Reduction Approximation Machine Learning Surrogates Emulators And Simulators

Author : Gianluigi Rozza,Giovanni Stabile,Max Gunzburger,Marta D'Elia
Publisher : Springer
Page : 0 pages
File Size : 42,7 Mb
Release : 2024-06-03
Category : Mathematics
ISBN : 3031550595

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Reduction, Approximation, Machine Learning, Surrogates, Emulators and Simulators by Gianluigi Rozza,Giovanni Stabile,Max Gunzburger,Marta D'Elia Pdf

This volume is focused on the review of recent algorithmic and mathematical advances and the development of new research directions for Mathematical Model Approximations via RAMSES (Reduced order models, Approximation theory, Machine learning, Surrogates, Emulators, Simulators) in the setting of parametrized partial differential equations also with sparse and noisy data in high-dimensional parameter spaces. The book is a valuable resource for researchers, as well as masters and Ph.D students.

Author : Gianluigi Rozza
Publisher : Springer Nature
Page : 265 pages
File Size : 47,9 Mb
Release : 2024-06-29
Category : Electronic
ISBN : 9783031550607

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Reduction, Approximation, Machine Learning, Surrogates, Emulators and Simulators by Gianluigi Rozza Pdf

Author : Timon Rabczuk,Klaus-Jürgen Bathe
Publisher : Springer Nature
Page : 456 pages
File Size : 50,8 Mb
Release : 2023-11-04
Category : Technology & Engineering
ISBN : 9783031366444

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Machine Learning in Modeling and Simulation by Timon Rabczuk,Klaus-Jürgen Bathe Pdf

Machine learning (ML) approaches have been extensively and successfully employed in various areas, like in economics, medical predictions, face recognition, credit card fraud detection, and spam filtering. There is clearly also the potential that ML techniques developed in Engineering and the Sciences will drastically increase the possibilities of analysis and accelerate the design to analysis time. With the use of ML techniques, coupled to conventional methods like finite element and digital twin technologies, new avenues of modeling and simulation can be opened but the potential of these ML techniques needs to still be fully harvested, with the methods developed and enhanced. The objective of this book is to provide an overview of ML in Engineering and the Sciences presenting fundamental theoretical ingredients with a focus on the next generation of computer modeling in Engineering and the Sciences in which the exciting aspects of machine learning are incorporated. The book is of value to any researcher and practitioner interested in research or applications of ML in the areas of scientific modeling and computer aided engineering.

Author : Lesley Walls,Matthew Revie,Tim Bedford
Publisher : CRC Press
Page : 6507 pages
File Size : 49,8 Mb
Release : 2016-11-25
Category : Technology & Engineering
ISBN : 9781315349169

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Risk, Reliability and Safety: Innovating Theory and Practice by Lesley Walls,Matthew Revie,Tim Bedford Pdf

The safe and reliable performance of many systems with which we interact daily has been achieved through the analysis and management of risk. From complex infrastructures to consumer durables, from engineering systems and technologies used in transportation, health, energy, chemical, oil, gas, aerospace, maritime, defence and other sectors, the management of risk during design, manufacture, operation and decommissioning is vital. Methods and models to support risk-informed decision-making are well established but are continually challenged by technology innovations, increasing interdependencies, and changes in societal expectations. Risk, Reliability and Safety contains papers describing innovations in theory and practice contributed to the scientific programme of the European Safety and Reliability conference (ESREL 2016), held at the University of Strathclyde in Glasgow, Scotland (25—29 September 2016). Authors include scientists, academics, practitioners, regulators and other key individuals with expertise and experience relevant to specific areas. Papers include domain specific applications as well as general modelling methods. Papers cover evaluation of contemporary solutions, exploration of future challenges, and exposition of concepts, methods and processes. Topics include human factors, occupational health and safety, dynamic and systems reliability modelling, maintenance optimisation, uncertainty analysis, resilience assessment, risk and crisis management.

Author : Robert B. Gramacy
Publisher : CRC Press
Page : 560 pages
File Size : 52,6 Mb
Release : 2020-03-10
Category : Mathematics
ISBN : 9781000766202

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Surrogates by Robert B. Gramacy Pdf

Computer simulation experiments are essential to modern scientific discovery, whether that be in physics, chemistry, biology, epidemiology, ecology, engineering, etc. Surrogates are meta-models of computer simulations, used to solve mathematical models that are too intricate to be worked by hand. Gaussian process (GP) regression is a supremely flexible tool for the analysis of computer simulation experiments. This book presents an applied introduction to GP regression for modelling and optimization of computer simulation experiments. Features: • Emphasis on methods, applications, and reproducibility. • R code is integrated throughout for application of the methods. • Includes more than 200 full colour figures. • Includes many exercises to supplement understanding, with separate solutions available from the author. • Supported by a website with full code available to reproduce all methods and examples. The book is primarily designed as a textbook for postgraduate students studying GP regression from mathematics, statistics, computer science, and engineering. Given the breadth of examples, it could also be used by researchers from these fields, as well as from economics, life science, social science, etc.

