Employing an ideal elasto-plastic model,the typically used strength reduction method reduced the strength of all soil elements of a slope.Therefore,this method was called the global strength reduction method(GSRM).How...Employing an ideal elasto-plastic model,the typically used strength reduction method reduced the strength of all soil elements of a slope.Therefore,this method was called the global strength reduction method(GSRM).However,the deformation field obtained by GSRM could not reflect the real deformation of a slope when the slope became unstable.For most slopes,failure occurs once the strength of some regional soil is sufficiently weakened; thus,the local strength reduction method(LSRM)was proposed to analyze slope stability.In contrast with GSRM,LSRM only reduces the strength of local soil,while the strength of other soil remains unchanged.Therefore,deformation by LSRM is more reasonable than that by GSRM.In addition,the accuracy of the slope's deformation depends on the constitutive model to a large degree,and the variable-modulus elasto-plastic model was thus adopted.This constitutive model was an improvement of the Duncan–Chang model,which modified soil's deformation modulus according to stress level,and it thus better reflected the plastic feature of soil.Most importantly,the parameters of the variable-modulus elasto-plastic model could be determined through in-situ tests,and parameters determination by plate loading test and pressuremeter test were introduced.Therefore,it is easy to put this model into practice.Finally,LSRM and the variable-modulus elasto-plastic model were used to analyze Egongdai ancient landslide.Safety factor,deformation field,and optimal reinforcement measures for Egongdai ancient landslide were obtained based on the proposed method.展开更多
A step-by-step load was utilized to mimic the load history of the backfill column in the in-situ curing process.The inner damage of the specimen during curing and uniaxial compressive testing was monitored by electric...A step-by-step load was utilized to mimic the load history of the backfill column in the in-situ curing process.The inner damage of the specimen during curing and uniaxial compressive testing was monitored by electrical resistivity and ultrasonic equipment.Results show that:1)Uniaxial compressive strength(UCS)and elastic modulus(EM)of the samples curing under pressure are higher than those of the control samples without pressure,ranging in ratio from 0.5%to 20.2%and 7.1%to 52.3%,respectively,and are influenced by the initial loading age(ILA)and stress strength ratio(SSR).The SSR during curing should not exceed 80%.2)The earlier the ILA is,the higher the total strain becomes.The higher the SSR applies,the larger the total strain gets.The creep strain increases with the increase of SSR and can be described by Burger’s viscoelastic creep model.When SSR is less than 80%,the earlier the ILA is,the smaller the creep strain becomes after the last step-loading.3)The stability of the early age backfill column under pressure can be monitored based on the change of ultrasonic pulse velocity(UPV)and electrical resistivity.展开更多
Deformation modulus is the important parameter in stability analysis of tunnels, dams and mining struc- tures. In this paper, two predictive models including Mamdani fuzzy system （MFS） and multivariable regression a...Deformation modulus is the important parameter in stability analysis of tunnels, dams and mining struc- tures. In this paper, two predictive models including Mamdani fuzzy system （MFS） and multivariable regression analysis （MVRA） were developed to predict deformation modulus based on data obtained from dilatometer tests carried out in Bakhtiary dam site and additional data collected from longwall coal mines. Models inputs were considered to be rock quality designation, overburden height, weathering, unconfined compressive strength, bedding inclination to core axis, joint roughness coefficient and fill thickness. To control the models performance, calculating indices such as root mean square error （RMSE）, variance account for （VAF） and determination coefficient （R^2） were used. The MFS results show the significant prediction accuracy along with high performance compared to MVRA results. Finally, the sensitivity analysis of MFS results shows that the most and the least effective parameters on deformation modulus are weatherin~ and overburden height, respectively.展开更多
基金Project([2005]205)supported by the Science and Technology Planning Project of Water Resources Department of Guangdong Province,ChinaProject(2012-7)supported by Guangdong Bureau of Highway Administration,ChinaProject(2012210020203)supported by the Fundamental Research Funds for the Central Universities,China
文摘Employing an ideal elasto-plastic model,the typically used strength reduction method reduced the strength of all soil elements of a slope.Therefore,this method was called the global strength reduction method(GSRM).However,the deformation field obtained by GSRM could not reflect the real deformation of a slope when the slope became unstable.For most slopes,failure occurs once the strength of some regional soil is sufficiently weakened; thus,the local strength reduction method(LSRM)was proposed to analyze slope stability.In contrast with GSRM,LSRM only reduces the strength of local soil,while the strength of other soil remains unchanged.Therefore,deformation by LSRM is more reasonable than that by GSRM.In addition,the accuracy of the slope's deformation depends on the constitutive model to a large degree,and the variable-modulus elasto-plastic model was thus adopted.This constitutive model was an improvement of the Duncan–Chang model,which modified soil's deformation modulus according to stress level,and it thus better reflected the plastic feature of soil.Most importantly,the parameters of the variable-modulus elasto-plastic model could be determined through in-situ tests,and parameters determination by plate loading test and pressuremeter test were introduced.Therefore,it is easy to put this model into practice.Finally,LSRM and the variable-modulus elasto-plastic model were used to analyze Egongdai ancient landslide.Safety factor,deformation field,and optimal reinforcement measures for Egongdai ancient landslide were obtained based on the proposed method.
基金Project(51974192)supported by the National Natural Science Foundation of ChinaProject(201803D31044)supported by the Program for Key Research Project of Shanxi Province in the Field of Social Development,ChinaProject(201801D121092)supported by the Applied Basic Research Project of Shanxi Province,China。
文摘A step-by-step load was utilized to mimic the load history of the backfill column in the in-situ curing process.The inner damage of the specimen during curing and uniaxial compressive testing was monitored by electrical resistivity and ultrasonic equipment.Results show that:1)Uniaxial compressive strength(UCS)and elastic modulus(EM)of the samples curing under pressure are higher than those of the control samples without pressure,ranging in ratio from 0.5%to 20.2%and 7.1%to 52.3%,respectively,and are influenced by the initial loading age(ILA)and stress strength ratio(SSR).The SSR during curing should not exceed 80%.2)The earlier the ILA is,the higher the total strain becomes.The higher the SSR applies,the larger the total strain gets.The creep strain increases with the increase of SSR and can be described by Burger’s viscoelastic creep model.When SSR is less than 80%,the earlier the ILA is,the smaller the creep strain becomes after the last step-loading.3)The stability of the early age backfill column under pressure can be monitored based on the change of ultrasonic pulse velocity(UPV)and electrical resistivity.
文摘Deformation modulus is the important parameter in stability analysis of tunnels, dams and mining struc- tures. In this paper, two predictive models including Mamdani fuzzy system （MFS） and multivariable regression analysis （MVRA） were developed to predict deformation modulus based on data obtained from dilatometer tests carried out in Bakhtiary dam site and additional data collected from longwall coal mines. Models inputs were considered to be rock quality designation, overburden height, weathering, unconfined compressive strength, bedding inclination to core axis, joint roughness coefficient and fill thickness. To control the models performance, calculating indices such as root mean square error （RMSE）, variance account for （VAF） and determination coefficient （R^2） were used. The MFS results show the significant prediction accuracy along with high performance compared to MVRA results. Finally, the sensitivity analysis of MFS results shows that the most and the least effective parameters on deformation modulus are weatherin~ and overburden height, respectively.
