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Application of artificial neural network for calculating anisotropic friction angle of sands and effect on slope stability 被引量:2
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作者 hamed farshbaf aghajani Hossein Salehzadeh Habib Shahnazari 《Journal of Central South University》 SCIE EI CAS CSCD 2015年第5期1878-1891,共14页
The anisotropy effect is one of the most prominent phenomena in soil mechanics. Although many experimental programs have investigated anisotropy in sand, a computational procedure for determining anisotropy is lacking... The anisotropy effect is one of the most prominent phenomena in soil mechanics. Although many experimental programs have investigated anisotropy in sand, a computational procedure for determining anisotropy is lacking. Thus, this work aims to develop a procedure for connecting the sand friction angle and the loading orientation. All principal stress rotation tests in the literatures were processed via an artificial neural network. Then, with sensitivity analysis, the effect of intrinsic soil properties,consolidation history, and test sample characteristics on enhancing anisotropy was examined. The results imply that decreasing the grain size of the soil increases the effect of anisotropy on soil shear strength. In addition, increasing the angularity of grains increases the anisotropy effect in the sample. The stability of a sandy slope was also examined by considering the anisotropy in shear strength parameters. If the anisotropy effect is neglected, slope safety is overestimated by 5%-25%. This deviation is more apparent in flatter slopes than in steeper ones. However, the critical slip surface in the most slopes is the same in isotropic and anisotropic conditions. 展开更多
关键词 ANISOTROPY artificial neural network SAND principal stress rotation slope stability
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A new procedure for determining dry density of mixed soil containing oversize gravel
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作者 hamed farshbaf aghajani Masoud Ghodrati YENGEJEH +1 位作者 Amirmohammad KARIMZADEH Hossein SOLTANI-JIGHEH 《Journal of Central South University》 SCIE EI CAS CSCD 2018年第12期2841-2856,共16页
This paper presents a novel computational procedure for the maximum dry density of mixed soils containing oversize particles.At first,the large-scale compaction test data for mixed soils are analyzed by an artificial ... This paper presents a novel computational procedure for the maximum dry density of mixed soils containing oversize particles.At first,the large-scale compaction test data for mixed soils are analyzed by an artificial neural network to determine the main factors affecting the compaction.These factors are then imposed on a genetic programming method and a new mathematical equation emerges.The new equation has more conformity with the experimental data in comparison with the previous correction methods.Besides,the mixed soil dry density is associated with most base soil and oversize fraction specifications.With regard to the sensitivity analyses,if the mixed soil contains high percentages of oversize fraction,the mixed soil composition is governed by the specification of oversized grains,such as specific gravity and the maximum grain size and by increasing these factors,the mixed soil dry density is increased.In mixed soil with a low content of oversize,the base soil specification mainly controls the compaction behavior of mixed soil.Furthermore,if the base soil is inherently compacted with greater dry density,adding the oversize slightly improves the mixed soil dry density.In contrast,adding oversized grains to the base soil with a lower dry density produces a mixed soil with greater dry density.By increasing the maximum grain size difference between the oversize fraction and base soil,the dry density of mixed soil is enhanced. 展开更多
关键词 mixed soil oversize COMPACTION genetic programming artificial neural network
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