Half-sine shock waveform generator design method based on bidirectional progressive structure

Abstract

The invention discloses a half-sine impact waveform generator design method based on a bidirectional progressive structure, and relates to the technical field of impact waveform generators and impact tests.The half-sine impact waveform generator design method comprises the following steps that an initial unit cell structure is selected, and topological optimization is conducted on the initial unit cell structure through a bidirectional progressive structure optimization method; and according to the optimized unit cell structure, assembling the semi-sine shock waveform generator by using a genetic algorithm. The design method capable of shortening the model selection time of the half-sinusoidal waveform generator and improving the test efficiency is adopted, the waveform generator capable of generating specific impact response is designed, and the pulse width and the peak value can be adjusted within a larger range.

Description

Technical Field

[0001] The present invention relates to the technical fields of shock waveform generators and shock test technologies, and in particular, to a design method for a half-sine shock waveform generator based on a bidirectional progressive structure. Background Art

[0002] In recent years, with the development of aerospace technologies, the technical indicators of aircraft and various types of weaponry and equipment have been continuously improved, the usage conditions have become increasingly harsh, and the intensity and frequency of the shock loads they are subjected to during service have also been increasing. Intense shock effects may cause damage to the overall structures of aircraft and weaponry and equipment as well as the internal devices, posing a serious threat to their operational effectiveness and survivability. Therefore, it is necessary to conduct shock tests on equipment such as aircraft to ensure their shock resistance of structures and devices. Since traditional physical testing methods (such as live ammunition shooting) have disadvantages such as long test cycles, cumbersome processes, and high costs, currently, methods of simulating the shock waveforms experienced under actual usage conditions are often used to conduct tests on various types of equipment. Among them, shock testing is a test method for verifying the adaptability of civilian and military equipment to shock environments and can provide a reference for improving the reliability of products. An ideal shock test device can simulate the real shock loads that a product may be subjected to during use, enabling the product to generate damage equivalent to the real situation. Therefore, the design of a waveform generator that can accurately generate the required specific shock response is one of the core technologies of this type of device.

[0003] National standard GB / T2423.5 stipulates three basic pulse waveforms: half-sine waveform, trapezoidal waveform, and post-peak sawtooth waveform. Among them, due to its uniform excitation characteristics and the concentration of energy on the main frequency and harmonics, the half-sine waveform can well describe the shock effect of the system's collision and rebound and is widely used in environmental reliability tests of electronic devices and shock simulation tests of artillery. Since rubber has advantages such as simple structure, reliable operation, and low cost, it is often used as a half-sine shock waveform generator, and the shock response waveform can be adjusted by changing parameters such as the thickness and radius of the rubber pad. However, due to the hyperelastic and viscoelastic characteristics of rubber, its shock dynamics model is not mature, it is difficult to establish the relationship between the specification parameters and the shock response, and a large number of tests are required to obtain the required specific waveform, which greatly increases the workload of shock tests and environmental pollution and reduces the efficiency of equipment research and development.

[0004] Therefore, there is a need in the current technical field for a half-sine shock waveform generator that can accurately, quickly, and efficiently generate a specific shock response waveform. Summary of the Invention

[0005] To solve the above problems, the object of the present invention is to provide a design method for a half-sine shock waveform generator based on a two-way progressive structure, aiming to shorten the selection time of the half-sine waveform generator, improve the test efficiency, and be able to generate a waveform generator with a specific shock response.

[0006] To achieve the above technical object, the present application provides a design method for a half-sine shock waveform generator based on a two-way progressive structure, including the following steps:

[0007] Select an initial unit cell structure and perform topology optimization on it using a two-way progressive structure optimization method;

[0008] According to the optimized unit cell structure, assemble a half-sine shock waveform generator using a genetic algorithm.

[0009] Preferably, when performing topology optimization, write topology optimization code using the Abaqus script interface, and based on the BESO soft-kill method, use the bisection method to obtain the sensitivity threshold and update the unit design variables and volume fraction to obtain optimized unit cells with different mechanical properties.

[0010] Preferably, when performing topology optimization, use the minimum compliance as the objective function of topology optimization.

[0011] Preferably, before the half-sine shock waveform generator, 3D print the optimized unit cell structure, and through shock tests, obtain the shock response waveform and compare it with the simulation results of the optimized unit cell structure to verify the effectiveness of the simulation.

[0012] Preferably, when verifying the effectiveness of the simulation, based on the shock response waveforms obtained from the simulation and the test, obtain the relationship between the topology optimization parameters and the shock response curve of the unit cell structure, which is used to guide the setting of the topology optimization parameters of the unit cell.

