Uncertainty And Error In Computational Simulations

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Uncertainty and Error in Computational Simulations

Author :
Publisher :
ISBN 13 :
Total Pages : 24 pages
Book Rating : 4.:/5 (684 download)

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Book Synopsis Uncertainty and Error in Computational Simulations by :

Download or read book Uncertainty and Error in Computational Simulations written by and published by . This book was released on 1997 with total page 24 pages. Available in PDF, EPUB and Kindle. Book excerpt: The present paper addresses the question: ''What are the general classes of uncertainty and error sources in complex, computational simulations?'' This is the first step of a two step process to develop a general methodology for quantitatively estimating the global modeling and simulation uncertainty in computational modeling and simulation. The second step is to develop a general mathematical procedure for representing, combining and propagating all of the individual sources through the simulation. The authors develop a comprehensive view of the general phases of modeling and simulation. The phases proposed are: conceptual modeling of the physical system, mathematical modeling of the system, discretization of the mathematical model, computer programming of the discrete model, numerical solution of the model, and interpretation of the results. This new view is built upon combining phases recognized in the disciplines of operations research and numerical solution methods for partial differential equations. The characteristics and activities of each of these phases is discussed in general, but examples are given for the fields of computational fluid dynamics and heat transfer. They argue that a clear distinction should be made between uncertainty and error that can arise in each of these phases. The present definitions for uncertainty and error are inadequate and. therefore, they propose comprehensive definitions for these terms. Specific classes of uncertainty and error sources are then defined that can occur in each phase of modeling and simulation. The numerical sources of error considered apply regardless of whether the discretization procedure is based on finite elements, finite volumes, or finite differences. To better explain the broad types of sources of uncertainty and error, and the utility of their categorization, they discuss a coupled-physics example simulation.

Error Estimation and Uncertainty Propagation in Computational Fluid Mechanics

Author : National Aeronautics and Space Adm Nasa
Publisher : Independently Published
ISBN 13 : 9781724087416
Total Pages : 30 pages
Book Rating : 4.0/5 (874 download)

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Book Synopsis Error Estimation and Uncertainty Propagation in Computational Fluid Mechanics by : National Aeronautics and Space Adm Nasa

Download or read book Error Estimation and Uncertainty Propagation in Computational Fluid Mechanics written by National Aeronautics and Space Adm Nasa and published by Independently Published. This book was released on 2018-09-27 with total page 30 pages. Available in PDF, EPUB and Kindle. Book excerpt: Numerical simulation has now become an integral part of engineering design process. Critical design decisions are routinely made based on the simulation results and conclusions. Verification and validation of the reliability of the numerical simulation is therefore vitally important in the engineering design processes. We propose to develop theories and methodologies that can automatically provide quantitative information about the reliability of the numerical simulation by estimating numerical approximation error, computational model induced errors and the uncertainties contained in the mathematical models so that the reliability of the numerical simulation can be verified and validated. We also propose to develop and implement methodologies and techniques that can control the error and uncertainty during the numerical simulation so that the reliability of the numerical simulation can be improved. Zhu, J. Z. and He, Guowei and Bushnell, Dennis M. (Technical Monitor) Langley Research Center NASA/CR-2002-211744, NAS 1.26:211744, ICASE-IR-41

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 in Computational Fluid Dynamics

Author : Hester Bijl
Publisher : Springer Science & Business Media
ISBN 13 : 3319008854
Total Pages : 347 pages
Book Rating : 4.3/5 (19 download)

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Book Synopsis Uncertainty Quantification in Computational Fluid Dynamics by : Hester Bijl

Download or read book Uncertainty Quantification in Computational Fluid Dynamics written by Hester Bijl and published by Springer Science & Business Media. This book was released on 2013-09-20 with total page 347 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fluid flows are characterized by uncertain inputs such as random initial data, material and flux coefficients, and boundary conditions. The current volume addresses the pertinent issue of efficiently computing the flow uncertainty, given this initial randomness. It collects seven original review articles that cover improved versions of the Monte Carlo method (the so-called multi-level Monte Carlo method (MLMC)), moment-based stochastic Galerkin methods and modified versions of the stochastic collocation methods that use adaptive stencil selection of the ENO-WENO type in both physical and stochastic space. The methods are also complemented by concrete applications such as flows around aerofoils and rockets, problems of aeroelasticity (fluid-structure interactions), and shallow water flows for propagating water waves. The wealth of numerical examples provide evidence on the suitability of each proposed method as well as comparisons of different approaches.