Author : Alexander Forrester,András Sobester,Andy Keane
Publisher : John Wiley & Sons
Page : 228 pages
File Size : 53,7 Mb
Release : 2008-09-15
Category : Technology & Engineering
ISBN : 9780470770795

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Engineering Design via Surrogate Modelling by Alexander Forrester,András Sobester,Andy Keane Pdf

Surrogate models expedite the search for promising designs by standing in for expensive design evaluations or simulations. They provide a global model of some metric of a design (such as weight, aerodynamic drag, cost, etc.), which can then be optimized efficiently. Engineering Design via Surrogate Modelling is a self-contained guide to surrogate models and their use in engineering design. The fundamentals of building, selecting, validating, searching and refining a surrogate are presented in a manner accessible to novices in the field. Figures are used liberally to explain the key concepts and clearly show the differences between the various techniques, as well as to emphasize the intuitive nature of the conceptual and mathematical reasoning behind them. More advanced and recent concepts are each presented in stand-alone chapters, allowing the reader to concentrate on material pertinent to their current design problem, and concepts are clearly demonstrated using simple design problems. This collection of advanced concepts (visualization, constraint handling, coping with noisy data, gradient-enhanced modelling, multi-fidelity analysis and multiple objectives) represents an invaluable reference manual for engineers and researchers active in the area. Engineering Design via Surrogate Modelling is complemented by a suite of Matlab codes, allowing the reader to apply all the techniques presented to their own design problems. By applying statistical modelling to engineering design, this book bridges the wide gap between the engineering and statistics communities. It will appeal to postgraduates and researchers across the academic engineering design community as well as practising design engineers. Provides an inclusive and practical guide to using surrogates in engineering design. Presents the fundamentals of building, selecting, validating, searching and refining a surrogate model. Guides the reader through the practical implementation of a surrogate-based design process using a set of case studies from real engineering design challenges. Accompanied by a companion website featuring Matlab software at http://www.wiley.com/go/forrester

Author : Lorenz Biegler,George Biros,Omar Ghattas,Matthias Heinkenschloss,David Keyes,Bani Mallick,Luis Tenorio,Bart van Bloemen Waanders,Karen Willcox,Youssef Marzouk
Publisher : John Wiley & Sons
Page : 403 pages
File Size : 44,8 Mb
Release : 2011-06-24
Category : Mathematics
ISBN : 9781119957584

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Large-Scale Inverse Problems and Quantification of Uncertainty by Lorenz Biegler,George Biros,Omar Ghattas,Matthias Heinkenschloss,David Keyes,Bani Mallick,Luis Tenorio,Bart van Bloemen Waanders,Karen Willcox,Youssef Marzouk Pdf

This book focuses on computational methods for large-scale statistical inverse problems and provides an introduction to statistical Bayesian and frequentist methodologies. Recent research advances for approximation methods are discussed, along with Kalman filtering methods and optimization-based approaches to solving inverse problems. The aim is to cross-fertilize the perspectives of researchers in the areas of data assimilation, statistics, large-scale optimization, applied and computational mathematics, high performance computing, and cutting-edge applications. The solution to large-scale inverse problems critically depends on methods to reduce computational cost. Recent research approaches tackle this challenge in a variety of different ways. Many of the computational frameworks highlighted in this book build upon state-of-the-art methods for simulation of the forward problem, such as, fast Partial Differential Equation (PDE) solvers, reduced-order models and emulators of the forward problem, stochastic spectral approximations, and ensemble-based approximations, as well as exploiting the machinery for large-scale deterministic optimization through adjoint and other sensitivity analysis methods. Key Features: Brings together the perspectives of researchers in areas of inverse problems and data assimilation. Assesses the current state-of-the-art and identify needs and opportunities for future research. Focuses on the computational methods used to analyze and simulate inverse problems. Written by leading experts of inverse problems and uncertainty quantification. Graduate students and researchers working in statistics, mathematics and engineering will benefit from this book.

Author : Alfio Quarteroni,Gianluigi Rozza
Publisher : Springer
Page : 338 pages
File Size : 55,7 Mb
Release : 2014-06-05
Category : Mathematics
ISBN : 9783319020907

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Reduced Order Methods for Modeling and Computational Reduction by Alfio Quarteroni,Gianluigi Rozza Pdf

This monograph addresses the state of the art of reduced order methods for modeling and computational reduction of complex parametrized systems, governed by ordinary and/or partial differential equations, with a special emphasis on real time computing techniques and applications in computational mechanics, bioengineering and computer graphics. Several topics are covered, including: design, optimization, and control theory in real-time with applications in engineering; data assimilation, geometry registration, and parameter estimation with special attention to real-time computing in biomedical engineering and computational physics; real-time visualization of physics-based simulations in computer science; the treatment of high-dimensional problems in state space, physical space, or parameter space; the interactions between different model reduction and dimensionality reduction approaches; the development of general error estimation frameworks which take into account both model and discretization effects. This book is primarily addressed to computational scientists interested in computational reduction techniques for large scale differential problems.

