Download or read book Multiscale Model Reduction written by Eric Chung and published by Springer Nature. This book was released on 2023-06-07 with total page 499 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Multiscale Modeling of Heterogeneous Structures written by Jurica Sorić and published by Springer. This book was released on 2017-11-30 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Principles of Multiscale Modeling written by Weinan E and published by Cambridge University Press. This book was released on 2011-07-07 with total page 485 pages. Available in PDF, EPUB and Kindle. Book excerpt: A systematic discussion of the fundamental principles, written by a leading contributor to the field.

Download or read book Multiscale Model Reduction Methods for Deterministic and Stochastic Partial Differential Equations written by Maolin Ci and published by . This book was released on 2014 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Interpolatory Methods for Model Reduction written by A. C. Antoulas and published by SIAM. This book was released on 2020-01-13 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dynamical systems are a principal tool in the modeling, prediction, and control of a wide range of complex phenomena. As the need for improved accuracy leads to larger and more complex dynamical systems, direct simulation often becomes the only available strategy for accurate prediction or control, inevitably creating a considerable burden on computational resources. This is the main context where one considers model reduction, seeking to replace large systems of coupled differential and algebraic equations that constitute high fidelity system models with substantially fewer equations that are crafted to control the loss of fidelity that order reduction may induce in the system response. Interpolatory methods are among the most widely used model reduction techniques, and Interpolatory Methods for Model Reduction is the first comprehensive analysis of this approach available in a single, extensive resource. It introduces state-of-the-art methods reflecting significant developments over the past two decades, covering both classical projection frameworks for model reduction and data-driven, nonintrusive frameworks. This textbook is appropriate for a wide audience of engineers and other scientists working in the general areas of large-scale dynamical systems and data-driven modeling of dynamics.

Download or read book Model Reduction and Coarse Graining Approaches for Multiscale Phenomena written by Alexander N. Gorban and published by Springer Science & Business Media. This book was released on 2006-09-22 with total page 554 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Multiscale Modeling in Solid Mechanics written by Ugo Galvanetto and published by Imperial College Press. This book was released on 2010 with total page 349 pages. Available in PDF, EPUB and Kindle. Book excerpt: This unique volume presents the state of the art in the field of multiscale modeling in solid mechanics, with particular emphasis on computational approaches. For the first time, contributions from both leading experts in the field and younger promising researchers are combined to give a comprehensive description of the recently proposed techniques and the engineering problems tackled using these techniques. The book begins with a detailed introduction to the theories on which different multiscale approaches are based, with regards to linear Homogenisation as well as various nonlinear approaches. It then presents advanced applications of multiscale approaches applied to nonlinear mechanical problems. Finally, the novel topic of materials with self-similar structure is discussed. Sample Chapter(s). Chapter 1: Computational Homogenisation for Non-Linear Heterogeneous Solids (808 KB). Contents: Computational Homogenisation for Non-Linear Heterogeneous Solids (V G Kouznetsova et al.); Two-Scale Asymptotic Homogenisation-Based Finite Element Analysis of Composite Materials (Q-Z Xiao & B L Karihaloo); Multi-Scale Boundary Element Modelling of Material Degradation and Fracture (G K Sfantos & M H Aliabadi); Non-Uniform Transformation Field Analysis: A Reduced Model for Multiscale Non-Linear Problems in Solid Mechanics (J-C Michel & P Suquet); Multiscale Approach for the Thermomechanical Analysis of Hierarchical Structures (M J Lefik et al.); Recent Advances in Masonry Modelling: Micro-Modelling and Homogenisation (P B Louren o); Mechanics of Materials with Self-Similar Hierarchical Microstructure (R C Picu & M A Soare). Readership: Researchers and academics in the field of heterogeneous materials and mechanical engineering; professionals in aeronautical engineering and materials science.

Download or read book High performance Model Reduction Procedures in Multiscale Simulations written by Joaquín A. Hernández Ortega and published by . This book was released on 2012 with total page 104 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Multiscale Modeling for Process Safety Applications written by Arnab Chakrabarty and published by Butterworth-Heinemann. This book was released on 2015-11-29 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multiscale Modeling for Process Safety Applications is a new reference demonstrating the implementation of multiscale modeling techniques on process safety applications. It is a valuable resource for readers interested in theoretical simulations and/or computer simulations of hazardous scenarios. As multi-scale modeling is a computational technique for solving problems involving multiple scales, such as how a flammable vapor cloud might behave if ignited, this book provides information on the fundamental topics of toxic, fire, and air explosion modeling, as well as modeling jet and pool fires using computational fluid dynamics. The book goes on to cover nanomaterial toxicity, QPSR analysis on relation of chemical structure to flash point, molecular structure and burning velocity, first principle studies of reactive chemicals, water and air reactive chemicals, and dust explosions. Chemical and process safety professionals, as well as faculty and graduate researchers, will benefit from the detailed coverage provided in this book. Provides the only comprehensive source addressing the use of multiscale modeling in the context of process safety Bridges multiscale modeling with process safety, enabling the reader to understand mapping between problem detail and effective usage of resources Presents an overall picture of addressing safety problems in all levels of modeling and the latest approaches to each in the field Features worked out examples, case studies, and a question bank to aid understanding and involvement for the reader

