ENGM 541 & ENGM 670-X5
Modeling and Simulation of Engineering Systems
January 2012 - April
2012
Lectures: Wednesdays from 5:00 PM to 8:00 PM, in ETLE 2-001
Labs: Thursdays from 5:00 PM to 8:00 PM, in ETLE 2-005
This Course Home Page is located at:
http://www.ualberta.ca/~mlipsett/ENGM541/ENGM541.htm
And was last updated
on October 16, 2011
Lecture Schedule and Links FAQ Examples Course
Outline General Course Information
Sample
Midterm (with solutions) Sample
Final (with solutions)
This course has not yet begun.
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Lecture # |
Date |
Topic |
Course Text
Chapter |
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1 |
Jan. 11, 2012 |
Intro
to Modeling and Simulation & Equilibrium Lumped Parameter Systems |
1 |
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Previous Lecture: |
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N/A |
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Assignment |
Assigned Date |
Due Date (in class) |
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To be posted |
Jan. 11, 2012 |
Jan 25, 2012 |
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Announcements:
October
20, 2011:
Formal announcements made to the class during lectures may be subsequently
posted on the course website.
(Revised
October 20, 2010 & Subject to Change):
(links will be made to files
in pdf format for lectures and m4a format for audio
files)
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Week |
Date |
Lecture |
Text Chapter |
|
1 |
Jan. 11, 2012 |
Lecture #1 – Intro Equilibrium
Systems |
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2 |
Jan. 18, 2012 |
Lecture #2 –
Equilibrium Solution Methods |
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3 |
Jan. 25, 2012 |
Lecture #3 – Eqlm Methods, Linearization, Propagation Systems |
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4 |
Feb. 1, 2012 |
Lecture #4 –
Propagation Systems |
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5 |
Feb. 8, 2012 |
Lecture #5 - Propagation
System Solution Methods |
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6 |
Feb.15, 2012 |
Lecture #6 – Modeling
Mixed Dynamics Systems (On-Line Lecture only, not presented in class) |
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- |
Feb. 22, 2012 |
Reading Week (no
lecture or lab) |
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7 |
Feb 29, 2012 |
Midterm Exam (in class) |
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8 |
Mar 7, 2012 |
Lecture #7 - Eigenvalue Systems & Solution Methods |
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9 |
Mar 14, 2012 |
Lecture #8 –
Discrete-Event Systems |
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10 |
Mar 21, 2012 |
Lecture #9 –
Scheduling, Inventory, Systems Thinking |
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11 |
Mar 28, 2012 |
Lecture #10 –
Uncertainty & Sensitivity Analysis |
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12 |
Apr 4, 2012 |
Lecture #11 – Model
Validation, Other Modeling Methods & Packages |
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13 |
Apr 11, 2012 |
Final Exam (in class) |
Week
One
January 11, 2012: Lecture
#1 – Intro
to Modeling and Simulation & Equilibrium Lumped Parameter Systems
What is modeling
Model types
What is simulation
Modeling approaches for
engineering systems for analysis and design
Direct formulation of
lumped-parameter equilibrium systems
Loop and node variables
Constitutive relationships
January 12, 2012: Lab #1 - Introduction
to Matlab
Week
Two
January 18, 2012: Lecture
#2 - General
Lumped-Parameter Equilibrium Problems
Extremum functions
Energy and Co-energy
Formulating the General
Equilibrium Problem
Matrix manipulation to solve
systems of equations
Intro to iterative solution
techniques
January 19, 2012: Lab #2 - MATLAB Functions & Data Visualisation
Week
Three
January 25, 2012: Lecture
#3 - Solving
Systems of Equations, Linearisation, Intro to
Propagation Problems
Iterative techniques to solve
systems of equations
Linearisation
Introduction to propagation
problems
Constitutive relationships
for elements with time-varying variables
January 26, 2012: Lab #3 - Solving
Systems of Simultaneous Equations & Linearisation
Week
Four
February 1, 2012: Lecture
#4 - Lumped-Parameter
Propagation Problems
Recasting 2nd-order
ordinary differential equations into first-order form
Nondimensionalising governing equations
Solution methods for
lumped-parameter propagation problems
Picard’s Method and Taylor
Series for small time intervals
Trial solutions by
undetermined parameters (collocation, subdomain, least squares, Galerkin)
February 2, 2012: Lab #4 - Picard
& Taylor Methods; symbolic differentiation and integration with Matlab; Intro to Simulink
Week
Five
February 8, 2012: Lecture
#5 - Solving
Lumped-Parameter Propagation Problems
Finite difference methods
Errors introduced by discrete
methods
Step Size Extrapolation
Recurrence formulae with
higher-order truncation errors (Runge-Kutta)
February 9, 2012: Lab #5 - Numerical
integration techniques in Matlab, Simulating
Propagation Models in Simulink, System Linearisation
Week
Six
February 15, 2012: Lecture
#6: - Modeling
of Mixed Dynamical Systems (This lecture will be posted online only, as
the instructor will be at research meetings in Germany)
Mixed Systems
Transducers
Multi-port elements
Mixed system formulations
Modeling damage accumulation
as a mixed system
February 16, 2012: Lab #6 –Modeling
Mixed Systems and Analysing Linear Systems in MATLAB Impact
Dynamics; Informal Midterm Preview; Project discussions
Project proposals are due by 5 p.m.
