Reduced-Order Modeling (ROM) for Simulation and Optimization

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Publisher : Springer
ISBN 13 : 3319753193
Total Pages : 179 pages
Book Rating : 4.3/5 (197 download)

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Book Synopsis Reduced-Order Modeling (ROM) for Simulation and Optimization by : Winfried Keiper

Download or read book Reduced-Order Modeling (ROM) for Simulation and Optimization written by Winfried Keiper and published by Springer. This book was released on 2018-04-11 with total page 179 pages. Available in PDF, EPUB and Kindle. Book excerpt: This edited monograph collects research contributions and addresses the advancement of efficient numerical procedures in the area of model order reduction (MOR) for simulation, optimization and control. The topical scope includes, but is not limited to, new out-of-the-box algorithmic solutions for scientific computing, e.g. reduced basis methods for industrial problems and MOR approaches for electrochemical processes. The target audience comprises research experts and practitioners in the field of simulation, optimization and control, but the book may also be beneficial for graduate students alike.

Reduced Order Methods for Modeling and Computational Reduction

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Publisher : Springer
ISBN 13 : 3319020900
Total Pages : 338 pages
Book Rating : 4.3/5 (19 download)

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Book Synopsis Reduced Order Methods for Modeling and Computational Reduction by : Alfio Quarteroni

Download or read book Reduced Order Methods for Modeling and Computational Reduction written by Alfio Quarteroni and published by Springer. This book was released on 2014-06-05 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Machine Learning, Low-Rank Approximations and Reduced Order Modeling in Computational Mechanics

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Publisher : MDPI
ISBN 13 : 3039214098
Total Pages : 254 pages
Book Rating : 4.0/5 (392 download)

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Book Synopsis Machine Learning, Low-Rank Approximations and Reduced Order Modeling in Computational Mechanics by : Felix Fritzen

Download or read book Machine Learning, Low-Rank Approximations and Reduced Order Modeling in Computational Mechanics written by Felix Fritzen and published by MDPI. This book was released on 2019-09-18 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: The use of machine learning in mechanics is booming. Algorithms inspired by developments in the field of artificial intelligence today cover increasingly varied fields of application. This book illustrates recent results on coupling machine learning with computational mechanics, particularly for the construction of surrogate models or reduced order models. The articles contained in this compilation were presented at the EUROMECH Colloquium 597, « Reduced Order Modeling in Mechanics of Materials », held in Bad Herrenalb, Germany, from August 28th to August 31th 2018. In this book, Artificial Neural Networks are coupled to physics-based models. The tensor format of simulation data is exploited in surrogate models or for data pruning. Various reduced order models are proposed via machine learning strategies applied to simulation data. Since reduced order models have specific approximation errors, error estimators are also proposed in this book. The proposed numerical examples are very close to engineering problems. The reader would find this book to be a useful reference in identifying progress in machine learning and reduced order modeling for computational mechanics.

Applications

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Publisher : Walter de Gruyter GmbH & Co KG
ISBN 13 : 3110499002
Total Pages : 474 pages
Book Rating : 4.1/5 (14 download)

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Book Synopsis Applications by : Peter Benner

Download or read book Applications written by Peter Benner and published by Walter de Gruyter GmbH & Co KG. This book was released on 2020-12-07 with total page 474 pages. Available in PDF, EPUB and Kindle. Book excerpt: An increasing complexity of models used to predict real-world systems leads to the need for algorithms to replace complex models with far simpler ones, while preserving the accuracy of the predictions. This three-volume handbook covers methods as well as applications. This third volume focuses on applications in engineering, biomedical engineering, computational physics and computer science.

Recent Numerical Advances in Fluid Mechanics

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Publisher : MDPI
ISBN 13 : 3039364022
Total Pages : 302 pages
Book Rating : 4.0/5 (393 download)

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Book Synopsis Recent Numerical Advances in Fluid Mechanics by : Omer San

Download or read book Recent Numerical Advances in Fluid Mechanics written by Omer San and published by MDPI. This book was released on 2020-07-03 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent decades, the field of computational fluid dynamics has made significant advances in enabling advanced computing architectures to understand many phenomena in biological, geophysical, and engineering fluid flows. Almost all research areas in fluids use numerical methods at various complexities: from molecular to continuum descriptions; from laminar to turbulent regimes; from low speed to hypersonic, from stencil-based computations to meshless approaches; from local basis functions to global expansions, as well as from first-order approximation to high-order with spectral accuracy. Many successful efforts have been put forth in dynamic adaptation strategies, e.g., adaptive mesh refinement and multiresolution representation approaches. Furthermore, with recent advances in artificial intelligence and heterogeneous computing, the broader fluids community has gained the momentum to revisit and investigate such practices. This Special Issue, containing a collection of 13 papers, brings together researchers to address recent numerical advances in fluid mechanics.