Author : Thomas J. Santner,Brian J. Williams,William I. Notz
Publisher : Springer
Page : 436 pages
File Size : 48,8 Mb
Release : 2019-01-08
Category : Mathematics
ISBN : 9781493988471

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The Design and Analysis of Computer Experiments by Thomas J. Santner,Brian J. Williams,William I. Notz Pdf

This book describes methods for designing and analyzing experiments that are conducted using a computer code, a computer experiment, and, when possible, a physical experiment. Computer experiments continue to increase in popularity as surrogates for and adjuncts to physical experiments. Since the publication of the first edition, there have been many methodological advances and software developments to implement these new methodologies. The computer experiments literature has emphasized the construction of algorithms for various data analysis tasks (design construction, prediction, sensitivity analysis, calibration among others), and the development of web-based repositories of designs for immediate application. While it is written at a level that is accessible to readers with Masters-level training in Statistics, the book is written in sufficient detail to be useful for practitioners and researchers. New to this revised and expanded edition: • An expanded presentation of basic material on computer experiments and Gaussian processes with additional simulations and examples • A new comparison of plug-in prediction methodologies for real-valued simulator output • An enlarged discussion of space-filling designs including Latin Hypercube designs (LHDs), near-orthogonal designs, and nonrectangular regions • A chapter length description of process-based designs for optimization, to improve good overall fit, quantile estimation, and Pareto optimization • A new chapter describing graphical and numerical sensitivity analysis tools • Substantial new material on calibration-based prediction and inference for calibration parameters • Lists of software that can be used to fit models discussed in the book to aid practitioners

Author : Nello Cristianini,John Shawe-Taylor
Publisher : Cambridge University Press
Page : 216 pages
File Size : 54,7 Mb
Release : 2000-03-23
Category : Computers
ISBN : 0521780195

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An Introduction to Support Vector Machines and Other Kernel-based Learning Methods by Nello Cristianini,John Shawe-Taylor Pdf

This is a comprehensive introduction to Support Vector Machines, a generation learning system based on advances in statistical learning theory.

Author : Organization for Economic Cooperation and Development
Publisher : Organization for Economic Co-Operation & Development
Page : 0 pages
File Size : 49,5 Mb
Release : 2017
Category : Groundwater
ISBN : 9264281525

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Groundwater Allocation by Organization for Economic Cooperation and Development Pdf

Groundwater allocation determines who is able to use groundwater resources, how, when and where. It directly affects the value (economic, ecological, socio-cultural) that individuals and society obtain from groundwater, today and in the future. Building on the 2015 OECD publication Water Resources Allocation: Sharing Risks and Opportunities, this report focuses on groundwater and how its allocation can be improved in terms of economic efficiency, environmental effectiveness and social equity. Drawing on an analysis of groundwater's distinctive features and nine case studies of groundwater allocation in a range of countries, the report provides practical policy guidance for groundwater allocation in the form of a "health check". This health check can be used to assess the performance of current arrangements and manage the transition towards improved allocation.

Author : Philippe Gourbesville,Jean Cunge,Guy Caignaert
Publisher : Springer
Page : 1231 pages
File Size : 45,8 Mb
Release : 2018-02-26
Category : Science
ISBN : 9789811072185

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Advances in Hydroinformatics by Philippe Gourbesville,Jean Cunge,Guy Caignaert Pdf

This book gathers a collection of extended papers based on presentations given during the SimHydro 2017 conference, held in Sophia Antipolis, Nice, France on June 14–16, 2017. It focuses on how to choose the right model in applied hydraulics and considers various aspects, including the modeling and simulation of fast hydraulic transients, 3D modeling, uncertainties and multiphase flows. The book explores both limitations and performance of current models and presents the latest developments in new numerical schemes, high-performance computing, multiphysics and multiscale methods, and better interaction with field or scale model data. It gathers the lastest theoretical and innovative developments in the modeling field and presents some of the most advance applications on various water related topics like uncertainties, flood simulation and complex hydraulic applications. Given its breadth of coverage, it addresses the needs and interests of practitioners, stakeholders, researchers and engineers alike.

