Computational Methods for Modeling of Nonlinear Systems by Anatoli Torokhti and Phil Howlett

Computational Methods for Modeling of Nonlinear Systems by Anatoli Torokhti and Phil Howlett
Author: Anatoli Torokhti,Phil Howlett
Publsiher: Elsevier
Total Pages: 322
Release: 2007-04-11
ISBN 10: 9780080475387
ISBN 13: 0080475388
Language: EN, FR, DE, ES & NL

Computational Methods for Modeling of Nonlinear Systems by Anatoli Torokhti and Phil Howlett Book Review:

In this book, we study theoretical and practical aspects of computing methods for mathematical modelling of nonlinear systems. A number of computing techniques are considered, such as methods of operator approximation with any given accuracy; operator interpolation techniques including a non-Lagrange interpolation; methods of system representation subject to constraints associated with concepts of causality, memory and stationarity; methods of system representation with an accuracy that is the best within a given class of models; methods of covariance matrix estimation; methods for low-rank matrix approximations; hybrid methods based on a combination of iterative procedures and best operator approximation; and methods for information compression and filtering under condition that a filter model should satisfy restrictions associated with causality and different types of memory. As a result, the book represents a blend of new methods in general computational analysis, and specific, but also generic, techniques for study of systems theory ant its particular branches, such as optimal filtering and information compression. Best operator approximation Non-Lagrange interpolation Generic Karhunen-Loeve transform Generalised low-rank matrix approximation Optimal data compression Optimal nonlinear filtering

Adaptive Learning Methods for Nonlinear System Modeling

Adaptive Learning Methods for Nonlinear System Modeling
Author: Danilo Comminiello,Jose C. Principe
Publsiher: Butterworth-Heinemann
Total Pages: 388
Release: 2018-06-11
ISBN 10: 0128129778
ISBN 13: 9780128129777
Language: EN, FR, DE, ES & NL

Adaptive Learning Methods for Nonlinear System Modeling Book Review:

Adaptive Learning Methods for Nonlinear System Modeling presents some of the recent advances on adaptive algorithms and machine learning methods designed for nonlinear system modeling and identification. Real-life problems always entail a certain degree of nonlinearity, which makes linear models a non-optimal choice. This book mainly focuses on those methodologies for nonlinear modeling that involve any adaptive learning approaches to process data coming from an unknown nonlinear system. By learning from available data, such methods aim at estimating the nonlinearity introduced by the unknown system. In particular, the methods presented in this book are based on online learning approaches, which process the data example-by-example and allow to model even complex nonlinearities, e.g., showing time-varying and dynamic behaviors. Possible fields of applications of such algorithms includes distributed sensor networks, wireless communications, channel identification, predictive maintenance, wind prediction, network security, vehicular networks, active noise control, information forensics and security, tracking control in mobile robots, power systems, and nonlinear modeling in big data, among many others. This book serves as a crucial resource for researchers, PhD and post-graduate students working in the areas of machine learning, signal processing, adaptive filtering, nonlinear control, system identification, cooperative systems, computational intelligence. This book may be also of interest to the industry market and practitioners working with a wide variety of nonlinear systems. Presents the key trends and future perspectives in the field of nonlinear signal processing and adaptive learning. Introduces novel solutions and improvements over the state-of-the-art methods in the very exciting area of online and adaptive nonlinear identification. Helps readers understand important methods that are effective in nonlinear system modelling, suggesting the right methodology to address particular issues.

Computational Methods for Modeling of Nonlinear Systems

Computational Methods for Modeling of Nonlinear Systems
Author: Anatoli Torokhti
Publsiher: Unknown
Total Pages: 251
Release: 1981
ISBN 10: 1928374650XXX
ISBN 13: OCLC:700688916
Language: EN, FR, DE, ES & NL

Computational Methods for Modeling of Nonlinear Systems Book Review:

In this book, we study theoretical and practical aspects of computing methods for mathematical modelling of nonlinear systems. A number of computing techniques are considered, such as methods of operator approximation with any given accuracy; operator interpolation techniques including a non-Lagrange interpolation; methods of system representation subject to constraints associated with concepts of causality, memory and stationarity; methods of system representation with an accuracy that is the best within a given class of models; methods of covariance matrix estimation;methods for low-rank mat.

