequence number of the damage characteristic parameter under this damage behavior category.

[0075] After obtaining various damage genes, a damage gene vector is constructed:

[0076] in, Represents the vector of damaged genes. Indicates the first Damage genes corresponding to damage-like behaviors This indicates the number of damage behavior categories. These categories include one or more of the following: crack propagation behavior, local buckling behavior, progressive collapse behavior, structural stability behavior, and energy dissipation behavior.

[0077] Damage gene vectors corresponding to different structures are stored in a damage gene database to form a structural damage pattern database. By comparing the differences in damage genes among different structures, the digital description and quantitative characterization of structural damage patterns can be achieved.

[0078] By constructing a damage gene system, the complex damage behavior generated during collisions is transformed into computable, comparable, and iteratively optimized damage gene information, providing a foundation for subsequent structural parameter-damage gene association analysis and damage mechanism analysis.

[0079] Step 3.2: Analyze the association between structural parameters and damage genes based on the damage gene system, and establish a contribution relationship model.

[0080] In one specific implementation, such as Figure 6As shown, a correlation model between structural parameters and damage genes is first established, namely, a contribution relationship model, including a structural parameter layer, a damage gene layer, and a damage mechanism layer. The contribution relationship model is used to characterize the influence of structural parameter changes on damage gene changes. Structural parameters are derived from the parametric design variables determined in step 1.1.2 for parametric modeling of the biomimetic energy-absorbing structure model, and are updated synchronously after each round of structural updates. Structural parameters include one or more of structural geometric parameters, material parameters, and topological configuration parameters; among them, structural geometric parameters include one or more of wall thickness, cell size, height, interlayer angle, gradient parameters, and number of layers; material parameters include one or more of elastic modulus, yield strength, and density; and topological configuration parameters include one or more of cell connection methods, gradient distribution forms, and hierarchical configuration characteristics. Collision condition parameters serve as input parameters for collision analysis, used to obtain damage data and damage gene responses under the corresponding structural parameters. To quantitatively characterize the influence of structural parameters on each damage gene, a contribution matrix of structural parameters and damage genes is constructed. This contribution matrix serves as a quantitative expression of the contribution relationship model, characterizing the influence of different structural parameters on different damage genes. It is represented as follows: .

[0081] in, Represents the structural parameters—damage gene contribution matrix; Indicates the first The structural parameter affects the first The contribution of each damage gene; Indicates the structural parameter number. Indicates the sequence number of the damaged gene; Indicates the number of structural parameters; This indicates the number of damage genes.

[0082] Elements in the contribution matrix It can be represented as: .

[0083] in, Indicates the first The amount of change in each structural parameter; This indicates the amount of change in the corresponding damaged gene; Used to characterize the The effect of the change of the first structural parameter on the... The sensitivity of each damaged gene change. Specifically, let the first... The first generation of biomimetic energy-absorbing structure model The structural parameters are The corresponding number The damage genes are ;No. The first generation of biomimetic energy-absorbing structure model The structural parameters are The corresponding number The damage genes are The changes in structural parameters and the changes in damage genes are expressed as follows: , .

[0084] in, This represents the iteration number. Therefore, based on the changes in structural parameters between adjacent generations and the resulting changes in damage genes, the number of iterations is calculated. The structural parameter affects the first The contribution of each damage gene.

[0085] In another implementation, the change in structural parameters and the amount of damage gene changes It can also be obtained through parameter perturbation analysis. Specifically, while keeping other structural parameters constant, the first... Preset perturbations were applied to each structural parameter, and collision analysis, damage identification, and damage gene construction were performed on the perturbed biomimetic energy-absorbing structural model to obtain the results before and after the perturbation. The change in each damage gene is used to calculate the contribution of the structural parameter to the corresponding damage gene. The preset perturbation amount can be determined based on the range of structural parameter values, processing constraints, design step size, or optimization algorithm step size.

