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Mechanical structure topological optimization method based on multi-population genetic algorithm

A topology optimization and genetic algorithm technology, applied in the field of lightweight design of mechanical structures, can solve the problems of unstable results, falling into local optimal solutions, and the structure cannot find a global optimal solution, etc., and achieves improved probability and structural flexibility. The effect of small degree and high computational efficiency

Active Publication Date: 2021-01-29
BEIJING INSTITUTE OF TECHNOLOGYGY
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004]In order to achieve a fixed target volume, the BESO method needs to delete a certain number of units in each iteration of the solution. Mistake and wrong deletion operations may cause the structure to find the overall situation optimal solution
Although the SGA-BESO method can increase the probability of finding the global optimal solution, immature convergence is a phenomenon that cannot be ignored in the SGA method, and the results obtained by optimization are unstable. In practical applications, there is still the possibility of falling into a local optimal solution.

Method used

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  • Mechanical structure topological optimization method based on multi-population genetic algorithm
  • Mechanical structure topological optimization method based on multi-population genetic algorithm
  • Mechanical structure topological optimization method based on multi-population genetic algorithm

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0072] Example 1: Optimization of a two-dimensional cantilever beam structure

[0073] The cantilever beam structure is as image 3 As shown, the specific structural parameters are: the size is 80mm×50mm×1mm, the elastic modulus of the material is 100GPa, and the Poisson’s ratio is 0.3, and a vertical downward concentrated load of F=100N is applied at the midpoint of the right end of the structure , the design area is discretized into 80×50 square units. The optimization parameters adopted are: penalty factor p=3, target volume constraint limit f V = 50%, unit sensitivity filter radius r min =3, the minimum relative density ρ of the unit min =0.001, the length of unit individual gene string length=4, the population size M=40, the convergence error limit τ=0.1%, the initial selection ratio f of the unit in the "low class" v-int = 0.8, at least keep algebra gen = 1, parameter pen = 1.5.

[0074] Adopt the method of the present invention to finish image 3 Topology optimiza...

Embodiment 2

[0079] Example 2: Topology optimization of a two-dimensional cantilever beam structure where the initial design area is a conjecture

[0080] The structural dimensions and material parameters of the cantilever beam are the same as in Example 1, but the initial design area is Figure 6 In the conjecture part shown, the finite element mesh is divided by square elements with a side length of 1 mm. The initial selection ratio f of units in the "lower class" v-int =0.66, parameter pen=1.0, and other optimization parameters are the same as embodiment 1. Figure 7 It is the optimization result of 8 times of topology optimization, and it can still be seen that the optimization result will not change significantly.

[0081] For Example 2, the optimal structural topological flexibility and corresponding calculation iteration steps obtained by the three methods are shown in Table 2:

[0082] Table 2 Comparison of the solution results of the three methods

[0083]

[0084] Table 2 ...

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Abstract

The invention provides a mechanical structure topological optimization method based on a multi-population genetic algorithm, which can realize topological design for minimizing structural flexibilityunder a volume constraint condition. The method comprises the following specific steps: 1, dividing finite element grids, and establishing an optimization model of a topological optimization problem;2, setting operation parameters of a multi-population genetic algorithm; 3, solving the topological optimization model, and drawing a topological optimization result. According to the method, the probability of searching for a topological optimization global optimal solution can be improved, and a stable topological optimization result is obtained; the method has the advantages of being fast in iterative convergence, clear and stable in optimization result and the like and can be popularized and applied to structural design of complex mechanical equipment.

Description

technical field [0001] The invention belongs to the field of lightweight design of mechanical structures, and relates to a mechanical structure topology optimization method based on multi-population genetic algorithm. Background technique [0002] In the design of mechanical structures, designers always hope to achieve the optimal performance of mechanical structures with the least amount of material. As the most basic mechanical structure design stage, topology design directly affects the subsequent shape and size design. If the structural topology is not optimal, it is difficult to obtain optimal structural performance. Therefore, it is necessary to determine the optimal topology of the structure in the initial conceptual design stage. form. The overall flexibility of the structure is an important performance that needs to be considered in the design of mechanical structures. A common situation in practice is the topology optimization problem of minimizing structural flex...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F30/17G06F30/23G06F111/06G06F111/10G06F119/14
CPCG06F30/17G06F30/23G06F2111/06G06F2111/10G06F2119/14
Inventor 廖静平黄高黄强余张国陈学超
Owner BEIJING INSTITUTE OF TECHNOLOGYGY
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