Computational Methods for Modeling of Nonlinear Systems

Computational Methods for Modeling of Nonlinear Systems
Author: Anatoli Torokhti,Phil Howlett
Publsiher: Elsevier Science Limited
Total Pages: 322
Release: 1967
ISBN 10: 9780124474505
ISBN 13: 0124474500
Language: EN, FR, DE, ES & NL

Computational Methods for Modeling of Nonlinear Systems Book Review:

In this book, we study theoretical and practical aspects of computing methods for mathematical modelling of nonlinear systems. A number of computing techniques are considered, such as methods of operator approximation with any given accuracy; operator interpolation techniques including a non-Lagrange interpolation; methods of system representation subject to constraints associated with concepts of causality, memory and stationarity; methods of system representation with an accuracy that is the best within a given class of models; methods of covariance matrix estimation; methods for low-rank matrix approximations; hybrid methods based on a combination of iterative procedures and best operator approximation; and methods for information compression and filtering under condition that a filter model should satisfy restrictions associated with causality and different types of memory. As a result, the book represents a blend of new methods in general computational analysis, and specific, but also generic, techniques for study of systems theory ant its particular branches, such as optimal filtering and information compression. - Best operator approximation, - Non-Lagrange interpolation, - Generic Karhunen-Loeve transform - Generalised low-rank matrix approximation - Optimal data compression - Optimal nonlinear filtering

Computational Methods in Earthquake Engineering

Computational Methods in Earthquake Engineering
Author: Manolis Papadrakakis,Vagelis Plevris,Nikos D. Lagaros
Publsiher: Springer
Total Pages: 418
Release: 2016-12-22
ISBN 10: 3319477986
ISBN 13: 9783319477985
Language: EN, FR, DE, ES & NL

Computational Methods in Earthquake Engineering Book Review:

This is the third book in a series on Computational Methods in Earthquake Engineering. The purpose of this volume is to bring together the scientific communities of Computational Mechanics and Structural Dynamics, offering a wide coverage of timely issues on contemporary Earthquake Engineering. This volume will facilitate the exchange of ideas in topics of mutual interest and can serve as a platform for establishing links between research groups with complementary activities. The computational aspects are emphasized in order to address difficult engineering problems of great social and economic importance.

Introduction to Stochastic Control Theory

Introduction to Stochastic Control Theory
Author: Anonim
Publsiher: Elsevier Science
Total Pages: 322
Release: 1970-12-12
ISBN 10: 9780120656509
ISBN 13: 0120656507
Language: EN, FR, DE, ES & NL

Introduction to Stochastic Control Theory Book Review:

In this book, we study theoretical and practical aspects of computing methods for mathematical modelling of nonlinear systems. A number of computing techniques are considered, such as methods of operator approximation with any given accuracy; operator interpolation techniques including a non-Lagrange interpolation; methods of system representation subject to constraints associated with concepts of causality, memory and stationarity; methods of system representation with an accuracy that is the best within a given class of models; methods of covariance matrix estimation; methods for low-rank matrix approximations; hybrid methods based on a combination of iterative procedures and best operator approximation; and methods for information compression and filtering under condition that a filter model should satisfy restrictions associated with causality and different types of memory. As a result, the book represents a blend of new methods in general computational analysis, and specific, but also generic, techniques for study of systems theory ant its particular branches, such as optimal filtering and information compression. - Best operator approximation, - Non-Lagrange interpolation, - Generic Karhunen-Loeve transform - Generalised low-rank matrix approximation - Optimal data compression - Optimal nonlinear filtering

Fast Numerical Methods for Mixed Integer Nonlinear Model Predictive Control

Fast Numerical Methods for Mixed Integer Nonlinear Model Predictive Control
Author: Christian Kirches
Publsiher: Springer Science & Business Media
Total Pages: 367
Release: 2011-11-23
ISBN 10: 383488202X
ISBN 13: 9783834882028
Language: EN, FR, DE, ES & NL

Fast Numerical Methods for Mixed Integer Nonlinear Model Predictive Control Book Review:

Christian Kirches develops a fast numerical algorithm of wide applicability that efficiently solves mixed-integer nonlinear optimal control problems. He uses convexification and relaxation techniques to obtain computationally tractable reformulations for which feasibility and optimality certificates can be given even after discretization and rounding.

