Method for predicting dynamic mechanical property of material based on BP artificial neural network

An artificial neural network and dynamic mechanics technology is applied in the field of material dynamic and mechanical properties prediction based on BP artificial neural network to achieve the effects of improving simulation accuracy, improving efficiency and reducing test costs.

Active Publication Date: 2015-11-25
CHINA AUTOMOTIVE ENG RES INST
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In addition, through the mechanical characteristics of the material under several strain rate conditions, the mechanical performance data of the material under any strain rate condition can be obtaine...

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  • Method for predicting dynamic mechanical property of material based on BP artificial neural network
  • Method for predicting dynamic mechanical property of material based on BP artificial neural network
  • Method for predicting dynamic mechanical property of material based on BP artificial neural network

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[0042] Embodiments of the present invention are described in detail below, examples of which are shown in the drawings, wherein the same or similar reference numerals designate the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the figures are exemplary only for explaining the present invention and should not be construed as limiting the present invention.

[0043]In describing the present invention, it should be understood that the terms "longitudinal", "transverse", "upper", "lower", "front", "rear", "left", "right", "vertical", The orientation or positional relationship indicated by "horizontal", "top", "bottom", "inner", "outer", etc. are based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than Nothing indicating or implying that a referenced device or eleme...

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Abstract

The invention relates to a method for predicting the dynamic mechanical property of a material based on a BP artificial neural network, aims at achieving the prediction of the dynamic mechanical property of the material through the BP artificial neural network, and belongs to the testing field of the dynamic mechanical property of the material. The principle of the method comprises the steps: collecting stress-strain data through employing a high-speed tensile test method, and obtaining a training sample set after normalization preprocessing; building a BP artificial neural network model through designing an input layer, a hidden layer and an output layer, and selecting a proper transfer function, a training function, and a learning function; carrying out the iterative training of the BP artificial neural network through employing the training sample set, and obtaining an optimal prediction network. The above prediction method can be used for the prediction of the dynamic mechanical property of the material, can achieve the quick prediction of a flow curve of the material at different strain rates in a short time, and can provide enough sample data for automobile safety simulation.

Description

technical field [0001] The invention belongs to the field of testing the dynamic mechanical properties of materials, and in particular relates to a method for predicting the dynamic mechanical properties of materials based on a BP artificial neural network. Background technique [0002] With the increasing number of automobiles, automobile safety accidents have increased significantly, and the passive safety technology of automobiles has attracted more and more attention. Finite element simulation technology is one of the main ways to study the passive safety of automobiles. In order to ensure the accuracy and validity of the simulation, in addition to strict requirements on the simulation geometric model, contact boundary conditions and actual collision conditions, an accurate material model should also be established. For crash simulation analysis, the material model mainly involves the dynamic mechanical properties of materials under different strain rate conditions. ...

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Application Information

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IPC IPC(8): G06N3/02
Inventor 周佳万鑫铭张钧萍赵岩李阳
Owner CHINA AUTOMOTIVE ENG RES INST
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