Building Software for Simulation: Theory and Algorithms, with Applications in C++

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Building Software for Simulation: Theory and Algorithms, with Applications in C++ by James J. Nutaro

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Building Software for Simulation is different from many other books on simulation because its focuses on the design and implementation of simulation software; by culminating in a complete system for simulation, this book makes itself unique. The design and construction of simulation software has been a topic persistently absent from textbooks even though many, if not most, simulation projects require the development of new software. By addressing this important topic, Building Software for Simulation will, I hope, complement other excellent textbooks on modeling and simulation. This book is intended as both an introduction to simulation programming and a reference for experienced practitioners. I hope you will find it useful in these respects.


This book approaches simulation from the perspective of Zeigler’s theory of modeling and simulation, introducing the theory’s fundamental concepts and showing how to apply these to problems in engineering. The original concept of the book was not so ambitious; its early stages more closely resembled a cookbook for building simulators, focusing almost exclusively on algorithms, examples of simulation programs, and guidelines for the object-oriented design of a simulator. The book retains much of this flavor, demonstrating each concept and algorithm with working code. Unlike a cookbook, however, concepts and algorithms discussed in the text are not disembodied; their origins in the theory of modeling and simulation are made apparent, and this motivates and provides greater insight into their application.


Chapters 3, 4, and 5, are the centerpiece of the text. I begin with discrete-time systems, their properties and structure, simulation algorithms, and applications. Discretetime system will be familiar to most readers and if not, they are easily grasped. Discrete-time systems are generalized to introduce discrete event systems; this approach leads naturally to Zeigler’s discrete-event system specification, its properties and structures, and simulation procedures. The central three chapters conclude with methods for modeling and simulating systems that have interacting continuous and discrete-event dynamics.


The three main chapters are bracketed by applications to robotics, control and communications, and electrical power systems. These examples are more complicated than might be expected in a textbook; three examples occupy two complete chapters. They are, however, described in sufficient detail for a student to reproduce the printed results and to go a step further by exploring unanswered questions about the example systems. The book’s appendixes discuss technical problems that do not fit cleanly into the narrative of the manuscript: testing and design, parallel computing, and a brief review of mathematical topics needed for the examples.


Many people contributed advice and guidance as the book evolved. I am particularly grateful to Vladimir Protopopescu at Oak Ridge National Laboratory for his review of and critical commentary on my rough drafts; his advice had a profound impact on the organization of the text and my presentation of much of the material. I’m also grateful to Angela, who reviewed very early drafts and remarked only rarely on the state of the yard and unfinished projects around the house. Last, but not least, thanks to Joe and Jake, who, in the early morning hours while I worked, quietly (for the most part) entertained themselves.


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