Author : Carl Edward Rasmussen,Christopher K. I. Williams
Publisher : MIT Press
Page : 266 pages
File Size : 43,6 Mb
Release : 2005-11-23
Category : Computers
ISBN : 9780262182539

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Gaussian Processes for Machine Learning by Carl Edward Rasmussen,Christopher K. I. Williams Pdf

A comprehensive and self-contained introduction to Gaussian processes, which provide a principled, practical, probabilistic approach to learning in kernel machines. Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning community over the past decade, and this book provides a long-needed systematic and unified treatment of theoretical and practical aspects of GPs in machine learning. The treatment is comprehensive and self-contained, targeted at researchers and students in machine learning and applied statistics. The book deals with the supervised-learning problem for both regression and classification, and includes detailed algorithms. A wide variety of covariance (kernel) functions are presented and their properties discussed. Model selection is discussed both from a Bayesian and a classical perspective. Many connections to other well-known techniques from machine learning and statistics are discussed, including support-vector machines, neural networks, splines, regularization networks, relevance vector machines and others. Theoretical issues including learning curves and the PAC-Bayesian framework are treated, and several approximation methods for learning with large datasets are discussed. The book contains illustrative examples and exercises, and code and datasets are available on the Web. Appendixes provide mathematical background and a discussion of Gaussian Markov processes.

Author : IWA Task Group on Biofilm Modeling
Publisher : IWA Publishing
Page : 194 pages
File Size : 55,7 Mb
Release : 2006-04-30
Category : Science
ISBN : 9781843390879

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Mathematical Modeling of Biofilms by IWA Task Group on Biofilm Modeling Pdf

Over 90% of bacterial biomass exists in the form of biofilms. The ability of bacteria to attach to surfaces and to form biofilms often is an important competitive advantage for them over bacteria growing in suspension. Some biofilms are "good" in natural and engineered systems; they are responsible for nutrient cycling in nature and are used to purify waters in engineering processes. Other biofilms are "bad" when they cause fouling and infections of humans and plants. Whether we want to promote good biofilms or eliminate bad biofilms, we need to understand how they work and what works to control them. Mathematical Modeling of Biofilms provides guidelines for the selection and use of mathematical models of biofilms. The whole range of existing models - from simple analytical expressions to complex numerical models - is covered. The application of the models for the solution of typical problems is demonstrated, and the performance of the models is tested in comparative studies. With the dramatic evolution of the computational capacity still going on, modeling tools for research and practice will become more and more significant in the next few years. This report provides the foundation to understand the models and to select the most appropriate one for a given use. Mathematical Modeling of Biofilms gives a state-of-the-art overview that is especially valuable for educating students, new biofilm researchers, and design engineers. Through a series of three benchmark problems, the report demonstrates how to use the different models and indicates when simple or highly complex models are most appropriate. This is the first report to give a quantitative comparison of existing biofilm models. The report supports model-based design of biofilm reactors. The report can be used as basis for teaching biofilm-system modeling. The report provides the foundation for researchers seeking to use biofilm modeling or to develop new biofilm models. Scientific and Technical Report No.18

Author : Barry Blesser,Linda-Ruth Salter
Publisher : MIT Press
Page : 453 pages
File Size : 44,8 Mb
Release : 2009-09-18
Category : Architecture
ISBN : 9780262513173

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Spaces Speak, Are You Listening? by Barry Blesser,Linda-Ruth Salter Pdf

How we experience space by listening: the concepts of aural architecture, with examples ranging from Gothic cathedrals to surround sound home theater. We experience spaces not only by seeing but also by listening. We can navigate a room in the dark, and "hear" the emptiness of a house without furniture. Our experience of music in a concert hall depends on whether we sit in the front row or under the balcony. The unique acoustics of religious spaces acquire symbolic meaning. Social relationships are strongly influenced by the way that space changes sound. In Spaces Speak, Are You Listening?, Barry Blesser and Linda-Ruth Salter examine auditory spatial awareness: experiencing space by attentive listening. Every environment has an aural architecture.The audible attributes of physical space have always contributed to the fabric of human culture, as demonstrated by prehistoric multimedia cave paintings, classical Greek open-air theaters, Gothic cathedrals, acoustic geography of French villages, modern music reproduction, and virtual spaces in home theaters. Auditory spatial awareness is a prism that reveals a culture's attitudes toward hearing and space. Some listeners can learn to "see" objects with their ears, but even without training, we can all hear spatial geometry such as an open door or low ceiling. Integrating contributions from a wide range of disciplines—including architecture, music, acoustics, evolution, anthropology, cognitive psychology, audio engineering, and many others—Spaces Speak, Are You Listening? establishes the concepts and language of aural architecture. These concepts provide an interdisciplinary guide for anyone interested in gaining a better understanding of how space enhances our well-being. Aural architecture is not the exclusive domain of specialists. Accidentally or intentionally, we all function as aural architects.