[0086] Step 3.3: Identify key structural features that influence structural damage patterns based on the contribution relationship model.

[0087] In one specific implementation, structural parameters are ranked according to the numerical value of each element in the contribution matrix, and key structural features are identified based on a preset contribution threshold or the ranking result. The identification results of key structural features are output in the form of structured data, which includes one or more of the following: key structural parameter name, corresponding damage gene type, contribution value, direction of influence, and degree of importance. The direction of influence characterizes the positive or negative correlation between changes in structural parameters and changes in damage genes, and the degree of importance characterizes the level of significance of the structural parameter in the damage pattern formation process. This structured data is used as input data for subsequent damage mechanism analysis and the generation of structural optimization strategies.

[0088] Step 3.4: Analyze the structural damage mechanism based on the correlation between the damage gene vector and the structural parameters.

[0089] In one specific implementation, structural damage patterns can be identified based on the proportion or numerical value of various damage genes in the damage gene vector. A high proportion of crack genes indicates a tendency for crack propagation in the structure; a high proportion of buckling genes indicates a susceptibility to local buckling failure; a high proportion of collapse genes indicates a clear progressive collapse characteristic; a low proportion of stability genes indicates a strong risk of instability; and a high proportion of energy-consuming genes indicates a good energy absorption capacity.

[0090] It is important to note that when multiple damage behaviors exist simultaneously during a structural collision, a joint discrimination of multiple damage modes is performed based on damage gene vectors, rather than using a single-damage-type mutually exclusive discrimination method. Specifically, the dominant, secondary, and coupled damage modes of the structure are determined based on the numerical values, proportions, and preset discrimination thresholds of crack genes, buckling genes, collapse genes, stability genes, and energy-consuming genes. When a damage gene exceeds a preset dominant threshold, its corresponding damage behavior is identified as the dominant damage mode; when two or more types of damage genes exceed their corresponding thresholds, it is identified as a coupled damage mode; when a damage gene does not reach the dominant threshold but exceeds a preset auxiliary threshold, it is identified as a secondary damage mode. This allows for the simultaneous identification of multiple damage behaviors and their coupling relationships, avoiding identification bias caused by judging a single damage type.

[0091] A mapping relationship is established between the structural parameter layer, the damage gene layer, and the damage mechanism layer. The structural parameter layer, represented by a structural parameter vector, characterizes parametric design variables such as wall thickness, cell size, gradient parameters, number of layers, material parameters, and topological configuration parameters. The damage gene layer, represented by a damage gene vector, characterizes damage mode features such as crack genes, buckling genes, collapse genes, stability genes, and energy dissipation genes. The damage mechanism layer, represented by damage mechanism states, characterizes failure mechanisms or energy dissipation mechanisms such as crack-dominated failure, local buckling failure, progressive collapse energy absorption, local instability, and uneven energy dissipation. The structural parameter layer and the damage gene layer are associated through a contribution matrix, and the damage gene layer and the damage mechanism layer are associated through damage gene proportion, damage gene threshold, and a joint discrimination rule for multiple damage modes, thus forming a mapping result of "structural parameters—damage genes—damage mechanism".

[0092] Through the above analysis process, key structural features affecting structural collision performance are identified, and the formation mechanism of structural damage behavior is revealed, thereby realizing the transformation from traditional performance index evaluation to damage mechanism evaluation, and providing a basis for the generation of subsequent structural optimization strategies.

[0093] Step 4: Generate a structural optimization strategy based on the damage mechanism analysis results, update the initial biomimetic energy-absorbing structural model according to the structural optimization strategy, and generate a new generation of biomimetic energy-absorbing structural model.

[0094] In one specific implementation, such as Figure 7 As shown, based on the obtained contribution relationship model and damage mechanism analysis results, the structural features that need to be retained, strengthened, weakened or reconstructed are determined, and corresponding structural optimization strategies are generated.