13th International Conference on Compressors and Their Systems

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Publisher : Springer Nature
ISBN 13 : 3031426630
Total Pages : 877 pages
Book Rating : 4.0/5 (314 download)

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Book Synopsis 13th International Conference on Compressors and Their Systems by : Matthew Read

Download or read book 13th International Conference on Compressors and Their Systems written by Matthew Read and published by Springer Nature. This book was released on 2024-01-01 with total page 877 pages. Available in PDF, EPUB and Kindle. Book excerpt: This new proceedings discusses developments in air, gas and refrigeration compressors, vacuum pumps, and expanders. It is the 13th edition of the International Conference on Compressors and their Systems, a three-day conference organised by the Centre for Compressors Technology at City, University of London in collaboration with, among other, the MEchE, IIR, and IOR. The conference offers a platform to identify current challenges in the field and provide the essential content and direction to shape future research. The International Conference on Compressors and their Systems series began in 1999 as a result of industrial consultation and a need for academic collaboration. Initially, the conference was organised by the Fluid Machinery Group of the Institution of Mechanical Engineers (IMechE) with the support of Holroyd. From 2009, the Centre for Compressor Technology at City, University of London took over its management and the conference is now one of the main conventions, taking place biennially in the UK, becoming world-renowned for its place in industry and academia to gather and discuss a broad range of topical issues related to compressors and compression systems. This year's conference has the theme "Compressors and Expanders in Future Energy Systems” and will be of interest to researchers and engineers in industry.

Data-driven modeling and optimization in fluid dynamics: From physics-based to machine learning approaches

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Author :
Publisher : Frontiers Media SA
ISBN 13 : 2832510701
Total Pages : 178 pages
Book Rating : 4.8/5 (325 download)

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Book Synopsis Data-driven modeling and optimization in fluid dynamics: From physics-based to machine learning approaches by : Michel Bergmann

Download or read book Data-driven modeling and optimization in fluid dynamics: From physics-based to machine learning approaches written by Michel Bergmann and published by Frontiers Media SA. This book was released on 2023-01-05 with total page 178 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Model Order Reduction: Theory, Research Aspects and Applications

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Author :
Publisher : Springer Science & Business Media
ISBN 13 : 3540788417
Total Pages : 471 pages
Book Rating : 4.5/5 (47 download)

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Book Synopsis Model Order Reduction: Theory, Research Aspects and Applications by : Wilhelmus H. Schilders

Download or read book Model Order Reduction: Theory, Research Aspects and Applications written by Wilhelmus H. Schilders and published by Springer Science & Business Media. This book was released on 2008-08-27 with total page 471 pages. Available in PDF, EPUB and Kindle. Book excerpt: The idea for this book originated during the workshop “Model order reduction, coupled problems and optimization” held at the Lorentz Center in Leiden from S- tember 19–23, 2005. During one of the discussion sessions, it became clear that a book describing the state of the art in model order reduction, starting from the very basics and containing an overview of all relevant techniques, would be of great use for students, young researchers starting in the ?eld, and experienced researchers. The observation that most of the theory on model order reduction is scattered over many good papers, making it dif?cult to ?nd a good starting point, was supported by most of the participants. Moreover, most of the speakers at the workshop were willing to contribute to the book that is now in front of you. The goal of this book, as de?ned during the discussion sessions at the workshop, is three-fold: ?rst, it should describe the basics of model order reduction. Second, both general and more specialized model order reduction techniques for linear and nonlinear systems should be covered, including the use of several related numerical techniques. Third, the use of model order reduction techniques in practical appli- tions and current research aspects should be discussed. We have organized the book according to these goals. In Part I, the rationale behind model order reduction is explained, and an overview of the most common methods is described.

Machine Learning for Model Order Reduction

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Author :
Publisher : Springer
ISBN 13 : 3319757148
Total Pages : 93 pages
Book Rating : 4.3/5 (197 download)

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Book Synopsis Machine Learning for Model Order Reduction by : Khaled Salah Mohamed

Download or read book Machine Learning for Model Order Reduction written by Khaled Salah Mohamed and published by Springer. This book was released on 2018-03-02 with total page 93 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Book discusses machine learning for model order reduction, which can be used in modern VLSI design to predict the behavior of an electronic circuit, via mathematical models that predict behavior. The author describes techniques to reduce significantly the time required for simulations involving large-scale ordinary differential equations, which sometimes take several days or even weeks. This method is called model order reduction (MOR), which reduces the complexity of the original large system and generates a reduced-order model (ROM) to represent the original one. Readers will gain in-depth knowledge of machine learning and model order reduction concepts, the tradeoffs involved with using various algorithms, and how to apply the techniques presented to circuit simulations and numerical analysis. Introduces machine learning algorithms at the architecture level and the algorithm levels of abstraction; Describes new, hybrid solutions for model order reduction; Presents machine learning algorithms in depth, but simply; Uses real, industrial applications to verify algorithms.