Numerical Methods for Unconstrained Optimization and Nonlinear Equations

Numerical Methods for Unconstrained Optimization and Nonlinear Equations
Author: J. E. Dennis, Jr.,Robert B. Schnabel
Publsiher: SIAM
Total Pages: 394
Release: 1996-12-01
ISBN 10: 9781611971200
ISBN 13: 1611971209
Language: EN, FR, DE, ES & NL

Numerical Methods for Unconstrained Optimization and Nonlinear Equations Book Review:

This book has become the standard for a complete, state-of-the-art description of the methods for unconstrained optimization and systems of nonlinear equations. Originally published in 1983, it provides information needed to understand both the theory and the practice of these methods and provides pseudocode for the problems. The algorithms covered are all based on Newton's method or "quasi-Newton" methods, and the heart of the book is the material on computational methods for multidimensional unconstrained optimization and nonlinear equation problems. The republication of this book by SIAM is driven by a continuing demand for specific and sound advice on how to solve real problems. The level of presentation is consistent throughout, with a good mix of examples and theory, making it a valuable text at both the graduate and undergraduate level. It has been praised as excellent for courses with approximately the same name as the book title and would also be useful as a supplemental text for a nonlinear programming or a numerical analysis course. Many exercises are provided to illustrate and develop the ideas in the text. A large appendix provides a mechanism for class projects and a reference for readers who want the details of the algorithms. Practitioners may use this book for self-study and reference. For complete understanding, readers should have a background in calculus and linear algebra. The book does contain background material in multivariable calculus and numerical linear algebra.

Computational Methods in Nonlinear Structural and Solid Mechanics

Computational Methods in Nonlinear Structural and Solid Mechanics
Author: Ahmed K. Noor,Harvey G. McComb
Publsiher: Elsevier
Total Pages: 470
Release: 2014-05-20
ISBN 10: 1483145646
ISBN 13: 9781483145648
Language: EN, FR, DE, ES & NL

Computational Methods in Nonlinear Structural and Solid Mechanics Book Review:

Computational Methods in Nonlinear Structural and Solid Mechanics covers the proceedings of the Symposium on Computational Methods in Nonlinear Structural and Solid Mechanics. The book covers the development of efficient discretization approaches; advanced numerical methods; improved programming techniques; and applications of these developments to nonlinear analysis of structures and solids. The chapters of the text are organized into 10 parts according to the issue they tackle. The first part deals with nonlinear mathematical theories and formulation aspects, while the second part covers computational strategies for nonlinear programs. Part 3 deals with time integration and numerical solution of nonlinear algebraic equations, while Part 4 discusses material characterization and nonlinear fracture mechanics, and Part 5 tackles nonlinear interaction problems. The sixth part discusses seismic response and nonlinear analysis of concrete structure, and the seventh part tackles nonlinear problems for nuclear reactors. Part 8 covers crash dynamics and impact problems, while Part 9 deals with nonlinear problems of fibrous composites and advanced nonlinear applications. The last part discusses computerized symbolic manipulation and nonlinear analysis software systems. The book will be of great interest to numerical analysts, computer scientists, structural engineers, and other professionals concerned with nonlinear structural and solid mechanics.

Nonlinear Systems

Nonlinear Systems
Author: Anonim
Publsiher: BoD – Books on Demand
Total Pages: 262
Release: 2018-07-18
ISBN 10: 1789234042
ISBN 13: 9781789234046
Language: EN, FR, DE, ES & NL

Nonlinear Systems Book Review:

This book focuses on several key aspects of nonlinear systems including dynamic modeling, state estimation, and stability analysis. It is intended to provide a wide range of readers in applied mathematics and various engineering disciplines an excellent survey of recent studies of nonlinear systems. With its thirteen chapters, the book brings together important contributions from renowned international researchers to provide an excellent survey of recent studies of nonlinear systems. The first section consists of eight chapters that focus on nonlinear dynamic modeling and analysis techniques, while the next section is composed of five chapters that center on state estimation methods and stability analysis for nonlinear systems.

