Uncertainty Modeling and Analysis in Civil Engineering
Uncertainty Modeling and Analysis in Civil Engineering

Author: Bilal M. Ayyub

Publisher: CRC Press

Published: 1997-12-29

Total Pages: 534

ISBN-13: 9780849331084

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With the expansion of new technologies, materials, and the design of complex systems, the expectations of society upon engineers are becoming larger than ever. Engineers make critical decisions with potentially high adverse consequences. The current political, societal, and financial climate requires engineers to formally consider the factors of uncertainty (e.g., floods, earthquakes, winds, environmental risks) in their decisions at all levels. Uncertainty Modeling and Analysis in Civil Engineering provides a thorough report on the immediate state of uncertainty modeling and analytical methods for civil engineering systems, presenting a toolbox for solving problems in real-world situations. Topics include Neural networks Genetic algorithms Numerical modeling Fuzzy sets and operations Reliability and risk analysis Systems control Uncertainty in probability estimates This compendium is a considerable reference for civil engineers as well as for engineers in other disciplines, computer scientists, general scientists, and students.

Uncertainty Analysis in Engineering and Sciences: Fuzzy Logic, Statistics, and Neural Network Approach
Uncertainty Analysis in Engineering and Sciences: Fuzzy Logic, Statistics, and Neural Network Approach

Author: Bilal Ayyub

Publisher: Springer Science & Business Media

Published: 1997-10-31

Total Pages: 414

ISBN-13: 9780792380306

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Uncertainty has been of concern to engineers, managers and . scientists for many centuries. In management sciences there have existed definitions of uncertainty in a rather narrow sense since the beginning of this century. In engineering and uncertainty has for a long time been considered as in sciences, however, synonymous with random, stochastic, statistic, or probabilistic. Only since the early sixties views on uncertainty have ~ecome more heterogeneous and more tools to model uncertainty than statistics have been proposed by several scientists. The problem of modeling uncertainty adequately has become more important the more complex systems have become, the faster the scientific and engineering world develops, and the more important, but also more difficult, forecasting of future states of systems have become. The first question one should probably ask is whether uncertainty is a phenomenon, a feature of real world systems, a state of mind or a label for a situation in which a human being wants to make statements about phenomena, i. e. , reality, models, and theories, respectively. One cart also ask whether uncertainty is an objective fact or just a subjective impression which is closely related to individual persons. Whether uncertainty is an objective feature of physical real systems seems to be a philosophical question. This shall not be answered in this volume.

Uncertainty Modeling in Finite Element, Fatigue and Stability of Systems
Uncertainty Modeling in Finite Element, Fatigue and Stability of Systems

Author: Achintya Haldar

Publisher: World Scientific

Published: 1997

Total Pages: 437

ISBN-13: 9810231288

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The functionality of modern structural, mechanical and electrical or electronic systems depends on their ability to perform under uncertain conditions. Consideration of uncertainties and their effect on system behavior is an essential and integral part of defining systems. In eleven chapters, leading experts present an overview of the current state of uncertainty modeling, analysis and design of large systems in four major areas: finite and boundary element methods (common structural analysis techniques), fatigue, stability analysis, and fault-tolerant systems. The content of this book is unique; it describes exciting research developments and challenges in emerging areas, and provide a sophisticated toolbox for tackling uncertainty modeling in real systems.

Sensitivity & Uncertainty Analysis, Volume 1
Sensitivity & Uncertainty Analysis, Volume 1

Author: Dan G. Cacuci

Publisher: CRC Press

Published: 2003-05-28

Total Pages: 304

ISBN-13: 0203498798

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As computer-assisted modeling and analysis of physical processes have continued to grow and diversify, sensitivity and uncertainty analyses have become indispensable investigative scientific tools in their own right. While most techniques used for these analyses are well documented, there has yet to appear a systematic treatment of the method based

Hydrosystems Engineering Uncertainty Analysis
Hydrosystems Engineering Uncertainty Analysis

Author: Yeou-Koung Tung

Publisher: McGraw Hill Professional

Published: 2005-04-14

Total Pages: 306

ISBN-13: 0071467084

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Failure of hydrosystems, such as dams, levees, storm sewers, or pollution control systems, pose threats to the public safety and health as well as potentially inflict enormous damages on properties and environments. Many failures of hydrosystems are mainly attributed by the existence of various uncertainties, including inherent natural randomness and the lack of complete understanding of involved geophysical processes. It is therefore essential to systematically quantify the degree of uncertainty for the problem in hand so that reliability assessment and risk-based design of hydrosystems can be made. The conventional approach of frequency analysis of heavy rainfalls or large floods consider only portion of the uncertainties involved in hydrosystem engineering problems. Over the past two decades or so, there has been a steady growth on the development and application of uncertainty analysis techniques in hydrosystems engineering and other disciplines. The aim of this book is to bring together these uncertainty analysis techniques in one book and to demonstrate their applications and limitations for a wide variety of hydrosystem engineering problems.

