COMP SCI 4177 - Solving Engineering Models - Honours
North Terrace Campus - Semester 1 - 2017
General Course Information
Course Code COMP SCI 4177 Course Solving Engineering Models - Honours Coordinating Unit School of Computer Science Term Semester 1 Level Undergraduate Location/s North Terrace Campus Units 3 Contact Up to 3 hours per week Available for Study Abroad and Exchange Course Description This course concerns techniques for the modelling and simulation of complex systems using a variety of methods and software tools. Students are introduced to the package Matlab and are taken through a study of the techniques used in sophisticated modelling packages to solve common engineering problems.
The Matlab programming language is used extensively and students learn to program their own solutions for these common engineering problems. In addition to studying the equations for these models and their solutions, students study the stability, accuracy and reliability of the solution methods.
Course Coordinator: Professor David Suter
The full timetable of all activities for this course can be accessed from Course Planner.
Course Learning OutcomesOn successful completion of this course students will be able to:
1 To demonstrate an understanding of the methods used to solve certain simulation problems that are common in engineering. 2 To demonstrate a proficiency in the programming language Matlab such as is necessary to solve certain simulation problems that are common in engineering. 3 To demonstrate an ability to write efficient and robust programs which solve certain simulation problems that are common in engineering and to demonstrate an ability to recognize aberrant behaviours of the numerical methods used to solve them.
University Graduate Attributes
This course will provide students with an opportunity to develop the Graduate Attribute(s) specified below:
University Graduate Attribute Course Learning Outcome(s) Deep discipline knowledge
- informed and infused by cutting edge research, scaffolded throughout their program of studies
- acquired from personal interaction with research active educators, from year 1
- accredited or validated against national or international standards (for relevant programs)
1-3 Critical thinking and problem solving
- steeped in research methods and rigor
- based on empirical evidence and the scientific approach to knowledge development
- demonstrated through appropriate and relevant assessment
1-3 Teamwork and communication skills
- developed from, with, and via the SGDE
- honed through assessment and practice throughout the program of studies
- encouraged and valued in all aspects of learning
Required ResourcesA comprehensive set of lecture notes will be given to each student at the start of the course. Students will be required to program extensively with the Matlab programming package. Matlab is available in many of the computing laboratories used by students. Tutorial and assignment questions will be posted on the course website
Students will need to submit their work via the MyUni website.
Recommended ResourcesThe course web page is at
There is no set text for this course but the following references may be useful. Some of these references will be discussed in lectures.
 K.E. Atkinson. An introduction to numerical analysis. Wiley, 1978.
 R.L. Burden and J.D. Faires. Numerical Analysis. PWS-Kent, Boston, 1993. 5th Edition.
 S.C. Chapra and R.P. Canale. Numerical methods for Engineers. McGraw-Hill, New York, 1989. 4th edition.
 W. Cheney and D. Kincaid. Numerical mathematics and computing. Brookes/Cole, 2nd edition, 1985.
 S.D. Conte and C. de Boor. Elementary numerical analysis. McGraw-Hill, 3rd edition, 1980.
 G. Dahlquist and A. Bjork. Numerical methods. Prentice-Hall, 1974.
 L. Fausett. Numerical Methods: Algorithms and Applications. Prentice-Hall, New Jersey, 2003.
 G.E. Forsythe, M. Malcolm, and C.B. Moler. Computer methods for mathematical computations.Prentice-Hall, 1977.
 G.E. Forsythe and C.B. Moler. Computer solution of linear algebraic systems. Prentice-Hall, 1967.
 C. Gerald and P. Wheatley. Applied numerical analysis. Addison-Wesley, 4th edition, 1989.
 W. Hager. Applied numerical linear algebra. Prentice-Hall, 1988.
 E. Isaacson and H.B. Keller. Analysis of numerical methods. Wiley, 1966.
 R.L. Johnston. Numerical methods: A software approach. Wiley, 1982.
 D. Kincaid and W. Cheney. Numerical Mathematics. Brookes/Cole, New York, 1996. 2nd Edition.
 G. Linfield and J. Penny. Numerical methods using Matlab. Ellis-Horwood, 1995.
 J.H. Matthews. Numerical methods. Prentice-Hall, 1987.
