Adaptive Reduced Basis Methods For Multiscale Problems And Large Scale Pde Constrained Optimization
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Adaptive Reduced Basis Methods For Multiscale Problems And Large Scale Pde Constrained Optimization
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Author : Tim Keil
language : en
Publisher:
Release Date : 2022
Adaptive Reduced Basis Methods For Multiscale Problems And Large Scale Pde Constrained Optimization written by Tim Keil and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with categories.
Real Time Pde Constrained Optimization
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Author : Lorenz T. Biegler
language : en
Publisher: SIAM
Release Date : 2007-01-01
Real Time Pde Constrained Optimization written by Lorenz T. Biegler and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-01-01 with Mathematics categories.
Many engineering and scientific problems in design, control, and parameter estimation can be formulated as optimization problems that are governed by partial differential equations (PDEs). The complexities of the PDEs--and the requirement for rapid solution--pose significant difficulties. A particularly challenging class of PDE-constrained optimization problems is characterized by the need for real-time solution, i.e., in time scales that are sufficiently rapid to support simulation-based decision making. Real-Time PDE-Constrained Optimization, the first book devoted to real-time optimization for systems governed by PDEs, focuses on new formulations, methods, and algorithms needed to facilitate real-time, PDE-constrained optimization. In addition to presenting state-of-the-art algorithms and formulations, the text illustrates these algorithms with a diverse set of applications that includes problems in the areas of aerodynamics, biology, fluid dynamics, medicine, chemical processes, homeland security, and structural dynamics. Audience: readers who have expertise in simulation and are interested in incorporating optimization into their simulations, who have expertise in numerical optimization and are interested in adapting optimization methods to the class of infinite-dimensional simulation problems, or who have worked in "offline" optimization contexts and are interested in moving to "online" optimization.
Large Scale Scientific Computations
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Author : Ivan Lirkov
language : en
Publisher: Springer Nature
Release Date : 2024-05-23
Large Scale Scientific Computations written by Ivan Lirkov and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-23 with Computers categories.
This book constitutes the refereed proceedings of the 14th International Conference on Large-Scale Scientific Computations, LSSC 2023, held in Sozopol, Bulgaria, during June 5–9, 2023. The 49 full papers included in this book were carefully reviewed and selected from 61 submissions. They were organized in topical sections as follows: preconditioning and multilevel methods; fractures and mixed dimensional modeling: discretizations, solvers, and methodology; machine learning and model order reduction for large scale predictive simulations; fractional differential problems: theoretical aspects, algorithms and applications; variational analysis and optimal control; stochastic optimal control and numerical methods in economics and finance; tensor methods for big data analytics and low-rank approximations of PDEs solutions; applications of metaheuristics to large-scale problems; large-scale models: numerical methods, parallel computations and applications; HPC and HPDA: algorithms and applications.
Error Control Adaptive Discretizations And Applications Part 2
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Author :
language : en
Publisher: Elsevier
Release Date : 2024-10-31
Error Control Adaptive Discretizations And Applications Part 2 written by and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-31 with Science categories.
Error Control, Adaptive Discretizations, and Applications, Volume 59, Part Two highlights new advances in the field, with this new volume presenting interesting chapters written by an international board of authors. Chapters in this release cover hp adaptive Discontinuous Galerkin strategies driven by a posteriori error estimation with application to aeronautical flow problems,An anisotropic mesh adaptation method based on gradient recovery and optimal shape elements, and Model reduction techniques for parametrized nonlinear partial differential equations. - Covers multi-scale modeling - Includes updates on data-driven modeling - Presents the latest information on large deformations of multi-scale materials
Frontiers In Pde Constrained Optimization
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Author : Harbir Antil
language : en
Publisher: Springer
Release Date : 2018-10-12
Frontiers In Pde Constrained Optimization written by Harbir Antil and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-12 with Mathematics categories.
This volume provides a broad and uniform introduction of PDE-constrained optimization as well as to document a number of interesting and challenging applications. Many science and engineering applications necessitate the solution of optimization problems constrained by physical laws that are described by systems of partial differential equations (PDEs). As a result, PDE-constrained optimization problems arise in a variety of disciplines including geophysics, earth and climate science, material science, chemical and mechanical engineering, medical imaging and physics. This volume is divided into two parts. The first part provides a comprehensive treatment of PDE-constrained optimization including discussions of problems constrained by PDEs with uncertain inputs and problems constrained by variational inequalities. Special emphasis is placed on algorithm development and numerical computation. In addition, a comprehensive treatment of inverse problems arising in the oil and gas industry is provided. The second part of this volume focuses on the application of PDE-constrained optimization, including problems in optimal control, optimal design, and inverse problems, among other topics.
Large Scale Scientific Computing
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Author : Ivan Lirkov
language : en
Publisher: Springer Nature
Release Date : 2022-03-17
Large Scale Scientific Computing written by Ivan Lirkov and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-17 with Computers categories.