Assessing the Reliability of Complex Models

Author : National Research Council
Publisher : National Academies Press
ISBN 13 : 0309256348
Total Pages : 144 pages
Book Rating : 4.3/5 (92 download)

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Book Synopsis Assessing the Reliability of Complex Models by : National Research Council

Download or read book Assessing the Reliability of Complex Models written by National Research Council and published by National Academies Press. This book was released on 2012-07-26 with total page 144 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in computing hardware and algorithms have dramatically improved the ability to simulate complex processes computationally. Today's simulation capabilities offer the prospect of addressing questions that in the past could be addressed only by resource-intensive experimentation, if at all. Assessing the Reliability of Complex Models recognizes the ubiquity of uncertainty in computational estimates of reality and the necessity for its quantification. As computational science and engineering have matured, the process of quantifying or bounding uncertainties in a computational estimate of a physical quality of interest has evolved into a small set of interdependent tasks: verification, validation, and uncertainty of quantification (VVUQ). In recognition of the increasing importance of computational simulation and the increasing need to assess uncertainties in computational results, the National Research Council was asked to study the mathematical foundations of VVUQ and to recommend steps that will ultimately lead to improved processes. Assessing the Reliability of Complex Models discusses changes in education of professionals and dissemination of information that should enhance the ability of future VVUQ practitioners to improve and properly apply VVUQ methodologies to difficult problems, enhance the ability of VVUQ customers to understand VVUQ results and use them to make informed decisions, and enhance the ability of all VVUQ stakeholders to communicate with each other. This report is an essential resource for all decision and policy makers in the field, students, stakeholders, UQ experts, and VVUQ educators and practitioners.

Methodology for Characterizing Modeling and Discretization Uncertainties in Computational Simulation

Author :
Publisher :
ISBN 13 :
Total Pages : 192 pages
Book Rating : 4.:/5 (684 download)

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Book Synopsis Methodology for Characterizing Modeling and Discretization Uncertainties in Computational Simulation by :

Download or read book Methodology for Characterizing Modeling and Discretization Uncertainties in Computational Simulation written by and published by . This book was released on 2000 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: This research effort focuses on methodology for quantifying the effects of model uncertainty and discretization error on computational modeling and simulation. The work is directed towards developing methodologies which treat model form assumptions within an overall framework for uncertainty quantification, for the purpose of developing estimates of total prediction uncertainty. The present effort consists of work in three areas: framework development for sources of uncertainty and error in the modeling and simulation process which impact model structure; model uncertainty assessment and propagation through Bayesian inference methods; and discretization error estimation within the context of non-deterministic analysis.

Uncertainty Quantification In Computational Science: Theory And Application In Fluids And Structural Mechanics

Author : Sunetra Sarkar
Publisher : World Scientific
ISBN 13 : 9814730599
Total Pages : 197 pages
Book Rating : 4.8/5 (147 download)

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Book Synopsis Uncertainty Quantification In Computational Science: Theory And Application In Fluids And Structural Mechanics by : Sunetra Sarkar

Download or read book Uncertainty Quantification In Computational Science: Theory And Application In Fluids And Structural Mechanics written by Sunetra Sarkar and published by World Scientific. This book was released on 2016-08-18 with total page 197 pages. Available in PDF, EPUB and Kindle. Book excerpt: During the last decade, research in Uncertainty Quantification (UC) has received a tremendous boost, in fluid engineering and coupled structural-fluids systems. New algorithms and adaptive variants have also emerged.This timely compendium overviews in detail the current state of the art of the field, including advances in structural engineering, along with the recent focus on fluids and coupled systems. Such a strong compilation of these vibrant research areas will certainly be an inspirational reference material for the scientific community.

Quantification of Uncertainty: Improving Efficiency and Technology

Author : Marta D'Elia
Publisher : Springer Nature
ISBN 13 : 3030487210
Total Pages : 290 pages
Book Rating : 4.0/5 (34 download)

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Book Synopsis Quantification of Uncertainty: Improving Efficiency and Technology by : Marta D'Elia

Download or read book Quantification of Uncertainty: Improving Efficiency and Technology written by Marta D'Elia and published by Springer Nature. This book was released on 2020-07-30 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores four guiding themes – reduced order modelling, high dimensional problems, efficient algorithms, and applications – by reviewing recent algorithmic and mathematical advances and the development of new research directions for uncertainty quantification in the context of partial differential equations with random inputs. Highlighting the most promising approaches for (near-) future improvements in the way uncertainty quantification problems in the partial differential equation setting are solved, and gathering contributions by leading international experts, the book’s content will impact the scientific, engineering, financial, economic, environmental, social, and commercial sectors.