[0013] Preferably, when assembling a half-sine shock waveform generator using a genetic algorithm, use the type and position of the unit cell as the genotype, and use the characteristic deviation between the waveform obtained by the finite element method and the target waveform as the fitness function. Obtain the offspring population through selection, crossover, and mutation, and at the same time introduce elitism to introduce the best individual of the parent generation into the offspring to assemble the half-sine shock waveform generator.

[0014] Preferably, when assembling a half-sine shock waveform generator, perform parametric modeling on the structure according to the genotype, and solve the fitness function through the finite element method to obtain the target superstructure to assemble the half-sine shock waveform generator.

[0015] The present invention discloses a design system for a half-sine shock waveform generator based on a two-way progressive structure, including:

[0016] A topology optimization module, which is used to select an initial unit cell structure and perform topology optimization on it by using the bi-directional evolutionary structural optimization method;

[0017] An assembly module, which is used to assemble a half-sine shock waveform generator by using a genetic algorithm according to the optimized unit cell structure.

[0018] The present invention discloses the following technical effects:

[0019] 1) The test efficiency is improved: Firstly, a topology optimization technology is adopted to generate a variety of unit cells with different mechanical properties, and then the unit cells are combined to form a half-sine shock waveform generator by using a genetic algorithm, so that any half-sine shock waveform can be obtained, avoiding complex dynamic models and constitutive equations, and there is no need to conduct repeated tests, thus significantly improving the test efficiency.

[0020] 2) The characteristics of the half-sine waveform are accurately regulated: In the process of designing and assembling the unit cells into a shock waveform generator, the present invention adopts an optimization method and algorithm with high precision and high efficiency, which can greatly increase the regulation precision of the half-sine waveform characteristics such as pulse width and peak value.

[0021] 3) A larger design space and adjustment range: The design variables of the topology optimization adopted by the present invention are often the representations of the existence or non-existence of structural elements, which means that the number of its design variables is greatly increased, having a larger design space; at the same time, the shock waveform generator obtained by assembling the unit cells can adjust the pulse width and peak value within a larger range. Description of the Drawings

[0022] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required to be used in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0023] Figure 1 It is a schematic diagram of the initial unit cell structure described in the present invention. Among them, the initial unit cell consists of two relatively wide bases at the upper and lower parts and a cuboid area in the middle, and the shaded part represents the area to be optimized;

[0024] Figure 2 It is a schematic diagram of the structure of the superstructure waveform generator described in the present invention;

[0025] Figure 3 It is a schematic diagram of the unit cell arrangement of the waveform generator described in the present invention. Among them, the basic arrangement mode of the unit cells of the shock waveform generator is in the form of 3*3, and each layer of unit cells is separated by a base (the shaded part in the figure);

[0026] Figure 4It is a schematic diagram of the assembly process of the shock waveform generator based on the genetic algorithm described in the present invention. Specific embodiments

[0027] To make the objectives, technical solutions, and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Usually, the components of the embodiments of the present application described and illustrated herein can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the accompanying drawings is not intended to limit the scope of the present application to be protected, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without creative efforts belong to the scope of protection of the present application.

[0028] As Figures 1-4 shown, the present invention provides a design method for a half-sine shock waveform generator based on a two-way progressive structure. For a shock waveform generator, the most common research method is to design a unit cell structure according to past research and experience, and then use methods such as periodic arrangement to combine the unit cell structures into a complete superstructure to achieve the design of the waveform generator; it includes the following contents:

[0029] For the topology optimization problem with the minimum compliance as the objective function, it is expressed in mathematical form as:

[0030]

[0031] In the formula, C(X) is the objective function, F is the global force matrix, U is the global displacement matrix, K is the global stiffness matrix, V(X) is the volume function, V * is the design volume fraction, X is the element relative density matrix, which is composed of the relative density x e of each element. If the element is solid, then x e = 1. If the element is empty, then x e = x min . The reason for not being 0 is to prevent numerical singularities.

[0032] For the BESO algorithm, the update of the design variables is based on the gradient of the objective function, that is

[0033]

[0034] Referring to the interpolation model of the SIMP method, that is

[0035]

[0036] Substituting the expression (1) again, the sensitivity of the \(i\)-th element can be obtained as follows:

[0037]

[0038] where \(p\) is the penalty coefficient, \(k_0\) is the element stiffness matrix in the solid state, \(E\) e is the element strain energy, \(u\) e represents the displacement vector of the element, and this value can be directly extracted from the Abaqus finite element calculation results.

[0039] To prevent the results from having mesh dependence and checkerboard phenomena, which may lead to the inability to implement the optimized structure in engineering, the following filtering scheme is adopted for sensitivity filtering:

[0040]

[0041] w(r mn ) = max(0, r min - r mn )(5)

[0042] where \(r\) mn is the center distance between element \(m\) and element \(n\), \(r\) min is the filtering radius, the function \(w(r)\) is the filtering weight function, and \(\eta\) n represents a coefficient, which is an abbreviation of a part of the terms in the second-to-last item in formula (5).

