[PDF] Adaptive Multiscale Modeling Of Polymeric Materials Using Goal Oriented Error Estimation Arlequin Coupling And Goals Algorithms - eBooks Review

Adaptive Multiscale Modeling Of Polymeric Materials Using Goal Oriented Error Estimation Arlequin Coupling And Goals Algorithms


Adaptive Multiscale Modeling Of Polymeric Materials Using Goal Oriented Error Estimation Arlequin Coupling And Goals Algorithms
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Adaptive Multiscale Modeling Of Polymeric Materials Using Goal Oriented Error Estimation Arlequin Coupling And Goals Algorithms


Adaptive Multiscale Modeling Of Polymeric Materials Using Goal Oriented Error Estimation Arlequin Coupling And Goals Algorithms
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Author : Paul Thomas Bauman
language : en
Publisher:
Release Date : 2008

Adaptive Multiscale Modeling Of Polymeric Materials Using Goal Oriented Error Estimation Arlequin Coupling And Goals Algorithms written by Paul Thomas Bauman and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with Algorithms categories.


Scientific theories that explain how physical systems behave are described by mathematical models which provide the basis for computer simulations of events that occur in the physical universe. These models, being only mathematical characterizations of actual phenomena, are obviously subject to error because of the inherent limitations of all mathematical abstractions. In this work, new theory and methodologies are developed to quantify such modeling error in a special way that resolves a fundamental and standing issue: multiscale modeling, the development of models of events that transcend many spatial and temporal scales. Specifically, we devise the machinery for a posteriori estimates of relative modeling error between a model of fine scale and another of coarser scale, and we use this methodology as a general approach to multiscale problems. The target application is one of critical importance to nanomanufacturing: imprint lithography of semiconductor devices. The development of numerical methods for multiscale modeling has become one of the most important areas of computational science. Technological developments in the manufacturing of semiconductors hinge upon the ability to understand physical phenomena from the nanoscale to the microscale and beyond. Predictive simulation tools are critical to the advancement of nanomanufacturing semiconductor devices. In principle, they can displace expensive experiments and testing and optimize the design of the manufacturing process. The development of such tools rest on the edge of contemporary methods and high-performance computing capabilities and is a major open problem in computational science. In this dissertation, a molecular model is used to simulate the deformation of polymeric materials used in the fabrication of semiconductor devices. Algorithms are described which lead to a complex molecular model of polymer materials designed to produce an etch barrier, a critical component in imprint lithography approaches to semiconductor manufacturing. Each application of this so-called polymerization process leads to one realization of a lattice-type model of the polymer, a molecular statics model of enormous size and complexity. This is referred to as the base model for analyzing the deformation of the etch barrier, a critical feature of the manufacturing process. To reduce the size and complexity of this model, a sequence of coarser surrogate models is generated. These surrogates are the multiscale models critical to the successful computer simulation of the entire manufacturing process. The surrogate involves a combination of particle models, the molecular model of the polymer, and a coarse-scale model of the polymer as a nonlinear hyperelastic material. Coefficients for the nonlinear elastic continuum model are determined using numerical experiments on representative volume elements of the polymer model. Furthermore, a simple model of initial strain is incorporated in the continuum equations to model the inherit shrinking of the A coupled particle and continuum model is constructed using a special algorithm designed to provide constraints on a region of overlap between the continuum and particle models. This coupled model is based on the so-called Arlequin method that was introduced in the context of coupling two continuum models with differing levels of discretization. It is shown that the Arlequin problem for the particle-tocontinuum model is well posed in a one-dimensional setting involving linear harmonic springs coupled with a linearly elastic continuum. Several numerical examples are presented. Numerical experiments in three dimensions are also discussed in which the polymer model is coupled to a nonlinear elastic continuum. Error estimates in local quantities of interest are constructed in order to estimate the modeling error due to the approximation of the particle model by the coupled multiscale surrogate model. The estimates of the error are computed by solving an auxiliary adjoint, or dual, problem that incorporates as data the quantity of interest or its derivatives. The solution of the adjoint problem indicates how the error in the approximation of the polymer model inferences the error in the quantity of interest. The error in the quantity of interest represents the relative error between the value of the quantity evaluated for the base model, a quantity typically unavailable or intractable, and the value of the quantity of interest provided by the multiscale surrogate model. To estimate the error in the quantity of interest, a theorem is employed that establishes that the error coincides with the value of the residual functional acting on the adjoint solution plus a higher-order remainder. For each surrogate in a sequence of surrogates generated, the residual functional acting on various approximations of the adjoint is computed. These error estimates are used to construct an adaptive algorithm whereby the model is adapted by supplying additional fine-scale data in certain subdomains in order to reduce the error in the quantity of interest. The adaptation algorithm involves partitioning the domain and selecting which subdomains are to use the particle model, the continuum model, and where the two overlap. When the algorithm identifies that a region contributes a relatively large amount to the error in the quantity of interest, it is scheduled for refinement by switching the model for that region to the particle model. Numerical experiments on several configurations representative of nano-features in semiconductor device fabrication demonstrate the effectiveness of the error estimate in controlling the modeling error as well as the ability of the adaptive algorithm to reduce the error in the quantity of interest. There are two major conclusions of this study: 1. an effective and well posed multiscale model that couples particle and continuum models can be constructed as a surrogate to molecular statics models of polymer networks and 2. an error estimate of the modeling error for such systems can be estimated with sufficient accuracy to provide the basis for very effective multiscale modeling procedures. The methodology developed in this study provides a general approach to multiscale modeling. The computational procedures, computer codes, and results could provide a powerful tool in understanding, designing, and optimizing an important class of semiconductormanufacturing processes. The study in this dissertation involves all three components of the CAM graduate program requirements: Area A, Applicable Mathematics; Area B, Numerical Analysis and Scientific Computation; and Area C, Mathematical Modeling and Applications. The multiscale modeling approach developed here is based on the construction of continuum surrogates and coupling them to molecular statics models of polymer as well as a posteriori estimates of error and their adaptive control. A detailed mathematical analysis is provided for the Arlequin method in the context of coupling particle and continuum models for a class of one-dimensional model problems. Algorithms are described and implemented that solve the adaptive, nonlinear problem proposed in the multiscale surrogate problem. Large scale, parallel computations for the base model are also shown. Finally, detailed studies of models relevant to applications to semiconductor manufacturing are presented.



