Multiscale Model Reduction

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Multiscale Model Reduction

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Author : Eric Chung
language : en
Publisher: Springer Nature
Release Date : 2023-06-07

Multiscale Model Reduction written by Eric Chung and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-07 with Mathematics categories.

This monograph is devoted to the study of multiscale model reduction methods from the point of view of multiscale finite element methods. Multiscale numerical methods have become popular tools for modeling processes with multiple scales. These methods allow reducing the degrees of freedom based on local offline computations. Moreover, these methods allow deriving rigorous macroscopic equations for multiscale problems without scale separation and high contrast. Multiscale methods are also used to design efficient solvers. This book offers a combination of analytical and numerical methods designed for solving multiscale problems. The book mostly focuses on methods that are based on multiscale finite element methods. Both applications and theoretical developments in this field are presented. The book is suitable for graduate students and researchers, who are interested in this topic.

Model Reduction And Coarse Graining Approaches For Multiscale Phenomena

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Author : Alexander N. Gorban
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-09-22

Model Reduction And Coarse Graining Approaches For Multiscale Phenomena written by Alexander N. Gorban 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 2006-09-22 with Science categories.

Model reduction and coarse-graining are important in many areas of science and engineering. How does a system with many degrees of freedom become one with fewer? How can a reversible micro-description be adapted to the dissipative macroscopic model? These crucial questions, as well as many other related problems, are discussed in this book. All contributions are by experts whose specialities span a wide range of fields within science and engineering.

Fundamentals Of Multiscale Modeling Of Structural Materials

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Author : Wenjie Xia
language : en
Publisher: Elsevier
Release Date : 2022-11-26

Fundamentals Of Multiscale Modeling Of Structural Materials written by Wenjie Xia and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-26 with Technology & Engineering categories.

Fundamentals of Multiscale Modeling of Structural Materials provides a robust introduction to the computational tools, underlying theory, practical applications, and governing physical phenomena necessary to simulate and understand a wide-range of structural materials at multiple time and length scales. The book offers practical guidelines for modeling common structural materials with well-established techniques, outlining detailed modeling approaches for calculating and analyzing mechanical, thermal and transport properties of various structural materials such as metals, cement/concrete, polymers, composites, wood, thin films, and more.Computational approaches based on artificial intelligence and machine learning methods as complementary tools to the physics-based multiscale techniques are discussed as are modeling techniques for additively manufactured structural materials. Special attention is paid to how these methods can be used to develop the next generation of sustainable, resilient and environmentally-friendly structural materials, with a specific emphasis on bridging the atomistic and continuum modeling scales for these materials. - Synthesizes the latest cutting-edge computational multiscale modeling techniques for an array of structural materials - Emphasizes the foundations of the field and offers practical guidelines for modeling material systems with well-established techniques - Covers methods for calculating and analyzing mechanical, thermal and transport properties of various structural materials such as metals, cement/concrete, polymers, composites, wood, and more - Highlights underlying theory, emerging areas, future directions and various applications of the modeling methods covered - Discusses the integration of multiscale modeling and artificial intelligence

Multiscale Modeling Of Heterogeneous Structures

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Author : Jurica Sorić
language : en
Publisher: Springer
Release Date : 2017-11-30

Multiscale Modeling Of Heterogeneous Structures written by Jurica Sorić and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-30 with Science categories.

This book provides an overview of multiscale approaches and homogenization procedures as well as damage evaluation and crack initiation, and addresses recent advances in the analysis and discretization of heterogeneous materials. It also highlights the state of the art in this research area with respect to different computational methods, software development and applications to engineering structures. The first part focuses on defects in composite materials including their numerical and experimental investigations; elastic as well as elastoplastic constitutive models are considered, where the modeling has been performed at macro- and micro levels. The second part is devoted to novel computational schemes applied on different scales and discusses the validation of numerical results. The third part discusses gradient enhanced modeling, in particular quasi-brittle and ductile damage, using the gradient enhanced approach. The final part addresses thermoplasticity, solid-liquid mixtures and ferroelectric models. The contents are based on the international workshop “Multiscale Modeling of Heterogeneous Structures” (MUMO 2016), held in Dubrovnik, Croatia in September 2016.

An Introduction To Multiscale Modeling With Applications

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Author : Pietro Asinari
language : en
Publisher: Società Editrice Esculapio
Release Date : 2013-09-01

An Introduction To Multiscale Modeling With Applications written by Pietro Asinari and has been published by Società Editrice Esculapio this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-09-01 with Science categories.

This book collects the slides prepared for the course of Advanced Engineering Thermodynamics (Master of Science in Mechanical Engineering) and those for the course of Multiscale Modelling and Simulation of Molecular and Mesoscopic Dynamics (PhD Program in Energetics), taught in English at Turin Polytechnic. Here, we provide a broad overview on the different topics taught in our classes. Even though not all topics are presented in the same class, students should be able to more easily reconstruct the connections among different phenomena (and scales), build their own mind map and, eventually, find their own way of deepening the subjects they are more interested in. Several engineering applications have been included. This helps in stressing that very different phenomena are described by transport theory and obey the same underlying fundamental laws of engineering thermodynamics. Detailed tutorials are reported, based on open-source codes for the laboratories (Gromacs, Palabos, OpenFoam and Cantera).

From Microstructure Investigations To Multiscale Modeling

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Author : Delphine Brancherie
language : en
Publisher: John Wiley & Sons
Release Date : 2018-01-04

From Microstructure Investigations To Multiscale Modeling written by Delphine Brancherie and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-04 with Science categories.

