# Search results for: inverse-analyses-with-model-reduction

## Inverse Analyses with Model Reduction

File Size : 20.58 MB
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In this self-consistent monograph, the author gathers and describes different mathematical techniques and combines all together to form practical procedures for the inverse analyses. It puts together topics coming from mathematical programming, with soft computing and Proper Orthogonal Decomposition, in order to show, in the context of structural analyses, how the things work and what are the main problems one needs to tackle. Throughout the book a number of examples and exercises are worked out in order to make reader practically familiar with discussed topics.

## Model Reduction Via Proper Orthogonal Decomposition of Transient Confined and Unconfined Groundwater Flow

Author : Scott Elliott Boyce
File Size : 67.67 MB
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Understanding groundwater resources is enhanced through the application of mathematical models that simulate the dynamics of an aquifer system. Conducting advanced analyses such as inverse problems for parameter estimation or optimization of pumping schedules under different scenarios requires a large number of simulations. Such analyses are intractable for complex, highly-discretized models with large computational requirements. Reducing the computational burden associated with these simulation models provides the opportunity to perform more advanced analyses on a wider spectrum of groundwater management problems. Projection based model reduction via Proper Orthogonal Decomposition (POD) has been shown to reduce the state space dimension by several orders of magnitude and thus reduces the computational burden. Two new POD techniques have been developed that improve the computation of high dimensional groundwater modeled systems. The first method provides a framework for developing parameter independent reduced models for solving inverse problems of confined groundwater models. This methodology is validated using synthetic test cases to solve a traditional inverse problem and Bayesian inverse problem. The second method presents a novel technique that allows for model reduction of unconfined groundwater flow, a nonlinear system of equations, using the Newton formulation of MODFLOW. This method extends POD to nonlinear equations and reduces the computational burden of solving the inverse of the Jacobian required by the Newton formulation. Multiple test cases are presented to illustrate how a POD model is constructed and applied to different groundwater models. These two techniques result in several orders of magnitude of reduction in the state dimension and reduce to the total CPU time. For the case of the Bayesian inverse problem, the synthetic example's parameter posterior distributions that are described with the Metropolis-Hastings Markov chain Monte Carlo method results in a time savings of 48 days when using the reduced model.

## Recent Numerical Advances in Fluid Mechanics

Author : Omer San
File Size : 58.33 MB
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In recent decades, the field of computational fluid dynamics has made significant advances in enabling advanced computing architectures to understand many phenomena in biological, geophysical, and engineering fluid flows. Almost all research areas in fluids use numerical methods at various complexities: from molecular to continuum descriptions; from laminar to turbulent regimes; from low speed to hypersonic, from stencil-based computations to meshless approaches; from local basis functions to global expansions, as well as from first-order approximation to high-order with spectral accuracy. Many successful efforts have been put forth in dynamic adaptation strategies, e.g., adaptive mesh refinement and multiresolution representation approaches. Furthermore, with recent advances in artificial intelligence and heterogeneous computing, the broader fluids community has gained the momentum to revisit and investigate such practices. This Special Issue, containing a collection of 13 papers, brings together researchers to address recent numerical advances in fluid mechanics.

## Fracture Phenomena in Nature and Technology

Author : Davide Bigoni
File Size : 89.47 MB
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This book contains contributions presented at the IUTAM Symposium "Fracture Phenomena in Nature and Technology" held in Brescia, Italy, 1-5 July, 2012.The objective of the Symposium was fracture research, interpreted broadly to include new engineering and structural mechanics treatments of damage development and crack growth and also large-scale failure processes as exemplified by earthquake or landslide failures, ice shelf break-up and hydraulic fracturing (natural or for resource extraction or CO2 sequestration), as well as small-scale rupture phenomena in materials physics including, e.g. inception of shear banding, void growth, adhesion and decohesion in contact and friction, crystal dislocation processes and atomic/electronic scale treatment of brittle crack tips and fundamental cohesive properties. Special emphasis was given to multiscale fracture description and new scale-bridging formulations capable to substantiate recent experiments and tailored to become the basis for innovative computational algorithms.

