Kriging in Slope Reliability Analysis
CRC Press (Verlag)
978-1-032-74527-5 (ISBN)
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Kriging can be used to determine optimal unbiased predictions for regionalized variables and has been shown to be a powerful tool in slope reliability analysis for reliability-based design. This is the first book to systematically cover the basic theory and applications of the method in slope reliability assessment.
The book gives an extensive and detailed presentation of principles and applications, introducing geostatistics and the basic theory of Kriging before addressing the challenges in the application of Kriging in slope reliability analysis. The latest advancements in Kriging application methods are introduced, which enhance computational accuracy and reduce model errors. These include optimization algorithms for spatial parameters in Kriging, adaptive modeling of spatial correlation structures, optimization sampling methods within Monte Carlo simulation, quantitative analysis of slope failure risks, and reliability analysis methods for unreinforced and reinforced slopes based on conditional random fields. Several case studies are presented to illustrate the practical application and implementation procedures, bridging theory, and practical engineering.
Kriging in Slope Reliability Analysis particularly suits consulting engineers, researchers, and postgraduate students.
Lei-Lei Liu is an associate professor in Department of Geological Engineering at Central South University, China. He is the co-author of Analysis, Design, and Construction of Foundations, also published by CRC Press. Jing-Ze Li is a research associate at Central South University, China. His PhD research was undertaken jointly with Central South University, china and Université Grenoble Alpes, France. Lei Huang is an associate professor at Sanming University, China. He received PhD in The Hong Kong Polytechnic University.
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.
| Erscheint lt. Verlag | 27.11.2024 |
|---|---|
| Zusatzinfo | 51 Tables, black and white; 187 Line drawings, black and white; 187 Illustrations, black and white |
| Verlagsort | London |
| Sprache | englisch |
| Maße | 156 x 234 mm |
| Themenwelt | Naturwissenschaften ► Geowissenschaften ► Geologie |
| Technik ► Bauwesen | |
| Technik ► Umwelttechnik / Biotechnologie | |
| ISBN-10 | 1-032-74527-4 / 1032745274 |
| ISBN-13 | 978-1-032-74527-5 / 9781032745275 |
| Zustand | Neuware |
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