This book constitutes revised selected papers from the 13th International Conference on Large-Scale Scientific Computing, LSSC 23021, which was held in Sozopol, Bulgaria, during June 7-11, 2021. The 60 papers included in this book were carefully reviewed and selected from a total of 73 submissions. The volume also includes two invited talks in full paper length. The papers were organized in topical sections as follows: Fractional diffusion problems: numerical methods, algorithms and applications; large-scale models: numerical methods, parallel computations and applications; application of metaheuristics to large-scale problems; advanced discretizations and solvers for coupled systems of partial differential equations; optimal control of ODEs, PDEs and applications; tensor and matrix factorization for big-data analysis; machine learning and model order reduction for large scale predictive simulations; HPC and big data: algorithms and applications; and contributed papers.
Snapshot Based Methods And Algorithms
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Author : Peter Benner
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2020-12-16
Snapshot Based Methods And Algorithms written by Peter Benner and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-16 with Mathematics categories.
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 second volume focuses on applications in engineering, biomedical engineering, computational physics and computer science.
An Introduction To Element Based Galerkin Methods On Tensor Product Bases
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Author : Francis X. Giraldo
language : en
Publisher: Springer Nature
Release Date : 2020-10-30
An Introduction To Element Based Galerkin Methods On Tensor Product Bases written by Francis X. Giraldo and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-30 with Mathematics categories.
This book introduces the reader to solving partial differential equations (PDEs) numerically using element-based Galerkin methods. Although it draws on a solid theoretical foundation (e.g. the theory of interpolation, numerical integration, and function spaces), the book’s main focus is on how to build the method, what the resulting matrices look like, and how to write algorithms for coding Galerkin methods. In addition, the spotlight is on tensor-product bases, which means that only line elements (in one dimension), quadrilateral elements (in two dimensions), and cubes (in three dimensions) are considered. The types of Galerkin methods covered are: continuous Galerkin methods (i.e., finite/spectral elements), discontinuous Galerkin methods, and hybridized discontinuous Galerkin methods using both nodal and modal basis functions. In addition, examples are included (which can also serve as student projects) for solving hyperbolic and elliptic partial differential equations, including both scalar PDEs and systems of equations.
Least Squares Finite Element Methods
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Author : Pavel B. Bochev
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-04-28
Least Squares Finite Element Methods written by Pavel B. Bochev and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-04-28 with Mathematics categories.
Since their emergence in the early 1950s, ?nite element methods have become one of the most versatile and powerful methodologies for the approximate numerical solution of partial differential equations. At the time of their inception, ?nite e- ment methods were viewed primarily as a tool for solving problems in structural analysis. However, it did not take long to discover that ?nite element methods could be applied with equal success to problems in other engineering and scienti?c ?elds. Today, ?nite element methods are also in common use, and indeed are often the method of choice, for incompressible ?uid ?ow, heat transfer, electromagnetics, and advection-diffusion-reaction problems, just to name a few. Given the early conn- tion between ?nite element methods and problems engendered by energy minimi- tion principles, it is not surprising that the ?rst mathematical analyses of ?nite e- ment methods were given in the environment of the classical Rayleigh–Ritz setting. Yet again, using the fertile soil provided by functional analysis in Hilbert spaces, it did not take long for the rigorous analysis of ?nite element methods to be extended to many other settings. Today, ?nite element methods are unsurpassed with respect to their level of theoretical maturity.
Reduced Basis Methods For Partial Differential Equations
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Author : Alfio Quarteroni
language : en
Publisher: Springer
Release Date : 2015-08-19
Reduced Basis Methods For Partial Differential Equations written by Alfio Quarteroni and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-08-19 with Mathematics categories.
This book provides a basic introduction to reduced basis (RB) methods for problems involving the repeated solution of partial differential equations (PDEs) arising from engineering and applied sciences, such as PDEs depending on several parameters and PDE-constrained optimization. The book presents a general mathematical formulation of RB methods, analyzes their fundamental theoretical properties, discusses the related algorithmic and implementation aspects, and highlights their built-in algebraic and geometric structures. More specifically, the authors discuss alternative strategies for constructing accurate RB spaces using greedy algorithms and proper orthogonal decomposition techniques, investigate their approximation properties and analyze offline-online decomposition strategies aimed at the reduction of computational complexity. Furthermore, they carry out both a priori and a posteriori error analysis. The whole mathematical presentation is made more stimulating by the use of representative examples of applicative interest in the context of both linear and nonlinear PDEs. Moreover, the inclusion of many pseudocodes allows the reader to easily implement the algorithms illustrated throughout the text. The book will be ideal for upper undergraduate students and, more generally, people interested in scientific computing. All these pseudocodes are in fact implemented in a MATLAB package that is freely available at https://github.com/redbkit