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Model Uncertainties in Foundation Design

Author/EditorTang, Chong (NUS Singapore, Dept of Civi (Author)
Phoon, Kok-Kwang (NUS Singapore, Dept of (Author)
ISBN: 9780367683955
Pub Date30/09/2022
BindingPaperback
Pages588
Dimensions (mm)234(h) * 156(w)
Geotechnical design codes worldwide are increasingly being directed to reliability-based design, for which the characterization of model uncertainty is a critical element. This practical book is based on a global load test database which provides information on the foundation, site or soil investigation, and load test results.
¥15,845
excluding shipping
Availability: Available to order but dispatch within 7-10 days
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Model Uncertainties in Foundation Design is unique in the compilation of the largest and the most diverse load test databases to date, covering many foundation types (shallow foundations, spudcans, driven piles, drilled shafts, rock sockets and helical piles) and a wide range of ground conditions (soil to soft rock).

All databases with names prefixed by NUS are available upon request. This book presents a comprehensive evaluation of the model factor mean (bias) and coefficient of variation (COV) for ultimate and serviceability limit state based on these databases. These statistics can be used directly for AASHTO LRFD calibration.

Besides load test databases, performance databases for other geo-structures and their model factor statistics are provided. Based on this extensive literature survey, a practical three-tier scheme for classifying the model uncertainty of geo-structures according to the model factor mean and COV is proposed. This empirically grounded scheme can underpin the calibration of resistance factors as a function of the degree of understanding - a concept already adopted in the Canadian Highway Bridge Design Code and being considered for the new draft for Eurocode 7 Part 1 (EN 1997-1:202x). The helical pile research in Chapter 7 was recognised by the 2020 ASCE Norman Medal.

Model Uncertainties in Foundation Design is unique in the compilation of the largest and the most diverse load test databases to date, covering many foundation types (shallow foundations, spudcans, driven piles, drilled shafts, rock sockets and helical piles) and a wide range of ground conditions (soil to soft rock).

All databases with names prefixed by NUS are available upon request. This book presents a comprehensive evaluation of the model factor mean (bias) and coefficient of variation (COV) for ultimate and serviceability limit state based on these databases. These statistics can be used directly for AASHTO LRFD calibration.

Besides load test databases, performance databases for other geo-structures and their model factor statistics are provided. Based on this extensive literature survey, a practical three-tier scheme for classifying the model uncertainty of geo-structures according to the model factor mean and COV is proposed. This empirically grounded scheme can underpin the calibration of resistance factors as a function of the degree of understanding - a concept already adopted in the Canadian Highway Bridge Design Code and being considered for the new draft for Eurocode 7 Part 1 (EN 1997-1:202x). The helical pile research in Chapter 7 was recognised by the 2020 ASCE Norman Medal.

Chong Tang is Senior Research Fellow in the Department of Civil and Environmental Engineering at the National University of Singapore. Kok-Kwang Phoon is Distinguished Professor and Senior Vice Provost for Academic Affairs at the National University of Singapore.

1. Geotechnical Engineering in the Era of Industry 4.0 2. Evaluation and Incorporation of Uncertainties in Geotechnical Engineering 3. Basics in Foundation Engineering 4. Evaluation of Design Methods for Shallow Foundations 5. Evaluation of Design Methods for Offshore Spudcans in Layered Soil 6. Evaluation of Design Methods for Driven Piles and Drilled Shafts 7. Evaluation of Design Methods for Helical Piles 8. Summary and Conclusions Appendix: Data Availability Statement

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