February 16, 2012
February
22 & 23, 2012: No lecture or lab (Winter Term Reading Week)
Week
Seven
February 29, 2012: MIDTERM EXAMINATION
(2 hours) 5 pm - 7 pm in ETLE 2-001
March 8, 2012: Lab – project work session
Week
Eight
March 7, 2012: Lecture #7: Eigenvalue Systems & Solution
Methods
Solution Methods: Classic
approaches & Diagonalisation using Jacobi
Rotation
Singular Value Decomposition
March 8, 2012: Lab #7 – Eigenvalue
Systems in MATLAB
Week
Nine
March 14, 2012: Lecture #8: Modeling
Discrete-Event Systems & Manufacturing Processes
Introduction to
discrete-event systems
Modeling states
Modeling conditions
State transitions
Forming system models from
elements
Synchronous and asynchronous
models
Model verification
Examples
March 15, 2012: Lab #8 - Modeling Discrete-Event Systems in SimEvents and Excel;
Project Work Session
Week
Ten
March 21, 2012: Lecture #9 Scheduling,
Financial Analysis & Systems in Organisations
Methods for Discrete-Event
Simulation
Modeling movement and
transformation of material, energy, and information in engineering systems
Scheduling & inventory as
discrete-event systems
Financial analysis of
engineering systems: transactions as discrete-events
Systems in organisations: Systems Thinking
March 22, 2012: Lab #9 Modeling DES (2); Project work
session
Project updates are due by 5 p.m.
March 22, 2011 (5 pages max)
Week
Eleven
March 28, 2012: Lecture #10 Uncertainty,
Sensitivity, and Monte Carlo Simulation
Uncertainty and sensitivity
analysis
Bayes Risk
Probability distribution
functions, estimating probabilities and loss functions
Probabilistic simulations: an
introduction to Monte Carlo methods for equilibrium lumped-parameter and
discrete-event systems
March 29, 2012: Lab #10 Monte Carlo simulation
Week
Twelve
April 4, 2012: Lecture #11 Model Validation & Applications
Model validation &
parameter estimation
Other Modeling Methods:
Hybrid systems models, physical systems models, analogues, multi-physics
modeling
Commercial simulation
packages
Course review of methods for
modeling, analysis, and simulation
April 5, 2011: Lab - Review of MATLAB methods and wrap-up Q&A; project
work.
PROJECT
DUE April 5, 2012 by 5 pm (submitted
to instructor or handed in at MEC E office)
Week
Thirteen
April 11, 2012:
FINAL
EXAMINATION (2.5
hours, in class) 5 pm – 7:30 pm in ETLE
2-001
(To be announced. Links are to files in pdf format)
|
Assignment |
Assigned Date |
Due Date (in class) |
|
|
Assignment #1; |
January
11, 2012 |
January 25, 2012 |
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Assignment #2; |
January 25, 2012 |
February 8, 2012 |
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Assignment #3 |
February 8, 2012 |
February 22, 2012 |
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Assignment #4 |
March 7, 2012 |
March 21, 2012 |
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Assignment #5 |
March 21, 2012 |
April 4, 2012 |
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# |
Project Assignment |
Proposal
Due Date |
Update
Due Date |
Project Due
Date |
|
Project |
Proposal to be approved by instructor |
Feb 16, 2012* |
Mar
22, 2012* |
April
5, 2012 by
5 pm |
*
Project proposals can be discussed with the instructor at any time. A project
on modeling and analysis of a system designed for another course (e.g. MEC E
460) is eligible, provided the instructor for the other course approves of the
topic (so that there is no double-credit given for the same work). The written
proposal for the project is due on February 11, 2010 by 5 p.m. The template
includes project expectations and types of topics. Late proposals will be
subject to penalty. A project update report (5 pages maximum length) is due on
March 18, 2010 by 5 pm. Late reports may be subject to
penalty.