[0043] To ensure the convergence of the structure, the average value can be taken according to the historical sensitivity information, that is:

[0044]

[0045] where \(k\) is the current iteration step and \(k - 1\) is the previous iteration step.

[0046] The BESO method usually starts from the complete design domain. During the optimization process, the volume fraction is gradually reduced by adjusting the values of the element design variables until the volume constraint is satisfied. During the iteration process, the volume fraction of the next iteration step is calculated from the volume fraction of the previous generation and the Evolutionary Volume Ratio (EVR):

[0047] V k+1 = V k (1 ± evr)(6)

[0048] For the update method of the element design variables, the present invention adopts the bisection method to adjust the sensitivity threshold based on the BESO SoftKill method. The specific method is as follows:

[0049] Define the lower bound of sensitivity: \(\alpha\)low = min(α e ), upper bound of sensitivity: α high = max(α e );

[0050] Calculate the sensitivity threshold: α th = (α low + α high ) / 2;

[0051] Traverse the sensitivities of all elements: a e :

[0052] If α e > α th : The element design variable x e = 1 (solid element);

[0053] Otherwise: The element design variable: x e = x min (void element);

[0054] If (sum(x e ) - V * ) > 0: α low = α th ;

[0055] Otherwise: α high = α th ;

[0056] Repeat steps 2 - 4 until (α high - α low ) / α high < 0.00001.

[0057] Using this method, the sensitivity threshold can be obtained in each iteration step, and the element design variables and volume fraction can be updated.

[0058] Using the above algorithm, design an initial unit cell with a large optimization potential, a wide design domain, and capable of periodic arrangement in a three - dimensional restricted design domain. In Figure 1 , the wider base is used to receive and conduct stress, and at the same time, when assembled into a shock waveform generator, it isolates different unit cell design domains to prevent mutual interference, and enables the bases between unit cells to be connected together to form a partition for hierarchical use. The shaded area is a cuboid structure, which expands the design domain as much as possible to improve the optimization potential. At the same time, the manufacturability of the optimization result of this structure is stronger compared to a structure with special mechanical properties (such as a bistable curved beam) itself, and it is suitable for engineering applications.

[0059] After determining the initial unit cell structure and the topology optimization method, by adjusting the parameters, a unit cell with specific mechanical properties can be obtained.

[0060] For the impact testing machine used in the present invention to provide mechanical impact to obtain the impact response waveform, its structure is as Figure 2 shown. The present invention creates a finite element model of the impact test system, sets reasonable loads and boundary conditions according to the test conditions, and simulates the impact response waveform of the superstructure. Then, the unit cells are prepared by 3D printing technology, the impact test is carried out, the impact response waveform is obtained and compared with the simulation results to verify the effectiveness of the simulation. According to the impact response waveforms obtained from the simulation and the test, the relationship between the topology optimization parameters and the unit cell structure and the impact response curve is studied, which prepares for the further assembly of the impact waveform generator and at the same time guides the setting of the topology optimization parameters of the unit cell in turn.

[0061] To prepare the waveform generator designed in the present invention, it is necessary to constrain the positions of the unit cells and assemble them into a superstructure according to a specific algorithm. According to the different positions, the numbers of the unit cells are as Figure 3 shown. Appropriate unit cells are selected for assembly through a specific algorithm and combined with the impact response waveform obtained by finite element solution. Considering that the genetic algorithm has the advantage of dealing with complex problems lacking mathematical expressions and obtaining the global optimal solution, the present invention selects the genetic algorithm as the method for assembling the impact waveform generator. The type and position of the unit cell are used as the genotype, and the characteristic deviation between the waveform obtained by finite element method and the target waveform is used as the fitness function. The offspring population is obtained through selection, crossover and mutation, and at the same time elitism is introduced to introduce the best individual of the parent generation into the offspring to improve the convergence efficiency. The specific process is as Figure 4 shown:

[0062] Step a numbers the unit cells with different mechanical properties after optimization;

[0063] Step b writes into different positions of the genotype according to the positions of the unit cells in the impact waveform generator, and different numbers represent different unit cell numbers;

[0064] Steps c and d perform operations such as mutation and crossover on the genotype;

[0065] Step e performs parametric modeling on the structure according to the genotype and solves the fitness function by finite element method.

[0066] After obtaining the target superstructure, simulation and experimental studies are carried out on this structure. For the simulation, the impact response waveform of the structure obtained by calling finite element solution in the assembly algorithm is used, and relevant data can be extracted to obtain the simulation results of this structure. For the experiment, a vertical impact table designed for the unit cell impact test is used, the impact waveform generator is prepared by 3D printing technology, and the impact response data is collected through a vertical drop test and compared with the simulation results to prove the effectiveness of the simulation and the credibility of the algorithm.

