A Constitutive Model of Grassroots-reinforced Soil Based on BP Neural Network
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    Abstract:

    Laboratory triaxial tests were carried out to obtain the stress-strain relationship of grassroots-reinforced soil(GRS).BP neural network constitutive models of soil and GRS reinforcement in mixing were established based on test data.The result from comparing predicted values and measured values shows that the network constitutive model has good fitting precision and good generalization ability and can fully describe the non-linear relationship of geo-materials. The shear strength indexes of GRS fitted by Mohr-Columb criterion may be used to analyze the mechanism of GRS protection of slope.The research results are of importance for establishing the constitutive model of GRS and understanding the mechanism of vegetation protection of slope.

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陈昌富,彭钊,刘怀星.基于BP神经网络的草根加筋土本构模型[J].水土保持通报英文版,2008,(3):93-96

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History
  • Received:November 15,2007
  • Revised:January 09,2008
  • Adopted:
  • Online: November 26,2014
  • Published: