A Constitutive Model of Grassroots-reinforced Soil Based on BP Neural Network
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A Constitutive Model of Grassroots-reinforced Soil Based on BP Neural Network
Bulletin of Soiland Water ConservationVol. 27, Issue 3, Pages: 93-96(2008)
作者机构:
湖南大学岩土工程研究所,湖南,长沙,410082
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Published:2008
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CHEN Chang-fu, PENG Zhao, LIU Huai-xing. A Constitutive Model of Grassroots-reinforced Soil Based on BP Neural Network[J]. Bulletin of Soiland Water Conservation, 2008, 27(3): 93-96.
DOI:
CHEN Chang-fu, PENG Zhao, LIU Huai-xing. A Constitutive Model of Grassroots-reinforced Soil Based on BP Neural Network[J]. Bulletin of Soiland Water Conservation, 2008, 27(3): 93-96.DOI:
A Constitutive Model of Grassroots-reinforced Soil Based on BP Neural Network
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.