Proceedings of the 8th International Conference on Foundations of Computer-Aided Process Design

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Publisher : Elsevier
ISBN 13 : 0444634428
Total Pages : 840 pages
Book Rating : 4.4/5 (446 download)

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Book Synopsis Proceedings of the 8th International Conference on Foundations of Computer-Aided Process Design by :

Download or read book Proceedings of the 8th International Conference on Foundations of Computer-Aided Process Design written by and published by Elsevier. This book was released on 2014-07-14 with total page 840 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume collects together the presentations at the Eighth International Conference on Foundations of Computer-Aided Process Design, FOCAPD-2014, an event that brings together researchers, educators, and practitioners to identify new challenges and opportunities for process and product design. The chemical industry is currently entering a new phase of rapid evolution. The availability of low-cost feedstocks from natural gas is causing renewed investment in basic chemicals in the OECD, while societal pressures for sustainability and energy security continue to be key drivers in technology development and product selection. This dynamic environment creates opportunities to launch new products and processes and to demonstrate new methodologies for innovation, synthesis and design. FOCAPD-2014 fosters constructive interaction among thought leaders from academia, industry, and government and provides a showcase for the latest research in product and process design. Focuses exclusively on the fundamentals and applications of computer-aided design for the process industries. Provides a fully archival and indexed record of the FOCAPD14 conference Aligns the FOCAPD series with the ESCAPE and PSE series

Model Reduction of Complex Dynamical Systems

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Publisher : Springer Nature
ISBN 13 : 3030729834
Total Pages : 415 pages
Book Rating : 4.0/5 (37 download)

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Book Synopsis Model Reduction of Complex Dynamical Systems by : Peter Benner

Download or read book Model Reduction of Complex Dynamical Systems written by Peter Benner and published by Springer Nature. This book was released on 2021-08-26 with total page 415 pages. Available in PDF, EPUB and Kindle. Book excerpt: This contributed volume presents some of the latest research related to model order reduction of complex dynamical systems with a focus on time-dependent problems. Chapters are written by leading researchers and users of model order reduction techniques and are based on presentations given at the 2019 edition of the workshop series Model Reduction of Complex Dynamical Systems – MODRED, held at the University of Graz in Austria. The topics considered can be divided into five categories: system-theoretic methods, such as balanced truncation, Hankel norm approximation, and reduced-basis methods; data-driven methods, including Loewner matrix and pencil-based approaches, dynamic mode decomposition, and kernel-based methods; surrogate modeling for design and optimization, with special emphasis on control and data assimilation; model reduction methods in applications, such as control and network systems, computational electromagnetics, structural mechanics, and fluid dynamics; and model order reduction software packages and benchmarks. This volume will be an ideal resource for graduate students and researchers in all areas of model reduction, as well as those working in applied mathematics and theoretical informatics.

Feature Papers

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Publisher : MDPI
ISBN 13 : 3038420700
Total Pages : 405 pages
Book Rating : 4.0/5 (384 download)

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Book Synopsis Feature Papers by : Michael Henson

Download or read book Feature Papers written by Michael Henson and published by MDPI. This book was released on 2018-10-04 with total page 405 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a printed edition of the Special Issue "Feature Papers" that was published in Processes

System- and Data-Driven Methods and Algorithms

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Publisher : Walter de Gruyter GmbH & Co KG
ISBN 13 : 3110497719
Total Pages : 346 pages
Book Rating : 4.1/5 (14 download)

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Book Synopsis System- and Data-Driven Methods and Algorithms by : Peter Benner

Download or read book System- and Data-Driven Methods and Algorithms written by Peter Benner and published by Walter de Gruyter GmbH & Co KG. This book was released on 2021-11-08 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: An increasing complexity of models used to predict real-world systems leads to the need for algorithms to replace complex models with far simpler ones, while preserving the accuracy of the predictions. This two-volume handbook covers methods as well as applications. This first volume focuses on real-time control theory, data assimilation, real-time visualization, high-dimensional state spaces and interaction of different reduction techniques.

