An Introduction To Computer Simulation In Applied Science

This set of lectures is the outgrowth of a new course in the Department of Materials Science at Stanford University. It was taught collectively by the authors of the various sections and represents an attempt to increase the awareness of students in the materials area of computer simulation techniques and potentialities. The topics often ranged far afield from the materials area; however, the total package served the intended purpose of being an initiation into the world of computer simulation and, as such, made a useful first iteration to the intended purpose. The second iteration, which is in process, deals exclusively with the materials area. The course was designed to teach students a new way to wrestle with "systems" problems in the materials science work area that require the synthesis and interactions of several disciplines of knowledge. This course was a response to the realization that effective handling of real problems, which are essentially systems problems, is one of the most important at tributes of a graduate materials scientist. About a third of the course was devoted to the student's selected problem, in the materials area, which he simulated using the digital computer.

What is it about the structure and organisation of science and technology that has led to the spectacularly successful growth of knowledge during this century? This book explores this important and much debated question in an innovative way, by using computer simulations. The computer simulation of societies and social processes is a methodology which is rapidly becoming recognised for its potential in the social sciences. This book applies the tools of simulation systematically to a specific domain: science and technology studies. The book shows how computer simulation can be applied both to questions in the history and philosophy of science and to issues of concern to sociologists of science and technology. Chapters in the book demonstrate the use of simulation for clarifying the notion of creativity and for understanding the logical processes employed by eminent scientists to make their discoveries. The book begins with three introductory chapters. The first introduces simulation for the social sciences, surveying current work and explaining the advantages and pitfalls of this new methodology. The second and third chapters review recent work on theoretical aspects of social simulation, introducing fundamental concepts such as self organisation and complexity and relating these to the simulation of scientific discovery.

Proceedings of the NATO Advanced Study Institute, Aussois, France, March 25-April 5, 1991

The result of lectures given by the authors at New York University, the University of Utah, and Michigan State University, the material is written for students who have had only one term of calculus, but it contains material that can be used in modeling courses in applied mathematics at all levels through early graduate courses. Numerous exercises are given as well as solutions to selected exercises, so as to lead readers to discover interesting extensions of that material. Throughout, illustrations depict physiological processes, population biology phenomena, corresponding models, and the results of computer simulations. Topics covered range from population phenomena to demographics, genetics, epidemics and dispersal; in physiological processes, including the circulation, gas exchange in the lungs, control of cell volume, the renal counter-current multiplier mechanism, and muscle mechanics; to mechanisms of neural control. Each chapter is graded in difficulty, so a reading of the first parts of each provides an elementary introduction to the processes and their models.

"The book provides a clear exposition of much that is relevant to simulation. . . . The authors then focus on the elements of computer simulation, namely, the assumptions upon which simulation is built: parameters, inputs or independent variables, algorithms or process decision rules, and outputs or dependent variables. Each of these facets, and the extent to which they need to be fully appreciated if simulation is to prove successful, is treated with care and clarity. . . Chapter 2 . . . is particularly well written and is exactly the type of treatment that should be included in a any graduate course on applied social research methods. . . Overall this is a book which many among the community of systems practitioners will find worthwhile reading." --Systems Practice "It is a readable book and--as intended--is easily accessible for the novice. The purpose and process of simulation modelling are described in brief, but clear, terms and are illustrated by the three well-chosen examples." --Telephone Surveys "This book is a good place to begin one's education in the potential for using computer simulations in theory building and policy analysis. As with any good book, it will whet your appetite and raise almost as many questions as it answers." --Social Science Computer Review Computer simulation represents one of the fastest growing areas for conducting research in the social sciences. Now, in Computer Simulation Applications, Marcia Lynn Whicker and Lee Sigelman show you how simulations can be used to analyze social systems for the purposes of theory building and policy analysis. They discuss the strengths and weaknesses of computer simulations as a research method and outline the various steps involved in designing a simulation model. In addition, they provide practical suggestions on how to use a simulation model to test hypotheses, how to evaluate and validate a model, and the relative advantages of general purpose programming languages versus specialized sensitivity testing. If you're currently conducting or considering computer simulations in your research, then this volume is a must for your professional toolkit.

This unique volume introduces and discusses the methods of validating computer simulations in scientific research. The core concepts, strategies, and techniques of validation are explained by an international team of pre-eminent authorities, drawing on expertise from various fields ranging from engineering and the physical sciences to the social sciences and history. The work also offers new and original philosophical perspectives on the validation of simulations. Topics and features: introduces the fundamental concepts and principles related to the validation of computer simulations, and examines philosophical frameworks for thinking about validation; provides an overview of the various strategies and techniques available for validating simulations, as well as the preparatory steps that have to be taken prior to validation; describes commonly used reference points and mathematical frameworks applicable to simulation validation; reviews the legal prescriptions, and the administrative and procedural activities related to simulation validation; presents examples of best practice that demonstrate how methods of validation are applied in various disciplines and with different types of simulation models; covers important practical challenges faced by simulation scientists when applying validation methods and techniques; offers a selection of general philosophical reflections that explore the significance of validation from a broader perspective. This truly interdisciplinary handbook will appeal to a broad audience, from professional scientists spanning all natural and social sciences, to young scholars new to research with computer simulations. Philosophers of science, and methodologists seeking to increase their understanding of simulation validation, will also find much to benefit from in the text.