This paper presents an artificial neural network（ANN）-based response surface method that can be used to predict the failure probability of c-φslopes with spatially variable soil.In this method,the Latin hypercube s...This paper presents an artificial neural network（ANN）-based response surface method that can be used to predict the failure probability of c-φslopes with spatially variable soil.In this method,the Latin hypercube sampling technique is adopted to generate input datasets for establishing an ANN model;the random finite element method is then utilized to calculate the corresponding output datasets considering the spatial variability of soil properties;and finally,an ANN model is trained to construct the response surface of failure probability and obtain an approximate function that incorporates the relevant variables.The results of the illustrated example indicate that the proposed method provides credible and accurate estimations of failure probability.As a result,the obtained approximate function can be used as an alternative to the specific analysis process in c-φslope reliability analyses.展开更多
This study presents a calibration process of three-dimensional particle flow code(PFC3D)simulation of intact and fissured granite samples.First,laboratory stressestrain response from triaxial testing of intact and fis...This study presents a calibration process of three-dimensional particle flow code(PFC3D)simulation of intact and fissured granite samples.First,laboratory stressestrain response from triaxial testing of intact and fissured granite samples is recalled.Then,PFC3D is introduced,with focus on the bonded particle models(BPM).After that,we present previous studies where intact rock is simulated by means of flatjoint approaches,and how improved accuracy was gained with the help of parametric studies.Then,models of the pre-fissured rock specimens were generated,including modeled fissures in the form of“smooth joint”type contacts.Finally,triaxial testing simulations of 1 t 2 and 2 t 3 jointed rock specimens were performed.Results show that both elastic behavior and the peak strength levels are closely matched,without any additional fine tuning of micro-mechanical parameters.Concerning the postfailure behavior,models reproduce the trends of decreasing dilation with increasing confinement and plasticity.However,the dilation values simulated are larger than those observed in practice.This is attributed to the difficulty in modeling some phenomena of fissured rock behaviors,such as rock piece corner crushing with dust production and interactions between newly formed shear bands or axial splitting cracks with pre-existing joints.展开更多
基金financially supported by the National Natural Science Foundation of China(Grant No.51278217)
文摘This paper presents an artificial neural network（ANN）-based response surface method that can be used to predict the failure probability of c-φslopes with spatially variable soil.In this method,the Latin hypercube sampling technique is adopted to generate input datasets for establishing an ANN model;the random finite element method is then utilized to calculate the corresponding output datasets considering the spatial variability of soil properties;and finally,an ANN model is trained to construct the response surface of failure probability and obtain an approximate function that incorporates the relevant variables.The results of the illustrated example indicate that the proposed method provides credible and accurate estimations of failure probability.As a result,the obtained approximate function can be used as an alternative to the specific analysis process in c-φslope reliability analyses.
基金The University of Vigo is acknowledged for financing part of the first author’s PhD studiesthe Spanish Ministry of Economy and Competitiveness for funding of the project‘Deepening on the behaviour of rock masses:Scale effects on the stressestrain response of fissured rock samples with particular emphasis on post-failure’,awarded under Contract Reference No.RTI2018-093563-B-I00partially financed by means of European Regional Development Funds from the European Union(EU)。
文摘This study presents a calibration process of three-dimensional particle flow code(PFC3D)simulation of intact and fissured granite samples.First,laboratory stressestrain response from triaxial testing of intact and fissured granite samples is recalled.Then,PFC3D is introduced,with focus on the bonded particle models(BPM).After that,we present previous studies where intact rock is simulated by means of flatjoint approaches,and how improved accuracy was gained with the help of parametric studies.Then,models of the pre-fissured rock specimens were generated,including modeled fissures in the form of“smooth joint”type contacts.Finally,triaxial testing simulations of 1 t 2 and 2 t 3 jointed rock specimens were performed.Results show that both elastic behavior and the peak strength levels are closely matched,without any additional fine tuning of micro-mechanical parameters.Concerning the postfailure behavior,models reproduce the trends of decreasing dilation with increasing confinement and plasticity.However,the dilation values simulated are larger than those observed in practice.This is attributed to the difficulty in modeling some phenomena of fissured rock behaviors,such as rock piece corner crushing with dust production and interactions between newly formed shear bands or axial splitting cracks with pre-existing joints.
