Honeycomb barrier simulation modeling cell parameter determination method

Abstract

The invention relates to the technical field of mathematical modeling, in particular to a cellular barrier simulation modeling cell parameter determination method. Performing equivalent cell expansion according to the size of the real object wall barrier unit, and determining a proportional relation between the span and the thickness of an equivalent cell element; grid division is carried out in the different-surface thickness direction of the equivalent cell elements; in a simulation environment, building a cell wall discrete model by using a thin plate unit; and according to the proportional relation, the cell element number of the cell wall discrete model in the coplanar transverse direction, the cell element number of the cell wall discrete model in the coplanar longitudinal direction and the cell wall thickness are optimized with the purposes of minimizing the peak load in the collision process, minimizing the deformation distance of the cell wall discrete model and maximizing the absorption energy of the cell wall discrete model. According to the method, the simulation efficiency of the model is improved while the deformation process in real object barrier collision is accurately simulated.

Description

Technical Field

[0001] The present invention relates to the technical field of mathematical modeling, and in particular to a method for determining cell parameters in honeycomb barrier simulation modeling. Background Art

[0002] The purpose of automobile collision safety test is to replicate the working conditions of two vehicles colliding. The barrier is used to simulate the deformation and mechanical characteristics of the front of the car. Because its stiffness is similar to the average stiffness of the front end of the car, the honeycomb is often used to simulate the characteristics of the other vehicle colliding with the test vehicle, and is used as the main scale and measuring tool for vehicle collision strength.

[0003] In order to reduce design costs and improve efficiency, computer simulation of the car collision process has become an important method and means for car collision safety design and improvement. Therefore, how to ensure the precision and accuracy of the simulation plays a vital role in engineering applications. In addition to being related to the finite element software's own algorithm, the precision and accuracy of car collision simulation also largely depends on the accuracy of the simulation model, and the accuracy of the barrier model is a very important aspect of this.

[0004] When constructing a simulation model of honeycomb aluminum, a variety of methods can be used, such as equivalent material model, solid unit model and shell unit model. Although the equivalent material model is computationally efficient, the material model is complex, resulting in limited simulation accuracy; although the solid unit model has high analysis accuracy, it is insufficient in local deformation simulation, and the hourglass energy problem is significant; the shell unit model can accurately reproduce the true geometric form of honeycomb aluminum and effectively capture its complex deformation characteristics, but the simulation accuracy still needs to be improved. Therefore, choosing the appropriate modeling method, accurately simulating the material properties of honeycomb aluminum, and taking into account the computational efficiency while improving the simulation accuracy will have a far-reaching impact on automobile collision safety testing. Summary of the invention

[0005] The purpose of the present invention is to provide a method for determining cell parameters in honeycomb barrier simulation modeling, which can improve the simulation efficiency of the model while accurately simulating the deformation process of the physical barrier collision.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions: The present invention provides a method for determining cell parameters of a honeycomb barrier simulation modeling, comprising: Perform equivalent cell expansion according to the size of the physical barrier unit to obtain an equivalent honeycomb model, and determine the proportional relationship between the span and thickness of the equivalent cell in the equivalent honeycomb model; Meshing the equivalent honeycomb model; In the simulation environment, the cell wall discrete model is constructed using thin plate elements; According to the proportional relationship, the peak load F during the collision is minimized. p, minimizing the deformation distance D of the cell wall discrete model and maximizing the absorbed energy W1 of the cell wall discrete model, and calculating the number of cells N of the cell wall discrete model in the coplanar lateral direction W , the number of cells in the coplanar longitudinal direction N L and cell wall thickness t2 are optimized.

