ME 6105: Modeling and Simulation in Design

Offered Every Spring

Credit Hours: 3-0-3
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 energy-based and discrete-event systems; modeling of design decisions; information modeling and knowledge representation; project.

R.T. Clemen, Making Hard Decision: An Introduction to Decision Analysis, Duxbury Press, 1997.

Instructors: David Rosen
    • A.P. Sage, J.E. Armstrong Jr., Introduction to Systems Engineering, Wiley & Sons, 2000.
    • Peter Fritzson, Principles of Object-Oriented Modeling and Simulation with Modelica 2.1, Wiley-IEEE 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, McGraw-Hill, 2003.

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, multi-attribute utilities, robustness
  • recognize the trade-offs between the costs and value of different simulation-based design process
  • Course Overview and Introduction
    • Modeling of energy-based 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 energy-based systems
    • The Modelica Language
    • Evaluation and comparison of continuous-time 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 trade-offs under certainty
    • Utility theory
    • Multi-attribute utility theory
    • The role of optimization in design
    • Information Economics -- trade-offs 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 object-oriented modeling in Dymola (10%) -- individual assignment
      • Homework Assignment 2: Planning your simulation-based design study (15%)
      • Homework Assignment 3: Energy-based modeling with Modelica (25%)
      • Homework Assignment 4:Uncertainty Analysis (20%)
      • Homework Assignment 5:Preference modeling and optimization (30%)