## Constitutive Modeling of Engineering Materials

File Size : 27.23 MB
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Constitutive Modeling of Engineering Materials provides an extensive theoretical overview of elastic, plastic, damage, and fracture models, giving readers the foundational knowledge needed to successfully apply them to and solve common engineering material problems. Particular attention is given to inverse analysis, parameter identification, and the numerical implementation of models with the finite element method. Application in practice is discussed in detail, showing examples of working computer programs for simple constitutive behaviors. Examples explore the important components of material modeling which form the building blocks of any complex constitutive behavior. • Addresses complex behaviors in a wide range of materials, from polymers, to metals and shape memory alloys • Covers constitutive models with both small and large deformations • Provides detailed examples of computer implementations for material models

## Engineering Optimization 2014

Author : Hélder Rodrigues
File Size : 28.6 MB
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Optimization methodologies are fundamental instruments to tackle the complexity of today's engineering processes. Engineering Optimization 2014 is dedicated to optimization methods in engineering, and contains the papers presented at the 4th International Conference on Engineering Optimization (ENGOPT2014, Lisbon, Portugal, 8-11 September 2014). The book will be of interest to engineers, applied mathematicians, and computer scientists working on research, development and practical applications of optimization methods in engineering.

## Proceedings of the 5th International Symposium on Uncertainty Quantification and Stochastic Modelling

Author : José Eduardo Souza De Cursi
File Size : 84.98 MB
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This proceedings book discusses state-of-the-art research on uncertainty quantification in mechanical engineering, including statistical data concerning the entries and parameters of a system to produce statistical data on the outputs of the system. It is based on papers presented at Uncertainties 2020, a workshop organized on behalf of the Scientific Committee on Uncertainty in Mechanics (Mécanique et Incertain) of the AFM (French Society of Mechanical Sciences), the Scientific Committee on Stochastic Modeling and Uncertainty Quantification of the ABCM (Brazilian Society of Mechanical Sciences) and the SBMAC (Brazilian Society of Applied Mathematics).

## Advances in Modeling and Interpretation in Near Surface Geophysics

Author : Arkoprovo Biswas
File Size : 44.5 MB
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This book deals primarily with the aspects of advances in near surface geophysical data modeling, different interpretation techniques, new ideas and an integrated study to delineate the subsurface structures. It also involves the practical application of different geophysical methods to delineate the subsurface structures associated with mineral, groundwater exploration, subsurface contamination, hot springs, coal fire etc. This book is specifically aimed with the state-of-art information regarding research advances and new developments in these areas of study, coupled to extensive modeling and field investigations obtained from around the world. It is extremely enlightening for the research workers, scientists, faculty members and students, in Applied Geophysics, Near Surface Geophysics, Potential Field, Electrical and Electromagnetic Methods, Mathematical Modeling Techniques in Earth Sciences, as well as Environmental Geophysics.

## Inverse Heat Transfer

Author : Helcio R.B. Orlande
File Size : 31.98 MB
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This book introduces the fundamental concepts of inverse heat transfer solutions and their applications for solving problems in convective, conductive, radiative, and multi-physics problems. Inverse Heat Transfer: Fundamentals and Applications, Second Edition includes techniques within the Bayesian framework of statistics for the solution of inverse problems. By modernizing the classic work of the late Professor M. Necati Özisik and adding new examples and problems, this new edition provides a powerful tool for instructors, researchers, and graduate students studying thermal-fluid systems and heat transfer. FEATURES Introduces the fundamental concepts of inverse heat transfer Presents in systematic fashion the basic steps of powerful inverse solution techniques Develops inverse techniques of parameter estimation, function estimation, and state estimation Applies these inverse techniques to the solution of practical inverse heat transfer problems Shows inverse techniques for conduction, convection, radiation, and multi-physics phenomena M. Necati Özisik (1923–2008) retired in 1998 as Professor Emeritus of North Carolina State University’s Mechanical and Aerospace Engineering Department. Helcio R. B. Orlande is a Professor of Mechanical Engineering at the Federal University of Rio de Janeiro (UFRJ), where he was the Department Head from 2006 to 2007.

## Coping with Complexity Model Reduction and Data Analysis

Author : Alexander N. Gorban
File Size : 24.69 MB
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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.

