Steven I. Gordon - Introduction to Modeling and Simulation with MATLAB® and Python (Chapman & Hall/CRC Computational Science)

Introduction to Modeling and Simulation with MATLAB and Python

Chapman & Hall/CRC Computational Science Series

SERIES EDITOR

Horst Simon

Deputy Director

Lawrence Berkeley National Laboratory

Berkeley, California, U.S.A.

PUBLISHED TITLES

COMBINATORIAL SCIENTIFIC COMPUTING

Edited by Uwe Naumann and Olaf Schenk

CONTEMPORARY HIGH PERFORMANCE COMPUTING: FROM PETASCALE TOWARD EXASCALE

Edited by Jeffrey S. Vetter

CONTEMPORARY HIGH PERFORMANCE COMPUTING: FROM PETASCALE TOWARD EXASCALE, VOLUME TWO

Edited by Jeffrey S. Vetter

DATA-INTENSIVE SCIENCE

Edited by Terence Critchlow and Kerstin Kleese van Dam

ELEMENTS OF PARALLEL COMPUTING

Eric Aubanel

THE END OF ERROR: UNUM COMPUTING

John L. Gustafson

EXASCALE SCIENTIFIC APPLICATIONS: SCALABILITY AND PERFORMANCE PORTABILITY

Edited by Tjerk P. Straatsma, Timothy J. Williams, and Katerina Antypas

FROM ACTION SYSTEMS TO DISTRIBUTED SYSTEMS: THE REFINEMENT APPROACH

Edited by Luigia Petre and Emil Sekerinski

FUNDAMENTALS OF MULTICORE SOFTWARE DEVELOPMENT

Edited by Victor Pankratius, Ali-Reza Adl-Tabatabai, and Walter Tichy

FUNDAMENTALS OF PARALLEL MULTICORE ARCHITECTURE

Yan Solihin

THE GREEN COMPUTING BOOK: TACKLING ENERGY EFFICIENCY AT LARGE SCALE

Edited by Wu-chun Feng

GRID COMPUTING: TECHNIQUES AND APPLICATIONS

Barry Wilkinson

HIGH PERFORMANCE COMPUTING: PROGRAMMING AND APPLICATIONS

John Levesque with Gene Wagenbreth

HIGH PERFORMANCE PARALLEL I/O

Prabhat and Quincey Koziol

HIGH PERFORMANCE VISUALIZATION: ENABLING EXTREME-SCALE SCIENTIFIC INSIGHT

Edited by E. Wes Bethel, Hank Childs, and Charles Hansen

INDUSTRIAL APPLICATIONS OF HIGH-PERFORMANCE COMPUTING: BEST GLOBAL PRACTICES

Edited by Anwar Osseyran and Merle Giles

INTRODUCTION TO COMPUTATIONAL MODELING USING C AND OPEN-SOURCE TOOLS

Jos M Garrido

INTRODUCTION TO CONCURRENCY IN PROGRAMMING LANGUAGES

Matthew J. Sottile, Timothy G. Mattson, and Craig E Rasmussen

INTRODUCTION TO ELEMENTARY COMPUTATIONAL MODELING: ESSENTIAL CONCEPTS, PRINCIPLES, AND PROBLEM SOLVING

Jos M. Garrido

INTRODUCTION TO HIGH PERFORMANCE COMPUTING FOR SCIENTISTS AND ENGINEERS

Georg Hager and Gerhard Wellein

INTRODUCTION TO MODELING AND SIMULATION WITH MATLAB AND PYTHON

Steven I. Gordon and Brian Guilfoos

INTRODUCTION TO REVERSIBLE COMPUTING

Kalyan S. Perumalla

INTRODUCTION TO SCHEDULING

Yves Robert and Frdric Vivien

INTRODUCTION TO THE SIMULATION OF DYNAMICS USING SIMULINK

Michael A. Gray

PEER-TO-PEER COMPUTING: APPLICATIONS, ARCHITECTURE, PROTOCOLS, AND CHALLENGES

Yu-Kwong Ricky Kwok

PERFORMANCE TUNING OF SCIENTIFIC APPLICATIONS

Edited by David Bailey, Robert Lucas, and Samuel Williams

PETASCALE COMPUTING: ALGORITHMS AND APPLICATIONS

Edited by David A. Bader

PROCESS ALGEBRA FOR PARALLEL AND DISTRIBUTED PROCESSING

Edited by Michael Alexander and William Gardner

PROGRAMMING FOR HYBRID MULTI/MANY-CORE MPP SYSTEMS

John Levesque and Aaron Vose

SCIENTIFIC DATA MANAGEMENT: CHALLENGES, TECHNOLOGY, AND DEPLOYMENT

Edited by Arie Shoshani and Doron Rotem

SOFTWARE ENGINEERING FOR SCIENCE

Edited by Jeffrey C. Carver, Neil P. Chue Hong, and George K. Thiruvathukal

Introduction to Modeling and Simulation with MATLAB and Python

Steven I. Gordon

Brian Guilfoos

MATLAB and Simulink are trademarks of the MathWorks, Inc. and are used with permission. The MathWorks does not warrant the accuracy of the text or exercises in this book. This books use or discussion of MATLAB and Simulink software or related products does not constitute endorsement or sponsorship by the MathWorks of a particular pedagogical approach or particular use of the MATLAB and Simulink software.

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Contents

M ODELING AND SIMULATION USING computation or computational science has become an essential part of the research and development process in the physical, biological, and social sciences and engineering. It allows the exploration of physical and biological systems at the micro- and molecular level that increase our understanding of their function and the discovery of new materials and new drugs. It allows us to understand the interactions of components in complex systems from those we engineer and build to our ecosystems and climate. In recent years, computational science has produced enormous advances in almost all fields of scientific and technological inquiry, including DNA sequencing, behavioral modeling, global climatic predictions, drug design, financial systems, and medical visualization. At the same time, it has become critical in the design, testing, and manufacturing of new products and services, saving millions of dollars in development costs and getting new products to market more rapidly.

Scientists, social scientists, and engineers must have an understanding of both modeling and computer programming principles so that they appropriately apply those techniques in their practice. Several sets of knowledge and skills are required to achieve that understanding. How do we translate the relationships within a system being modeled into a set of mathematical functions that accurately portray the behavior of that system? How are the mathematics translated into computer code that correctly simulates those relationships? What is the nature of errors introduced by simplifying the depiction of the system, introduced by the computer algorithm used to solve the equations, and limited by our knowledge of the system behavior? How accurate is the model? How do we know the model is logically correct and follows from the physical and mathematical laws used to create it (verification)? How do we demonstrate that the model correctly predicts the phenomena modeled (validation)? These are the underlying questions that are the focus of this book.