Using Fidelity

Computer simulations is a fundamental tool of the design process in many engineering disciplines including aerospace engineering. However, although high-fidelity numerical models are accurate, they can be computationally expensive with evaluation time for a single design as long as hours, days or even weeks. Simulation-driven design using conventional optimization techniques may be therefore prohibitive. This book explores the alternative: performing computationally efficient design using surrogate-based optimization, where the high-fidelity model is replaced by its computationally cheap but still reasonably accurate representation: a surrogate. The emphasis is on physics-based surrogates. Application-wise, the focus is on aerodynamics and the methods and techniques described in the book are demonstrated using aerodynamic shape optimization cases. Applications in other engineering fields are also demonstrated. State-of-the-art techniques and a depth of coverage never published before make this a unique and essential book for all researchers working in aerospace and other engineering areas and dealing with optimization, computationally expensive design problems, and simulation-driven design. Contents:Motivation and Problem Formulation:IntroductionAerodynamic Shape OptimizationOptimization Techniques:Simulation-Driven Design: Direct MethodsSurrogate-Based OptimizationSBO with Approximation-Based SurrogatesSBO with Physics-Based SurrogatesAerodynamics Modeling:Geometry ParameterizationHigh-Fidelity Aerodynamic ModelsLow-Fidelity Aerodynamics ModelsApplications:Transonic Airfoil Shape DesignTransonic Wing Shape DesignSubsonic Shape DesignSelected Applications of Surrogate-Based Optimization in Other AreasSurrogate-Based Optimization with MATLABConclusion:Practical Aspects of Variable-Fidelity Design Readership: Graduate students and researchers in the field of engineering, in particular, aerospace engineering. Key Features:Gathers a number of relevant techniques that were never compiled in one publication before, and certain state-of-the-art techniques have never been published in book formCompact and self-contained introduction to the area of surrogate-based optimization and variable-fidelity optimizationAt present, this is the only book available on the market that offers coverage of variable-fidelity optimization methodsKeywords:Aerodynamic Shape Optimization;Computational Fluid Dynamics (CFD);Surrogate Modeling;Surrogate-based Optimization;Variable-fidelity Simulations;Simulation-driven Design

This book investigates two types of static multi-fidelity surrogates modeling approaches, sequential multi-fidelity surrogates modeling approaches, the multi-fidelity surrogates-assisted efficient global optimization, reliability analysis, robust design optimization, and evolutionary optimization. Multi-fidelity surrogates have attracted a significant amount of attention in simulation-based design and optimization in recent years. Some real-life engineering design problems, such as prediction of angular distortion in the laser welding, optimization design of micro-aerial vehicle fuselage, and optimization design of metamaterial vibration isolator, are also provided to illustrate the ability and merits of multi-fidelity surrogates in support of engineering design. Specifically, lots of illustrative examples are adopted throughout the book to help explain the approaches in a more “hands-on” manner. This book is a useful reference for postgraduates and researchers of mechanical engineering, as well as engineers of enterprises in related fields.

Tom Rademacher wishes someone had handed him this sort of book along with his teaching degree: a clear-eyed, frank, boots-on-the ground account of what he was getting into. But first he had to write it. And as 2014’s Minnesota Teacher of the Year, Rademacher knows what he’s talking about. Less a how-to manual than a tribute to an impossible and impossibly rewarding profession, It Won’t Be Easy captures the experience of teaching in all its messy glory. The book follows a year of teaching, with each chapter tackling a different aspect of the job. Pulling no punches (and resisting no punch lines), he writes about establishing yourself in a new building; teaching meaningful classes, keeping students a priority; investigating how race, gender, and identity affect your work; and why it’s a good idea to keep an extra pair of pants at school. Along the way he answers the inevitable and the unanticipated questions, from what to do with Google to how to tell if you’re really a terrible teacher, to why “Keep your head down” might well be the worst advice for a new teacher. Though directed at prospective and newer teachers, It Won’t Be Easy is mercifully short on jargon and long on practical wisdom, accessible to anyone—teacher, student, parent, pundit—who is interested in a behind-the-curtain look at teaching and willing to understand that, while there are no simple answers, there is power in learning to ask the right questions.

This book addresses computationally-efficient multi-objective optimization of antenna structures using variable-fidelity electromagnetic simulations, surrogate modeling techniques, and design space reduction methods. Based on contemporary research, it formulates multi-objective design tasks, highlights related challenges in the context of antenna design, and discusses solution approaches. Specific focus is on providing methodologies for handling computationally expensive simulation models of antenna structures in the sense of their multi-objective optimization. Also given is a summary of recent developments in antenna design optimization using variable-fidelity simulation models. Numerous examples of real-world antenna design problems are provided along with discussions and recommendations for the readers interested in applying the considered methods in their design work.Written with researchers and students in mind, topics covered can also be applied across a broad spectrum of aeronautical, mechanical, electrical, biomedical and civil engineering. It is of particular interest to those dealing with optimization, computationally expensive design tasks and simulation-driven design.

