Introduction to mathematical methods for environmental engineers and scientists

著者

書誌事項

Introduction to mathematical methods for environmental engineers and scientists

Charles Prochaska, Louis Theodore

Wiley , Scrivener, 2018

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注記

Includes bibliographical references and index

内容説明・目次

内容説明

The authors' aim is to offer the reader the fundamentals of numerous mathematical methods with accompanying practical environmental applications. The material in this book addresses mathematical calculations common to both the environmental science and engineering professionals. It provides the reader with nearly 100 solved illustrative examples and the interrelationship between both theory and applications is emphasized in nearly all of the 35 chapters. One key feature of this book is that the solutions to the problems are presented in a stand-alone manner. Throughout the book, the illustrative examples are laid out in such a way as to develop the reader's technical understanding of the subject in question, with more difficult examples located at or near the end of each set. In presenting the text material, the authors have stressed the pragmatic approach in the application of mathematical tools to assist the reader in grasping the role of mathematical skills in environmental problem-solving situations. The book is divided up into 5 parts: Introduction; Analytical Analysis; Numerical Analysis; Statistical Analysis; and Optimization. The analytical analysis includes graphical, trial-and-error, search, etc. methods. The numerical analysis includes integration, differentiation, differential equation, Monte Carlo, etc. The statistical analysis includes probability, probability distribution, decision trees, regression analysis, etc. Optimization includes both traditional approaches and linear programming.

目次

Preface ix Part I: Introduction 1 1 Fundamentals and Principles of Numbers 3 2 Series Analysis 21 3 Graphical Analysis 29 4 Flow Diagrams 43 5 Dimensional Analysis 53 6 Economics 73 7 Problem Solving 89 Part II: Analytical Analysis 99 8 Analytical Geometry 101 9 Differentiation 115 10 Integration 121 11 Differential Calculus 133 12 Integral Calculus 147 13 Matrix Algebra 161 14 Laplace Transforms 173 Part III: Numerical Analysis 183 15 Trial-and-Error Solutions 185 16 Nonlinear Algebraic Equations 195 17 Simultaneous Linear Algebraic Equations 209 18 Differentiation 219 19 Integration 225 20 Ordinary Differential Equations 235 21 Partial Differential Equations 247 Part IV: Statistical Analysis 259 22 Basic Probability Concepts 261 23 Estimation of Mean and Variance 275 24 Discrete Probability Distribution 287 25 Continuous Probability Distribution 307 26 Fault Tree and Event Tree Analysis 343 27 Monte Carlo Simulation 357 28 Regression Analysis 371 Part V: Optimization 385 29 Introduction to Optimization 387 30 Perturbation Techniques 395 31 Search Methods 405 32 Graphical Analysis 419 33 Analytical Analysis 435 34 Introduction to Linear Programming 449 35 Linear Programming Applications 465

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