[0095] Structural optimization strategies are used to determine the direction of structural parameter adjustment and the structural evolution path, so that the structural optimization process is transformed from being driven by traditional performance indicators to being driven by damage mechanisms, thereby guiding the structure to evolve continuously along the direction of favorable damage modes.

[0096] Based on the generated structural optimization strategy, the current biomimetic energy-absorbing structural model is updated to generate a new generation of biomimetic energy-absorbing structural models. Structural updates include one or more of the following: adjustment of structural geometric parameters, gradient features, hierarchical configuration, topological configuration, and material distribution. The new generation of biomimetic energy-absorbing structural models retains structural features conducive to stable gradual collapse and efficient energy absorption, while weakening or reconstructing structural features that lead to premature crack propagation, local instability, or uneven energy dissipation.

[0097] Specifically, when a crack gene indicates that the structure has a risk of premature crack propagation or crack penetration, an optimization strategy is generated to inhibit crack propagation or guide crack deflection; when a buckling gene indicates that the structure has local buckling concentration, an optimization strategy is generated to disperse buckling locations or adjust local stiffness distribution; when a collapse gene indicates that the structure has an unstable collapse sequence, an optimization strategy is generated to guide progressive collapse or adjust hierarchical configuration; when a stability gene indicates that the structure has a risk of local instability, an optimization strategy is generated to enhance local stability or optimize topological connectivity; and when an energy dissipation gene indicates that the structure has uneven energy dissipation, an optimization strategy is generated to balance energy dissipation or adjust material distribution.

[0098] Specifically, the local load-bearing capacity of the structure can be changed by adjusting the wall thickness parameters; the deformation mode and collapse path of the structure can be changed by adjusting the cell size; the stiffness distribution of the structure along the impact direction or the lateral direction can be changed by adjusting the gradient parameters; the multi-level energy dissipation characteristics of the structure can be changed by adjusting the hierarchical configuration; the connection relationship and load transfer path of the structure can be changed by adjusting the topological configuration; and the deformation capacity and energy dissipation capacity of different regions of the structure can be changed by adjusting the material distribution.

[0099] In one specific implementation, the adjustment range of the structural parameters is determined based on damage gene deviation, contribution relationship model, preset optimization target, and structural design constraints. Specifically, based on the deviation between the damage gene value corresponding to the current biomimetic energy-absorbing structural model and the target damage gene value, the damage behavior that needs to be enhanced or weakened is determined; the influence degree and direction of the key structural parameters on the corresponding damage genes are determined based on the contribution relationship model; and then, combined with the value range of the structural parameters, lightweight constraints, manufacturing constraints, strength constraints, and preset optimization step size, the adjustment range of the structural parameters is determined.

[0100] In one alternative quantization method, the first The adjustment amount of each structural parameter can be expressed as: .

[0101] in, Indicates the first The adjustment amount of each structural parameter; Indicates the first The adjustment step size coefficient of each structural parameter; Indicates the first The structural parameter affects the first The contribution of each damage gene; Indicates the first The deviation of each damaged gene relative to the target damaged gene; This indicates the number of damage genes.

[0102] The updated structural parameters are represented as follows: .

[0103] in, Indicates the first The first generation of biomimetic energy-absorbing structure model One structural parameter, Indicates the updated number One structural parameter.

[0104] To avoid structural performance fluctuations or failure to meet manufacturing constraints due to excessive adjustments to structural parameters, an upper limit constraint can be set on the adjustment amount of structural parameters: .

[0105] in, Indicates the first The maximum allowable adjustment amount of each structural parameter can be determined. This allows for the quantitative determination of the parameter adjustment range in the structural optimization strategy, making the structural update process executable and controllable.

[0106] Through the above process, the damage mechanism analysis results are transformed into an executable structural parameter adjustment scheme, so that the structural optimization process is transformed from being driven by simple performance indicators to being driven by damage mechanisms, thereby guiding the biomimetic energy-absorbing structure to iteratively evolve along the direction of favorable damage modes.

