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Author: Kok-Kwang Phoon
Publisher:
ISBN: 9781032367507
Category : Geotechnical engineering
Languages : en
Pages : 0
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Book Description
"This book 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. It 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. 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: Kok-Kwang Phoon
Publisher:
ISBN: 9781032367507
Category : Geotechnical engineering
Languages : en
Pages : 0
Get Book Here
Book Description
"This book 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. It 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. 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: 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:
Publisher:
ISBN: 9781003333586
Category : Geotechnical engineering
Languages : en
Pages : 0
Get Book Here
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: Pijush Samui
Publisher: Academic Press
ISBN: 0128218525
Category : Technology & Engineering
Languages : en
Pages : 518
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Book Description
Modeling in Geotechnical Engineering is a one stop reference for a range of computational models, the theory explaining how they work, and case studies describing how to apply them. Drawing on the expertise of contributors from a range of disciplines including geomechanics, optimization, and computational engineering, this book provides an interdisciplinary guide to this subject which is suitable for readers from a range of backgrounds. Before tackling the computational approaches, a theoretical understanding of the physical systems is provided that helps readers to fully grasp the significance of the numerical methods. The various models are presented in detail, and advice is provided on how to select the correct model for your application. - Provides detailed descriptions of different computational modelling methods for geotechnical applications, including the finite element method, the finite difference method, and the boundary element method - Gives readers the latest advice on the use of big data analytics and artificial intelligence in geotechnical engineering - Includes case studies to help readers apply the methods described in their own work
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: Phung Duc Long
Publisher: Springer Nature
ISBN: 9819997224
Category :
Languages : en
Pages : 2890
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Book Description
Author: Xiaodong Fu
Publisher: Frontiers Media SA
ISBN: 2832502938
Category : Science
Languages : en
Pages : 539
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Book Description
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: Chong Tang
Publisher: CRC Press
ISBN: 0429655959
Category : Technology & Engineering
Languages : en
Pages : 497
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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.