Numerical Analysis Of Multiscale Computations


Numerical Analysis Of Multiscale Computations
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Author : Björn Engquist
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-10-14

Numerical Analysis Of Multiscale Computations written by Björn Engquist 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 2011-10-14 with Computers categories.


This book is a snapshot of current research in multiscale modeling, computations and applications. It covers fundamental mathematical theory, numerical algorithms as well as practical computational advice for analysing single and multiphysics models containing a variety of scales in time and space. Complex fluids, porous media flow and oscillatory dynamical systems are treated in some extra depth, as well as tools like analytical and numerical homogenization, and fast multipole method.



Multiscale Methods


Multiscale Methods
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Author : Jacob Fish
language : en
Publisher: Oxford University Press
Release Date : 2010

Multiscale Methods written by Jacob Fish and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with Mathematics categories.


Small scale features and processes occurring at nanometer and femtosecond scales have a profound impact on what happens at a larger scale and over an extensive period of time. The primary objective of this volume is to reflect the state-of-the-art in multiscale mathematics, modeling, and simulations and to address the following barriers: What is the information that needs to be transferred from one model or scale to another and what physical principles must be satisfied during thetransfer of information? What are the optimal ways to achieve such transfer of information? How can variability of physical parameters at multiple scales be quantified and how can it be accounted for to ensure design robustness?The multiscale approaches in space and time presented in this volume are grouped into two main categories: information-passing and concurrent. In the concurrent approaches various scales are simultaneously resolved, whereas in the information-passing methods the fine scale is modeled and its gross response is infused into the continuum scale. The issue of reliability of multiscale modeling and simulation tools which focus on a hierarchy of multiscale models and an a posteriori model of errorestimation including uncertainty quantification, is discussed in several chapters. Component software that can be effectively combined to address a wide range of multiscale simulations is also described. Applications range from advanced materials to nanoelectromechanical systems (NEMS), biologicalsystems, and nanoporous catalysts where physical phenomena operates across 12 orders of magnitude in time scales and 10 orders of magnitude in spatial scales.This volume is a valuable reference book for scientists, engineers and graduate students practicing in traditional engineering and science disciplines as well as in emerging fields of nanotechnology, biotechnology, microelectronics and energy.



Assessing The Reliability Of Complex Models


Assessing The Reliability Of Complex Models
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Author : National Research Council
language : en
Publisher: National Academies Press
Release Date : 2012-07-26

Assessing The Reliability Of Complex Models written by National Research Council and has been published by National Academies Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-07-26 with Mathematics categories.


Advances in computing hardware and algorithms have dramatically improved the ability to simulate complex processes computationally. Today's simulation capabilities offer the prospect of addressing questions that in the past could be addressed only by resource-intensive experimentation, if at all. Assessing the Reliability of Complex Models recognizes the ubiquity of uncertainty in computational estimates of reality and the necessity for its quantification. As computational science and engineering have matured, the process of quantifying or bounding uncertainties in a computational estimate of a physical quality of interest has evolved into a small set of interdependent tasks: verification, validation, and uncertainty of quantification (VVUQ). In recognition of the increasing importance of computational simulation and the increasing need to assess uncertainties in computational results, the National Research Council was asked to study the mathematical foundations of VVUQ and to recommend steps that will ultimately lead to improved processes. Assessing the Reliability of Complex Models discusses changes in education of professionals and dissemination of information that should enhance the ability of future VVUQ practitioners to improve and properly apply VVUQ methodologies to difficult problems, enhance the ability of VVUQ customers to understand VVUQ results and use them to make informed decisions, and enhance the ability of all VVUQ stakeholders to communicate with each other. This report is an essential resource for all decision and policy makers in the field, students, stakeholders, UQ experts, and VVUQ educators and practitioners.



