Digital Continuous System Simulation

obtained by simulation more quickly, effec Computer simulation of dynamic systems is a topic which is growing steadily in importance tively and cheaply than by experimentation and testing of the real system. System perfor in the physical sciences, engineering, biology and medicine. The reasons for this trend mance can also be investigated using simula relate not only to the steadily increasing tion for a much wider range of conditions than can be contemplated for the real system power of computers and the rapidly falling costs of hardware, but also to the availability because of operating constraints or safety of appropriate software tools in the form of requirements. Similar factors can apply in simulation languages. Problem-oriented lan other fields, such as biomedical systems guages of this kind assist those who are not engineering. specialists in computational methods to trans System simulation, using digital computers, can relate either to models based on continu late a mathematical description into a simula tion program in a simple and straightforward ous variables or to discrete-event descriptions. fashion. They can also provide useful diag Continuous system simulation techniques are applied to systems described by sets of differ nostic information when difficulties are encountered. Therefore, a simulation lan ential equations and algebraic equations.

Highly computer-oriented text, introducing numerical methods and algorithms along with the applications and conceptual tools. Includes homework problems, suggestions for research projects, and open-ended questions at the end of each chapter. Written by our successful author who also wrote Continuous System Modeling, a best-selling Springer book first published in the 1991 (sold about 1500 copies).

Modeling and Simulation have become endeavors central to all disciplines of science and engineering. They are used in the analysis of physical systems where they help us gain a better understanding of the functioning of our physical world. They are also important to the design of new engineering systems where they enable us to predict the behavior of a system before it is ever actually built. Modeling and simulation are the only techniques available that allow us to analyze arbitrarily non-linear systems accurately and under varying experimental conditions. Continuous System Modeling introduces the student to an important subclass of these techniques. They deal with the analysis of systems described through a set of ordinary or partial differential equations or through a set of difference equations. This volume introduces concepts of modeling physical systems through a set of differential and/or difference equations. The purpose is twofold: it enhances the scientific understanding of our physical world by codifying (organizing) knowledge about this world, and it supports engineering design by allowing us to assess the consequences of a particular design alternative before it is actually built. This text has a flavor of the mathematical discipline of dynamical systems, and is strongly oriented towards Newtonian physical science.

Provides a basic and unifying model for all possible approaches to CSS and computer simulation.

This text presents dynamic systems simulation in an accessible manner for both experienced users and newcomers to the field. The book focuses on the methods and tools available for computer simulation of predominantly continuous systems and offers many case study examples.

This is a basic textbook for those who wish to use digital computers for simulating engineering and business systems. It is meant for the students of engineering and business management as well as for systems analysts, industrial engineers and operations research professionals.The reader has been given enough grounding so that he can use simulation to solve simple but mathematically intractable problems. This compact basic textbook has been well received by students and professionals for many years.

Teaches digital simulation of continuous systems with MIMIC, DSL/90 and FORTRAN IV programming and presents the logic and construction of a simplified MIMC processor, the SIMIC processor.