Simulation Of Nonlinear Systems In Physics Proceedings Of The Enea Workshops On Nonlinear Dynamics

Simulation Of Nonlinear Systems In Physics   Proceedings Of The Enea Workshops On Nonlinear Dynamics
Author: Pettini M,Maino Giuseppe,Fronzoni L
Publsiher: World Scientific
Total Pages: 236
Release: 1991-10-31
ISBN 10: 9814569720
ISBN 13: 9789814569729
Language: EN, FR, DE, ES & NL

Simulation Of Nonlinear Systems In Physics Proceedings Of The Enea Workshops On Nonlinear Dynamics Book Review:

Data mining and data modeling are hot topics and are under fast development. Because of their wide applications and rich research contents, many practitioners and academics are attracted to work in these areas. With a view to promoting communication and collaboration among the practitioners and researchers in Hong Kong, a workshop on data mining and modeling was held in June 2002. Prof Ngaiming Mok, Director of the Institute of Mathematical Research, The University of Hong Kong, and Prof Tze Leung Lai (Stanford University), C V Starr Professor of the University of Hong Kong, initiated the workshop.This book contains selected papers presented at the workshop. The papers fall into two main categories: data mining and data modeling. Data mining papers deal with pattern discovery, clustering algorithms, classification and practical applications in the stock market. Data modeling papers treat neural network models, time series models, statistical models and practical applications.

Computational Methods in Neural Modeling

Computational Methods in Neural Modeling
Author: José Mira,José R. Álvarez
Publsiher: Springer
Total Pages: 772
Release: 2003-08-03
ISBN 10: 3540448683
ISBN 13: 9783540448686
Language: EN, FR, DE, ES & NL

Computational Methods in Neural Modeling Book Review:

The two-volume set LNCS 2686 and LNCS 2687 constitute the refereed proceedings of the 7th International Work-Conference on Artificial and Natural Neural Networks, IWANN 2003, held in MaÃ3, Menorca, Spain in June 2003.The 197 revised papers presented were carefully reviewed and selected for inclusion in the book and address the following topics: mathematical and computational methods in neural modelling, neurophysiological data analysis and modelling, structural and functional models of neurons, learning and other plasticity phenomena, complex systems dynamics, cognitive processes and artificial intelligence, methodologies for net design, bio-inspired systems and engineering, and applications in a broad variety of fields.

Modeling and Control of Uncertain Nonlinear Systems with Fuzzy Equations and Z Number

Modeling and Control of Uncertain Nonlinear Systems with Fuzzy Equations and Z Number
Author: Wen Yu,Raheleh Jafari
Publsiher: John Wiley & Sons
Total Pages: 208
Release: 2019-06-27
ISBN 10: 1119491541
ISBN 13: 9781119491545
Language: EN, FR, DE, ES & NL

Modeling and Control of Uncertain Nonlinear Systems with Fuzzy Equations and Z Number Book Review:

An original, systematic-solution approach to uncertain nonlinear systems control and modeling using fuzzy equations and fuzzy differential equations There are various numerical and analytical approaches to the modeling and control of uncertain nonlinear systems. Fuzzy logic theory is an increasingly popular method used to solve inconvenience problems in nonlinear modeling. Modeling and Control of Uncertain Nonlinear Systems with Fuzzy Equations and Z-Number presents a structured approach to the control and modeling of uncertain nonlinear systems in industry using fuzzy equations and fuzzy differential equations. The first major work to explore methods based on neural networks and Bernstein neural networks, this innovative volume provides a framework for control and modeling of uncertain nonlinear systems with applications to industry. Readers learn how to use fuzzy techniques to solve scientific and engineering problems and understand intelligent control design and applications. The text assembles the results of four years of research on control of uncertain nonlinear systems with dual fuzzy equations, fuzzy modeling for uncertain nonlinear systems with fuzzy equations, the numerical solution of fuzzy equations with Z-numbers, and the numerical solution of fuzzy differential equations with Z-numbers. Using clear and accessible language to explain concepts and principles applicable to real-world scenarios, this book: Presents the modeling and control of uncertain nonlinear systems with fuzzy equations and fuzzy differential equations Includes an overview of uncertain nonlinear systems for non-specialists Teaches readers to use simulation, modeling and verification skills valuable for scientific research and engineering systems development Reinforces comprehension with illustrations, tables, examples, and simulations Modeling and Control of Uncertain Nonlinear Systems with Fuzzy Equations and Z-Number is suitable as a textbook for advanced students, academic and industrial researchers, and practitioners in fields of systems engineering, learning control systems, neural networks, computational intelligence, and fuzzy logic control.

System and Data Driven Methods and Algorithms

System  and Data Driven Methods and Algorithms
Author: Peter Benner,et al.
Publsiher: Walter de Gruyter GmbH & Co KG
Total Pages: 388
Release: 2021-11-08
ISBN 10: 3110497719
ISBN 13: 9783110497717
Language: EN, FR, DE, ES & NL

System and Data Driven Methods and Algorithms Book Review:

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 first volume focuses on real-time control theory, data assimilation, real-time visualization, high-dimensional state spaces and interaction of different reduction techniques.

