This covers the basic theory and applications of Kriging in slope reliability assessment. It gives an extensive and detailed presentation of principles and the latest applications and includes several case studies illustrating practical application and implementation procedures.
This covers the basic theory and applications of Kriging in slope reliability assessment. It gives an extensive and detailed presentation of principles and the latest applications and includes several case studies illustrating practical application and implementation procedures.
Lei-Lei Liu is an associate professor in Geological Engineering at the Central South University, China. He is co-author of Analysis, Design, and Construction of Foundations, also published by CRC Press. Jing-Ze Li is a post-doctoral fellow at Central South University, China. His PhD research was undertaken jointly with Université Grenoble Alpes, France. Lei Huang is an assistant professor at Wenzhou University and a member of the Key Laboratory of Engineering and Technology for Soft Soil Foundation and Tideland Reclamation of Zhejiang Province, China.
Inhaltsangabe
1. Introduction. 2. Overview of Geostatistics and Spatial Sampling. 3. Basic Theory of Kriging. 4. Application of Kriging in Slope Reliability Analysis. 5. Genetic Algorithm Optimized Taylor Kriging Surrogate Model for System Reliability Analysis of Soil Slopes. 6. Adaptively Selected Autocorrelation Structure-Based Kriging Metamodel for Slope Reliability Analysis. 7. System Reliability Analysis of Soil Slopes Using an Advanced Kriging Metamodel and Quasi Monte Carlo Simulation. 8. Efficient Slope Reliability Analysis and Risk Assessment Based on Multiple Kriging Surrogate Models. 9. A New Active Learning Kriging Surrogate Model for Structural System Reliability Analysis with Multiple Failure Modes. 10. New Kriging Methods for Efficient System Slope Reliability Analysis Considering Soil Spatial Variability. 11. Conditional Random Field Reliability Analysis of a Cohesion-Frictional Slope. 12. Reliability Analysis and Risk Assessment of Pile-Reinforced Slopes Considering Spatial Soil Variability and Site Investigation. 13. Summary and Concluding Remarks.
1. Introduction. 2. Overview of Geostatistics and Spatial Sampling. 3. Basic Theory of Kriging. 4. Application of Kriging in Slope Reliability Analysis. 5. Genetic Algorithm Optimized Taylor Kriging Surrogate Model for System Reliability Analysis of Soil Slopes. 6. Adaptively Selected Autocorrelation Structure-Based Kriging Metamodel for Slope Reliability Analysis. 7. System Reliability Analysis of Soil Slopes Using an Advanced Kriging Metamodel and Quasi Monte Carlo Simulation. 8. Efficient Slope Reliability Analysis and Risk Assessment Based on Multiple Kriging Surrogate Models. 9. A New Active Learning Kriging Surrogate Model for Structural System Reliability Analysis with Multiple Failure Modes. 10. New Kriging Methods for Efficient System Slope Reliability Analysis Considering Soil Spatial Variability. 11. Conditional Random Field Reliability Analysis of a Cohesion-Frictional Slope. 12. Reliability Analysis and Risk Assessment of Pile-Reinforced Slopes Considering Spatial Soil Variability and Site Investigation. 13. Summary and Concluding Remarks.
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