Computational Methods For Solids And Fluids


Computational Methods For Solids And Fluids
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Author : Adnan Ibrahimbegovic
language : en
Publisher: Springer
Release Date : 2016-02-12

Computational Methods For Solids And Fluids written by Adnan Ibrahimbegovic and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-02-12 with Technology & Engineering categories.


This volume contains the best papers presented at the 2nd ECCOMAS International Conference on Multiscale Computations for Solids and Fluids, held June 10-12, 2015. Topics dealt with include multiscale strategy for efficient development of scientific software for large-scale computations, coupled probability-nonlinear-mechanics problems and solution methods, and modern mathematical and computational setting for multi-phase flows and fluid-structure interaction. The papers consist of contributions by six experts who taught short courses prior to the conference, along with several selected articles from other participants dealing with complementary issues, covering both solid mechanics and applied mathematics.



Dissertation Abstracts International


Dissertation Abstracts International
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Author :
language : en
Publisher:
Release Date : 2008

Dissertation Abstracts International written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with Dissertations, Academic categories.




Multiscale Modelling Of Polymer Properties


Multiscale Modelling Of Polymer Properties
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Author : E. Perpète
language : en
Publisher: Elsevier
Release Date : 2006-11-18

Multiscale Modelling Of Polymer Properties written by E. Perpète and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-11-18 with Technology & Engineering categories.


Modelling in polymer materials science has experienced a dramatic growth in the last two decades. Advances in modeling methodologies together with rapid growth in computational power have made it possible to address increasingly complex questions both of a fundamental and of a more applied nature.Multiscale Modelling of Polymer Properties assembles research done on modeling of polymeric materials from a hierarchical point of view, in which several methods are combined in a multilevel approach to complex polymeric materials. Contributions from academic and industrial experts are organized in two parts: the first one addresses the methodological aspects while the second one focuses on specific applications. The book aims at comprehensively assessing the current state of the field, including the strengths and shortcomings of available modelling techniques, and at identifying future needs and trends. * Several levels of approximation to the field of polymer modelling; ranging from first-principles to purely macroscopic * Contributions from both academic and industrial experts with varying fields of expertise* Assesses current state of this emerging and rapidly growing field



The Proper Generalized Decomposition For Advanced Numerical Simulations


The Proper Generalized Decomposition For Advanced Numerical Simulations
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Author : Francisco Chinesta
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-10-08

The Proper Generalized Decomposition For Advanced Numerical Simulations written by Francisco Chinesta 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 2013-10-08 with Technology & Engineering categories.


Many problems in scientific computing are intractable with classical numerical techniques. These fail, for example, in the solution of high-dimensional models due to the exponential increase of the number of degrees of freedom. Recently, the authors of this book and their collaborators have developed a novel technique, called Proper Generalized Decomposition (PGD) that has proven to be a significant step forward. The PGD builds by means of a successive enrichment strategy a numerical approximation of the unknown fields in a separated form. Although first introduced and successfully demonstrated in the context of high-dimensional problems, the PGD allows for a completely new approach for addressing more standard problems in science and engineering. Indeed, many challenging problems can be efficiently cast into a multi-dimensional framework, thus opening entirely new solution strategies in the PGD framework. For instance, the material parameters and boundary conditions appearing in a particular mathematical model can be regarded as extra-coordinates of the problem in addition to the usual coordinates such as space and time. In the PGD framework, this enriched model is solved only once to yield a parametric solution that includes all particular solutions for specific values of the parameters. The PGD has now attracted the attention of a large number of research groups worldwide. The present text is the first available book describing the PGD. It provides a very readable and practical introduction that allows the reader to quickly grasp the main features of the method. Throughout the book, the PGD is applied to problems of increasing complexity, and the methodology is illustrated by means of carefully selected numerical examples. Moreover, the reader has free access to the Matlab© software used to generate these examples.



Principles Of Multiscale Modeling


Principles Of Multiscale Modeling
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Author : Weinan E
language : en
Publisher: Cambridge University Press
Release Date : 2011-07-07

Principles Of Multiscale Modeling written by Weinan E and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-07-07 with Mathematics categories.


A systematic discussion of the fundamental principles, written by a leading contributor to the field.



Encyclopedia Of Computational Mechanics


Encyclopedia Of Computational Mechanics
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Author : Erwin Stein
language : en
Publisher:
Release Date : 2004

Encyclopedia Of Computational Mechanics written by Erwin Stein and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with Dynamics categories.


The Encyclopedia of Computational Mechanics provides a comprehensive collection of knowledge about the theory and practice of computational mechanics.