The Experts below are selected from a list of 219 Experts worldwide ranked by ideXlab platform
Liu Zhu-ping - One of the best experts on this subject based on the ideXlab platform.
-
Reliability Assessment of Seismic Soil Liquefaction
Journal of Kunming University of Science and Technology, 2020Co-Authors: Liu Zhu-pingAbstract:Based on the Limit State Equation of blow count of SPT,the Monte Carlo reliability analysis method for seismic soil liquefaction is established,which refers to structure reliability analysis methods.The corresponding programmers for computing liquefaction probability are compiled with MATLAB7.0.The results of seismic soil liquefaction analysis for the Tangshan earthquake in 1976 are compared with the measurements and requirements of the building codes.The feasibility and accuracy of this method are validated and some meaningful results are obtained.
-
Reliability Analysis Method for Sandy Soil Liquefaction Based on Monte Carlo
Science Technology and Engineering, 2020Co-Authors: Liu Zhu-pingAbstract:Based on the Limit State Equation of blow count of SPT,Monte Carlo reliability analysis method for sandy soil liquefaction was established,which refers to structure reliability analysis method. The corresponding programmers for computing liquefaction probability are compiled with MATLAB7.0. The analysis results of sandy soil liquefaction are compared with the results of measurement and the code methods,which are obtained from the seismic data of Tangshan. The feasibility and accuracy of this method are validated and some meaningful results are obtained.
R. K. Bhasin - One of the best experts on this subject based on the ideXlab platform.
-
Probabilistic Stability Evaluation of Oppstadhornet Rock Slope, Norway
Rock Mechanics and Rock Engineering, 2008Co-Authors: H. S. B. Duzgun, R. K. BhasinAbstract:Probabilistic analyses provide rational means to treat the uncertainties associated with underlying parameters in a systematic manner. The stability of a 734-m-high jointed rock slope in the west of Norway, the Oppstadhornet rock slope, is investigated by using a probabilistic method. The first-order reliability method (FORM) is used for probabilistic modeling of the plane failure problem in the rock slope. The Barton–Bandis (BB) shear strength criterion is used for the Limit State Equation. The statistical distributions of the BB criterion parameters, for which comprehensive data were collected and statistically analyzed, are determined by using distribution fitting algorithms. The sensitivity of the FORM model for the BB criterion is also investigated. It is found that the model is most sensitive to the mean value of the residual friction angle ( ϕ _r) and least sensitive to the mean value of the slope angle ( β _f). It is also found that the standard deviation of joint compressive strength (JCS) causes the greatest difference in the reliability index, which has the least sensitivity to the change in the mean and standard deviation of joint roughness coefficient (JRC).
Lu Zhenzhou - One of the best experts on this subject based on the ideXlab platform.
-
Support Vector Machine response surface method based on fast Markov chain simulation
2009 IEEE International Conference on Intelligent Computing and Intelligent Systems, 2009Co-Authors: Yuan Xiukai, Lu Zhenzhou, Lu YuanboAbstract:The support vector machine (SVM) response surface method (RSM) is proposed on fast Markov chain simulation for the problem with implicit Limit State function usually encountered in engineering reliability analysis and design. In the proposed method, Markov chain is used to generate the samples in the important region of the Limit State function, and the SVM is employed to construct the response surface by use of these samples. Since Markov chain can adaptively simulate the samples in the important region, and the candidate State but not Markov State is used as the training samples for SVM, the proposed method can well approximate the Limit State Equation in the zone surrounding the design point, and can make full use of information provided by Markov chain simulation. In addition, the iterative strategy is adopted to improve the convergence speed of the failure probability. Moreover, the proposed method uses the SVM regression method to construct the response surface, which can automatically apply the structural risk minimization (SRM) inductive principle in approximating the Limit State Equation, thus it can approximate the failure probability with high accuracy. Finally applications in a numerical example and an engineering example indicate that the proposed method owns good performance in calculating efficiency and accuracy.
-
a composite response surface method for failure probability calculation of nonlinear implicit Limit State Equation
Engineering mechanics, 2006Co-Authors: Lu ZhenzhouAbstract:To solve failure probability of the implicit Limit State Equation with high curvature in the vicinity of the design point,a new composite response surface method(RSM) is presented.The major response surface and some sub-response surfaces are adopted in the method.The function form of response surface is taken as a quadratic polynomial without cross terms.According to the conventional RSM,the major response surface is obtained by the proper selection of sampling points and iterative calculation.The design point of the major response surface is named as the major design point.A pair of quasi-mean value points are taken by perturbing the major design point along the positive and negative direction of each coordinate axis.Based on the quasi-mean value point,a pair of sub-response surfaces are obtained in the similar manner as the major response surface.And the tangent hypersurfaces of all response surfaces are used to fit the actual implicit Limit State Equation and solve failure probability.Illustrations show that the accuracy of the present method is very high.