Coupled Multiscale Simulation and Optimization in Nanoelectronics

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Publisher : Springer
ISBN 13 : 3662466724
Total Pages : 565 pages
Book Rating : 4.6/5 (624 download)

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Book Synopsis Coupled Multiscale Simulation and Optimization in Nanoelectronics by : Michael Günther

Download or read book Coupled Multiscale Simulation and Optimization in Nanoelectronics written by Michael Günther and published by Springer. This book was released on 2015-06-15 with total page 565 pages. Available in PDF, EPUB and Kindle. Book excerpt: Designing complex integrated circuits relies heavily on mathematical methods and calls for suitable simulation and optimization tools. The current design approach involves simulations and optimizations in different physical domains (device, circuit, thermal, electromagnetic) and in a range of electrical engineering disciplines (logic, timing, power, crosstalk, signal integrity, system functionality). COMSON was a Marie Curie Research Training Network created to meet these new scientific and training challenges by (a) developing new descriptive models that take these mutual dependencies into account, (b) combining these models with existing circuit descriptions in new simulation strategies and (c) developing new optimization techniques that will accommodate new designs. The book presents the main project results in the fields of PDAE modeling and simulation, model order reduction techniques and optimization, based on merging the know-how of three major European semiconductor companies with the combined expertise of university groups specialized in developing suitable mathematical models, numerical schemes and e-learning facilities. In addition, a common Demonstrator Platform for testing mathematical methods and approaches was created to assess whether they are capable of addressing the industry’s problems, and to educate young researchers by providing hands-on experience with state-of-the-art problems.

Large-Scale Inverse Problems and Quantification of Uncertainty

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Author :
Publisher : John Wiley & Sons
ISBN 13 : 1119957583
Total Pages : 403 pages
Book Rating : 4.1/5 (199 download)

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Book Synopsis Large-Scale Inverse Problems and Quantification of Uncertainty by : Lorenz Biegler

Download or read book Large-Scale Inverse Problems and Quantification of Uncertainty written by Lorenz Biegler and published by John Wiley & Sons. This book was released on 2011-06-24 with total page 403 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Handbook of Numerical Simulation of In-Flight Icing

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Author :
Publisher : Springer Nature
ISBN 13 : 3031338456
Total Pages : 1278 pages
Book Rating : 4.0/5 (313 download)

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Book Synopsis Handbook of Numerical Simulation of In-Flight Icing by : Wagdi George Habashi

Download or read book Handbook of Numerical Simulation of In-Flight Icing written by Wagdi George Habashi and published by Springer Nature. This book was released on 2024-01-12 with total page 1278 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Handbook of Numerical Simulation of In-Flight Icing covers an array of methodologies and technologies on numerical simulation of in-flight icing and its applications. Comprised of contributions from internationally recognized experts from the Americas, Asia, and the EU, this authoritative, self-contained reference includes best practices and specification data spanning the gamut of simulation tools available internationally that can be used to speed up the certification of aircraft and make them safer to fly into known icing. The collection features nine sections concentrating on aircraft, rotorcraft, jet engines, UAVs; ice protection systems, including hot-air, electrothermal, and others; sensors and probes, CFD in the aid of testing, flight simulators, and certification process acceleration methods. Incorporating perspectives from academia, commercial, government R&D, the book is ideal for a range of engineers and scientists concerned with in-flight icing applications.

Advances in Automotive Production Technology – Towards Software-Defined Manufacturing and Resilient Supply Chains

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Publisher : Springer Nature
ISBN 13 : 3031279336
Total Pages : 395 pages
Book Rating : 4.0/5 (312 download)

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Book Synopsis Advances in Automotive Production Technology – Towards Software-Defined Manufacturing and Resilient Supply Chains by : Niklas Kiefl

Download or read book Advances in Automotive Production Technology – Towards Software-Defined Manufacturing and Resilient Supply Chains written by Niklas Kiefl and published by Springer Nature. This book was released on 2023-06-04 with total page 395 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume of the series ARENA2036 compiles the outcome of the 2nd Stuttgart Conference on Automotive Production (SCAP2022). The peer-reviewed contributions in this book are arranged thematically in three parts and cover a wide variety of topics: (A) Software-defined Manufacturing, (B) Data-driven Technologies, and (C) Advanced Manufacturing and Sustainability. SCAP2022 was organized by ARENA2036 in close collaboration with the Institute for Control Engineering of Machine Tools and Manufacturing Units of the University of Stuttgart. The Conference took place on site from November 16 - 18, 2022 and provided the opportunity for national and international scientists to present their latest research results. The conference has taken another big step in becoming an established forum for topics related to the production of the future. The great success of this year's conference will be continued with the next SCAP in 2024 with new forward-looking topics. This is an open access book.