Reduced Order Methods For Modeling And Computational Reduction
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Reduced Order Methods For Modeling And Computational Reduction
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Author : Alfio Quarteroni
language : en
Publisher: Springer
Release Date : 2014-06-05
Reduced Order Methods For Modeling And Computational Reduction 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 2014-06-05 with Mathematics categories.
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.
Reduced Order Models For The Biomechanics Of Living Organs
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Author : Francisco Chinesta
language : en
Publisher: Elsevier
Release Date : 2023-05-25
Reduced Order Models For The Biomechanics Of Living Organs written by Francisco Chinesta and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-05-25 with Technology & Engineering categories.
Reduced Order Models for the Biomechanics of Living Organs, a new volume in the Biomechanics of Living Organisms series, provides a comprehensive overview of the state-of-the-art in biomechanical computations using reduced order models, along with a deeper understanding of the associated reduction algorithms that will face students, researchers, clinicians and industrial partners in the future. The book gathers perspectives from key opinion scientists who describe and detail their approaches, methodologies and findings. It is the first to synthesize complementary advances in Biomechanical modelling of living organs using reduced order techniques in the design of medical devices and clinical interventions, including surgical procedures. This book provides an opportunity for students, researchers, clinicians and engineers to study the main topics related to biomechanics and reduced models in a single reference, with this volume summarizing all biomechanical aspects of each living organ in one comprehensive reference. - Introduces the fundamental aspects of reduced order models - Presents the main computational studies in the field of solid and fluid biomechanical modeling of living organs - Explores the use of reduced order models in the fields of biomechanical electrophysiology, tissue growth and prosthetic designs
Model Reduction Of Complex Dynamical Systems
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Author : Peter Benner
language : en
Publisher: Springer Nature
Release Date : 2021-08-26
Model Reduction Of Complex Dynamical Systems written by Peter Benner and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-26 with Mathematics categories.
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.
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.
Cardiovascular Mechanics
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Author : Michel Labrosse
language : en
Publisher: CRC Press
Release Date : 2018-09-13
Cardiovascular Mechanics written by Michel Labrosse and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-13 with Medical categories.
The objective of this book is to illustrate in specific detail how cardiovascular mechanics stands as a common pillar supporting such different clinical successes as drugs for high blood pressure, prosthetic heart valves and coronary artery bypass grafting, among others. This information is conveyed through a comprehensive treatment of the overarching principles and theories that are behind mechanobiological processes, aortic and arterial mechanics, atherosclerosis, blood and microcirculation, hear valve mechanics, as well as medical devices and drugs. Examines all major theoretical and practical aspects of mechanical forces related to the cardiovascular system. Discusses a unique coverage of mechanical changes related to an aging cardiovascular system. Provides an overview of experimental methods in cardiovascular mechanics. Written by world-class researchers from Canada, the US and EU. Extensive references are provided at the end of each chapter to enhance further study. Michel R. Labrosse is the founder of the Cardiovascular Mechanics Laboratory at the University of Ottawa, where he is a full professor within the Department of Mechanical Engineering. He has been an active researcher in academia along with being heavily associated with the University of Ottawa Heart Institute. He has authored or co-authored over 90 refereed communications, and supervised or co-supervised over 40 graduate students and post-docs.
Machine Learning Low Rank Approximations And Reduced Order Modeling In Computational Mechanics
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Author : Felix Fritzen
language : en
Publisher: MDPI
Release Date : 2019-09-18
Machine Learning Low Rank Approximations And Reduced Order Modeling In Computational Mechanics written by Felix Fritzen and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-18 with Technology & Engineering categories.
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.
Fundamentals Of Uncertainty Quantification For Engineers
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Author : Yan Wang
language : en
Publisher: Elsevier
Release Date : 2025-05-30
Fundamentals Of Uncertainty Quantification For Engineers written by Yan Wang and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-30 with Technology & Engineering categories.
Fundamentals of Uncertainty Quantification for Engineers: Methods and Models provides a comprehensive introduction to uncertainty quantification (UQ) accompanied by a wide variety of applied examples and implementation details to reinforce the concepts outlined in the book. Sections start with an introduction to the history of probability theory and an overview of recent developments of UQ methods in the domains of applied mathematics and data science. Major concepts of copula, Monte Carlo sampling, Markov chain Monte Carlo, polynomial regression, Gaussian process regression, polynomial chaos expansion, stochastic collocation, Bayesian inference, modelform uncertainty, multi-fidelity modeling, model validation, local and global sensitivity analyses, linear and nonlinear dimensionality reduction are included. Advanced UQ methods are also introduced, including stochastic processes, stochastic differential equations, random fields, fractional stochastic differential equations, hidden Markov model, linear Gaussian state space model, as well as non-probabilistic methods such as robust Bayesian analysis, Dempster-Shafer theory, imprecise probability, and interval probability. The book also includes example applications in multiscale modeling, reliability, fatigue, materials design, machine learning, and decision making. • Introduces all major topics of uncertainty quantification with engineering examples and implementation details• Features examples from a wide variety of science and engineering disciplines (e.g., fluids, structural dynamics, materials, manufacturing, multiscale simulation)• Discusses sampling methods, surrogate modeling, stochastic expansion, sensitivity analysis, dimensionality reduction and more
Scientific Computing In Electrical Engineering
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Author : Andreas Bartel
language : en
Publisher: Springer
Release Date : 2016-05-09
Scientific Computing In Electrical Engineering written by Andreas Bartel and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-05-09 with Mathematics categories.
