Simulation in Systems Engineering: Discrete-Time Systems

Catalog description

The scale and cost of typical systems engineering projects mandate that proposed solutions are explored through integrated models and simulations such that stakeholders are confident that the system will work as intended upon deployment. In this course we examine the use of discrete-time approaches to these integrated models and their application to systems engineering. The course covers fundamental concepts, methods, and applications of modeling and simulation with a particular emphasis on problem framing, conceptual model development, and modeling systems of interconnected heterogeneous systems using hybrid simulation. The course begins with an overview of different types of systems and models, model verification and validation processes, sources of randomness and uncertainty, and reviews basic concepts related to computer simulation. Students are given an overview of two types of simulation, namely Monte Carlo and discrete event simulation. Basic concepts related to input modeling, experimentation, and output analysis are covered. Students will then learn how to combine the two simulation methods and develop hybrid simulations to model a system of interconnected subsystems and the importance of modeling these interrelationships. The students also gain hands-on experience on additional topics such as simulation-based optimization by using a commercial simulation software package.