Mechanical behaviors of materials are highly influenced by their architectures and/or microstructures. Hence, progress in material science involves understanding and modeling the link between the microstructure and the material behavior at different scales. This book gathers contributions from eminent researchers in the field of computational and experimental material modeling. It presents advanced experimental techniques to acquire the microstructure features together with dedicated numerical and analytical tools to take into account the randomness of the micro-structure.

Coping With Complexity Model Reduction And Data Analysis

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Author : Alexander N. Gorban
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-10-21

Coping With Complexity Model Reduction And Data Analysis written by Alexander N. Gorban 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 2010-10-21 with Mathematics categories.

This volume contains the extended version of selected talks given at the international research workshop "Coping with Complexity: Model Reduction and Data Analysis", Ambleside, UK, August 31 – September 4, 2009. The book is deliberately broad in scope and aims at promoting new ideas and methodological perspectives. The topics of the chapters range from theoretical analysis of complex and multiscale mathematical models to applications in e.g., fluid dynamics and chemical kinetics.

Multiscale Model Reduction Methods For Deterministic And Stochastic Partial Differential Equations

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Author : Maolin Ci
language : en
Publisher:
Release Date : 2014

Multiscale Model Reduction Methods For Deterministic And Stochastic Partial Differential Equations written by Maolin Ci and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014 with Differential equations, Partial categories.

Partial differential equations (PDEs) with multiscale coefficients are very difficult to solve due to the wide range of scales in the solutions. In the thesis, we propose some efficient numerical methods for both deterministic and stochastic PDEs based on the model reduction technique. For the deterministic PDEs, the main purpose of our method is to derive an effective equation for the multiscale problem. An essential ingredient is to decompose the harmonic coordinate into a smooth part and a highly oscillatory part of which the magnitude is small. Such a decomposition plays a key role in our construction of the effective equation. We show that the solution to the effective equation is smooth, and could be resolved on a regular coarse mesh grid. Furthermore, we provide error analysis and show that the solution to the effective equation plus a correction term is close to the original multiscale solution. For the stochastic PDEs, we propose the model reduction based data-driven stochastic method and multilevel Monte Carlo method. In the multiquery, setting and on the assumption that the ratio of the smallest scale and largest scale is not too small, we propose the multiscale data-driven stochastic method. We construct a data-driven stochastic basis and solve the coupled deterministic PDEs to obtain the solutions. For the tougher problems, we propose the multiscale multilevel Monte Carlo method. We apply the multilevel scheme to the effective equations and assemble the stiffness matrices efficiently on each coarse mesh grid. In both methods, the $\KL$ expansion plays an important role in extracting the main parts of some stochastic quantities. For the stochastic PDEs, we propose the model reduction based data-driven stochastic method and multilevel Monte Carlo method. In the multiquery, setting and on the assumption that the ratio of the smallest scale and largest scale is not too small, we propose the multiscale data-driven stochastic method. We construct a data-driven stochastic basis and solve the coupled deterministic PDEs to obtain the solutions. For the tougher problems, we propose the multiscale multilevel Monte Carlo method. We apply the multilevel scheme to the effective equations and assemble the stiffness matrices efficiently on each coarse mesh grid. In both methods, the $\KL$ expansion plays an important role in extracting the main parts of some stochastic quantities.

Separated Representations And Pgd Based Model Reduction

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Author : Francisco Chinesta
language : en
Publisher: Springer
Release Date : 2014-09-02

Separated Representations And Pgd Based Model Reduction written by Francisco Chinesta and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-09-02 with Technology & Engineering categories.

The papers in this volume start with a description of the construction of reduced models through a review of Proper Orthogonal Decomposition (POD) and reduced basis models, including their mathematical foundations and some challenging applications, then followed by a description of a new generation of simulation strategies based on the use of separated representations (space-parameters, space-time, space-time-parameters, space-space,...), which have led to what is known as Proper Generalized Decomposition (PGD) techniques. The models can be enriched by treating parameters as additional coordinates, leading to fast and inexpensive online calculations based on richer offline parametric solutions. Separated representations are analyzed in detail in the course, from their mathematical foundations to their most spectacular applications. It is also shown how such an approximation could evolve into a new paradigm in computational science, enabling one to circumvent various computational issues in a vast array of applications in engineering science.

Model Reduction And Approximation

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Author : Peter Benner
language : en
Publisher: SIAM
Release Date : 2017-07-06

Model Reduction And Approximation written by Peter Benner and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-06 with Science categories.

Many physical, chemical, biomedical, and technical processes can be described by partial differential equations or dynamical systems. In spite of increasing computational capacities, many problems are of such high complexity that they are solvable only with severe simplifications, and the design of efficient numerical schemes remains a central research challenge. This book presents a tutorial introduction to recent developments in mathematical methods for model reduction and approximation of complex systems. Model Reduction and Approximation: Theory and Algorithms contains three parts that cover (I) sampling-based methods, such as the reduced basis method and proper orthogonal decomposition, (II) approximation of high-dimensional problems by low-rank tensor techniques, and (III) system-theoretic methods, such as balanced truncation, interpolatory methods, and the Loewner framework. It is tutorial in nature, giving an accessible introduction to state-of-the-art model reduction and approximation methods. It also covers a wide range of methods drawn from typically distinct communities (sampling based, tensor based, system-theoretic).?? This book is intended for researchers interested in model reduction and approximation, particularly graduate students and young researchers.