 A. Ralston and P. Rabinowitz. A first course in numerical analysis. McGraw-Hill, 2nd edition,1978.
 G. Strang. Linear algebra and its applications. HBJ, 3rd edition, 1988.
 A. Gilat. MATLAB An Introduction with Applications. . 2nd Ed, John Wiley & Sons, 2005.
Online LearningTutorial and assignment questions will be posted on the MyUni course website.
Tutorial problem questions will be posted about one week before the tutorial session where the problems will be discussed. Students will be expected to attempt the problems and to engage in their discussion during the tutorial session. An announcement will be made in lectures before each assignment is posted. Students will need to submit their assignment work via the MyUni forum website
Students can use the Moodle forum to exchange ideas with other students in the course and ask questions about the course.
Learning & Teaching Activities
Learning & Teaching ModesThe course will be taught by lectures supported by problem-solving tutorials developing material covered in the lectures. There will be a strong emphasis on programming in Matlab.
The information below is provided as a guide to assist students in engaging appropriately with the course requirements.The information below is provided as a guide to assist students in engaging appropriately with the course requirements.
Students should expect to spend about 12 hours/week on reviewing lecture material, solving tutorial and assignment problems. Tutorials will start in the second week of the semester.
Learning Activities SummaryA brief introduction to Matlab
Examples of simple applications that lead to linear systems of equations Numrical solution of ODEs in 1D
Initial value problems
Examples of engineering systems that lead to ODEs
Review of the numerical solution of first order ODEs
Adaptive step-size control
Numerical solution of systems of simultaneous first order ODEs
Numerical solution of second and higher order ODEs
Boundary value problems
An explicit finite difference method for the 1D wave equation
Finite difference solution of the potential equation
Systems of linear equations
Review of solution of linear systems of equations
Methods for special matrices arising from engineering problems
Iterative methods for large sparse systems
The ADI method for the 2D heat equation
The University's policy on Assessment for Coursework Programs is based on the following four principles:
- Assessment must encourage and reinforce learning.
- Assessment must enable robust and fair judgements about student performance.
- Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
- Assessment must maintain academic standards.
Assessment SummaryAttendance at all tutorials is compulsory. There will be a written exam for this course. It will count for 70% of the final assessment (learning outcomes 1-3). There will be two assignments, each of which will count for 15% of the final assessment for the course (learning outcomes 1-3). The first assignment will be handed out before the mid-semester break. There are no joint or collaborative assessment tasks for this course.
Assessment DetailThere will be two compulsory assignment tasks set during the course. Students will be required to submit their Matlab program work via MyUni. Assignments which are submitted late will incur a penalty which caps the maximum mark obtainable by 25% for each day late. Thus, submissions which are
1 day late - mark capped at 75%
2 days late - mark capped at 50%
3 days late - mark capped at 25%
more than 3 days late - no marks available.
Students may wish to submit their work even if no marks are available in order to get some feedback about the quality of their work from the markers of the assignments.
SubmissionStudents will be required to submit their Matlab program work via MyUni
Grades for your performance in this course will be awarded in accordance with the following scheme:
M11 (Honours Mark Scheme) Grade Grade reflects following criteria for allocation of grade Reported on Official Transcript Fail A mark between 1-49 F Third Class A mark between 50-59 3 Second Class Div B A mark between 60-69 2B Second Class Div A A mark between 70-79 2A First Class A mark between 80-100 1 Result Pending An interim result RP Continuing Continuing CN
Further details of the grades/results can be obtained from Examinations.
Grade Descriptors are available which provide a general guide to the standard of work that is expected at each grade level. More information at Assessment for Coursework Programs.
Final results for this course will be made available through Access Adelaide.
The University places a high priority on approaches to learning and teaching that enhance the student experience. Feedback is sought from students in a variety of ways including on-going engagement with staff, the use of online discussion boards and the use of Student Experience of Learning and Teaching (SELT) surveys as well as GOS surveys and Program reviews.
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