Did you know that 1 out of every 12 dollars invested in mutual funds is invested in the industry giant, Fidelity? Although more and more people are investing their money in mutual fund companies, can this really help you reach your financial goals? Author Jack Bowers reveals to readers in his book, "Successful Investing with Fidelity Funds, that Fidelity funds are extremely important in building significant wealth with long-term investing. "What I hope to establish is a framework for investing with Fidelity," says Bower, "one that takes away some of the uncertainty and confusion that can exist when trying to make investment decisions on your own." Drawing from his experience as a chief investment strategist for a money management firm, Bowers tackles such topics as: Fidelity's Strengths and Weaknesses The Benefits and Risks of Long-Term Investing Designing a Suitable Portfolio How and When to Avoid Loan Fees Bowers will also utilize his expert insights when offering advice regarding "Ten Fidelity Managers to Watch" and "The VIP Alternative" as well as taking a look at taxes, compounding, and long-term rates of return."Successful Investing with Fidelity Funds is an extensive guide that will benefit both the experienced and first time Fidelity funds investor. About the Author Jack Bowers is the editor of "Fidelity Monitor," an independent newsletter that focuses exclusively on Fidelity mutual funds and, according to "The Wall Street Journal, ..."ranks as the top-performing mutual fund newsletter for the past five years."

The International Conference on Intelligent Computing (ICIC) was formed to p- vide an annual forum dedicated to the emerging and challenging topics in artificial intelligence, machine learning, bioinformatics, and computational biology, etc. It aims to bring together researchers and practitioners from both academia and ind- try to share ideas, problems and solutions related to the multifaceted aspects of intelligent computing. ICIC 2008, held in Shanghai, China, September 15–18, 2008, constituted the 4th International Conference on Intelligent Computing. It built upon the success of ICIC 2007, ICIC 2006 and ICIC 2005 held in Qingdao, Kunming and Hefei, China, 2007, 2006 and 2005, respectively. This year, the conference concentrated mainly on the theories and methodologies as well as the emerging applications of intelligent computing. Its aim was to unify the picture of contemporary intelligent computing techniques as an integral concept that highlights the trends in advanced computational intelligence and bridges theoretical research with applications. Therefore, the theme for this conference was “Emerging Intelligent Computing Technology and Applications”. Papers focusing on this theme were solicited, addressing theories, methodologies, and applications in science and technology.

Treatment Fidelity in Studies of Educational Intervention is a detailed guide to the increasing emphasis on methodological rigor and implementation fidelity in educational research. A timely contribution to the field, this book offers practical guidance and systematic research on the nature of implementation fidelity in experimental settings, and provides strategies for combining fidelity-related data with other data types to evaluate a program’s impact in schools and other educational settings. With contributions from leading scholars in the area of research methods in education, Treatment Fidelity synthesizes recommendations for current measurement practices, case studies of recent or ongoing research programs, and technical evaluation reports on studies that measure and model fidelity as part of estimating a treatment’s impact. Intended for scholars, professionals, and graduate students interested in school-based intervention, this volume presents information on how to address implementation in applied research.

Computational optimization is an important paradigm with a wide range of applications. In virtually all branches of engineering and industry, we almost always try to optimize something - whether to minimize the cost and energy consumption, or to maximize profits, outputs, performance and efficiency. In many cases, this search for optimality is challenging, either because of the high computational cost of evaluating objectives and constraints, or because of the nonlinearity, multimodality, discontinuity and uncertainty of the problem functions in the real-world systems. Another complication is that most problems are often NP-hard, that is, the solution time for finding the optimum increases exponentially with the problem size. The development of efficient algorithms and specialized techniques that address these difficulties is of primary importance for contemporary engineering, science and industry. This book consists of 12 self-contained chapters, contributed from worldwide experts who are working in these exciting areas. The book strives to review and discuss the latest developments concerning optimization and modelling with a focus on methods and algorithms for computational optimization. It also covers well-chosen, real-world applications in science, engineering and industry. Main topics include derivative-free optimization, multi-objective evolutionary algorithms, surrogate-based methods, maximum simulated likelihood estimation, support vector machines, and metaheuristic algorithms. Application case studies include aerodynamic shape optimization, microwave engineering, black-box optimization, classification, economics, inventory optimization and structural optimization. This graduate level book can serve as an excellent reference for lecturers, researchers and students in computational science, engineering and industry.