[0107] Step 5: Evaluate the performance and damage of the new generation of biomimetic energy-absorbing structure model to determine whether it meets the preset optimization objectives.

[0108] In one specific implementation, the preset optimization objectives include performance evaluation indicators and damage evaluation indicators; the performance evaluation indicators include one or more of specific energy absorption, peak impact force, average impact force and crushing force efficiency; the damage evaluation indicators include one or more of crack propagation degree, progressive collapse stability, structural stability and energy dissipation uniformity.

[0109] When the new generation of biomimetic energy-absorbing structure model meets the preset optimization target, the iteration process is terminated and the final optimization result is output; when the preset optimization target is not met, the new generation of biomimetic energy-absorbing structure model is used as the initial structure for the next iteration.

[0110] Specifically, a comprehensive evaluation can be performed based on preset performance evaluation indicators and damage evaluation indicators. When the comprehensive evaluation value meets the preset optimization objective, or when the performance evaluation indicators and damage evaluation indicators meet the preset requirements according to the preset termination rules, the iteration process is terminated, and the final optimized structure is output. When the comprehensive evaluation value does not meet the preset optimization objective, or when the performance evaluation indicators and damage evaluation indicators do not meet the preset requirements according to the preset termination rules, the current structure is used as the initial structure for the next round of iteration optimization, and the process returns to step S2 to re-perform collision analysis and damage evaluation.

[0111] By repeatedly performing collision analysis, damage identification, damage gene construction, damage mechanism analysis, and structural optimization, the structural damage mode and energy absorption mechanism are continuously optimized, enabling the structure to gradually evolve towards stable progressive collapse, efficient energy absorption, and uniform damage evolution, ultimately obtaining a biomimetic energy absorption structure with excellent collision protection performance.

[0112] In short, such as Figures 1 to 7 As shown in the figure, the biomimetic energy-absorbing structure iterative optimization method based on collision damage mode feedback provided in this embodiment first constructs an initial biomimetic energy-absorbing structure model according to the target collision protection requirements, and then parametrically describes the model so that it has the basis for subsequent structural updates and iterative adjustments.

[0113] Subsequently, collision analysis was performed on the initial biomimetic energy-absorbing structure model under preset collision conditions to obtain the dynamic response process of the structure under impact load. Deformation image sequences, stress field data, strain field data, displacement field data and energy response data were collected during the collision process to form a collision damage evolution database.

[0114] Based on this, the intelligent damage identification model is used to identify and classify multimodal data in the collision damage evolution database to obtain damage behavior information such as crack propagation behavior, local buckling behavior, progressive collapse behavior, instability behavior, and energy dissipation behavior. Furthermore, the corresponding damage feature parameters are extracted to form a structural damage feature vector.

[0115] Then, the damage characteristic parameters are normalized, and crack genes, buckling genes, collapse genes, stability genes, and energy dissipation genes are constructed according to different damage behavior categories to form a damage gene vector. The damage gene vector is used to uniformly encode and represent the damage patterns in the structural collision process, transforming the complex damage evolution behavior into calculable, comparable, and iteratively optimized digital information.

[0116] Furthermore, based on the contribution relationship between structural parameters and damage genes, the mapping relationship between structural parameters, damage genes and damage mechanisms is analyzed to determine the key structural features affecting the collision performance of the structure, and corresponding structural optimization strategies are generated based on the damage mechanism analysis results.

[0117] Finally, the current biomimetic energy-absorbing structure model is parameterized and updated according to the structural optimization strategy to generate a new generation of biomimetic energy-absorbing structure model. Collision analysis, damage identification, damage gene construction, and damage mechanism analysis are then performed again. When the new generation of biomimetic energy-absorbing structure model meets the preset optimization objective, the iteration terminates and the final optimized structure is output; if the preset optimization objective is not met, the next round of iteration optimization continues. Thus, this embodiment achieves closed-loop optimization of biomimetic energy-absorbing structures driven by damage evolution information, enabling the structure to gradually evolve towards stable progressive collapse, efficient energy absorption, and uniform damage evolution.