[0007] Compared with the prior art, the present invention has the following beneficial effects: The present invention deeply optimizes the equivalent cell expansion method to reduce errors and improve simulation accuracy while maintaining calculation efficiency, thereby achieving the optimal parameter design of honeycomb aluminum, which has great practical significance and application value for the simulation research of honeycomb aluminum. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0009] Figure 1 is a schematic diagram of a honeycomb aluminum structure provided by an embodiment of the present invention; Figure 2 is a schematic diagram of a hexagonal honeycomb structure cell provided by an embodiment of the present invention; Figure 3 It is a flow chart of a method for determining cell parameters of a honeycomb barrier simulation modeling provided by an embodiment of the present invention; Figure 4 is a schematic diagram of a double rigid wall provided by an embodiment of the present invention; Figure 5 is a schematic diagram of an area equivalent constraint condition provided by an embodiment of the present invention; Figure 6 It is a comparison diagram of honeycomb deformation modes before and after optimization provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0010] The following is a description of exemplary embodiments of the present invention in conjunction with the accompanying drawings, including various details of the embodiments of the present invention to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be recognized by those of ordinary skill in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present invention. Similarly, for clarity and conciseness, the description of well-known functions and structures is omitted in the following description.

[0011] The embodiment of the present invention is applicable to a scenario in which parameters of a honeycomb model (ie, a cell wall discrete model) are optimized during simulation modeling of honeycomb aluminum in a vehicle collision scenario using an equivalent cell expansion method.

[0012] In order to conveniently introduce the method provided by the present invention, the honeycomb aluminum structure is first introduced.

[0013] Honeycomb is an anisotropic material made based on bionics. Figure 1 As shown in the figure, the dimension in the L direction is called the coplanar longitudinal length, the dimension in the W direction is called the coplanar transverse length, and the dimension in the T direction is called the skew thickness. Loading along the L or W direction is called coplanar loading, and loading along the T direction is called skew loading. As a buffer energy-absorbing material, the skew bearing capacity of aluminum honeycomb is much better than that of coplanar bearing capacity, so the collision energy absorption of honeycomb structure is usually based on skew compression.

[0014] See also Figure 2 The cell parameters of the hexagonal honeycomb structure include cell length l, cell span h, cell thickness t and cell wall inner angle θ. The thickness of the cell bonding surface is double layer thickness, which is 2t.

[0015] See also Figure 3 , the method provided by the embodiment of the present invention includes: S110, performing equivalent cell expansion according to the size of the physical barrier unit to obtain an equivalent honeycomb model, and determining the proportional relationship between the span and thickness of the equivalent cell in the equivalent honeycomb model.

[0016] In one embodiment, select h / l =1 and Of course, cells of other sizes can also be used for research.

[0017] The energy absorption characteristics of the honeycomb structure are directly related to t / l For a regular hexagonal honeycomb structure ( t=l ), without considering the effect of the joints on the volume, in order to ensure the consistency of energy absorption characteristics, when selecting the size of the honeycomb modeling unit cell, it should be ensured that t / l Keep the number consistent or within a certain range, that is, ensure t / h The number remains consistent or controlled within a certain range. After equivalent cell expansion, an equivalent honeycomb model consisting of multiple equivalent cells is obtained.

[0018] S120. Mesh the equivalent honeycomb model.

[0019] Optionally, the three-dimensional space of the equivalent honeycomb model is meshed. The following is an illustration taking the T direction as an example.

[0020] The grid unit size of the cell in the T direction directly determines the wavelength λ of the plastic folding of the pore wall, which is usually approximately equal to the cell size h. Therefore, the grid unit size in the T direction has an important influence on the deformation mode of the aluminum honeycomb. The calculation of the critical time step (i.e., the simulation step) depends on the type of element used. The critical time step of the shell element is calculated by the Courant criterion: ;Formula (1) in, is the critical time step, is the minimum edge length, and c is the stress propagation velocity. The Courant criterion defines the relationship between the time step and the space step, ensuring stability and convergence during the numerical simulation.

[0021] For the shell element modeling of the present invention, the stress propagation velocity c is: ;Formula (2) Where E is Young's modulus, is the Poisson's ratio, is the material mass density.

[0022] The smaller the grid unit size in the T direction, the closer the hole wall buckling wavelength in the simulation is to the actual wavelength in practice. However, the size of the grid unit directly determines the simulation time step of the cell wall discrete model. The most commonly used simulation time step in automobile collision simulation is 1ms.

