Fundamentals Of Uncertainty Quantification For Engineers

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Uncertainty Quantification and Predictive Computational Science

Author : Ryan G. McClarren
Publisher : Springer
ISBN 13 : 3319995251
Total Pages : 349 pages
Book Rating : 4.3/5 (199 download)

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Book Synopsis Uncertainty Quantification and Predictive Computational Science by : Ryan G. McClarren

Download or read book Uncertainty Quantification and Predictive Computational Science written by Ryan G. McClarren and published by Springer. This book was released on 2018-11-23 with total page 349 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook teaches the essential background and skills for understanding and quantifying uncertainties in a computational simulation, and for predicting the behavior of a system under those uncertainties. It addresses a critical knowledge gap in the widespread adoption of simulation in high-consequence decision-making throughout the engineering and physical sciences. Constructing sophisticated techniques for prediction from basic building blocks, the book first reviews the fundamentals that underpin later topics of the book including probability, sampling, and Bayesian statistics. Part II focuses on applying Local Sensitivity Analysis to apportion uncertainty in the model outputs to sources of uncertainty in its inputs. Part III demonstrates techniques for quantifying the impact of parametric uncertainties on a problem, specifically how input uncertainties affect outputs. The final section covers techniques for applying uncertainty quantification to make predictions under uncertainty, including treatment of epistemic uncertainties. It presents the theory and practice of predicting the behavior of a system based on the aggregation of data from simulation, theory, and experiment. The text focuses on simulations based on the solution of systems of partial differential equations and includes in-depth coverage of Monte Carlo methods, basic design of computer experiments, as well as regularized statistical techniques. Code references, in python, appear throughout the text and online as executable code, enabling readers to perform the analysis under discussion. Worked examples from realistic, model problems help readers understand the mechanics of applying the methods. Each chapter ends with several assignable problems. Uncertainty Quantification and Predictive Computational Science fills the growing need for a classroom text for senior undergraduate and early-career graduate students in the engineering and physical sciences and supports independent study by researchers and professionals who must include uncertainty quantification and predictive science in the simulations they develop and/or perform.

Uncertainty Quantification

Author : Ralph C. Smith
Publisher : SIAM
ISBN 13 : 161197321X
Total Pages : 400 pages
Book Rating : 4.6/5 (119 download)

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Book Synopsis Uncertainty Quantification by : Ralph C. Smith

Download or read book Uncertainty Quantification written by Ralph C. Smith and published by SIAM. This book was released on 2013-12-02 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: The field of uncertainty quantification is evolving rapidly because of increasing emphasis on models that require quantified uncertainties for large-scale applications, novel algorithm development, and new computational architectures that facilitate implementation of these algorithms. Uncertainty Quantification: Theory, Implementation, and Applications provides readers with the basic concepts, theory, and algorithms necessary to quantify input and response uncertainties for simulation models arising in a broad range of disciplines. The book begins with a detailed discussion of applications where uncertainty quantification is critical for both scientific understanding and policy. It then covers concepts from probability and statistics, parameter selection techniques, frequentist and Bayesian model calibration, propagation of uncertainties, quantification of model discrepancy, surrogate model construction, and local and global sensitivity analysis. The author maintains a complementary web page where readers can find data used in the exercises and other supplementary material.

An Introduction to Data Analysis and Uncertainty Quantification for Inverse Problems

Author : Luis Tenorio
Publisher : SIAM
ISBN 13 : 1611974917
Total Pages : 275 pages
Book Rating : 4.6/5 (119 download)

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Book Synopsis An Introduction to Data Analysis and Uncertainty Quantification for Inverse Problems by : Luis Tenorio