## Computational Materials Engineering

Author : Maciej Pietrzyk
File Size : 26.43 MB
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Computational Materials Engineering: Achieving High Accuracy and Efficiency in Metals Processing Simulations describes the most common computer modeling and simulation techniques used in metals processing, from so-called "fast" models to more advanced multiscale models, also evaluating possible methods for improving computational accuracy and efficiency. Beginning with a discussion of conventional fast models like internal variable models for flow stress and microstructure evolution, the book moves on to advanced multiscale models, such as the CAFÉ method, which give insights into the phenomena occurring in materials in lower dimensional scales. The book then delves into the various methods that have been developed to deal with problems, including long computing times, lack of proof of the uniqueness of the solution, difficulties with convergence of numerical procedures, local minima in the objective function, and ill-posed problems. It then concludes with suggestions on how to improve accuracy and efficiency in computational materials modeling, and a best practices guide for selecting the best model for a particular application. Presents the numerical approaches for high-accuracy calculations Provides researchers with essential information on the methods capable of exact representation of microstructure morphology Helpful to those working on model classification, computing costs, heterogeneous hardware, modeling efficiency, numerical algorithms, metamodeling, sensitivity analysis, inverse method, clusters, heterogeneous architectures, grid environments, finite element, flow stress, internal variable method, microstructure evolution, and more Discusses several techniques to overcome modeling and simulation limitations, including distributed computing methods, (hyper) reduced-order-modeling techniques, regularization, statistical representation of material microstructure, and the Gaussian process Covers both software and hardware capabilities in the area of improved computer efficiency and reduction of computing time

## Large Scale Inverse Problems and Quantification of Uncertainty

Author : Lorenz Biegler
File Size : 88.74 MB
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This book focuses on computational methods for large-scale statistical inverse problems and provides an introduction to statistical Bayesian and frequentist methodologies. Recent research advances for approximation methods are discussed, along with Kalman filtering methods and optimization-based approaches to solving inverse problems. The aim is to cross-fertilize the perspectives of researchers in the areas of data assimilation, statistics, large-scale optimization, applied and computational mathematics, high performance computing, and cutting-edge applications. The solution to large-scale inverse problems critically depends on methods to reduce computational cost. Recent research approaches tackle this challenge in a variety of different ways. Many of the computational frameworks highlighted in this book build upon state-of-the-art methods for simulation of the forward problem, such as, fast Partial Differential Equation (PDE) solvers, reduced-order models and emulators of the forward problem, stochastic spectral approximations, and ensemble-based approximations, as well as exploiting the machinery for large-scale deterministic optimization through adjoint and other sensitivity analysis methods. Key Features: Brings together the perspectives of researchers in areas of inverse problems and data assimilation. Assesses the current state-of-the-art and identify needs and opportunities for future research. Focuses on the computational methods used to analyze and simulate inverse problems. Written by leading experts of inverse problems and uncertainty quantification. Graduate students and researchers working in statistics, mathematics and engineering will benefit from this book.

## Modelling and Control in Biomedical Systems 2006

Author : David Dagan Feng
File Size : 56.40 MB
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Modelling and Control in Biomedical Systems (including Biological Systems) was held in Reims, France, 20-22 August 2006. This Symposium was organised by the University of Reims Champagne Ardenne and the Société de l’Electricité, de l’Electronique et des TIC (SEE). The Symposium attracted practitioners in engineering, information technology, mathematics, medicine and biology, and other related disciplines, with authors from 24 countries. Besides the abstracts of the four plenary lectures, this volume contains the 92 papers that were presented by their authors at the Symposium. The papers included two invited keynote presentations given by internationally prominent and well-recognised research leaders: Claudio Cobelli, whose talk is titled "Dynamic modelling in diabetes: from whole body to genes"; and Irving J. Bigio, whose talk is titled "Elastic scattering spectroscopy for non-invasive detection of cancer". Two prestigious industrial speakers were also invited to give keynote presentations: Terry O'Brien from LIDCO, whose talk is titled "LIDCO: From the laboratory to protocolized goal directed therapy"; and Lorenzo Quinzio of Philips, whose talk is titled "Clinical decision support in monitoring and information systems". A valuable source of information on the state-of- the-art in Modelling and Control in Biomedical Systems Including abstracts of four plenary lectures, and 92 papers presented by their authors