Numerical Methods for Nonlinear Engineering Models

Numerical Methods for Nonlinear Engineering Models
Author: John R. Hauser
Publsiher: Springer Science & Business Media
Total Pages: 1013
Release: 2009-03-24
ISBN 10: 1402099207
ISBN 13: 9781402099205
Language: EN, FR, DE, ES & NL

Numerical Methods for Nonlinear Engineering Models Book Review:

There are many books on the use of numerical methods for solving engineering problems and for modeling of engineering artifacts. In addition there are many styles of such presentations ranging from books with a major emphasis on theory to books with an emphasis on applications. The purpose of this book is hopefully to present a somewhat different approach to the use of numerical methods for - gineering applications. Engineering models are in general nonlinear models where the response of some appropriate engineering variable depends in a nonlinear manner on the - plication of some independent parameter. It is certainly true that for many types of engineering models it is sufficient to approximate the real physical world by some linear model. However, when engineering environments are pushed to - treme conditions, nonlinear effects are always encountered. It is also such - treme conditions that are of major importance in determining the reliability or failure limits of engineering systems. Hence it is essential than engineers have a toolbox of modeling techniques that can be used to model nonlinear engineering systems. Such a set of basic numerical methods is the topic of this book. For each subject area treated, nonlinear models are incorporated into the discussion from the very beginning and linear models are simply treated as special cases of more general nonlinear models. This is a basic and fundamental difference in this book from most books on numerical methods.

Model Reduction of Nonlinear Mechanical Systems Via Optimal Projection and Tensor Approximation

Model Reduction of Nonlinear Mechanical Systems Via Optimal Projection and Tensor Approximation
Author: Anonim
Publsiher: Stanford University
Total Pages: 135
Release: 2011
ISBN 10: 1928374650XXX
ISBN 13: STANFORD:td542hm2304
Language: EN, FR, DE, ES & NL

Model Reduction of Nonlinear Mechanical Systems Via Optimal Projection and Tensor Approximation Book Review:

Despite the advent and maturation of high-performance computing, high-fidelity physics-based numerical simulations remain computationally intensive in many fields. As a result, such simulations are often impractical for time-critical applications such as fast-turnaround design, control, and uncertainty quantification. The objective of this thesis is to enable rapid, accurate analysis of high-fidelity nonlinear models to enable their use in time-critical settings. Model reduction presents a promising approach for realizing this goal. This class of methods generates low-dimensional models that preserves key features of the high-fidelity model. Such methods have been shown to generate fast, accurate solutions when applied to specialized problems such as linear time-invariant systems. However, model reduction techniques for highly nonlinear systems has been limited primarily to approaches based on the heuristic proper orthogonal decomposition (POD)--Galerkin approach. These methods often generate inaccurate responses because 1) POD--Galerkin does not generally minimize any measure of the system error, and 2) the POD basis is not constructed to minimize errors in the system's outputs of interest. Furthermore, simulation times for these models usually remain large, as reducing the dimension of a nonlinear system does not necessarily reduce its computational complexity. This thesis presents two model reduction techniques that addresses these shortcomings of the POD--Galerkin method. The first method is a `compact POD' approach for computing the small-dimensional trial basis; this approach is applicable to parameterized static systems. The compact POD basis is constructed using a goal-oriented framework that allows sensitivity derivatives to be employed as snapshots. The second method is a Gauss--Newton with approximated tensors (GNAT) method applicable to nonlinear systems. Similar to other POD-based approaches, the GNAT method first executes high-fidelity simulations during a costly `offline' stage; it computes a POD subspace that optimally represents the state as observed during these simulations. To compute fast, accurate `online' solutions, the method introduces two approximations that satisfy optimality and consistency conditions. First, the method decreases the system dimension by searching for the solutions in the low-dimensional POD subspace. As opposed to performing a Galerkin projection, the method handles the resulting overdetermined system of equations arising at each time step by formulating a least-squares problem; this ensures that a measure of the system error (i.e. the residual) is minimized. Second, the method decreases the model's computational complexity by approximating the residual and Jacobian using the `gappy POD' technique; this requires computing only a few rows of the approximated quantities. For computational mechanics problems, the GNAT method leads to the concept of a sample mesh: the subset of the mesh needed to compute the selected rows of the residual and Jacobian. Because the reduced-order model uses only the sample mesh for computations, the online stage requires minimal computational resources.