Download or read book An Introduction to Data Analysis and Uncertainty Quantification for Inverse Problems written by Luis Tenorio and published by SIAM. This book was released on 2017-07-06 with total page 275 pages. Available in PDF, EPUB and Kindle. Book excerpt: Inverse problems are found in many applications, such as medical imaging, engineering, astronomy, and geophysics, among others. To solve an inverse problem is to recover an object from noisy, usually indirect observations. Solutions to inverse problems are subject to many potential sources of error introduced by approximate mathematical models, regularization methods, numerical approximations for efficient computations, noisy data, and limitations in the number of observations; thus it is important to include an assessment of the uncertainties as part of the solution. Such assessment is interdisciplinary by nature, as it requires, in addition to knowledge of the particular application, methods from applied mathematics, probability, and statistics. This book bridges applied mathematics and statistics by providing a basic introduction to probability and statistics for uncertainty quantification in the context of inverse problems, as well as an introduction to statistical regularization of inverse problems. The author covers basic statistical inference, introduces the framework of ill-posed inverse problems, and explains statistical questions that arise in their applications. An Introduction to Data Analysis and Uncertainty Quantification for Inverse Problems?includes many examples that explain techniques which are useful to address general problems arising in uncertainty quantification, Bayesian and non-Bayesian statistical methods and discussions of their complementary roles, and analysis of a real data set to illustrate the methodology covered throughout the book.

Handbook of Uncertainty Quantification

Author : Roger Ghanem
Publisher : Springer
ISBN 13 : 9783319123844
Total Pages : 0 pages
Book Rating : 4.1/5 (238 download)

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Book Synopsis Handbook of Uncertainty Quantification by : Roger Ghanem

Download or read book Handbook of Uncertainty Quantification written by Roger Ghanem and published by Springer. This book was released on 2016-05-08 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The topic of Uncertainty Quantification (UQ) has witnessed massive developments in response to the promise of achieving risk mitigation through scientific prediction. It has led to the integration of ideas from mathematics, statistics and engineering being used to lend credence to predictive assessments of risk but also to design actions (by engineers, scientists and investors) that are consistent with risk aversion. The objective of this Handbook is to facilitate the dissemination of the forefront of UQ ideas to their audiences. We recognize that these audiences are varied, with interests ranging from theory to application, and from research to development and even execution.

Model Uncertainties in Foundation Design

Author : Chong Tang
Publisher : CRC Press
ISBN 13 : 0429655959
Total Pages : 497 pages
Book Rating : 4.4/5 (296 download)

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Book Synopsis Model Uncertainties in Foundation Design by : Chong Tang

Download or read book Model Uncertainties in Foundation Design written by Chong Tang and published by CRC Press. This book was released on 2021-03-17 with total page 497 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Princeton Companion to Applied Mathematics

Author : Nicholas J. Higham
Publisher : Princeton University Press
ISBN 13 : 0691150397
Total Pages : 1014 pages
Book Rating : 4.6/5 (911 download)

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Book Synopsis Princeton Companion to Applied Mathematics by : Nicholas J. Higham

Download or read book Princeton Companion to Applied Mathematics written by Nicholas J. Higham and published by Princeton University Press. This book was released on 2015-09-09 with total page 1014 pages. Available in PDF, EPUB and Kindle. Book excerpt: The must-have compendium on applied mathematics This is the most authoritative and accessible single-volume reference book on applied mathematics. Featuring numerous entries by leading experts and organized thematically, it introduces readers to applied mathematics and its uses; explains key concepts; describes important equations, laws, and functions; looks at exciting areas of research; covers modeling and simulation; explores areas of application; and more. Modeled on the popular Princeton Companion to Mathematics, this volume is an indispensable resource for undergraduate and graduate students, researchers, and practitioners in other disciplines seeking a user-friendly reference book on applied mathematics. Features nearly 200 entries organized thematically and written by an international team of distinguished contributors Presents the major ideas and branches of applied mathematics in a clear and accessible way Explains important mathematical concepts, methods, equations, and applications Introduces the language of applied mathematics and the goals of applied mathematical research Gives a wide range of examples of mathematical modeling Covers continuum mechanics, dynamical systems, numerical analysis, discrete and combinatorial mathematics, mathematical physics, and much more Explores the connections between applied mathematics and other disciplines Includes suggestions for further reading, cross-references, and a comprehensive index

The Uncertainty Analysis of Model Results

Author : Eduard Hofer
Publisher : Springer
ISBN 13 : 9783319762968
Total Pages : 346 pages
Book Rating : 4.7/5 (629 download)

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Book Synopsis The Uncertainty Analysis of Model Results by : Eduard Hofer