[0023] Since the strain gradient at the connection between the cell wall and the cell wall edge is much higher than that in the center of the cell wall, smaller mesh units should be used at locations with large strain gradients to obtain accurate results, while larger mesh units can be used at locations with small strain gradients. Therefore, the cell wall discrete model is divided using a gradient grid, that is, the grid at the edge of the aluminum honeycomb cell wall is a square unit, whose side length is determined by the required model time step, while the grid unit at the center of the cell wall uses a rectangular unit with a high aspect ratio.

[0024] S130. In the simulation environment, use thin plate elements to construct a cell wall discrete model.

[0025] Optionally, a display dynamics solution software package (such as DYNA3D) is first used to numerically verify the structure before and after cell expansion.

[0026] The cell wall discrete model is constructed using the Belytschko-Tsay thin plate element. The cell wall discrete model and boundary conditions are as follows Figure 4 The cell substrate is aluminum A3003, density ρ = 2100 kg / m 3 , elastic modulus E = 70 GPa, Poisson's ratio ν = 0.33, yield strength σ yｓ=190MPa, ultimate tensile strength 800MPa. Since the intercellular adhesive has sufficient strength when the cell wall is subjected to low-speed impact, it will not cause tearing between the double cell walls, so the intercellular adhesive is not considered during modeling. The equivalent cells all adopt the double rigid wall mode, with a fixed rigid wall at the bottom as a rigid boundary and a mobile rigid wall at the top, loaded at a constant speed of 5m / s. In order to prevent intercellular penetration, the automatic single-sided contact algorithm is selected, and the friction factor is 0.2.

[0027] S140, based on the proportional relationship, to minimize the peak load F during the collision p , minimizing the deformation distance D of the cell wall discrete model and maximizing the absorbed energy W1 of the cell wall discrete model, and calculating the number of cells N of the cell wall discrete model in the coplanar lateral direction W , the number of cells in the coplanar longitudinal direction N L And the equivalent cell wall thickness t2 is optimized.

[0028] If only the thickness of the cell wall is modified to maintain the strength of the cell wall discrete model in the T direction after the honeycomb hole type is expanded, without optimizing other parameters in the cell wall discrete model (such as materials, failure, etc.), the cell wall discrete model will lose the gradual collapse deformation mode. Therefore, in order to maintain the strength and gradual collapse deformation mode of the honeycomb in the T direction after the hole type is expanded, it is necessary to continue to optimize the compression simulation of the cell wall discrete model in the T direction.

[0029] When the moving distance of the moving rigid wall is constant, the smaller the deformation distance of the honeycomb, the smaller the buckling wavelength of the honeycomb aluminum pore wall, the more concentrated the deformation of the honeycomb aluminum in the T direction, and the more consistent with the actual collision compression. At the same time, when honeycomb aluminum is used as an energy-absorbing element, in order to minimize the kinetic energy of the impactor, the peak load of the honeycomb structure should be minimized and the absorbed energy should be increased during the collision.

[0030] Based on the above analysis, the optimization objectives include: minimizing the deformation distance D of the cell wall discrete model in the T-direction compression simulation, minimizing the peak load F during the collision process p , maximize the absorbed energy W1 of the cell wall discrete model.

[0031] Figure 5 Schematic diagram of area equivalent constraint conditions provided by an embodiment of the present invention. The bold black hexagon is the equivalent cell, with a span of , thickness is t2, the unbold black hexagon is the cell before equivalent, span is h1, thickness is t1. Assume that the number of cells in the W direction and L direction is N W and N L , the total length of the model in the W direction is d W , the total length of the model in the L direction is dL θ is the angle inside the cell wall. For a regular hexagon, h=l , and ignoring the intercellular glue thickness, it can be seen from the geometric relationship that the equivalent cell needs to meet the following conditions in the W and L directions respectively: ;Formula (3) ;Formula (4) The optimal value of the equivalent cell span is given by N W and N L The overall goal is to determine the optimal combination of As large as possible, the difference in the equivalent front and rear bearing area meets the error limit ε requirement. W and N L Does the load-bearing area difference caused by this method meet the requirements of the error limit ε? If not, reset N W and N L , until the load-bearing area difference meets the error limit ε. In barrier design, different stiffness regions are usually used to optimize its performance to adapt to different impact conditions and protection requirements. In the present invention, the cell span of different stiffness regions (hereinafter referred to as regions) that meet the conditions They are 8, 10, 12, 14 and 16 respectively.