This book is a collection of selected papers presented at the 10th International Conference on Scientific Computing in Electrical Engineering (SCEE), held in Wuppertal, Germany in 2014. The book is divided into five parts, reflecting the main directions of SCEE 2014: 1. Device Modeling, Electric Circuits and Simulation, 2. Computational Electromagnetics, 3. Coupled Problems, 4. Model Order Reduction, and 5. Uncertainty Quantification. Each part starts with a general introduction followed by the actual papers. The aim of the SCEE 2014 conference was to bring together scientists from academia and industry, mathematicians, electrical engineers, computer scientists, and physicists, with the goal of fostering intensive discussions on industrially relevant mathematical problems, with an emphasis on the modeling and numerical simulation of electronic circuits and devices, electromagnetic fields, and coupled problems. The methodological focus was on model order reduction and uncertainty quantification. this book="" will="" appeal="" to="" mathematicians="" and="" electrical="" engineers.="" it="" offers="" a="" valuable="" starting="" point="" for="" developers="" of="" algorithms="" programs="" who="" want="" learn="" about="" recent="" advances="" in="" other="" fields="" as="" well="" open="" problems="" coming="" from="" industry.="" moreover,="" be="" use="" representatives="" industry="" with="" an="" interest="" new="" program="" tools="" mathematical="" methods.
Nanoelectronic Coupled Problems Solutions
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Author : E. Jan W. ter Maten
language : en
Publisher: Springer Nature
Release Date : 2019-11-06
Nanoelectronic Coupled Problems Solutions written by E. Jan W. ter Maten and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-06 with Mathematics categories.
Designs in nanoelectronics often lead to challenging simulation problems and include strong feedback couplings. Industry demands provisions for variability in order to guarantee quality and yield. It also requires the incorporation of higher abstraction levels to allow for system simulation in order to shorten the design cycles, while at the same time preserving accuracy. The methods developed here promote a methodology for circuit-and-system-level modelling and simulation based on best practice rules, which are used to deal with coupled electromagnetic field-circuit-heat problems, as well as coupled electro-thermal-stress problems that emerge in nanoelectronic designs. This book covers: (1) advanced monolithic/multirate/co-simulation techniques, which are combined with envelope/wavelet approaches to create efficient and robust simulation techniques for strongly coupled systems that exploit the different dynamics of sub-systems within multiphysics problems, and which allow designers to predict reliability and ageing; (2) new generalized techniques in Uncertainty Quantification (UQ) for coupled problems to include a variability capability such that robust design and optimization, worst case analysis, and yield estimation with tiny failure probabilities are possible (including large deviations like 6-sigma); (3) enhanced sparse, parametric Model Order Reduction techniques with a posteriori error estimation for coupled problems and for UQ to reduce the complexity of the sub-systems while ensuring that the operational and coupling parameters can still be varied and that the reduced models offer higher abstraction levels that can be efficiently simulated. All the new algorithms produced were implemented, transferred and tested by the EDA vendor MAGWEL. Validation was conducted on industrial designs provided by end-users from the semiconductor industry, who shared their feedback, contributed to the measurements, and supplied both material data and process data. In closing, a thorough comparison to measurements on real devices was made in order to demonstrate the algorithms’ industrial applicability.
Advanced Reduced Order Methods And Applications In Computational Fluid Dynamics
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Author : Gianluigi Rozza
language : en
Publisher: SIAM
Release Date : 2022-11-21
Advanced Reduced Order Methods And Applications In Computational Fluid Dynamics written by Gianluigi Rozza and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-21 with Mathematics categories.
Reduced order modeling is an important, growing field in computational science and engineering, and this is the first book to address the subject in relation to computational fluid dynamics. It focuses on complex parametrization of shapes for their optimization and includes recent developments in advanced topics such as turbulence, stability of flows, inverse problems, optimization, and flow control, as well as applications. This book will be of interest to researchers and graduate students in the field of reduced order modeling.