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Influences of nonassociated flow rules on three-dimensional seismic stability of loaded slopes 被引量:3
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作者 N.GANJIAN F.ASKARI O.FARZANEH 《Journal of Central South University》 SCIE EI CAS 2010年第3期603-611,共9页
The influences of soil dilatancy angle on three-dimensional (3D) seismic stability of locally-loaded slopes in nonassociated flow rule materials were investigated using a new rotational collapse mechanism and quasi-... The influences of soil dilatancy angle on three-dimensional (3D) seismic stability of locally-loaded slopes in nonassociated flow rule materials were investigated using a new rotational collapse mechanism and quasi-static coefficient concept. Extended Bishop method and Boussinesq theorem were employed to establish the stress distribution along the rupture surfaces that are required to obtain the rate of internal energy dissipation for the nonassociated flow rule materials in rotational collapse mechanisms. Good agreement was observed by comparing the current results with those obtained using the translational or rotational mechanisms and numerical finite difference method. The results indicate that the seismic stability of slopes reduces by decreasing the dilatancy angle for nonassociated flow rule materials. The amount of the mentioned decrease is more significant in the case of mild slopes in frictional soils. A nearly infinite slope under local loading, whether its critical failure surface is 2D or 3D, not only depends on the magnitude of the external load, but also depends on the dilataney angle of soil and the coefficient of seismic load. 展开更多
关键词 3D slope stability failure analysis nonassociated flow rule
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共溶剂-SC CO_2中固体溶解度的小波神经网络关联与预测
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作者 胡德栋 王威强 《计算机与应用化学》 CAS CSCD 北大核心 2009年第1期101-104,共4页
为了更好地关联和预测共溶剂-超临界(SC)CO2中固体的溶解度,本文采用经局部动量法和自适应理论优化的小波神经网络模型(WNN),分别以共溶剂的溶剂参数α、β、π^*和溶解度参数δd、δp、δh为影响因素,关联了4种共溶剂-SC CO2... 为了更好地关联和预测共溶剂-超临界(SC)CO2中固体的溶解度,本文采用经局部动量法和自适应理论优化的小波神经网络模型(WNN),分别以共溶剂的溶剂参数α、β、π^*和溶解度参数δd、δp、δh为影响因素,关联了4种共溶剂-SC CO2体系中萘普生的溶解度,以预测其在乙醇-SC CO2中的溶解度。其关联误差AARD分别为1.94%和2.12%;其预测误差AARD分别为8.14%和30.32%。以上结果表明共溶剂的溶剂参数α、β、π^*是共溶剂-SC CO2中固体溶解度的主要影响因素;优化的WNN模型能较好地关联和预测共溶剂-SC CO2中固体的溶解度。 展开更多
关键词 小波神经网络 局部动量法 自适应算 共溶剂 固体溶解度 关联 预测
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