[0032] For a regular hexagon, the error limit ε is: ;Formula (5) ;Formula (6) in, Indicates iter The equivalent cell span in iterations, Indicates iter The error limit corresponding to the difference in bearing area in the iteration is, Indicates iter+1 The error limit corresponding to the difference in bearing area in the iterations.

[0033] According to the proportional relationship between the span and thickness of the equivalent cell, when the cell side length is determined, the cell wall thickness of the cell in the ith region after equivalent is preliminarily obtained. for: ;Formula (7) in, is the cell span of the cell in the equivalent i-th region, is the cell span of the cell in the ith region after equivalence, is the cell wall thickness of the cell in the ith region before equivalent.

[0034] In this embodiment, the number of cells N in the cell wall discrete model in the coplanar lateral direction is W , the number of cells in the coplanar longitudinal direction N L The cell wall thickness t2 is optimized. The cell elements in five different regions are optimized. The objective function is shown in formula (8).

[0035] 1; Formula (8) The optimization conditions during the optimization process are as follows: For the following five optional cell honeycomb structures: , The value range of is: 0.04≤ ≤0.52( =8) 0.04≤ ≤0.52( =10) 0.04≤ ≤0.52( =12); Formula (9) 0.04≤ ≤0.52( =14) 0.04≤ ≤0.52( =16) For the above five types of cell honeycomb structures: The value range of is: ;Formula (10) In summary, the mathematical model of this optimization problem can be constructed as follows: ;Formula (11) Optional, since the variables of the objective function f are , then after minimizing the objective function, we get , and then according to formula (7) and each , calculated .

[0036] The number of cells in the coplanar lateral direction for the i-th region cell is calculated according to the following formula: , the number of cells in the coplanar longitudinal direction : ;Formula (12) ;Formula (13) Optionally, a memory algorithm of a crow population is used to minimize the peak load F during the collision according to the proportional relationship. p, minimizing the deformation distance D of the cell wall discrete model and maximizing the absorbed energy W1 of the cell wall discrete model as the goal, and obtaining the cell wall thickness of the i-th cell honeycomb structure and cell span .

[0037] The memory algorithm of the crow population provided in this embodiment includes the following operations: The specific steps are as follows: Step 1: Initialize algorithm parameters, including: crow population n, flight distance fl, perception probability Ap, iteration number iter, and maximum iteration number itermax.

[0038] Step 2: Initialize the crow positions and crow memories. n crows are randomly placed in the d-dimensional search space. Each crow represents a feasible solution to a problem, and d is the dimension of the decision variable; ;Formula (14) In formula (14), Crows is the initialization position of the crows, is the position of the nth crow in the d-dimensional search space (the d-th decision variable space).

[0039] ;Formula (15) In formula (15), Memory is the initialized crow memory, which represents the optimal feasible solution matrix after initialization; is the memory of the nth crow in the d-dimensional search space (the dth decision variable space), which represents the best value of the nth feasible solution in the dth decision variable space under the current number of iterations.

[0040] For this problem, we only need to solve the cell span h and cell thickness t, so d is 2, and equations (14) and (15) can be changed to: ;Formula (16) ;Formula (17) Step 3: Evaluate the fitness of each crow's position according to formula (8). For this problem, formula (11) shows that the crow position corresponding to the smaller solution value of formula (8) has better fitness.

[0041] Step 4: Generate new positions for each crow.

[0042] ;Formula (18) In formula (18), is the position of crow i in the iter-th iteration, is the new position of crow i in the iter+1th iteration, is the flight distance of crow i in the iter-th iteration, is the memory of crow i in the iterth iteration, r i is a random number in [0, 1], is the perception probability of crow i in the iter-th iteration, Represents a random position.

[0043] Step 5: Check the feasibility of the new position. If the fitness function corresponding to the crow's new position is high, the crow will update its position to the crow memory matrix; otherwise, the crow memory matrix will not be updated.

[0044] Step 6: Evaluate the fitness of the new position and update the memory according to formula (18); ;Formula (19) In formula (19), is the new memory of crow i in the iter+1th iteration, is the memory of crow i in the iter-th iteration, is the position of crow i in the iter+1th iteration, is the objective function (8).

[0045] Step 7: Test the termination criteria. Repeat steps 4 to 6 until the maximum number of iterations itermax or other constraints are reached. When the termination criteria are met, consider the optimal position of the crow memory corresponding to the minimum value of the objective function as the solution to the problem.

[0046] The logic of the memory algorithm of the entire crow population is to compare the fitness function value corresponding to the crow position at the tth iteration with the fitness function value corresponding to the crow position at the t-1th iteration, and put the crow position corresponding to the function value with the higher fitness into the crow memory matrix, and then compare the newly generated crow position with the crow memory to determine whether to update the crow memory matrix again. After repeated iterations, the crow memory matrix stores the best crow position.

[0047] According to the crow search algorithm, the minimum objective function value that satisfies the iteration stop condition and the variable cell wall thickness corresponding to the minimum objective function value can be output. , cell span At this time, according to formula (7), the cell wall thickness of cells in five different regions can be calculated: ; According to formula (12) and formula (13), the number of cells in the W direction and L direction are calculated respectively, which are N W and N L .

[0048] Figure 6It is a comparison diagram of the honeycomb deformation mode before and after optimization provided by the embodiment of the present invention. The left side is the discrete model of the cell wall before optimization, and the right side is the discrete model of the cell wall after optimization. After optimization, the deformation area of ​​the model in the compression direction is mainly concentrated at the top, which is closer to the deformation area of ​​the actual barrier. In addition to the deformation at the top, the model before optimization also has corresponding deformation at the bottom, which does not conform to the actual deformation area.

[0049] The method provided by the present invention is described in detail below with a specific implementation manner.

[0050] The optimization goal is to minimize the objective function, see formula (8), to minimize the peak load F p , minimize the deformation distance D and maximize the absorbed energy W1.

[0051] The variables are: the number of cells N in the W and L directions W , N L , the cell thickness is t2.

[0052] d W and d L It is known that formula (12) and formula (13) are satisfied in the W direction and the L direction.

[0053] For various stiffness regions: h1=8, 10, 12, 14, 16, taking h1=8 as an example, there are the following formulas: ;Formula (20) The constraints when h1=8 are as follows: ;Formula (21) Then the optimal solution is found through the memory algorithm of the crow population.

[0054] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution disclosed in the present invention can be achieved, and this document does not limit this.

[0055] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for determining cell parameters for honeycomb barrier simulation modeling, characterized in that: include: Perform equivalent cell expansion according to the size of the physical barrier unit to obtain an equivalent honeycomb model, and determine the proportional relationship between the span and thickness of the equivalent cell in the equivalent honeycomb model; Meshing the equivalent honeycomb model; In the simulation environment, the cell wall discrete model is constructed using thin plate elements; According to the proportional relationship, the peak load F during the collision is minimized. p , minimizing the deformation distance D of the cell wall discrete model and maximizing the absorbed energy W1 of the cell wall discrete model, and calculating the number of cells N of the cell wall discrete model in the coplanar lateral direction W , the number of cells in the coplanar longitudinal direction N L and cell wall thickness t2 are optimized.

2. The method for determining cell parameters of honeycomb barrier simulation modeling according to claim 1, characterized in that: Meshing of the equivalent cellular model, including: Performing mesh division using a gradient grid in the non-planar thickness direction of the equivalent cell; The gradient grid includes: the grid located at the edge of the aluminum honeycomb hole wall is a square unit, and the grid located in the center of the hole wall is a rectangular unit.

3. The method for determining cell parameters of honeycomb barrier simulation modeling according to claim 2, characterized in that: Before using thin plate elements to build a cell wall discretization model, it also includes: The explicit dynamics solution software package was used to numerically verify the structure before and after cell expansion.

4. The method for determining cell parameters of honeycomb barrier simulation modeling according to claim 3, characterized in that: The parameters and boundary conditions of the cell wall discrete model include: The cell base material is aluminum A3003, density ρ = 2100kg / m 3 , elastic modulus E = 70 GPa, Poisson's ratio ν = 0.33, yield strength σ yｓ =190MPa, ultimate tensile strength 800MPa; The equivalent cells all adopt a double rigid wall mode, with a fixed rigid wall at the bottom as a rigid boundary and a movable rigid wall at the top, which is loaded at a constant speed. In order to prevent inter-cell penetration, the automatic single-sided contact algorithm is selected, and the friction factor is 0.

2.

5. The method for determining cell parameters of honeycomb barrier simulation modeling according to claim 4, characterized in that: The constraints in the optimization process include: 0.04≤ ≤0.52； ； in, is the cell wall thickness of the cell structure in the ith region before equivalent, is the cell span of the honeycomb structure of the ith region before the equivalent, is the cell wall inner angle, d W and d L is the length of the cell wall discrete model in the coplanar transverse direction and the coplanar longitudinal direction, is the cell span of the cell in the ith region after equivalence.

6. The method for determining cell parameters of honeycomb barrier simulation modeling according to claim 5, characterized in that: According to the proportional relationship, the peak load F during the collision is minimized. p , minimizing the deformation distance D of the cell wall discrete model and maximizing the absorbed energy W1 of the cell wall discrete model, and calculating the number of cells N of the cell wall discrete model in the coplanar lateral direction W , the number of cells in the coplanar longitudinal direction N L and cell wall thickness t2, including: According to the proportional relationship, the cell wall thickness of the cell element in the ith region before the equivalent is obtained by minimizing the peak load Fp during the collision, minimizing the deformation distance D of the cell wall discrete model, and maximizing the absorbed energy W1 of the cell wall discrete model. and the cell span of the cell in the ith region after equivalence ; The cell wall thickness of the cell in the ith region is calculated according to the following formula: : ； in, is the cell span of the cell in the equivalent i-th region, is the cell wall thickness of the cell in the ith region after equivalent; The number of cells in the coplanar lateral direction for the i-th region cell is calculated according to the following formula: N Wi , the number of cells in the coplanar longitudinal direction N Li : ； 。 7. The method for determining cell parameters of honeycomb barrier simulation modeling according to claim 6, characterized in that: According to the proportional relationship, the cell wall thickness of the i-th cell honeycomb structure is obtained by minimizing the peak load Fp during the collision, minimizing the deformation distance D of the cell wall discrete model, and maximizing the absorbed energy W1 of the cell wall discrete model. and cell span ,include: The memory algorithm of the crow population is used to minimize the peak load F during the collision according to the proportional relationship. p , minimizing the deformation distance D of the cell wall discrete model and maximizing the absorbed energy W1 of the cell wall discrete model as the goal, and obtaining the cell wall thickness of the i-th cell honeycomb structure and cell span .

8. The method for determining cell parameters of honeycomb barrier simulation modeling according to claim 7, characterized in that: The cell span of the i-th cell honeycomb structure This is determined in the following way: The number of cells N in the coplanar lateral direction of the cell wall discretization model is W , the number of cells in the coplanar longitudinal direction N L Optimize the combination so that the difference in bearing area before and after the equivalent meets the error limit requirements, and obtain They are 8, 10, 12, 14 and 16 respectively.

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