## Model Order Reduction Techniques with Applications in Finite Element Analysis

Author : Zu-Qing Qu
File Size : 88.62 MB
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Despite the continued rapid advance in computing speed and memory the increase in the complexity of models used by engineers persists in outpacing them. Even where there is access to the latest hardware, simulations are often extremely computationally intensive and time-consuming when full-blown models are under consideration. The need to reduce the computational cost involved when dealing with high-order/many-degree-of-freedom models can be offset by adroit computation. In this light, model-reduction methods have become a major goal of simulation and modeling research. Model reduction can also ameliorate problems in the correlation of widely used finite-element analyses and test analysis models produced by excessive system complexity. Model Order Reduction Techniques explains and compares such methods focusing mainly on recent work in dynamic condensation techniques: - Compares the effectiveness of static, exact, dynamic, SEREP and iterative-dynamic condensation techniques in producing valid reduced-order models; - Shows how frequency shifting and the number of degrees of freedom affect the desirability and accuracy of using dynamic condensation; - Answers the challenges involved in dealing with undamped and non-classically damped models; - Requires little more than first-engineering-degree mathematics and highlights important points with instructive examples. Academics working in research on structural dynamics, MEMS, vibration, finite elements and other computational methods in mechanical, aerospace and structural engineering will find Model Order Reduction Techniques of great interest while it is also an excellent resource for researchers working on commercial finite-element-related software such as ANSYS and Nastran.

## Combining Soft Computing and Statistical Methods in Data Analysis

Author : Christian Borgelt
File Size : 67.2 MB
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Over the last forty years there has been a growing interest to extend probability theory and statistics and to allow for more flexible modelling of imprecision, uncertainty, vagueness and ignorance. The fact that in many real-life situations data uncertainty is not only present in the form of randomness (stochastic uncertainty) but also in the form of imprecision/fuzziness is but one point underlining the need for a widening of statistical tools. Most such extensions originate in a "softening" of classical methods, allowing, in particular, to work with imprecise or vague data, considering imprecise or generalized probabilities and fuzzy events, etc. About ten years ago the idea of establishing a recurrent forum for discussing new trends in the before-mentioned context was born and resulted in the first International Conference on Soft Methods in Probability and Statistics (SMPS) that was held in Warsaw in 2002. In the following years the conference took place in Oviedo (2004), in Bristol (2006) and in Toulouse (2008). In the current edition the conference returns to Oviedo. This edited volume is a collection of papers presented at the SMPS 2010 conference held in Mieres and Oviedo. It gives a comprehensive overview of current research into the fusion of soft methods with probability and statistics.

## Bridge Maintenance Safety Management Resilience and Sustainability

Author : Fabio Biondini
File Size : 87.3 MB
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Bridge Maintenance, Safety, Management, Resilience and Sustainability contains the lectures and papers presented at The Sixth International Conference on Bridge Maintenance, Safety and Management (IABMAS 2012), held in Stresa, Lake Maggiore, Italy, 8-12 July, 2012. This volume consists of a book of extended abstracts (800 pp) and a DVD (4057 pp) co

## Bioinformatics and Biomedical Engineering

Author : Ignacio Rojas
File Size : 42.96 MB
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This two-volume set LNBI 10813 and LNBI 10814 constitutes the proceedings of the 6th International Work-Conference on Bioinformatics and Biomedical Engineering, IWBBIO 2018, held in Granada, Spain, in April 2018.The 88 regular papers presented were carefully reviewed and selected from 273 submissions. The scope of the conference spans the following areas: bioinformatics for healthcare and diseases; bioinformatics tools to integrate omics dataset and address biological question; challenges and advances in measurement and self-parametrization of complex biological systems; computational genomics; computational proteomics; computational systems for modelling biological processes; drug delivery system design aided by mathematical modelling and experiments; generation, management and biological insights from big data; high-throughput bioinformatic tools for medical genomics; next generation sequencing and sequence analysis; interpretable models in biomedicine and bioinformatics; little-big data. Reducing the complexity and facing uncertainty of highly underdetermined phenotype prediction problems; biomedical engineering; biomedical image analysis; biomedical signal analysis; challenges in smart and wearable sensor design for mobile health; and healthcare and diseases.

## Brittle Materials in Mechanical Extremes

Author : Giovanni Bruno
File Size : 88.38 MB
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The goal of the Special Issue “Brittle Materials in Mechanical Extremes” is to spark a discussion of the analogies and the differences between different brittle materials, such as ceramics and concrete. The contributions to the Issue span from construction materials (asphalt and concrete) to structural ceramics to ice. Data reported in the Issue were obtained by advanced microstructural techniques (microscopy, 3D imaging, etc.) and linked to mechanical properties (and their changes as a function of aging, composition, etc.). The description of the mechanical behavior of brittle materials under operational loads, for instance, concrete and ceramics under very high temperatures, offers an unconventional viewpoint on the behavior of such materials. While it is by no means exhaustive, this Special Issue paves the road for the fundamental understanding and further development of materials.

## Desenvolvimento Economico Local No Estado

Author : Fauré
File Size : 65.70 MB
Format : PDF, Docs