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The ANN application in FEM modeling of mechanical properties of Al-Si alloy

机译:人工神经网络在铝硅合金力学性能有限元建模中的应用

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摘要

Artificial neural network (ANN) is a nonlinear dynamic computational system suitable for simulations which are hard to be described by physical models where, rather than relying on a number of predetermined assumptions, data is used to form the model. In order to predict the mechanical properties of A356 including yield stress, ultimate tensile strength and elongation percentage, a relatively new approach that uses artificial neural network and finite element technique is presented which combines mechanical properties data in the form of experimental and simulated solidification conditions. It was observed that predictions of this study are consistent with experimental measurements for A356 alloy. The results of this research were also used for solidification codes of SUT CAST software.
机译:人工神经网络(ANN)是一种非线性动态计算系统,适用于难以用物理模型描述的模拟,在该模型中,不是依赖于多个预定假设,而是使用数据来形成模型。为了预测A356的机械性能,包括屈服应力,极限抗拉强度和伸长率,提出了一种相对较新的方法,该方法使用人工神经网络和有限元技术,以实验和模拟凝固条件的形式结合了机械性能数据。据观察,这项研究的预测与A356合金的实验测量结果一致。这项研究的结果还用于SUT CAST软件的固化代码。

著录项

  • 来源
    《Applied Mathematical Modelling》 |2011年第12期|p.5707-5713|共7页
  • 作者单位

    Materials and Energy Research Center (MERC), Tehran, Iran;

    School of Metallurgy and Materials Engineering, University of Tehran, Tehran, Iran;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    AI; ANN; FEM;

    机译:AI;人工神经网络有限元法;
  • 入库时间 2022-08-18 03:00:05

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