[0067] In summary, the present invention selects an initial unit cell structure and then performs topology optimization on it using a two-way progressive structure optimization method to obtain optimized unit cells with different mechanical properties. Topology optimization code is written using the Abaqus scripting interface, and the sensitivity threshold is obtained by the bisection method based on the BESO (Soft Kill) method, and the element design variables and volume fraction are updated. The initial unit cell design is the basis of the present invention. For this purpose, an initial unit cell with a three-dimensional restricted design domain is proposed. After determining the initial unit cell structure and topology optimization method, by adjusting parameters, unit cells with specific mechanical properties are obtained. A vertical impact table for impact tests is designed and manufactured, and unit cells are prepared using 3D printing technology. Impact tests are carried out, and the impact response waveforms are obtained and compared with the simulation results to verify the effectiveness of the simulation. The half-sine impact waveform generator designed by the present invention is assembled from unit cells according to a specific algorithm, and constraints are imposed on the positions of the unit cells for preparation and testing. The genetic algorithm is used to assemble the half-sine impact waveform generator. The type and position of the unit cell are used as the genotype, and the characteristic deviation between the waveform obtained by the finite element method and the target waveform is used as the fitness function. The offspring population is obtained through selection, crossover, and mutation. At the same time, elitism is introduced, and the best individual of the parent generation is introduced into the offspring to improve the convergence efficiency.

[0068] The present invention is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to embodiments of the present invention. It should be understood that each flow and / or block in the flowchart and / or block diagram, and the combination of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in one Figure 1 flow or multiple flows and / or blocks Figure 1 or multiple blocks.

[0069] In the description of the present invention, it should be understood that the terms "first" and "second" are only used for descriptive purposes and cannot be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, features defined with "first" and "second" may explicitly or implicitly include one or more of such features. In the description of the present invention, "a plurality of" means two or more unless otherwise specifically defined.

[0070] Obviously, those skilled in the art can make various modifications and variations to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention is also intended to include these modifications and variations.

Claims

1. A design method of a half - sine shock waveform generator based on a two - way progressive structure, characterized in that, It includes the following steps: Select an initial unit cell structure and perform topology optimization on it using the bi-directional evolutionary structural optimization method; According to the optimized unit cell structure, assemble a half-sine shock waveform generator using the genetic algorithm.

2. The design method of a half-sine shock waveform generator based on bi-directional evolutionary structure according to claim 1, wherein: When performing topology optimization, write topology optimization code using the Abaqus script interface, and based on the BESO soft killing method, use the bisection method to obtain the sensitivity threshold and update the element design variables and volume fraction to obtain optimized unit cells with different mechanical properties.

3. The design method of a half-sine shock waveform generator based on bi-directional evolutionary structure according to claim 2, wherein: When performing topology optimization, use the minimum compliance as the objective function of topology optimization.

4. The design method of a half-sine shock waveform generator based on bi-directional evolutionary structure according to claim 3, wherein: Before the half-sine shock waveform generator, 3D print the optimized unit cell structure, and through shock tests, obtain the shock response waveform and compare it with the simulation results of the optimized unit cell structure to verify the effectiveness of the simulation.

5. The design method of a half-sine shock waveform generator based on bi-directional evolutionary structure according to claim 4, wherein: When verifying the effectiveness of the simulation, based on the shock response waveforms obtained from the simulation and the test, obtain the relationship between the topology optimization parameters and the shock response curve of the unit cell structure, which is used to guide the setting of the topology optimization parameters of the unit cell.

6. The design method of a half-sine shock waveform generator based on bi-directional evolutionary structure according to claim 5, wherein: When assembling the half-sine shock waveform generator using the genetic algorithm, use the type and position of the unit cell as the genotype, and use the characteristic deviation between the waveform obtained by finite element method and the target waveform as the fitness function. Obtain the offspring population through selection, crossover, and mutation, and at the same time introduce elitism to introduce the best individual of the parent generation into the offspring to assemble the half-sine shock waveform generator.

7. The design method of a half-sine shock waveform generator based on bi-directional evolutionary structure according to claim 6, wherein: When assembling the half-sine shock waveform generator, perform parametric modeling on the structure according to the genotype, and solve the fitness function through the finite element method to obtain the target superstructure to assemble the half-sine shock waveform generator.

8. A design method of a half-sine shock waveform generator based on a bidirectional progressive structure according to any one of claims 1-7, characterized in that, The half-sine shock waveform generator design system for implementing this method includes: A topology optimization module for selecting an initial unit cell structure and performing topology optimization on it using the bi-directional evolutionary structure optimization method; An assembly module for assembling a half-sine shock waveform generator using the genetic algorithm according to the optimized unit cell structure.

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