Uncertainty Quantification in Multiscale Materials Modeling

Author : Yan Wang
Publisher : Woodhead Publishing Limited
ISBN 13 : 0081029411
Total Pages : 604 pages
Book Rating : 4.0/5 (81 download)

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Book Synopsis Uncertainty Quantification in Multiscale Materials Modeling by : Yan Wang

Download or read book Uncertainty Quantification in Multiscale Materials Modeling written by Yan Wang and published by Woodhead Publishing Limited. This book was released on 2020-03-12 with total page 604 pages. Available in PDF, EPUB and Kindle. Book excerpt: Uncertainty Quantification in Multiscale Materials Modeling provides a complete overview of uncertainty quantification (UQ) in computational materials science. It provides practical tools and methods along with examples of their application to problems in materials modeling. UQ methods are applied to various multiscale models ranging from the nanoscale to macroscale. This book presents a thorough synthesis of the state-of-the-art in UQ methods for materials modeling, including Bayesian inference, surrogate modeling, random fields, interval analysis, and sensitivity analysis, providing insight into the unique characteristics of models framed at each scale, as well as common issues in modeling across scales.

Computer Simulation Validation

Author : Claus Beisbart
Publisher : Springer
ISBN 13 : 3319707663
Total Pages : 1074 pages
Book Rating : 4.3/5 (197 download)

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Book Synopsis Computer Simulation Validation by : Claus Beisbart

Download or read book Computer Simulation Validation written by Claus Beisbart and published by Springer. This book was released on 2019-04-09 with total page 1074 pages. Available in PDF, EPUB and Kindle. Book excerpt: This unique volume introduces and discusses the methods of validating computer simulations in scientific research. The core concepts, strategies, and techniques of validation are explained by an international team of pre-eminent authorities, drawing on expertise from various fields ranging from engineering and the physical sciences to the social sciences and history. The work also offers new and original philosophical perspectives on the validation of simulations. Topics and features: introduces the fundamental concepts and principles related to the validation of computer simulations, and examines philosophical frameworks for thinking about validation; provides an overview of the various strategies and techniques available for validating simulations, as well as the preparatory steps that have to be taken prior to validation; describes commonly used reference points and mathematical frameworks applicable to simulation validation; reviews the legal prescriptions, and the administrative and procedural activities related to simulation validation; presents examples of best practice that demonstrate how methods of validation are applied in various disciplines and with different types of simulation models; covers important practical challenges faced by simulation scientists when applying validation methods and techniques; offers a selection of general philosophical reflections that explore the significance of validation from a broader perspective. This truly interdisciplinary handbook will appeal to a broad audience, from professional scientists spanning all natural and social sciences, to young scholars new to research with computer simulations. Philosophers of science, and methodologists seeking to increase their understanding of simulation validation, will also find much to benefit from in the text.

Uncertainty in Geometric Computations

Author : Joab Winkler
Publisher : Springer Science & Business Media
ISBN 13 : 1461508134
Total Pages : 220 pages
Book Rating : 4.4/5 (615 download)

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Book Synopsis Uncertainty in Geometric Computations by : Joab Winkler

Download or read book Uncertainty in Geometric Computations written by Joab Winkler and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains the proceedings of the workshop Uncertainty in Geomet ric Computations that was held in Sheffield, England, July 5-6, 2001. A total of 59 delegates from 5 countries in Europe, North America and Asia attended the workshop. The workshop provided a forum for the discussion of com putational methods for quantifying, representing and assessing the effects of uncertainty in geometric computations. It was organised around lectures by invited speakers, and presentations in poster form from participants. Computer simulations and modelling are used frequently in science and engi neering, in applications ranging from the understanding of natural and artificial phenomena, to the design, test and manufacturing stages of production. This widespread use necessarily implies that detailed knowledge of the limitations of computer simulations is required. In particular, the usefulness of a computer simulation is directly dependent on the user's knowledge of the uncertainty in the simulation. Although an understanding of the phenomena being modelled is an important requirement of a good computer simulation, the model will be plagued by deficiencies if the errors and uncertainties in it are not consid ered when the results are analysed. The applications of computer modelling are large and diverse, but the workshop focussed on the management of un certainty in three areas : Geometric modelling, computer vision, and computer graphics.