Fuzzy Randomness
Fuzzy Randomness

Author: Bernd Möller

Publisher: Springer Science & Business Media

Published: 2013-03-14

Total Pages: 351

ISBN-13: 3662073587

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sections dealing with fuzzy functions and fuzzy random functions are certain to be of special interest. The reader is expected to be in command of the knowledge gained in a basic university mathematics course, with the inclusion of stochastic elements. A specification of uncertainty in any particular case is often difficult. For this reason Chaps. 3 and 4 are devoted solely to this problem. The derivation of fuzzy variables for representing informal and lexical uncertainty reflects the subjective assessment of objective conditions in the form of a membership function. Techniques for modeling fuzzy random variables are presented for data that simultaneously exhibit stochastic and nonstochastic properties. The application of fuzzy randomness is demonstrated in three fields of civil engineering and computational mechanics: structural analysis, safety assessment, and design. The methods of fuzzy structural analysis and fuzzy probabilistic structural analysis developed in Chap. 5 are applicable without restriction to arbitrary geometrically and physically nonlinear problems. The most important forms of the latter are the Fuzzy Finite Element Method (FFEM) and the Fuzzy Stochastic Finite Element Method (FSFEM).

Modeling in Geotechnical Engineering
Modeling in Geotechnical Engineering

Author: Pijush Samui

Publisher: Academic Press

Published: 2020-12-01

Total Pages: 518

ISBN-13: 0128218525

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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

Uncertainty Modeling and Analysis in Engineering and the Sciences
Uncertainty Modeling and Analysis in Engineering and the Sciences

Author: Bilal M. Ayyub

Publisher: CRC Press

Published: 2006-05-25

Total Pages: 401

ISBN-13: 1420011456

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Engineers and scientists often need to solve complex problems with incomplete information resources, necessitating a proper treatment of uncertainty and a reliance on expert opinions. Uncertainty Modeling and Analysis in Engineering and the Sciences prepares current and future analysts and practitioners to understand the fundamentals of knowledge a

Experimentation, Validation, and Uncertainty Analysis for Engineers
Experimentation, Validation, and Uncertainty Analysis for Engineers

Author: Hugh W. Coleman

Publisher: John Wiley & Sons

Published: 2018-04-09

Total Pages: 404

ISBN-13: 1119417708

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Helps engineers and scientists assess and manage uncertainty at all stages of experimentation and validation of simulations Fully updated from its previous edition, Experimentation, Validation, and Uncertainty Analysis for Engineers, Fourth Edition includes expanded coverage and new examples of applying the Monte Carlo Method (MCM) in performing uncertainty analyses. Presenting the current, internationally accepted methodology from ISO, ANSI, and ASME standards for propagating uncertainties using both the MCM and the Taylor Series Method (TSM), it provides a logical approach to experimentation and validation through the application of uncertainty analysis in the planning, design, construction, debugging, execution, data analysis, and reporting phases of experimental and validation programs. It also illustrates how to use a spreadsheet approach to apply the MCM and the TSM, based on the authors’ experience in applying uncertainty analysis in complex, large-scale testing of real engineering systems. Experimentation, Validation, and Uncertainty Analysis for Engineers, Fourth Edition includes examples throughout, contains end of chapter problems, and is accompanied by the authors’ website www.uncertainty-analysis.com. Guides readers through all aspects of experimentation, validation, and uncertainty analysis Emphasizes the use of the Monte Carlo Method in performing uncertainty analysis Includes complete new examples throughout Features workable problems at the end of chapters Experimentation, Validation, and Uncertainty Analysis for Engineers, Fourth Edition is an ideal text and guide for researchers, engineers, and graduate and senior undergraduate students in engineering and science disciplines. Knowledge of the material in this Fourth Edition is a must for those involved in executing or managing experimental programs or validating models and simulations.