Author: Kok-Kwang Phoon
Publisher: CRC Press
ISBN: 1003801250
Category : Technology & Engineering
Languages : en
Pages : 521
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Book Description
Uncertainty, Modeling, and Decision Making in Geotechnics shows how uncertainty quantification and numerical modeling can complement each other to enhance decision-making in geotechnical practice, filling a critical gap in guiding practitioners to address uncertainties directly. The book helps practitioners acquire a working knowledge of geotechnical risk and reliability methods and guides them to use these methods wisely in conjunction with data and numerical modeling. In particular, it provides guidance on the selection of realistic statistics and a cost-effective, accessible method to address different design objectives, and for different problem settings, and illustrates the value of this to decision-making using realistic examples. Bringing together statistical characterization, reliability analysis, reliability-based design, probabilistic inverse analysis, and physical insights drawn from case studies, this reference guide from an international team of experts offers an excellent resource for state-of-the-practice uncertainty-informed geotechnical design for specialist practitioners and the research community.
Author: Jianye Ching
Publisher: CRC Press
ISBN: 1040097774
Category : Computers
Languages : en
Pages : 189
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Book Description
Bayesian data analysis and modelling linked with machine learning offers a new tool for handling geotechnical data. This book presents recent advancements made by the author in the area of probabilistic geotechnical site characterization. Two types of correlation play central roles in geotechnical site characterization: cross-correlation among soil properties and spatial-correlation in the underground space. The book starts with the introduction of Bayesian notion of probability “degree of belief”, showing that well-known probability axioms can be obtained by Boolean logic and the definition of plausibility function without the use of the notion “relative frequency”. It then reviews probability theories and useful probability models for cross-correlation and spatial correlation. Methods for Bayesian parameter estimation and prediction are also presented, and the use of these methods demonstrated with geotechnical site characterization examples. Bayesian Machine Learning in Geotechnical Site Characterization suits consulting engineers and graduate students in the area.
Author: Phung Duc Long
Publisher: Springer Nature
ISBN: 9819997224
Category :
Languages : en
Pages : 2890
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Book Description
Author: Cavit Atalar
Publisher: Springer Nature
ISBN: 3031201728
Category : Science
Languages : en
Pages : 483
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Book Description
This volume highlights the latest advances and innovations in the field of soil mechanics and geotechnical engineering, as presented by leading international researchers and engineers at the 5th International Conference on New Developments in Soil Mechanics and Geotechnical Engineering (ZM), held in Nicosia, Northern Cyprus on June 30-July 2, 2022. It covers a diverse range of topics such as soil properties and characterization; shallow and deep foundations; soil improvement; excavations, support systems, earth-retaining structures and underground systems; earthquake geotechnical engineering; stability of slopes and landslides; fills and embankments; environmental preservation, water and energy; modelling and analyses in geotechnical engineering. The contributions, which were selected by means of a rigorous international peer-review process, present a wealth of exciting ideas that will open novel research directions and foster multidisciplinary collaboration among different specialists.
Author: Xiaodong Fu
Publisher: Frontiers Media SA
ISBN: 2832502938
Category : Science
Languages : en
Pages : 539
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Book Description
Author: Kok-Kwang Phoon
Publisher: Challenges in Geotechnical and Rock Engineering
ISBN: 9781032367491
Category :
Languages : en
Pages : 0
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Book Description
Uncertainty, Modelling, and Decision Making in Geotechnics shows how uncertainty quantification and numerical modeling can complement each other to enhance decision making in geotechnical practice, filling a critical gap in guiding practitioners to address uncertainties directly. The book helps practitioners acquire a working knowledge of geotechnical risk and reliability methods and guides them to use these methods wisely in conjunction with data and numerical modeling. In particular, it provides guidance on the selection of realistic statistics and a cost-effective, accessible method to address different design objectives, and for different problem settings, and illustrates the value of this to decision making using realistic examples. Bringing together statistical characterization, reliability analysis, reliability-based design, probabilistic inverse analysis, and physical insights drawn from case studies, this reference guide from an international team of experts offers an excellent resource for state-of-the-practice uncertainty-informed geotechnical design for specialist practitioners and the research community.
Author: Chong Tang
Publisher: CRC Press
ISBN: 0429655959
Category : Technology & Engineering
Languages : en
Pages : 557
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Book Description
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.
Author: D. V. Griffiths
Publisher: Springer Science & Business Media
ISBN: 3211733663
Category : Science
Languages : en
Pages : 346
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Book Description
Learn to use probabilistic techniques to solve problems in geotechnical engineering. The book reviews the statistical theories needed to develop the methodologies and interpret the results. Next, the authors explore probabilistic methods of analysis, such as the first order second moment method, the point estimate method, and random set theory. Examples and case histories guide you step by step in applying the techniques to particular problems.
Author: Asadullah Khalid
Publisher: BoD – Books on Demand
ISBN: 0854665668
Category : Mathematics
Languages : en
Pages : 204
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Book Description
Applications and Optimizations of Kalman Filter and Their Variants is a comprehensive exploration of Kalman filters’ diverse applications and refined optimizations across various domains. It meticulously examines their role in microgrid management, offering adaptive estimation techniques for effective control strategies. The book then delves into distribution system state estimation, showcasing an innovative stochastic programming model using extended Kalman filters for reliable monitoring and control. In the realm of financial modeling, readers gain insights into how Kalman filters enhance trading strategies like pairs trading and partial co-integration, bridging finance and analytics. Moreover, the book discusses Kalman filter optimization, addressing challenges in object tracking and error reduction with techniques like dynamic stochastic approximation algorithms and M-robust estimates. With practical examples and interdisciplinary approaches, this book serves as a valuable resource for researchers, practitioners, and students looking to harness Kalman filter techniques for enhanced efficiency and accuracy across diverse fields.
Author: Sumanta Haldar
Publisher: Springer Nature
ISBN: 9811568324
Category : Technology & Engineering
Languages : en
Pages : 432
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Book Description
This book comprises select proceedings of the First Indian Symposium on Offshore Geotechnics. It addresses state of the art and emerging challenges in offshore design and construction. The theme papers from leading academicians and practitioners provide a comprehensive overview of the broad topics encompassing various challenges in offshore geotechnical engineering. It covers various aspects pertaining to offshore geotechnics, such as offshore site investigation, soil characterization, geotechnics related to offshore renewable energy converters, offshore foundations and anchoring systems, pipelines, and deep sea explorations. This volume provides a comprehensive reference for professionals and researchers in offshore, civil and maritime engineering and for soil mechanics specialists.