Zach Liang - One of the best experts on this subject based on the ideXlab platform.
-
Bridge pier failure probabilities under combined hazard effects of scour, truck and earthquake. Part I: occurrence probabilities
Earthquake Engineering and Engineering Vibration, 2013Co-Authors: Zach LiangAbstract:In many regions of the world, a bridge will experience multiple extreme hazards during its expected service life. The current American Association of State Highway and Transportation Officials (AASHTO) load and resistance factor design (LRFD) specifications are formulated based on failure probabilities, which are fully calibrated for dead load and nonextreme live loads. Design against earthquake loads is established separately. Design against scour effect is also formulated separately by using the concept of capacity reduction (or increased scour depth). Furthermore, scour effect cannot be linked directly to an LRFD Limit State Equation, because the latter is formulated using force-based analysis. This paper (in two parts) presents a probability-based procedure to estimate the combined hazard effects on bridges due to truck, earthquake and scour, by treating the effect of scour as an equivalent load effect so that it can be included in reliability-based bridge failure calculations. In Part I of this series, the general principle of treating the scour depth as an equivalent load effect is presented. The individual and combined partial failure probabilities due to truck, earthquake and scour effects are described. To explain the method of including non-force-based natural hazards effects, two types of common scour failures are considered. In Part II, the corresponding bridge failure probability, the occurrence of scour as well as simultaneously having both truck load and equivalent scour load are quantitatively discussed.
-
Bridge pier failure probabilities under combined hazard effects of scour, truck and earthquake. Part II: failure probabilities
Earthquake Engineering and Engineering Vibration, 2013Co-Authors: Zach LiangAbstract:In many regions of the world, a bridge will experience multiple extreme hazards during its expected service life. The current American Association of State Highway and Transportation Officials (AASHTO) load and resistance factor design (LRFD) specifications are formulated based on failure probabilities, which are fully calibrated for dead load and non-extreme live loads. Design against earthquake load effect is established separately. Design against scour effect is also formulated separately by using the concept of capacity reduction (or increased scour depth). Furthermore, scour effect cannot be linked directly to an LRFD Limit State Equation because the latter is formulated using force-based analysis. This paper (in two parts) presents a probability-based procedure to estimate the combined hazard effects on bridges due to truck, earthquake and scour, by treating the effect of scour as an equivalent load effect so that it can be included in reliability-based failure calculations. In Part I of this series, the general principle for treating the scour depth as an equivalent load effect is presented. In Part II, the corresponding bridge failure probability, the occurrence of scour as well as simultaneously having both truck load and equivalent scour load effect are quantitatively discussed. The key formulae of the conditional partial failure probabilities and the necessary conditions are established. In order to illustrate the methodology, an example of dead, truck, earthquake and scour effects on a simple bridge pile foundation is represented.
H. S. B. Duzgun - One of the best experts on this subject based on the ideXlab platform.
-
Probabilistic Stability Evaluation of Oppstadhornet Rock Slope, Norway
Rock Mechanics and Rock Engineering, 2008Co-Authors: H. S. B. Duzgun, R. K. BhasinAbstract:Probabilistic analyses provide rational means to treat the uncertainties associated with underlying parameters in a systematic manner. The stability of a 734-m-high jointed rock slope in the west of Norway, the Oppstadhornet rock slope, is investigated by using a probabilistic method. The first-order reliability method (FORM) is used for probabilistic modeling of the plane failure problem in the rock slope. The Barton–Bandis (BB) shear strength criterion is used for the Limit State Equation. The statistical distributions of the BB criterion parameters, for which comprehensive data were collected and statistically analyzed, are determined by using distribution fitting algorithms. The sensitivity of the FORM model for the BB criterion is also investigated. It is found that the model is most sensitive to the mean value of the residual friction angle ( ϕ _r) and least sensitive to the mean value of the slope angle ( β _f). It is also found that the standard deviation of joint compressive strength (JCS) causes the greatest difference in the reliability index, which has the least sensitivity to the change in the mean and standard deviation of joint roughness coefficient (JRC).