Applied Dimensional Analysis and Modeling

Applied Dimensional Analysis and Modeling

Author: Thomas Szirtes

Publisher: Butterworth-Heinemann

Published: 2007-04-27

Total Pages: 853

ISBN-13: 0080555454

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Applied Dimensional Analysis and Modeling provides the full mathematical background and step-by-step procedures for employing dimensional analyses, along with a wide range of applications to problems in engineering and applied science, such as fluid dynamics, heat flow, electromagnetics, astronomy and economics. This new edition offers additional worked-out examples in mechanics, physics, geometry, hydrodynamics, and biometry. Covers 4 essential aspects and applications: principal characteristics of dimensional systems, applications of dimensional techniques in engineering, mathematics and geometry, applications in biosciences, biometry and economics, applications in astronomy and physics Offers more than 250 worked-out examples and problems with solutions Provides detailed descriptions of techniques of both dimensional analysis and dimensional modeling


Dimensional Analysis In The Identification Of Mathematical Models

Dimensional Analysis In The Identification Of Mathematical Models

Author: Lysik Bertold

Publisher: World Scientific

Published: 1990-09-12

Total Pages: 206

ISBN-13: 981450677X

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This book is the first textbook with the generalization of Dimensional Analysis, specially prepared to solve problems of identification of mathematical models based on experimental data. The generalization gives the possibility of mathematical model invariant with regard to gauge group, groups of rotation and others. The resulting formalism generates the most general and tensor homogeneous form of possible functional dependence.


Similitude and Approximation Theory

Similitude and Approximation Theory

Author: S.J. Kline

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 246

ISBN-13: 3642616380

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There are a number of reasons for producing this edition of Simili tude and Approximation Theory. The methodologies developed remain important in many areas of technical work. No other equivalent work has appeared in the two decades since the publication of the first edition. The materials still provide an important increase in understanding for first-year graduate students in engineering and for workers in research and development at an equivalent level. In addition, consulting experiences in a number of industries indi cate that many technical workers in research and development lack knowledge of the methodologies given in this work. This lack makes the work of planning and controlling computations and experiments less efficient in many cases. It also implies that the coordinated grasp of the phenomena (which is so critical to effective research and develop ment work) will be less than it might be. The materials covered in this work focus on the relationship between mathematical models and the physical reality such models are intended v vi Preface to the Springer Edition to portray. Understanding these relationships remains a key factor in simplifying and generalizing correlations, predictions, test programs, and computations. Moreover, as many teachers of engineering know, this kind of understanding is typically harder for students to develop than an understanding of either the mathematics or the physics alone.


High-Dimensional Data Analysis with Low-Dimensional Models

High-Dimensional Data Analysis with Low-Dimensional Models

Author: John Wright

Publisher: Cambridge University Press

Published: 2022-01-13

Total Pages: 718

ISBN-13: 1108805558

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Connecting theory with practice, this systematic and rigorous introduction covers the fundamental principles, algorithms and applications of key mathematical models for high-dimensional data analysis. Comprehensive in its approach, it provides unified coverage of many different low-dimensional models and analytical techniques, including sparse and low-rank models, and both convex and non-convex formulations. Readers will learn how to develop efficient and scalable algorithms for solving real-world problems, supported by numerous examples and exercises throughout, and how to use the computational tools learnt in several application contexts. Applications presented include scientific imaging, communication, face recognition, 3D vision, and deep networks for classification. With code available online, this is an ideal textbook for senior and graduate students in computer science, data science, and electrical engineering, as well as for those taking courses on sparsity, low-dimensional structures, and high-dimensional data. Foreword by Emmanuel Candès.


Application of Dimensional Analysis in Economics

Application of Dimensional Analysis in Economics

Author: W.M. Grudzewski

Publisher: IOS Press

Published: 2013-08-20

Total Pages: 152

ISBN-13: 1614992800

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The modeling of economic phenomena and processes, in terms of their static and dynamic features and with regard to the characteristics of their course, is a major methodological trend in studies of the nature, properties and functioning of contemporary management systems. Models describing management systems must be of a multi-aspect nature, entailing aspects such as technical, economic and sociological factors on the one hand, and forecasting, planning, leading, controlling etc., on the other. Developing a method for incorporating such diverse data into a system of analysis is, needless to say, a complex process. Dimensional analysis is a tool which might be useful in this process, but one which, up to now, has been little explored in the economic sciences. This book explores the application of dimensional analysis in the field of economics. It has been structured in a way which corresponds to the formulation of economic quantities, and is divided into five sections: measuring of economic quantities, modeling of economic processes, principles of dimensional analysis, building of quantified dimensional models, and experiment and practical verification.