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Scatterer three-dimensional finite element mesh optimization method based on neural network

A technology of neural network and optimization method, applied in the field of grid, can solve the problem of low calculation accuracy of finite element model, and achieve the effect of improving calculation accuracy

Pending Publication Date: 2021-11-30
XIAN CETC XIDIAN UNIV RADAR TECH COLLABORATIVE INNOVATION INST CO LTD +1
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[0004] The purpose of the present invention is to overcome the deficiencies in the above-mentioned prior art, and propose a three-dimensional finite element grid optimization method for scatterers based on neural networks, which is used to solve the problem of low calculation accuracy of the subdivided finite element model existing in the prior art. technical problem

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  • Scatterer three-dimensional finite element mesh optimization method based on neural network
  • Scatterer three-dimensional finite element mesh optimization method based on neural network
  • Scatterer three-dimensional finite element mesh optimization method based on neural network

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[0031] In order to make the purpose, technical solutions and advantages of the present invention clearer, the present invention will be described in further detail below in conjunction with the accompanying drawings and specific embodiments:

[0032] Refer to attached figure 1 , the present invention comprises the following steps:

[0033] (1) Obtain training sample set and test sample set:

[0034] (1a) Use electromagnetic simulation software to build a 3D model of the scatterer, and perform finite element meshing on the 3D model of the scatterer through C groups of different meshing features consisting of meshing sizes and mesh transition factors points, get C different 3D finite element mesh data files Mesh={Mesh 1 ,Mesh 2 ,...,Mesh c ,...,Mesh C}, where, C≥200, Mesh c Indicates the cth finite element grid data file;

[0035] In this embodiment, the selected scatterer is a metal ball with a radius of 300 mm, and C=1000.

[0036] (1b) Extract each 3D finite element g...

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Abstract

The invention provides a scatterer three-dimensional finite element mesh optimization method based on a neural network. The method comprises the implementation steps: obtaining a training sample set and a test sample set; establishing a mapping relation from the A-dimensional grid characteristic variable to a far-field radar cross section root-mean-square error by using a neural network; solving an optimal grid characteristic variable value by adopting a differential evolution algorithm; and obtaining an optimization result of the scatterer three-dimensional finite element mesh. According to the method, a neural network is utilized to establish a mapping relation from an A-dimensional grid characteristic variable to a far-field radar cross section root-mean-square error, and then the optimal value of the A-dimensional grid characteristic variable is solved by taking reduction of the far-field radar cross section root-mean-square error as a target; and the three-dimensional finite element mesh of the scatterer is optimized through a node insertion or node movement method, so that the calculation precision of the three-dimensional finite element model of the scatterer is improved.

Description

technical field [0001] The invention belongs to the grid technical field, and relates to a three-dimensional finite element grid optimization method for a scatterer, in particular to a neural network-based three-dimensional finite element grid optimization method for a scatterer. Background technique [0002] With the rapid development and popularization of computer technology, the finite element method has rapidly expanded from the strength analysis and calculation of engineering structures to almost all scientific and technological fields, and has become a widely used and efficient numerical analysis method. Early finite element analysis research focused on deriving new high-efficiency solution methods and high-precision elements. With the gradual improvement of numerical analysis methods and the rapid improvement of computer computing speed, the time for the entire computing system to solve and calculate is getting shorter and shorter, but the problems of data preparation...

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Application Information

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IPC IPC(8): G06F30/23G06F30/27G06K9/62
CPCG06F30/27G06F30/23G06F18/214
Inventor 焦永昌于洪飞翁子彬张玉朱海明
Owner XIAN CETC XIDIAN UNIV RADAR TECH COLLABORATIVE INNOVATION INST CO LTD
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