Verification and Validation in Computational Science and Engineering

Author : Patrick J. Roache
Publisher :
ISBN 13 : 9780913478080
Total Pages : 0 pages
Book Rating : 4.4/5 (78 download)

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Book Synopsis Verification and Validation in Computational Science and Engineering by : Patrick J. Roache

Download or read book Verification and Validation in Computational Science and Engineering written by Patrick J. Roache and published by . This book was released on 1998 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Applied Research in Uncertainty Modeling and Analysis

Author : Bilal M. Ayyub
Publisher : Springer Science & Business Media
ISBN 13 : 0387235507
Total Pages : 547 pages
Book Rating : 4.3/5 (872 download)

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Book Synopsis Applied Research in Uncertainty Modeling and Analysis by : Bilal M. Ayyub

Download or read book Applied Research in Uncertainty Modeling and Analysis written by Bilal M. Ayyub and published by Springer Science & Business Media. This book was released on 2007-12-29 with total page 547 pages. Available in PDF, EPUB and Kindle. Book excerpt: The application areas of uncertainty are numerous and diverse, including all fields of engineering, computer science, systems control and finance. Determining appropriate ways and methods of dealing with uncertainty has been a constant challenge. The theme for this book is better understanding and the application of uncertainty theories. This book, with invited chapters, deals with the uncertainty phenomena in diverse fields. The book is an outgrowth of the Fourth International Symposium on Uncertainty Modeling and Analysis (ISUMA), which was held at the center of Adult Education, College Park, Maryland, in September 2003. All of the chapters have been carefully edited, following a review process in which the editorial committee scrutinized each chapter. The contents of the book are reported in twenty-three chapters, covering more than . . ... pages. This book is divided into six main sections. Part I (Chapters 1-4) presents the philosophical and theoretical foundation of uncertainty, new computational directions in neural networks, and some theoretical foundation of fuzzy systems. Part I1 (Chapters 5-8) reports on biomedical and chemical engineering applications. The sections looks at noise reduction techniques using hidden Markov models, evaluation of biomedical signals using neural networks, and changes in medical image detection using Markov Random Field and Mean Field theory. One of the chapters reports on optimization in chemical engineering processes.

Uncertainty Quantification in Computational Fluid Dynamics and Aircraft Engines

Author : Francesco Montomoli
Publisher : Springer
ISBN 13 : 3319929437
Total Pages : 204 pages
Book Rating : 4.3/5 (199 download)

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Book Synopsis Uncertainty Quantification in Computational Fluid Dynamics and Aircraft Engines by : Francesco Montomoli

Download or read book Uncertainty Quantification in Computational Fluid Dynamics and Aircraft Engines written by Francesco Montomoli and published by Springer. This book was released on 2018-06-21 with total page 204 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces design techniques developed to increase the safety of aircraft engines, and demonstrates how the application of stochastic methods can overcome problems in the accurate prediction of engine lift caused by manufacturing error. This in turn addresses the issue of achieving required safety margins when hampered by limits in current design and manufacturing methods. The authors show that avoiding the potential catastrophe generated by the failure of an aircraft engine relies on the prediction of the correct behaviour of microscopic imperfections. This book shows how to quantify the possibility of such failure, and that it is possible to design components that are inherently less risky and more reliable. This new, updated and significantly expanded edition gives an introduction to engine reliability and safety to contextualise this important issue, evaluates newly-proposed methods for uncertainty quantification as applied to jet engines. Uncertainty Quantification in Computational Fluid Dynamics and Aircraft Engines will be of use to gas turbine manufacturers and designers as well as CFD practitioners, specialists and researchers. Graduate and final year undergraduate students in aerospace or mathematical engineering may also find it of interest.