[0118] Example 2: Embodiment 2 of the present invention provides a biomimetic energy-absorbing structure optimization system based on collision damage mode feedback, comprising: The initial model building module is configured to build an initial biomimetic energy-absorbing structure model based on the collision protection requirements of the target structure, and to perform collision analysis on the initial biomimetic energy-absorbing structure model to obtain damage data. The damage identification and parameter extraction module is configured to use an intelligent damage identification model to identify damage data, obtain structural damage behavior information and extract damage feature parameters. The damage correlation and mechanism analysis module is configured to uniformly encode and characterize the damage evolution characteristics generated during structural collision based on damage characteristic parameters, thereby constructing a damage gene system. Based on the damage gene system, the module analyzes the correlation between structural parameters and damage genes, establishes a contribution relationship model, identifies key structural features affecting structural damage patterns based on the contribution relationship model, and analyzes the structural damage mechanism. The structural optimization and model update module is configured to generate a structural optimization strategy based on the damage mechanism analysis results, and to update the initial biomimetic energy-absorbing structural model according to the structural optimization strategy to generate a new generation of biomimetic energy-absorbing structural model.

[0119] Example 3: Embodiment 3 of the present invention provides a computer-readable storage medium storing a computer program adapted for loading by a processor and executing the steps in the biomimetic energy-absorbing structure optimization method based on collision damage mode feedback as described in Embodiment 1 of the present invention.

[0120] Example 4: Embodiment 4 of the present invention provides a computer device, the device comprising: A processor, adapted to execute computer programs; A computer-readable storage medium storing a computer program, which, when executed by the processor, implements the steps in the biomimetic energy-absorbing structure optimization method based on collision damage mode feedback as described in Embodiment 1 of the present invention.

[0121] Example 5: Embodiment 5 of the present invention provides a computer program product or computer program, which includes computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the steps in the biomimetic energy-absorbing structure optimization method based on collision damage mode feedback as described in Embodiment 1 of the present invention.

[0122] The steps and methods involved in Examples 2, 3, 4 and 5 above correspond to those in Example 1. For specific implementation methods, please refer to the relevant description section of Example 1.

[0123] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed in this application can be implemented in electronic hardware or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0124] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product. A computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the flow or function according to the embodiments of this application is generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in or transmitted through a computer-readable storage medium. The computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired or wireless means. The computer-readable storage medium can be any available medium that a computer can access or a data processing device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium, an optical medium, or a semiconductor medium, etc.

[0125] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A biomimetic energy-absorbing structure optimization method based on collision damage mode feedback, characterized in that, Includes the following steps: An initial biomimetic energy-absorbing structure model was constructed based on the collision protection requirements of the target structure, and collision analysis was performed on the initial biomimetic energy-absorbing structure model to obtain damage data. The intelligent damage identification model is used to identify damage data, obtain information on structural damage behavior, and extract damage feature parameters. Based on the damage characteristic parameters, the damage evolution characteristics generated during the structural collision are uniformly encoded and characterized to construct a damage gene system. Based on the damage gene system, the correlation between structural parameters and damage genes is analyzed, a contribution relationship model is established, the key structural features affecting the structural damage mode are identified based on the contribution relationship model, and the structural damage mechanism is analyzed. Based on the damage mechanism analysis results, a structural optimization strategy is generated. The initial biomimetic energy-absorbing structural model is then updated according to the structural optimization strategy to generate a new generation of biomimetic energy-absorbing structural model.

