• 全国中文核心期刊
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ZHANG Xiao-ling, LI Xiu-yu, DU Xiu-li. Hyperbolic model for estimating liquefaction potential of sand considering the influences of fine grains[J]. Chinese Journal of Geotechnical Engineering, 2021, 43(3): 448-455. DOI: 10.11779/CJGE202103007
Citation: ZHANG Xiao-ling, LI Xiu-yu, DU Xiu-li. Hyperbolic model for estimating liquefaction potential of sand considering the influences of fine grains[J]. Chinese Journal of Geotechnical Engineering, 2021, 43(3): 448-455. DOI: 10.11779/CJGE202103007

Hyperbolic model for estimating liquefaction potential of sand considering the influences of fine grains

  • In the evaluation models for seismic liquefaction of sand, most models are proposed for the liquefaction potential of clean sand, and the influence of fine grain content is often ignored. However, the fine grain content is an important factor of soil liquefaction, and it will result in the conservative result if neglected. Based on the previous liquefaction data in the mainland of China and the standard penetration test data of Chi-Chi earthquake in Taiwan of China, the modified coefficient of influence term of fine grains is proposed, and the hyperbolic model of liquefaction evaluation for fine-grained sand is established. The proposed model is applied to the data for estimating, and its success rate is discussed. Finally, the model is examined by the large seismic liquefaction data set, and its validity and applicability are verified by comparing with the standard method. The results show the proposed modified liquefaction hyperbolic model is applicable to the liquefaction evaluation of soils in the areas with different intensities, and can effectively estimate liquefaction of sand within the soil depth of 20 m. The proposed correction coefficient of fine grain content in sand can make up for the limitation of the application range of the hyperbolic model for liquefaction evaluation, and on the basis of keeping the evaluation success rate for liquefaction samples, the evaluation success rate for non-liquefaction samples is improved.
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