Download or read book The Uncertainty Analysis of Model Results written by Eduard Hofer and published by Springer. This book was released on 2018-07-01 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a practical guide to the uncertainty analysis of computer model applications. Used in many areas, such as engineering, ecology and economics, computer models are subject to various uncertainties at the level of model formulations, parameter values and input data. Naturally, it would be advantageous to know the combined effect of these uncertainties on the model results as well as whether the state of knowledge should be improved in order to reduce the uncertainty of the results most effectively. The book supports decision-makers, model developers and users in their argumentation for an uncertainty analysis and assists them in the interpretation of the analysis results.

Optimization Under Uncertainty with Applications to Aerospace Engineering

Author : Massimiliano Vasile
Publisher : Springer Nature
ISBN 13 : 3030601668
Total Pages : 573 pages
Book Rating : 4.0/5 (36 download)

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Book Synopsis Optimization Under Uncertainty with Applications to Aerospace Engineering by : Massimiliano Vasile

Download or read book Optimization Under Uncertainty with Applications to Aerospace Engineering written by Massimiliano Vasile and published by Springer Nature. This book was released on 2021-02-15 with total page 573 pages. Available in PDF, EPUB and Kindle. Book excerpt: In an expanding world with limited resources, optimization and uncertainty quantification have become a necessity when handling complex systems and processes. This book provides the foundational material necessary for those who wish to embark on advanced research at the limits of computability, collecting together lecture material from leading experts across the topics of optimization, uncertainty quantification and aerospace engineering. The aerospace sector in particular has stringent performance requirements on highly complex systems, for which solutions are expected to be optimal and reliable at the same time. The text covers a wide range of techniques and methods, from polynomial chaos expansions for uncertainty quantification to Bayesian and Imprecise Probability theories, and from Markov chains to surrogate models based on Gaussian processes. The book will serve as a valuable tool for practitioners, researchers and PhD students.

Fundamentals of Finite Element Analysis

Author : Ioannis Koutromanos
Publisher : John Wiley & Sons
ISBN 13 : 1119260086
Total Pages : 724 pages
Book Rating : 4.1/5 (192 download)

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Book Synopsis Fundamentals of Finite Element Analysis by : Ioannis Koutromanos

Download or read book Fundamentals of Finite Element Analysis written by Ioannis Koutromanos and published by John Wiley & Sons. This book was released on 2018-02-12 with total page 724 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introductory textbook covering the fundamentals of linear finite element analysis (FEA) This book constitutes the first volume in a two-volume set that introduces readers to the theoretical foundations and the implementation of the finite element method (FEM). The first volume focuses on the use of the method for linear problems. A general procedure is presented for the finite element analysis (FEA) of a physical problem, where the goal is to specify the values of a field function. First, the strong form of the problem (governing differential equations and boundary conditions) is formulated. Subsequently, a weak form of the governing equations is established. Finally, a finite element approximation is introduced, transforming the weak form into a system of equations where the only unknowns are nodal values of the field function. The procedure is applied to one-dimensional elasticity and heat conduction, multi-dimensional steady-state scalar field problems (heat conduction, chemical diffusion, flow in porous media), multi-dimensional elasticity and structural mechanics (beams/shells), as well as time-dependent (dynamic) scalar field problems, elastodynamics and structural dynamics. Important concepts for finite element computations, such as isoparametric elements for multi-dimensional analysis and Gaussian quadrature for numerical evaluation of integrals, are presented and explained. Practical aspects of FEA and advanced topics, such as reduced integration procedures, mixed finite elements and verification and validation of the FEM are also discussed. Provides detailed derivations of finite element equations for a variety of problems. Incorporates quantitative examples on one-dimensional and multi-dimensional FEA. Provides an overview of multi-dimensional linear elasticity (definition of stress and strain tensors, coordinate transformation rules, stress-strain relation and material symmetry) before presenting the pertinent FEA procedures. Discusses practical and advanced aspects of FEA, such as treatment of constraints, locking, reduced integration, hourglass control, and multi-field (mixed) formulations. Includes chapters on transient (step-by-step) solution schemes for time-dependent scalar field problems and elastodynamics/structural dynamics. Contains a chapter dedicated to verification and validation for the FEM and another chapter dedicated to solution of linear systems of equations and to introductory notions of parallel computing. Includes appendices with a review of matrix algebra and overview of matrix analysis of discrete systems. Accompanied by a website hosting an open-source finite element program for linear elasticity and heat conduction, together with a user tutorial. Fundamentals of Finite Element Analysis: Linear Finite Element Analysis is an ideal text for undergraduate and graduate students in civil, aerospace and mechanical engineering, finite element software vendors, as well as practicing engineers and anybody with an interest in linear finite element analysis.

An Introduction to Uncertainty in Measurement

Author : L. Kirkup
Publisher : Cambridge University Press
ISBN 13 : 1139454900
Total Pages : 196 pages
Book Rating : 4.1/5 (394 download)

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Book Synopsis An Introduction to Uncertainty in Measurement by : L. Kirkup

Download or read book An Introduction to Uncertainty in Measurement written by L. Kirkup and published by Cambridge University Press. This book was released on 2006-06-01 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt: Measurement shapes scientific theories, characterises improvements in manufacturing processes and promotes efficient commerce. In concert with measurement is uncertainty, and students in science and engineering need to identify and quantify uncertainties in the measurements they make. This book introduces measurement and uncertainty to second and third year students of science and engineering. Its approach relies on the internationally recognised and recommended guidelines for calculating and expressing uncertainty (known by the acronym GUM). The statistics underpinning the methods are considered and worked examples and exercises are spread throughout the text. Detailed case studies based on typical undergraduate experiments are included to reinforce the principles described in the book. This guide is also useful to professionals in industry who are expected to know the contemporary methods in this increasingly important area. Additional online resources are available to support the book at www.cambridge.org/9780521605793.

Handbook of Probabilistic Models

Author : Pijush Samui
Publisher : Butterworth-Heinemann
ISBN 13 : 0128165464
Total Pages : 592 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis Handbook of Probabilistic Models by : Pijush Samui

Download or read book Handbook of Probabilistic Models written by Pijush Samui and published by Butterworth-Heinemann. This book was released on 2019-10-05 with total page 592 pages. Available in PDF, EPUB and Kindle. Book excerpt: Handbook of Probabilistic Models carefully examines the application of advanced probabilistic models in conventional engineering fields. In this comprehensive handbook, practitioners, researchers and scientists will find detailed explanations of technical concepts, applications of the proposed methods, and the respective scientific approaches needed to solve the problem. This book provides an interdisciplinary approach that creates advanced probabilistic models for engineering fields, ranging from conventional fields of mechanical engineering and civil engineering, to electronics, electrical, earth sciences, climate, agriculture, water resource, mathematical sciences and computer sciences. Specific topics covered include minimax probability machine regression, stochastic finite element method, relevance vector machine, logistic regression, Monte Carlo simulations, random matrix, Gaussian process regression, Kalman filter, stochastic optimization, maximum likelihood, Bayesian inference, Bayesian update, kriging, copula-statistical models, and more. - Explains the application of advanced probabilistic models encompassing multidisciplinary research - Applies probabilistic modeling to emerging areas in engineering - Provides an interdisciplinary approach to probabilistic models and their applications, thus solving a wide range of practical problems

Numerical Methods for Stochastic Computations

Author : Dongbin Xiu
Publisher : Princeton University Press
ISBN 13 : 1400835348
Total Pages : 142 pages
Book Rating : 4.4/5 (8 download)

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Book Synopsis Numerical Methods for Stochastic Computations by : Dongbin Xiu

Download or read book Numerical Methods for Stochastic Computations written by Dongbin Xiu and published by Princeton University Press. This book was released on 2010-07-01 with total page 142 pages. Available in PDF, EPUB and Kindle. Book excerpt: The@ first graduate-level textbook to focus on fundamental aspects of numerical methods for stochastic computations, this book describes the class of numerical methods based on generalized polynomial chaos (gPC). These fast, efficient, and accurate methods are an extension of the classical spectral methods of high-dimensional random spaces. Designed to simulate complex systems subject to random inputs, these methods are widely used in many areas of computer science and engineering. The book introduces polynomial approximation theory and probability theory; describes the basic theory of gPC methods through numerical examples and rigorous development; details the procedure for converting stochastic equations into deterministic ones; using both the Galerkin and collocation approaches; and discusses the distinct differences and challenges arising from high-dimensional problems. The last section is devoted to the application of gPC methods to critical areas such as inverse problems and data assimilation. Ideal for use by graduate students and researchers both in the classroom and for self-study, Numerical Methods for Stochastic Computations provides the required tools for in-depth research related to stochastic computations. The first graduate-level textbook to focus on the fundamentals of numerical methods for stochastic computations Ideal introduction for graduate courses or self-study Fast, efficient, and accurate numerical methods Polynomial approximation theory and probability theory included Basic gPC methods illustrated through examples

Uncertainty Quantification in Laminated Composites

Author : Sudip Dey
Publisher : CRC Press
ISBN 13 : 1498784461
Total Pages : 375 pages
Book Rating : 4.4/5 (987 download)

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Book Synopsis Uncertainty Quantification in Laminated Composites by : Sudip Dey

Download or read book Uncertainty Quantification in Laminated Composites written by Sudip Dey and published by CRC Press. This book was released on 2018-09-19 with total page 375 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the last few decades, uncertainty quantification in composite materials and structures has gained a lot of attention from the research community as a result of industrial requirements. This book presents computationally efficient uncertainty quantification schemes following meta-model-based approaches for stochasticity in material and geometric parameters of laminated composite structures. Several metamodels have been studied and comparative results have been presented for different static and dynamic responses. Results for sensitivity analyses are provided for a comprehensive coverage of the relative importance of different material and geometric parameters in the global structural responses.

Fundamentals of Design of Experiments for Automotive Engineering Volume I

Author : Young J. Chiang
Publisher : SAE International
ISBN 13 : 1468606034
Total Pages : 358 pages
Book Rating : 4.4/5 (686 download)

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Book Synopsis Fundamentals of Design of Experiments for Automotive Engineering Volume I by : Young J. Chiang

Download or read book Fundamentals of Design of Experiments for Automotive Engineering Volume I written by Young J. Chiang and published by SAE International. This book was released on 2023-11-28 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt: In a world where innovation and sustainability are paramount, Fundamentals of Design of Experiments for Automotive Engineering: Volume I serves as a definitive guide to harnessing the power of statistical thinking in product development. As first of four volumes in SAE International’s DOE for Product Reliability Growth series, this book presents a practical, application-focused approach by emphasizing DOE as a dynamic tool for automotive engineers. It showcases real-world examples, demonstrating how process improvements and system optimizations can significantly enhance product reliability. The author, Yung Chiang, leverages extensive product development expertise to present a comprehensive process that ensures product performance and reliability throughout its entire lifecycle. Whether individuals are involved in research, design, testing, manufacturing, or marketing, this essential reference equips them with the skills needed to excel in their respective roles. This book explores the potential of Reliability and Sustainability with DOE, featuring the following topics: - Fundamental prerequisites for deploying DOE: Product reliability processes, measurement uncertainty, failure analysis, and design for reliability. - Full factorial design 2K: A system identification tool for relating objectives to factors and understanding main and interactive effects. - Fractional factorial design 2RK-P: Ideal for identifying main effects and 2-factor interactions. - General fractional factorial design LK-P: Systematically identification of significant inputs and analysis of nonlinear behaviors. - Composite designs as response surface methods: Resolving interactions and optimizing decisions with limited factors. - Adapting to practical challenges with “short” DOE: Leveraging optimization schemes like D-optimality, and A-optimality for optimal results. Readers are encouraged not to allow product failures to hinder progress but to embrace the "statistical thinking" embedded in DOE. This book can illuminate the path to designing products that stand the test of time, resulting in satisfied customers and thriving businesses. (ISBN 9781468606027, ISBN 9781468606034, ISBN 9781468606041, DOI 10.4271/9781468606034)

Fundamentals of Uncertainty Quantification for Engineers

Author : Yan Wang
Publisher : Elsevier
ISBN 13 : 9780443136610
Total Pages : 0 pages
Book Rating : 4.1/5 (366 download)

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Book Synopsis Fundamentals of Uncertainty Quantification for Engineers by : Yan Wang

Download or read book Fundamentals of Uncertainty Quantification for Engineers written by Yan Wang and published by Elsevier. This book was released on 2024-04-01 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fundamentals of Uncertainty Quantification for Engineers provides a comprehensive introduction to uncertainty quantification (UQ) accompanied by a wide variety of applied examples, implementation details, and practical exercises to reinforce the concepts outlined in the book. It starts with review of the history of probability theory and recent development of UQ methods in the domains of applied mathematics and data science. Major concepts of probability axioms, conditional probability, and Bayes' rule are discussed and examples of probability distributions in parametric data analysis, reliability, risk analysis, and materials informatics are included. Random processes, sampling methods, and surrogate modeling techniques including multivariate polynomial regression, Gaussian process regression, multi-fidelity surrogate, support-vector machine, and decision tress are also covered. Methods for model selection, calibration, and validation are introduced next, followed by chapters on sensitivity analysis, stochastic expansion methods, Markov models, and non-probabilistic methods. The book concludes with a chapter describing the methods that can be used to predict UQ in systems, such as Monte Carlo, stochastic expansion, upscaling, Langevin dynamics, and inverse problems, with example applications in multiscale modeling, simulations, and materials design.

Handbook of Performability Engineering

Author : Krishna B. Misra
Publisher : Springer Science & Business Media
ISBN 13 : 1848001312
Total Pages : 1331 pages
Book Rating : 4.8/5 (48 download)

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Book Synopsis Handbook of Performability Engineering by : Krishna B. Misra

Download or read book Handbook of Performability Engineering written by Krishna B. Misra and published by Springer Science & Business Media. This book was released on 2008-08-24 with total page 1331 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dependability and cost effectiveness are primarily seen as instruments for conducting international trade in the free market environment. These factors cannot be considered in isolation of each other. This handbook considers all aspects of performability engineering. The book provides a holistic view of the entire life cycle of activities of the product, along with the associated cost of environmental preservation at each stage, while maximizing the performance.

Engineering Emergence

Author : Larry B. Rainey
Publisher : CRC Press
ISBN 13 : 1351694855
Total Pages : 548 pages
Book Rating : 4.3/5 (516 download)

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Book Synopsis Engineering Emergence by : Larry B. Rainey

Download or read book Engineering Emergence written by Larry B. Rainey and published by CRC Press. This book was released on 2018-09-03 with total page 548 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book examines the nature of emergence in context of man-made (i.e. engineered) systems, in general, and system of systems engineering applications, specifically. It investigates emergence to interrogate or explore the domain space from a modeling and simulation perspective to facilitate understanding, detection, classification, prediction, control, and visualization of the phenomenon. Written by leading international experts, the text is the first to address emergence from an engineering perspective. "System engineering has a long and proud tradition of establishing the integrative view of systems. The field, however, has not always embraced and assimilated well the lessons and implications from research on complex adaptive systems. As the editors’ note, there have been no texts on Engineering Emergence: Principles and Applications. It is therefore especially useful to have this new, edited book that pulls together so many of the key elements, ranging from the theoretical to the practical, and tapping into advances in methods, tools, and ways to study system complexity. Drs. Rainey and Jamshidi are to be congratulated both for their vision of the book and their success in recruiting contributors with so much to say. Most notable, however, is that this is a book with engineering at its core. It uses modeling and simulation as the language in which to express principles and insights in ways that include tight thinking and rigor despite dealing with notably untidy and often surprising phenomena." — Paul K. Davis, RAND and Frederick S. Pardee RAND Graduate School The first chapter is an introduction and overview to the text. The book provides 12 chapters that have a theoretical foundation for this subject. Includes 7 specific example chapters of how various modeling and simulation paradigms/techniques can be used to investigate emergence in an engineering context to facilitate understanding, detection, classification, prediction, control and visualization of emergent behavior. The final chapter offers lessons learned and the proposed way-ahead for this discipline.