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Genetic evolution topological optimization improvement method

A technology of topology optimization and genetics, applied in the direction of genetic rules, genetic models, etc., to achieve the effects of improving stability, avoiding unit deletion by mistake, and avoiding inefficiency

Active Publication Date: 2018-03-02
QINGDAO TECHNOLOGICAL UNIVERSITY
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  • Claims
  • Application Information

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Problems solved by technology

However, GESO is powerless against the Zhou-Rozvany counterexample, and the probabilistic properties of the GESO algorithm can easily cause the evolution process to prematurely enter the branch where the solution fails.

Method used

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  • Genetic evolution topological optimization improvement method
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  • Genetic evolution topological optimization improvement method

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Embodiment 1

[0059] Embodiment 1: Take the famous "Zhou-Rozvany counterexample" as an example.

[0060] The present invention can be realized by using MATLAB to call ANSYS (finite element calculation) cyclically. The structure is as figure 2 As shown, the material is isotropic, the elastic modulus is 1, Poisson’s ratio is 0, the horizontal load intensity is 2, the vertical load intensity is 1, the volume constraint is 40%, the structure is divided into 100 elements, and the objective function Topology optimization for minimizing strain energy.

[0061] The specific implementation method is:

[0062] Step 1: According to the given boundary conditions and loads, define the initial design domain, and divide the finite element mesh discretization design domain.

[0063] Step 2: Set calculation parameters: PI th =0.347, penalty coefficient d=0.01, state gene string n=4, selection probability q=0.5, hybridization rate P c =0.1, variation rate P m =1.

[0064] Step 3: Perform finite eleme...

Embodiment 2

[0073] Embodiment 2: Take a simply supported beam bearing three points as an example.

[0074] For example Figure 4 The shown three-point loaded simply supported beam was subjected to topology optimization. The simply supported beam has a span of 200mm, a height of 100mm, and a thickness of 5mm. Three concentrated loads P=10kN act on 1 / 4, 1 / 2, and 3 / 4 of the beam span at the same time. The elastic modulus E=207Gpa, Poisson’s ratio ν = 0.3. Divide into 5000 units (2mm×2mm). P.I. th The value is set to 1 to ensure that the results after topology optimization are better than the initial design domain. Penalty coefficient d=0.01.

[0075] Reference 2 for other calculation parameters, set as: state gene string n=2, selection probability q=0.5, hybridization rate P c =0.2, variation rate P m = 0.8. When the volume removal rate is 85%, the GESO algorithm in Reference 2 has a non-optimized solution, and some important units are mistakenly deleted in a certain iteration, as sh...

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Abstract

The invention relates to a genetic evolution topological optimization improvement method, and belongs to the technical field of topological optimization. The punishment gene is added to the chromosome, and the sensitivity is reduced and the removal probability of high error units is computed so as to avoid emergence of non-optimal solutions. The change of the performance index PI is monitored in the iterative process. When the PI is lower than the preset threshold value Pith, removal of the selected units is stopped and the units are punished and the selection probability is enabled to be reduced, and then reaction of selection, mutation and crossover operators is performed to generate new units required to be removed to perform iterative computation. Mistaken deleting of units caused by high computation error of the unit sensitivity in the genetic evolution topological optimization algorithm can be avoided, accidental removal of certain important units in the probability removal process can also be avoided and emergence of the non-optimal solutions can be avoided so that the computation stability of the genetic evolution topological optimization algorithm can be enhanced. The genetic evolution topological optimization improvement method can be widely applied to the field of topological optimization.

Description

technical field [0001] The invention relates to an improved method for genetic evolution topology optimization, which belongs to the technical field of topology optimization. Background technique [0002] Topology optimization is to obtain the best topological shape of the structure that satisfies all constraints in the field of initial design, which belongs to the category of structure selection and plays a decisive role in saving costs and improving the efficiency of material use. Topology optimization is a research field that starts late but develops rapidly. It involves mathematics, mechanics, physics and computer science. It is of great significance to the construction industry and manufacturing industry, especially automobiles and aerospace. Fields also play an important role. [0003] Progressive structure optimization (ESO) is one of the mainstream topology optimization methods, which is widely used because of its flexible solution and high computational efficiency....

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/12
CPCG06N3/126
Inventor 张春巍崔楠楠贾布裕余晓琳颜全胜杨铮
Owner QINGDAO TECHNOLOGICAL UNIVERSITY
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