**
The final project report will only be accepted late in the case of a
documented medical or personal emergency. There is a schedule for mark losses
described in the course outline.
Lecture Room: ETLE 2-001 (ETLC); Laboratory: ETLE 2-005
Instructor: MG Lipsett,
Department of Mechanical Engineering, Engineering Management Group
Email: Michael [dot] Lipsett [at] ualberta [dot] ca
Office: 5-8J Mechanical Engineering Building (5th Floor West)
Office Hours: Wednesday 1:00 PM to 3:00 PM, or by appointment (and whenever my door
is open, but I may ask you to come back later).
TA: Masoud Mashkournia
Email: masoudm [at] ualberta
[dot] ca
Course Text:
Kulakowski, B.T., Gardner, J.F., Shearer, J.L. Dynamic Modeling and Control of
Engineering Systems. Third Ed. Cambridge University Press, 2007.
Marking
Scheme:
Assignments: 25% of course mark (lab exercises and analysis problem sets - extra
questions for grad students taking MECE 758). No late assignments will be
accepted once solutions are posted.
Project: 20% of
course mark (chosen midway through course). A range
of topics can be selected; see the template
for more information (an
RTF version which can be used for your proposal is posted here). The final
project report is due on April 7, 2010 before 5 p.m. No late projects accepted,
except in the case of a valid documented medical or personal emergency.
Midterm Exam: 25% of course mark. The midterm will be held during the regular
classroom session on Wednesday March 3, 2010, from 5:00 pm to 7:00 pm in ETLE
2-001. The midterm will be two hours in duration, open book, open notes.
Programmable calculators allowed.
Final Exam: 30% of course mark. The final exam will be held during the classroom
session on Wednesday April 7, 2010, from 5:00 pm to 7:00 pm in ETLE 2-001. The
final exam will be two-and-a-half hours in duration, open book, open notes. Programmable calculators allowed.
Course Overview
& Format:
The lectures cover theory and methods for developing
governing equations for different types of engineering systems (equilibrium,
eigenvalue, and propagation), and how to solve them numerically.
The laboratory part of the course uses MATLAB® and SIMULINK® to analyze different systems, understand the limitations of different
methods, and interpret the modeling and simulation results. Lab assignments
follow naturally from lectures, with worked examples. There is a minimum of
numerical method coding; the lab work focuses on how to model systems, apply
appropriate numerical procedures, and interpret results in context. (MECE 758
students are responsible for the lab material, but do not have to attend the
lab sessions.)
Emphasis is on lumped-parameter formulations as
opposed to continuous systems, and primarily for physical systems. Model
representations of information flow and finance are also discussed for decision
making. Issues of numerical stability and model validation are also discussed.
This course
will be lecture based, primarily using slides in pdf
format that will be made available in advance from the course web-site. These
lecture slides are supplemented with notes for selected discussions, and with
in-class computer-based problem-solving examples. Resources are contained in
the text-book and the course web-site (this site). Formal announcements made to
the class may be subsequently posted on the course website.
All
overheads and notes for the course are subject to copyright. Reproduction for
distribution other than for your personal use is prohibited unless explicit
specific permission is granted. Recording of lectures is prohibited unless part
of an approved accommodation, or unless there is prior written approval from
the course instructor.
Other Sources of Course Material:
Course
Outline:
Link to course outline for ENGM 541.
Link to course
outline for MECE 758-X5.
Note:
The University of Alberta is committed to the highest
standards of academic integrity and honesty. Students are expected to be
familiar with these standards regarding academic honesty and to uphold the
policies of the University in this respect. Students are particularly urged to
familiarize themselves with the provisions of the Code of Student Behaviour
(online at www.ualberta.ca/secretariat/appeals.htm)
and avoid any behaviour which could potentially result in suspicions of
cheating, plagiarism, misrepresentation of facts and/or participation in an
offence. Academic dishonesty is a serious offence and can result in suspension
or expulsion from the University. Policy about course outlines can be found in
Section 23.4(2) of the University Calendar.
Feedback:
Good managers are committed to effective interactions
with the people they work with. It is critical that there be good lines of
communication, not only for stating expectations but also for accepting
feedback on performance. (Of course, this communication has to go both ways to
be effective: the employee has to trust the manager to accept feedback
non-judgmentally.) In this course, the instructor welcomes constructive
feedback (which can be positive or negative) and any suggestions for
improvements to the course. Discussion during the class can significantly
improve the learning experience. If you have a question for clarification or a
relevant comment (or if the instructor has made an error…), please share it
with the class.