Ground improvement has been used on many construction sites to densify granular materials, in other word, to improve soil properties and reduce potential settlement. This work presents a case study of ground improveme...Ground improvement has been used on many construction sites to densify granular materials, in other word, to improve soil properties and reduce potential settlement. This work presents a case study of ground improvement using rapid impact compaction （RIC）. The research site comprises the construction of workshop and depots as part of railway development project at Batu Gajah-Ipoh, Malaysia. In-situ testing results show that the subsurface soil comprises mainly of sand and silty sand through the investigated depth extended to 10 m. Groundwater is approximately 0.5 m below the ground surface. Evaluation of improvement was based on the results of pre- and post-improvement cone penetration test （CPT）. Interpretation software has been used to infer soil properties. Load test was conducted to estimate soil settlement. It is found that the technique succeeds in improving soil properties namely the relative density increases from 45% to 70%, the friction angle of soil is increased by an average of 3°, and the soil settlement is reduced by 50%： The technique succeeds in improving soil properties to approximately 5.0 m in depth depending on soil uniformity with depth.展开更多
Discernment of seismic soil liquefaction is a complex and non-linear procedure that is affected by diversified factors of uncertainties and complexity.The Bayesian belief network(BBN)is an effective tool to present a ...Discernment of seismic soil liquefaction is a complex and non-linear procedure that is affected by diversified factors of uncertainties and complexity.The Bayesian belief network(BBN)is an effective tool to present a suitable framework to handle insights into such uncertainties and cause–effect relationships.The intention of this study is to use a hybrid approach methodology for the development of BBN model based on cone penetration test(CPT)case history records to evaluate seismic soil liquefaction potential.In this hybrid approach,naive model is developed initially only by an interpretive structural modeling(ISM)technique using domain knowledge(DK).Subsequently,some useful information about the naive model are embedded as DK in the K2 algorithm to develop a BBN-K2 and DK model.The results of the BBN models are compared and validated with the available artificial neural network(ANN)and C4.5 decision tree(DT)models and found that the BBN model developed by hybrid approach showed compatible and promising results for liquefaction potential assessment.The BBN model developed by hybrid approach provides a viable tool for geotechnical engineers to assess sites conditions susceptible to seismic soil liquefaction.This study also presents sensitivity analysis of the BBN model based on hybrid approach and the most probable explanation of liquefied sites,owing to know the most likely scenario of the liquefaction phenomenon.展开更多
目前国内外已有的液化判别方法大多依据易液化土层自身的原位测试数据静态地计算场地液化势,而忽略了在实际地震动作用下,由于土层结构和土体物理力学参数不均匀分布的影响,孔隙水压力分布会发生动态变化,进而导致测试点液化势的变化。...目前国内外已有的液化判别方法大多依据易液化土层自身的原位测试数据静态地计算场地液化势,而忽略了在实际地震动作用下,由于土层结构和土体物理力学参数不均匀分布的影响,孔隙水压力分布会发生动态变化,进而导致测试点液化势的变化。文中以2010—2011年间新西兰的坎特伯雷地震序列中的液化场地为例,基于新西兰岩土工程数据库提供的钻孔和静力触探资料建立典型液化场地凯什米尔高中(Cashmere High School,CMHS)的二维地质剖面,采用Flac软件对相应的场地模型进行数值模拟,研究土层结构和物理力学参数对场地砂土液化的影响机制。结果表明:砂质砾石层良好的渗透性可以有效地降低相邻液化砂土层的孔压累积,降低了砂土层的液化能力;黏土、粉质黏土等透水性差的土层有利于相邻液化砂土的孔压累积,促进了砂土液化的发生。因此,在砂土液化判别的方法中需要考虑液化土壤相邻土层的结构特征、渗透性等影响因素。展开更多
基金Projects(RG148/12AET,RG086/10AET) supported by the UMRG,MalaysiaProject(PS05812010B) supported by the Post Graduate Research Fund,Malaysia
文摘Ground improvement has been used on many construction sites to densify granular materials, in other word, to improve soil properties and reduce potential settlement. This work presents a case study of ground improvement using rapid impact compaction （RIC）. The research site comprises the construction of workshop and depots as part of railway development project at Batu Gajah-Ipoh, Malaysia. In-situ testing results show that the subsurface soil comprises mainly of sand and silty sand through the investigated depth extended to 10 m. Groundwater is approximately 0.5 m below the ground surface. Evaluation of improvement was based on the results of pre- and post-improvement cone penetration test （CPT）. Interpretation software has been used to infer soil properties. Load test was conducted to estimate soil settlement. It is found that the technique succeeds in improving soil properties namely the relative density increases from 45% to 70%, the friction angle of soil is increased by an average of 3°, and the soil settlement is reduced by 50%： The technique succeeds in improving soil properties to approximately 5.0 m in depth depending on soil uniformity with depth.
基金Projects(2016YFE0200100,2018YFC1505300-5.3)supported by the National Key Research&Development Plan of ChinaProject(51639002)supported by the Key Program of National Natural Science Foundation of China
文摘Discernment of seismic soil liquefaction is a complex and non-linear procedure that is affected by diversified factors of uncertainties and complexity.The Bayesian belief network(BBN)is an effective tool to present a suitable framework to handle insights into such uncertainties and cause–effect relationships.The intention of this study is to use a hybrid approach methodology for the development of BBN model based on cone penetration test(CPT)case history records to evaluate seismic soil liquefaction potential.In this hybrid approach,naive model is developed initially only by an interpretive structural modeling(ISM)technique using domain knowledge(DK).Subsequently,some useful information about the naive model are embedded as DK in the K2 algorithm to develop a BBN-K2 and DK model.The results of the BBN models are compared and validated with the available artificial neural network(ANN)and C4.5 decision tree(DT)models and found that the BBN model developed by hybrid approach showed compatible and promising results for liquefaction potential assessment.The BBN model developed by hybrid approach provides a viable tool for geotechnical engineers to assess sites conditions susceptible to seismic soil liquefaction.This study also presents sensitivity analysis of the BBN model based on hybrid approach and the most probable explanation of liquefied sites,owing to know the most likely scenario of the liquefaction phenomenon.
文摘目前国内外已有的液化判别方法大多依据易液化土层自身的原位测试数据静态地计算场地液化势,而忽略了在实际地震动作用下,由于土层结构和土体物理力学参数不均匀分布的影响,孔隙水压力分布会发生动态变化,进而导致测试点液化势的变化。文中以2010—2011年间新西兰的坎特伯雷地震序列中的液化场地为例,基于新西兰岩土工程数据库提供的钻孔和静力触探资料建立典型液化场地凯什米尔高中(Cashmere High School,CMHS)的二维地质剖面,采用Flac软件对相应的场地模型进行数值模拟,研究土层结构和物理力学参数对场地砂土液化的影响机制。结果表明:砂质砾石层良好的渗透性可以有效地降低相邻液化砂土层的孔压累积,降低了砂土层的液化能力;黏土、粉质黏土等透水性差的土层有利于相邻液化砂土的孔压累积,促进了砂土液化的发生。因此,在砂土液化判别的方法中需要考虑液化土壤相邻土层的结构特征、渗透性等影响因素。