Probabilistic Methods for the Quantification of Uncertainty and Error in Computational Fluid Dynamics Simulations

Author : John Simon Faragher
Publisher :
ISBN 13 :
Total Pages : 30 pages
Book Rating : 4.:/5 (224 download)

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Book Synopsis Probabilistic Methods for the Quantification of Uncertainty and Error in Computational Fluid Dynamics Simulations by : John Simon Faragher

Download or read book Probabilistic Methods for the Quantification of Uncertainty and Error in Computational Fluid Dynamics Simulations written by John Simon Faragher and published by . This book was released on 2004 with total page 30 pages. Available in PDF, EPUB and Kindle. Book excerpt: The life of engine components is determined by a combination of the material properties and the applied stresses and temperatures. As a consequence of variability in these parameters, the component life is not fixed (deterministic) but stochastic (random) and may be characterised by a probability density function (PDF). In order to reduce the cost of ownership of ADF aircraft these PDFs need to be determined as accurately as possible. Probabilistic techniques offer significant potential for accurate and realistic estimates of component lives by quantifying stochastic elements of an analysis rather than introducing excessive conservatism to allow for them. This report examines the feasibility of using a probabilistic approach for modelling the component temperatures in an engine using CFD (Computational Fluid Dynamics).

Modeling, Design, and Simulation of Systems with Uncertainties

Author : Andreas Rauh
Publisher : Springer Science & Business Media
ISBN 13 : 3642159567
Total Pages : 356 pages
Book Rating : 4.6/5 (421 download)

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Book Synopsis Modeling, Design, and Simulation of Systems with Uncertainties by : Andreas Rauh

Download or read book Modeling, Design, and Simulation of Systems with Uncertainties written by Andreas Rauh and published by Springer Science & Business Media. This book was released on 2011-06-06 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: To describe the true behavior of most real-world systems with sufficient accuracy, engineers have to overcome difficulties arising from their lack of knowledge about certain parts of a process or from the impossibility of characterizing it with absolute certainty. Depending on the application at hand, uncertainties in modeling and measurements can be represented in different ways. For example, bounded uncertainties can be described by intervals, affine forms or general polynomial enclosures such as Taylor models, whereas stochastic uncertainties can be characterized in the form of a distribution described, for example, by the mean value, the standard deviation and higher-order moments. The goal of this Special Volume on Modeling, Design, and Simulation of Systems with Uncertainties is to cover modern methods for dealing with the challenges presented by imprecise or unavailable information. All contributions tackle the topic from the point of view of control, state and parameter estimation, optimization and simulation. Thematically, this volume can be divided into two parts. In the first we present works highlighting the theoretic background and current research on algorithmic approaches in the field of uncertainty handling, together with their reliable software implementation. The second part is concerned with real-life application scenarios from various areas including but not limited to mechatronics, robotics, and biomedical engineering.

Uncertainty Management in Simulation-Optimization of Complex Systems

Author : Gabriella Dellino
Publisher : Springer
ISBN 13 : 1489975470
Total Pages : 282 pages
Book Rating : 4.4/5 (899 download)

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Book Synopsis Uncertainty Management in Simulation-Optimization of Complex Systems by : Gabriella Dellino

Download or read book Uncertainty Management in Simulation-Optimization of Complex Systems written by Gabriella Dellino and published by Springer. This book was released on 2015-06-29 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book aims at illustrating strategies to account for uncertainty in complex systems described by computer simulations. When optimizing the performances of these systems, accounting or neglecting uncertainty may lead to completely different results; therefore, uncertainty management is a major issues in simulation-optimization. Because of its wide field of applications, simulation-optimization issues have been addressed by different communities with different methods, and from slightly different perspectives. Alternative approaches have been developed, also depending on the application context, without any well-established method clearly outperforming the others. This editorial project brings together — as chapter contributors — researchers from different (though interrelated) areas; namely, statistical methods, experimental design, stochastic programming, global optimization, metamodeling, and design and analysis of computer simulation experiments. Editors’ goal is to take advantage of such a multidisciplinary environment, to offer to the readers a much deeper understanding of the commonalities and differences of the various approaches to simulation-based optimization, especially in uncertain environments. Editors aim to offer a bibliographic reference on the topic, enabling interested readers to learn about the state-of-the-art in this research area, also accounting for potential real-world applications to improve also the state-of-the-practice. Besides researchers and scientists of the field, the primary audience for the proposed book includes PhD students, academic teachers, as well as practitioners and professionals. Each of these categories of potential readers present adequate channels for marketing actions, e.g. scientific, academic or professional societies, internet-based communities, and authors or buyers of related publications.