Credit Hours: 
303 
Prerequisites: 
Graduate standing in engineering or related discipline; Undergraduate seniors with permission of the instructor. 
Catalog Description: 
Modeling and simutaltion concepts, algorithms, and methods; modeling of energybased and discreteevent systems; modeling of design decisions; information modeling and knowledge representation; project. 
Textbooks: 
R.T. Clemen, Making Hard Decision: An Introduction to Decision Analysis, Duxbury Press, 1997. 
Instructors: 
David Rosen 
References: 
 A.P. Sage, J.E. Armstrong Jr., Introduction to Systems Engineering, Wiley & Sons, 2000.
 Peter Fritzson, Principles of ObjectOriented Modeling and Simulation with Modelica 2.1, WileyIEEE Computer Society Press, 2003.
 F. E. Cellier and E. Kofman, Continuous System Simulation, Springer, 2006.
 W. Kelton, R. Sadowski, D. Sturrock, Simulation with Arena, 3rd edition, McGrawHill, 2003.

Goals: 
Upon completion of this course, the student should be able to:
 frame decisions: objectives, alternatives, outcomes, preferences.
 evaluate design alternatives by conducting simulation studies
 select the appropriate modeling paradigm to support a design decision
 select a solution algorithm that matches the characteristics of an analysis model
 critically evaluate analysis results in the presence of uncertainty
 model designer preferences  risk averseness, multiattribute utilities, robustness
 recognize the tradeoffs between the costs and value of different simulationbased design process

Topics: 
 Course Overview and Introduction
 Modeling of energybased systems
 Object Oriented Modeling in Dymola
 Modeling the structure of design problems
 Modeling the structure of design problems: Influence diagrams
 Modeling Design Objectives
 What is modeling and Simulation?
 Modeling of energybased systems
 The Modelica Language
 Evaluation and comparison of continuoustime M&S software
 Solving differential (algebraic) equations
 Debugging Modelica Models
 Modeling uncertainty
 Sources and types of uncertainty
 Representation of uncertainty
 Computing with uncertainty information
 Sensitivity Analysis
 The Method of Morris
 Modeling preferences
 Value functions and tradeoffs under certainty
 Utility theory
 Multiattribute utility theory
 The role of optimization in design
 Information Economics  tradeoffs between (design) process and system objective
 Selected Topics
 Information Modeling for Systems Engineering  SysML
 Example: Discrete event simulation in Arena



Grading Scheme (%): 
There are no exams. The entire grade will be based on a comprehensive course project that is divided into 5 homework assignments:
 Homework Assignment 1: Becoming familiar with objectoriented modeling in Dymola (10%)  individual assignment
 Homework Assignment 2: Planning your simulationbased design study (15%)
 Homework Assignment 3: Energybased modeling with Modelica (25%)
 Homework Assignment 4:Uncertainty Analysis (20%)
 Homework Assignment 5:Preference modeling and optimization (30%)

