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Application of Artificial Neural Network for Identification of Parameters of a Constitutive Law for Soils

机译:人工神经网络在土壤本构关系参数辨识中的应用

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摘要

A common problem of excavation machinery based on mechanical actions is the unknown interaction of the cutting tools with geological settings. This interaction determines for different soils a different wear and consequently different economical costs for the excavation. We apply a strategy for soil modelling which is based on discretization of the continuum with rigid disks and suitable contact models and concentrate at contact level the real mechanical behaviour of the soil. In order to carry out the proposed strategy a "macro" and a "micro" level are established. In this paper an application of Artificial Neural Network (ANN) for identification of the parameters of the contact constitutive law is shown. The ANN is first trained using the theoretical results obtained from the developed numerical model. Results of some numerical tests concerning the choice of the proper topology of ANN, the best training set and the sensitivity of the identified parameters are shown.
机译:基于机械作用的挖掘机械的常见问题是切削工具与地质环境之间的未知相互作用。这种相互作用为不同的土壤确定了不同的磨损,因此确定了不同的开挖经济成本。我们将土壤建模应用一种策略,该策略基于具有刚性圆盘的连续体的离散化和合适的接触模型,并在接触层面集中土壤的真实机械行为。为了执行所提出的策略,建立了“宏观”和“微观”水平。在本文中,应用了人工神经网络(ANN)来识别接触本构定律的参数。首先使用从开发的数值模型获得的理论结果来训练ANN。显示了一些有关选择ANN的正确拓​​扑,最佳训练集和所识别参数的敏感性的数值测试结果。

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