Nonlinear System Identification

Nonlinear System Identification
Author: Stephen A. Billings
Publsiher: John Wiley & Sons
Total Pages: 576
Release: 2013-07-29
ISBN 10: 1118535553
ISBN 13: 9781118535554
Language: EN, FR, DE, ES & NL

Nonlinear System Identification Book Review:

Nonlinear System Identification: NARMAX Methods in the Time, Frequency, and Spatio-Temporal Domains describes a comprehensive framework for the identification and analysis of nonlinear dynamic systems in the time, frequency, and spatio-temporal domains. This book is written with an emphasis on making the algorithms accessible so that they can be applied and used in practice. Includes coverage of: The NARMAX (nonlinear autoregressive moving average with exogenous inputs) model The orthogonal least squares algorithm that allows models to be built term by term where the error reduction ratio reveals the percentage contribution of each model term Statistical and qualitative model validation methods that can be applied to any model class Generalised frequency response functions which provide significant insight into nonlinear behaviours A completely new class of filters that can move, split, spread, and focus energy The response spectrum map and the study of sub harmonic and severely nonlinear systems Algorithms that can track rapid time variation in both linear and nonlinear systems The important class of spatio-temporal systems that evolve over both space and time Many case study examples from modelling space weather, through identification of a model of the visual processing system of fruit flies, to tracking causality in EEG data are all included to demonstrate how easily the methods can be applied in practice and to show the insight that the algorithms reveal even for complex systems NARMAX algorithms provide a fundamentally different approach to nonlinear system identification and signal processing for nonlinear systems. NARMAX methods provide models that are transparent, which can easily be analysed, and which can be used to solve real problems. This book is intended for graduates, postgraduates and researchers in the sciences and engineering, and also for users from other fields who have collected data and who wish to identify models to help to understand the dynamics of their systems.

Applications of Turbulent and Multi Phase Combustion

Applications of Turbulent and Multi Phase Combustion
Author: Kenneth Kuan-yun Kuo,Ragini Acharya
Publsiher: John Wiley & Sons
Total Pages: 576
Release: 2012-05-01
ISBN 10: 1118127560
ISBN 13: 9781118127568
Language: EN, FR, DE, ES & NL

Applications of Turbulent and Multi Phase Combustion Book Review:

"This book is the second of two follow-on volumes to the author's bestseller, Principles of Combustion, Second Edition published in 2005. This text focuses on applications, with coverage not available elsewhere, including solid propellants, burning behavior, and chemical boundary layer flows. Kuo provides a multiphase systems approach beginning with more common topics and moving to higher level applications. As with Kuo's earlier book, large numbers of examples and problems and a solutions manual are provided"--Provided by publisher.

Modeling Mesh Generation and Adaptive Numerical Methods for Partial Differential Equations

Modeling  Mesh Generation  and Adaptive Numerical Methods for Partial Differential Equations
Author: Ivo Babuska,Joseph E. Flaherty,William D. Henshaw,John E. Hopcroft,Joseph E. Oliger,Tayfun Tezduyar
Publsiher: Springer Science & Business Media
Total Pages: 450
Release: 2012-12-06
ISBN 10: 1461242487
ISBN 13: 9781461242482
Language: EN, FR, DE, ES & NL

Modeling Mesh Generation and Adaptive Numerical Methods for Partial Differential Equations Book Review:

With considerations such as complex-dimensional geometries and nonlinearity, the computational solution of partial differential systems has become so involved that it is important to automate decisions that have been normally left to the individual. This book covers such decisions: 1) mesh generation with links to the software generating the domain geometry, 2) solution accuracy and reliability with mesh selection linked to solution generation. This book is suited for mathematicians, computer scientists and engineers and is intended to encourage interdisciplinary interaction between the diverse groups.

Scientific and Technical Aerospace Reports

Scientific and Technical Aerospace Reports
Author: Anonim
Publsiher: Unknown
Total Pages: 135
Release: 1994
ISBN 10: 1928374650XXX
ISBN 13: UIUC:30112005547648
Language: EN, FR, DE, ES & NL

Scientific and Technical Aerospace Reports Book Review: