Download or read book Probabilistic Design for Optimization and Robustness for Engineers written by Bryan Dodson and published by John Wiley & Sons. This book was released on 2014-10-06 with total page 275 pages. Available in PDF, EPUB and Kindle. Book excerpt: Probabilistic Design for Optimization and Robustness: Presents the theory of modeling with variation using physical models and methods for practical applications on designs more insensitive to variation. Provides a comprehensive guide to optimization and robustness for probabilistic design. Features examples, case studies and exercises throughout. The methods presented can be applied to a wide range of disciplines such as mechanics, electrics, chemistry, aerospace, industry and engineering. This text is supported by an accompanying website featuring videos, interactive animations to aid the readers understanding.

Download or read book Probabilistic Design for Optimization and Robustness for Engineers written by Bryan Dodson and published by John Wiley & Sons. This book was released on 2014-07-21 with total page 267 pages. Available in PDF, EPUB and Kindle. Book excerpt: Probabilistic Design for Optimization and Robustness: Presents the theory of modeling with variation using physical models and methods for practical applications on designs more insensitive to variation. Provides a comprehensive guide to optimization and robustness for probabilistic design. Features examples, case studies and exercises throughout. The methods presented can be applied to a wide range of disciplines such as mechanics, electrics, chemistry, aerospace, industry and engineering. This text is supported by an accompanying website featuring videos, interactive animations to aid the readers understanding.

Download or read book Engineering Design Optimization written by Joaquim R. R. A. Martins and published by Cambridge University Press. This book was released on 2021-11-18 with total page 653 pages. Available in PDF, EPUB and Kindle. Book excerpt: Based on course-tested material, this rigorous yet accessible graduate textbook covers both fundamental and advanced optimization theory and algorithms. It covers a wide range of numerical methods and topics, including both gradient-based and gradient-free algorithms, multidisciplinary design optimization, and uncertainty, with instruction on how to determine which algorithm should be used for a given application. It also provides an overview of models and how to prepare them for use with numerical optimization, including derivative computation. Over 400 high-quality visualizations and numerous examples facilitate understanding of the theory, and practical tips address common issues encountered in practical engineering design optimization and how to address them. Numerous end-of-chapter homework problems, progressing in difficulty, help put knowledge into practice. Accompanied online by a solutions manual for instructors and source code for problems, this is ideal for a one- or two-semester graduate course on optimization in aerospace, civil, mechanical, electrical, and chemical engineering departments.

Download or read book Probabilistic Engineering Design written by James N. Siddall and published by CRC Press. This book was released on 1983-09-29 with total page 552 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Probabilistic Engineering Design Optimization written by Samuel Phillip Pullen and published by . This book was released on 1996 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Probabilistic and Randomized Methods for Design under Uncertainty written by Giuseppe Calafiore and published by Springer Science & Business Media. This book was released on 2006-03-06 with total page 454 pages. Available in PDF, EPUB and Kindle. Book excerpt: Probabilistic and Randomized Methods for Design under Uncertainty is a collection of contributions from the world’s leading experts in a fast-emerging branch of control engineering and operations research. The book will be bought by university researchers and lecturers along with graduate students in control engineering and operational research.

Download or read book Scalable Optimization via Probabilistic Modeling written by Martin Pelikan and published by Springer Science & Business Media. This book was released on 2006-09-25 with total page 363 pages. Available in PDF, EPUB and Kindle. Book excerpt: I’m not usually a fan of edited volumes. Too often they are an incoherent hodgepodge of remnants, renegades, or rejects foisted upon an unsuspecting reading public under a misleading or fraudulent title. The volume Scalable Optimization via Probabilistic Modeling: From Algorithms to Applications is a worthy addition to your library because it succeeds on exactly those dimensions where so many edited volumes fail. For example, take the title, Scalable Optimization via Probabilistic M- eling: From Algorithms to Applications. You need not worry that you’re going to pick up this book and ?nd stray articles about anything else. This book focuseslikealaserbeamononeofthehottesttopicsinevolutionary compu- tion over the last decade or so: estimation of distribution algorithms (EDAs). EDAs borrow evolutionary computation’s population orientation and sel- tionism and throw out the genetics to give us a hybrid of substantial power, elegance, and extensibility. The article sequencing in most edited volumes is hard to understand, but from the get go the editors of this volume have assembled a set of articles sequenced in a logical fashion. The book moves from design to e?ciency enhancement and then concludes with relevant applications. The emphasis on e?ciency enhancement is particularly important, because the data-mining perspectiveimplicitinEDAsopensuptheworldofoptimizationtonewme- ods of data-guided adaptation that can further speed solutions through the construction and utilization of e?ective surrogates, hybrids, and parallel and temporal decompositions.

Download or read book Design Optimization Under Uncertainty written by Weifei Hu and published by Springer Nature. This book was released on 2023-12-22 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces the fundamentals of probability, statistical, and reliability concepts, the classical methods of uncertainty quantification and analytical reliability analysis, and the state-of-the-art approaches of design optimization under uncertainty (e.g., reliability-based design optimization and robust design optimization). The topics include basic concepts of probability and distributions, uncertainty quantification using probabilistic methods, classical reliability analysis methods, time-variant reliability analysis methods, fundamentals of deterministic design optimization, reliability-based design optimization, robust design optimization, other methods of design optimization under uncertainty, and engineering applications of design optimization under uncertainty.

Download or read book Reliability based Structural Design written by Seung-Kyum Choi and published by Springer Science & Business Media. This book was released on 2006-11-15 with total page 309 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides readers with an understanding of the fundamentals and applications of structural reliability, stochastic finite element method, reliability analysis via stochastic expansion, and optimization under uncertainty. It examines the use of stochastic expansions, including polynomial chaos expansion and Karhunen-Loeve expansion for the reliability analysis of practical engineering problems.

Download or read book Probabilistic Machine Learning for Advanced Engineering Design Optimization and Diagnostics written by Sudeepta Mondal and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Mechanical systems often involve multi-physics interactions and complex nonlinearities due to which design optimization and diagnostics become challenging. The inherent complexity of the processes, along with limitations in data availability, mandates principled uncertainty estimates in modeling, something which probabilistic machine learning techniques offer. Budget restrictions pose serious data limitations in the development and testing phases of the product pipeline, particularly in the presence of a hierarchy in the associated multi-physics process models with respect to their fidelity levels. This thesis focuses on some fundamental developments and applications of probabilistic machine learning strategies in design optimization and advanced diagnostics. Novel multi-fidelity surrogate modeling and optimization strategies will be discussed with respect to data-driven engineering design optimization problems, for example, process parameter optimization in additive manufacturing, phase-field model calibration and compressor rotor design. Even in applications involving high data volumes, quantification of aleatoric and epistemic uncertainties in the dataset often becomes useful in having conservative estimates of the predictions, an application of which has been discussed with respect to optimal selection of chemistry solvers for IC engine simulations. During the product testing phase, advanced diagnostics in performance critical applications mandate the detection of anomalies with as little data as possible. The thesis also focuses on some of the applications of a class of probabilistic sequential models, called hidden Markov models in the detection of thermoacoustic instabilities and lean blow-out in combustion systems using acoustic and chemiluminescence sensor data. The framework achieves computationally efficient and robust predictions of regime changes with parsimonious data requirements, which deems it suitable for online applications.

Download or read book Optimization Of Structural And Mechanical Systems written by Jasbir S Arora and published by World Scientific. This book was released on 2007-09-05 with total page 610 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational optimization methods have matured over the last few years due to extensive research by applied mathematicians and engineers. These methods have been applied to many practical applications. Several general-purpose optimization programs and programs for specific engineering applications have become available to solve particular optimization problems.Written by leading researchers in the field of optimization, this highly readable book covers state-of-the-art computational algorithms as well as applications of optimization to structural and mechanical systems. Formulations of the problems and numerical solutions are presented, and topics requiring further research are also suggested.

Download or read book Probability Applications in Mechanical Design written by Franklin Fisher and published by CRC Press. This book was released on 2000-06-15 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: The authors of this text seek to clarify mechanical fatigue and design problems by applying probability and computer analysis, and further extending the uses of probability to determine mechanical reliability and achieve optimization. The work solves examples using commercially available software. It is formatted with examples and problems for use in a one-semester graduate course.

Download or read book Structural Seismic Design Optimization and Earthquake Engineering Formulations and Applications written by Plevris, Vagelis and published by IGI Global. This book was released on 2012-05-31 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt: Throughout the past few years, there has been extensive research done on structural design in terms of optimization methods or problem formulation. But, much of this attention has been on the linear elastic structural behavior, under static loading condition. Such a focus has left researchers scratching their heads as it has led to vulnerable structural configurations. What researchers have left out of the equation is the element of seismic loading. It is essential for researchers to take this into account in order to develop earthquake resistant real-world structures. Structural Seismic Design Optimization and Earthquake Engineering: Formulations and Applications focuses on the research around earthquake engineering, in particular, the field of implementation of optimization algorithms in earthquake engineering problems. Topics discussed within this book include, but are not limited to, simulation issues for the accurate prediction of the seismic response of structures, design optimization procedures, soft computing applications, and other important advancements in seismic analysis and design where optimization algorithms can be implemented. Readers will discover that this book provides relevant theoretical frameworks in order to enhance their learning on earthquake engineering as it deals with the latest research findings and their practical implementations, as well as new formulations and solutions.

Download or read book 18th International Probabilistic Workshop written by José C. Matos and published by Springer Nature. This book was released on 2021-05-07 with total page 855 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume presents the proceedings of the 18th International Probabilistic Workshop (IPW), which was held in Guimarães, Portugal in May 2021. Probabilistic methods are currently of crucial importance for research and developments in the field of engineering, which face challenges presented by new materials and technologies and rapidly changing societal needs and values. Contemporary needs related to, for example, performance-based design, service-life design, life-cycle analysis, product optimization, assessment of existing structures and structural robustness give rise to new developments as well as accurate and practically applicable probabilistic and statistical engineering methods to support these developments. These proceedings are a valuable resource for anyone interested in contemporary developments in the field of probabilistic engineering applications.

Download or read book Modern Trends in Structural and Solid Mechanics 3 written by Noel Challamel and published by John Wiley & Sons. This book was released on 2021-06-29 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book – comprised of three separate volumes – presents the recent developments and research discoveries in structural and solid mechanics; it is dedicated to Professor Isaac Elishakoff. This third volume is devoted to non-deterministic mechanics. Modern Trends in Structural and Solid Mechanics 3 has broad scope, covering topics such: design optimization under uncertainty, interval field approaches, convex analysis, quantum inspired topology optimization and stochastic dynamics. The book is illustrated by many applications in the field of aerospace engineering, mechanical engineering, civil engineering, biomedical engineering and automotive engineering. This book is intended for graduate students and researchers in the field of theoretical and applied mechanics.

Download or read book Engineering Design Reliability Handbook written by Efstratios Nikolaidis and published by CRC Press. This book was released on 2004-12-22 with total page 1216 pages. Available in PDF, EPUB and Kindle. Book excerpt: Researchers in the engineering industry and academia are making important advances on reliability-based design and modeling of uncertainty when data is limited. Non deterministic approaches have enabled industries to save billions by reducing design and warranty costs and by improving quality. Considering the lack of comprehensive and defini

Download or read book Engineering Design Reliability Applications written by Efstratios Nikolaidis and published by CRC Press. This book was released on 2007-09-19 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the current, increasingly aggressive business environment, crucial decisions about product design often involve significant uncertainty. Highlighting the competitive advantage available from using risk-based reliability design, Engineering Design Reliability Applications: For the Aerospace, Automotive, and Ship Industries provides an overview of