ECE 59500 - Modeling and Simulation of Multidisciplinary Systems

Lecture Hours: 3 Credits: 3

Counts as:
EE Elective

Experimental Course Offered: Spring 2011

Requisites:
MA 26500 and MA 26500 or MA 26200 and PHYS 27200 or PHYS 24100.

Catalog Description:
Physical systems are becoming increasingly multidisciplinary. Design and development is now viewed as a problem in systems, requiring a systems perspective. This is because subsystem components designed by specialists often do not work as efficiently or as robustly as a comparable system designed in a unified way. So today's engineer must be technically competent beyond her or his core discipline. In this course, the student is introduced to the design, modeling, and simulation of multidisciplinary engineered systems. The types of analyses include system-level lumped and distributed. The physical disciplines introduced include electrical, mechanical, thermal, and fluid domains at the nano, micro, and macroscopic length scales. Examples of topics include micro and nano electro mechanical systems (M/NEMS), pressure sensors, accelerometers, gyros, biological sensors, positioners, robotics, system of systems, etc. The student learns how to create behavioral models and how to systematically represent multidisciplinary systems in a unified manner.

Supplementary Information:
The online text, lecture notes, and tutorials contain analytical and computer-based exercises and homework problems utilizing Comsol and Matlab. Students will have access to the computer tools at no additional charge. Course co-listed with ME 59700.

Required Text(s): None.

Recommended Text(s):
  1. Computer Methods for Ordinary Differential Equations and Differential-Algebraic Equations, 1st Edition, Uri M. Ascher, Linda R. Petzold, SIAM, 1998, ISBN No. 0898714125.
  2. Modeling and Simulation of Multidisciplinary Systems, ISBN No. J.V. Clark.

Learning Outcomes:

  1. An understanding of the fundamentals of unified system dynamics. [a,k]
  2. An understanding of representation of holonomic and nonholonomic constraints. . [a,k]
  3. An understanding of variational concepts. . [a,k]
  4. An ability to apply LDAE (Lagrangian Differential Algebraic Equations) to model multidisciplinary systems. . [a,c,e,k]
  5. An ability to simulate LDAEs and assess the reliability of DAE solvers.. [a,b,e,k]
  6. An ability to create nonlinear lumped behavioral models from numerical or experimental data.. [a,e,k]
  7. An ability to apply standard device models to explain/calculate critical internal parameters and standard characteristics of the Bipolar Junction Transistor. . [a,c,e,k]
  8. An ability to design complex engineered systems. . [b,c,e,i,j,k]
  9. An ability to professionally present an original design, modeling, and simulation project in both an oral and a publication style report. . [g,j]

Lecture Outline:

Weeks Major Topics
.5 Module 1: Introduction to complex engineered systems 1. What are complex systems 2. Tomorrow's vs yesterday's systems 3. Lumped vs distributed analyses 4. Simulation vs experiment / Verification vs validation 5. Accuracy vs precision / Robustness 6. State of the art
.5 Module 2: Fundamentals of unified system dynamics 1. Unified set of variables 2. Discrete elements 3. Kinetic stores 4. Potential stores 5. Path-independent dissipators 6. Path-dependent dissipators
1 Module 3: Representation of motion, constraints 1. Variable pairs 2. Configuration & state spaces 3. Displacement constraints 4. Flow constraints 5. Effort constraints 6. Dynamic constraints 7. Degrees of freedom
1 Module 4: Variational concepts, geometry of constraint 1. Types of displacement 2. Virtual work 3. Lagrange's principle 4. Effort classification 5. Holonomic constraints 6. Nonholonomic constraints 7. Virtual momentum
2 Module 5 : Lagrangian and Hamiltonian differential algebraic equations of motion 1. 1st law of thermodynamics in variational form 2. Work and energy 3. Lagrange equation 4. Euler-Lagrange eqn. 5. Lagrange multipliers 6. Lagrangian DAE 7. Underlying ODE 8. Legendre transform 9. Hamiltonian DAE 10. LDAE vs HDAE
3 Module 6 : Modeling multidisciplinary systems 1. Schematics, configuration 2. Formulating models 3. Model automation 4. Sensors & actuators 5. Nanoscale systems 6. Microscale systems 7. Robotic systems 8. Transport systems 9. Industrial systems
2 Module 7: Simulating multidisciplinary systems 1. Software tools for DAEs 2. Software tools for PDEs 3. Reduced order modeling 4. Behavioral modeling from data 5. Modeling convergence 6. Verification vs Validation
2 Module 8: Special topics 1. How to write a scientific publication. How to patent. 2. Optimization, genetic algorithms, genetic programming 3. Hybrid systems 4. Hierarchical Temporal Memory
3 Module 9 : Numerical methods 1. Differential index 2. Mathematical structure 3. Special DAE forms 4. DAE stability 5. Index reduction 6. Reformulation of higher-index DAEs 7. Modified Newton 8. Backward Difference Formulation 9. Implicit Runge-Kutta for DAEs 10. DAE manifolds 11. Stabilization matrix
3 Module 9 : Numerical methods 1. Differential index 2. Mathematical structure 3. Special DAE forms 4. DAE stability 5. Index reduction 6. Reformulation of higher-index DAEs 7. Modified Newton 8. Backward Difference Formulation 9. Implicit Runge-Kutta for DAEs 10. DAE manifolds 11. Stabilization matrix

Engineering Design Content:

Establishment of Objectives and Criteria
Synthesis
Analysis
Construction
Testing
Evaluation

Engineering Design Consideration(s):

Economic
Environmental
Ethical
Health/Safety
Manufacturability
Social
Sustainability