2. The biomimetic energy-absorbing structure optimization method based on collision damage mode feedback as described in claim 1, characterized in that, The specific steps for constructing an initial biomimetic energy-absorbing structure model based on the collision protection requirements of the target structure are as follows: Based on the application scenario, load type, impact direction, lightweight constraints, and expected damage mode of the target structure, the collision protection requirements of the target structure are determined, and a corresponding biological prototype is selected according to the collision protection requirements to establish a biomimetic energy-absorbing structure model. Parametric modeling of the biomimetic energy-absorbing structure model was performed to determine the structural geometric parameters, material parameters, and topological configuration parameters, forming an initial biomimetic energy-absorbing structure model for subsequent collision analysis and structural optimization.

3. The biomimetic energy-absorbing structure optimization method based on collision damage mode feedback as described in claim 1, characterized in that, The specific steps for collision analysis of the initial biomimetic energy-absorbing structure model are as follows: The collision condition parameters are determined based on the application scenario of the target structure. The collision condition parameters include one or more of the following: impact velocity, impact mass, impact angle, constraint conditions, and load type. Collision analysis was performed on the initial biomimetic energy-absorbing structure model based on the collision condition parameters, and the dynamic response results of the structure during the collision process were obtained as damage data.

4. The biomimetic energy-absorbing structure optimization method based on collision damage mode feedback as described in claim 3, characterized in that, Collision analysis is conducted using finite element numerical simulation, physical collision tests, or a combination of numerical simulation and physical tests. During the collision analysis, the deformation evolution process of the structure from the initial contact to the end of the collision is recorded to obtain information on the damage evolution and energy absorption response of the structure under impact load.

5. The biomimetic energy-absorbing structure optimization method based on collision damage mode feedback as described in claim 1, characterized in that, Damage characteristic parameters include one or more of the following: crack propagation characteristics, local buckling characteristics, progressive collapse characteristics, structural stability characteristics, and energy dissipation characteristics. The damage gene system is composed of damage genes, which correspond to damage characteristic parameters and specifically include crack genes, buckling genes, collapse genes, stability genes, and energy dissipation genes.

6. The biomimetic energy-absorbing structure optimization method based on collision damage mode feedback as described in claim 1, characterized in that, The performance and damage of the new generation of biomimetic energy-absorbing structure model are evaluated to determine whether it meets the preset optimization target. When the new generation of biomimetic energy-absorbing structure model meets the preset optimization target, the iteration process is terminated and the final optimization result is output. If the preset optimization target is not met, the new generation of biomimetic energy-absorbing structure model will be used as the initial structure for the next iteration.

7. A biomimetic energy-absorbing structure optimization system based on collision damage mode feedback, characterized in that, include: The initial model building module is configured to build an initial biomimetic energy-absorbing structure model based on the collision protection requirements of the target structure, and to perform collision analysis on the initial biomimetic energy-absorbing structure model to obtain damage data. The damage identification and parameter extraction module is configured to use an intelligent damage identification model to identify damage data, obtain structural damage behavior information and extract damage feature parameters. The damage correlation and mechanism analysis module is configured to uniformly encode and characterize the damage evolution characteristics generated during structural collision based on damage characteristic parameters, thereby constructing a damage gene system. Based on the damage gene system, the module analyzes the correlation between structural parameters and damage genes, establishes a contribution relationship model, identifies key structural features affecting structural damage patterns based on the contribution relationship model, and analyzes the structural damage mechanism. The structural optimization and model update module is configured to generate a structural optimization strategy based on the damage mechanism analysis results, and to update the initial biomimetic energy-absorbing structural model according to the structural optimization strategy to generate a new generation of biomimetic energy-absorbing structural model.

8. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the biomimetic energy-absorbing structure optimization method based on collision damage mode feedback as described in any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program adapted to be loaded by a processor and executed as described in any one of claims 1-6, for the optimization of a biomimetic energy-absorbing structure based on collision damage mode feedback.

10. A computer device, characterized in that, include: A processor, adapted to execute computer programs; A computer-readable storage medium storing a computer program, which, when executed by the processor, implements the biomimetic energy-absorbing structure optimization method based on collision damage mode feedback as described in any one of claims 1-6.

Images