Download or read book Practical Multiscaling written by Jacob Fish and published by John Wiley & Sons. This book was released on 2013-09-03 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt: Practical Multiscaling covers fundamental modelling techniques aimed at bridging diverse temporal and spatial scales ranging from the atomic level to a full-scale product level. It focuses on practical multiscale methods that account for fine-scale (material) details but do not require their precise resolution. The text material evolved from over 20 years of teaching experience at Rensselaer and Columbia University, as well as from practical experience gained in the application of multiscale software. This book comprehensively covers theory and implementation, providing a detailed exposition of the state-of-the-art multiscale theories and their insertion into conventional (single-scale) finite element code architecture. The robustness and design aspects of multiscale methods are also emphasised, which is accomplished via four building blocks: upscaling of information, systematic reduction of information, characterization of information utilizing experimental data, and material optimization. To ensure the reader gains hands-on experience, a companion website hosting a lite version of the multiscale design software (MDS-Lite) is available. Key features: Combines fundamental theory and practical methods of multiscale modelling Covers the state-of-the-art multiscale theories and examines their practical usability in design Covers applications of multiscale methods Accompanied by a continuously updated website hosting the multiscale design software Illustrated with colour images Practical Multiscaling is an ideal textbook for graduate students studying multiscale science and engineering. It is also a must-have reference for government laboratories, researchers and practitioners in civil, aerospace, pharmaceutical, electronics, and automotive industries, and commercial software vendors.

Download or read book Fundamentals of Multiscale Modeling of Structural Materials written by Wenjie Xia and published by Elsevier. This book was released on 2022-11-26 with total page 450 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

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.

Download or read book Multiscale Model Reduction for Unsteady Fluid Flow written by Jared Callaham and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation develops methods for constructing simplified models of unsteady fluid flows in regimes ranging from weakly nonlinear to fully turbulent. These models can provide valuable insights into the flow physics, as well as inexpensive surrogate models suitable for analytic study and controller design. The emphasis is on extending traditional methods using recent advances in data-driven modeling in a manner that preserves the interpretability and robustness of classical analysis. Throughout, the proposed methodological developments are critically evaluated against extensive computational fluid dynamics simulations and experimental wind tunnel observations representing a variety of fundamental features of unsteady flows. This work takes three distinct approaches to model reduction. First, a perspective of the fluid flow as a high-dimensional, dissipative dynamical system with emergent large-scale coherence leads to approximations in terms of low-dimensional nonlinear dynamics. These models can be derived by projection of the governing equations or sparse model discovery; in either case it is crucial to systematically account for the influence of unresolved degrees of freedom. Alternatively, in fully-developed turbulence the evolution of global integral quantities can be viewed as deterministic motion forced by incoherent fluctuations. The analogy with statistical mechanics cannot be made rigorous for turbulence, but an empirical method is developed to approximate these generalized Brownian motions from limited experimental data. Finally, the observation that the behavior of physical systems is often determined by a dominant balance between a small subset of physical mechanisms motivates the development of an algorithm for objective identification of regions with different active physics. Underlying all of these frameworks is a unifying perspective of the flow as a system with complex nonlinear interactions across a wide range of spatiotemporal scales.

Download or read book Model Reduction and Approximation written by Peter Benner and published by SIAM. This book was released on 2017-07-06 with total page 421 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Multiscale Modeling Simulation and Visualization and Their Potential for Future Aerospace Systems written by and published by . This book was released on 2002 with total page 462 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book An Introduction to multiscale modeling with applications written by Pietro Asinari and published by Società Editrice Esculapio. This book was released on 2019-01-01 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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).

Download or read book Multiscale Model Reduction for High contrast Flow Problems written by Guanglian Li and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Many applications involve media that contain multiple scales and physical properties that vary in orders of magnitude. One example is a rock sample, which has many micro-scale features. Most multiscale problems are often parameter-dependent, where the parameters represent variations in medium properties, randomness, or spatial heterogeneities. Because of disparity of scales in multiscale problems, solving such problems is prohibitively expensive. Among the most popular and developed techniques for efficiently solving the global system arising from a finite element approximation of the underlying problem on a very fine mesh are multigrid methods, multilevel methods, and domain decomposition techniques. More recently, a new large class of accurate reduced-order methods has been introduced and used in various applications. These include Galerkin multiscale finite element methods, mixed multiscale finite element methods, multiscale finite volume methods, and mortar multiscale methods, and so on. In this dissertation, a multiscale finite element method is studied for the computation of heterogeneous problems involving high-contrast, no-scale separation, parameter dependency and nonlinearities. A general formulation of the elliptic heterogeneous problems is discussed, including an oversampling strategy and randomized snapshots generation for a more efficient and accurate computation. Furthermore, a multiscale adaptive algorithm is proposed and analyzed to reduce the computational cost. Then, this multiscale finite element method is extended to the nonlinear high-contrast elliptic problems. Specifically, both continuous and discontinuous Galerkin formulations are considered. In the end, an application to high-contrast heterogeneous Brinkman flow is analyzed. The electronic version of this dissertation is accessible from http://hdl.handle.net/1969.1/155073