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Grading & evaluation policy
✓ Final grade: Quizzes (5%), Homeworks (20%), Midterm (30%) and Final (45%).
✓ Late homeworks: half credit if the homework is turned in late but before
Thursday at 10a in the instructor’s office. Zero grade afterward.
✓ In homeworks and exams: to obtain full credit, clearly justify your answers. A
result with no proof will only receive partial credit.
✓ Make-up exam: only for medical reason with proper documentation.
✓ Regrading: submit a request in writing to the instructor within one week of
getting your assignment back. Include a clear justification of why you think your
work should be regraded.
Also keep in mind that your entire assignment could be re-considered for
regrading and your grade will be modified (up or down) accordingly.
Academic dishonesty
✓ I remind you the University’s policy on the matter:
http://www-senate.ucsd.edu/manual/Appendices/app2.html
✓ Any student caught cheating will have to face the academic consequences.
✓ Homeworks: you are allowed to discuss the problems among each others but
the work you turn in should be your own.
✓ Exams: no collaboration or discussion of any kind is allowed. Closed-books and
closed-notes exams.
Some recommendations
✓ Try not to fall behind in your studying/reading: the Summer Session goes fast!
✓ If you have questions, seek help from the instructor or the TAs during office
hours: do not wait until Final’s week!
✓ Start thinking about the homework problems early!
✓ Get used to MATLAB as soon as possible (this week).
✓ When writing a MATLAB code, make a generous use of comments.
✓ To ensure the proper grading of your assignment or exam: do not forget to
staple all papers and clearly indicate your name on it.
✓ Please turn off your cellphones and restrict your use of laptop computers to
matters exclusively related to the class.
Questions?
Introduction to scientific computing
in engineering problems
MAE 107: Computational methods in engineering
Lecture Outline
I. Solving an engineering problem
1. Examples of engineering problems and general form
2. Four important steps to model an engineering problem
3. Four possible sources of errors
4. Constraints on scientific computing
II. Numerical methods - importance and overview
1. What are numerical methods?
2. Why should we study numerical methods?
3. Why Matlab?
4. Overview of the numerical methods studied in this class
Engineering problems - Some examples
A single system can correspond to a large variety of
engineering problems:
✓ Mechanical engineering: lift generation,
trajectory control....
✓ Chemical engineering: propellant combustion
and temperature control in the reactors...
✓ Structural engineering: material resistance to
vibrations, heat or shocks,....
✓ Electrical engineering: design and response of
the flight commands...
Space shuttle launch
Airbus jumbo jet A380
Experiments & numerical simulation
in engineering problems
➡ When studying a physical system, experiments can be
performed to obtain some information on its behavior
(wind tunnel, static resistance test, probes, in-flight
measurements...).
➡ However not all the system’s characteristics can be
studied experimentally (stress distribution,
temperature distribution inside the engine, flow profile
around the wing in in-flight conditions)
➡ For some large systems, experiments are also difficult
to perform (e.g. you can not fit an A380 in a wind
tunnel! instead use reduced-size models).
Airbus jumbo jet A380
Numerical simulations are useful to access information that is not available from
experiments.
Numerical simulations must be validated against some experimental data.
Engineering problems - General definition
General objective in solving an engineering problem:
“Given a physical system on which some measurements can be
performed, find a model that describes the behavior of the system
and can be validated against some test experiments, and use it to
predict some characteristics of interest.”
Why are computers necessary?
Most engineering systems are too complex to be solved by hand, and the
computational power of modern computers is an essential element of an
engineer’s life.
Simulation of the flow past a sphere (top) and an
airfoil (bottom) (from NCAR website)
Large systems Continuous systems
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