Students
COMP350 – Special Topics in Computing and Information Systems
2015 – S2 Day
General Information
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| Unit convenor and teaching staff |
Unit convenor and teaching staff
Shaokoon Cheng
Lecturer
Ann Lee
Contact via 9850 9069
Christophe Doche
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|---|---|
| Credit points |
Credit points
3
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| Prerequisites |
Prerequisites
Permission of Executive Dean of Faculty
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| Corequisites |
Corequisites
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| Co-badged status |
Co-badged status
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| Unit description |
Unit description
This unit is a special topic unit that may be offered from time to time in new areas of computing and information systems, or as a special project under the supervision of a member of staff.
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Important Academic Dates
Information about important academic dates including deadlines for withdrawing from units are available at https://www.mq.edu.au/study/calendar-of-dates
Learning Outcomes
On successful completion of this unit, you will be able to:
- Understand how engineering problems can be solved using basic mathematical models and numerical methods.
- Ability to identify risk associated with floating point computations and perform error analysis.
- Ability to develop techniques for accurate and efficient solution of models based on linear and nonlinear equations, ordinary differential equations and partial differential equations.
- Demonstrate skill in Matlab as the tool to implement numerical analysis for practical engineering problems.
General Assessment Information
The following conditions apply for assessments:
In the event that an assessment task is submitted late, the following penalties will apply; 0 to 24 hours - 25%, 24 hours to 48 hours - 50%, greater than 48 hours will result in no mark being awarded.
For both the midterm and final examinations, not following instructions as indicated may result in the affected questions not being marked.
It is a requirement of the course that students perform satisfactorily in the final examination.
Assignments (4)
Four individual assignments will test the student’s understanding of the course material taught up to the point each assignment is distributed. The student is expected to solve problems which test both the concepts taught as well as the technical capabilities of the students in doing numerical analysis. These assignments must be completed individually.
Tutorial (3)
Three individual tutorial problems will test the student’s numerical skill in solving practical engineering problems. These assignments must be completed individually.
Mid Term Test (1)
An in-class 1hr test assessing material delivered between weeks 1 and 6.
Final Examination (1)
Final examination assessing all material delivered throughout the course
Assessment Tasks
| Name | Weighting | Due |
|---|---|---|
| Assignments | 20% | Week 3, 5, 7, and 11 |
| Tutorial Problem Solving | 15% | Week 4, Week 8, Week 12 |
| Mid term Test | 15% | Week 7 |
| Final Examination | 50% | During Exam Period |
Assignments
Due: Week 3, 5, 7, and 11
Weighting: 20%
4 Assignments based on problem solving
On successful completion you will be able to:
- Understand how engineering problems can be solved using basic mathematical models and numerical methods.
- Ability to identify risk associated with floating point computations and perform error analysis.
- Ability to develop techniques for accurate and efficient solution of models based on linear and nonlinear equations, ordinary differential equations and partial differential equations.
- Demonstrate skill in Matlab as the tool to implement numerical analysis for practical engineering problems.
Tutorial Problem Solving
Due: Week 4, Week 8, Week 12
Weighting: 15%
Tutorial Problem Solving
On successful completion you will be able to:
- Understand how engineering problems can be solved using basic mathematical models and numerical methods.
- Ability to develop techniques for accurate and efficient solution of models based on linear and nonlinear equations, ordinary differential equations and partial differential equations.
- Demonstrate skill in Matlab as the tool to implement numerical analysis for practical engineering problems.
Mid term Test
Due: Week 7
Weighting: 15%
Mid term Examination
On successful completion you will be able to:
- Ability to develop techniques for accurate and efficient solution of models based on linear and nonlinear equations, ordinary differential equations and partial differential equations.
Final Examination
Due: During Exam Period
Weighting: 50%
3 Hour Final Exam, Closed book.
On successful completion you will be able to:
- Ability to develop techniques for accurate and efficient solution of models based on linear and nonlinear equations, ordinary differential equations and partial differential equations.
Delivery and Resources
There is no single core text for this course. However the following texts are recommended:
“Applied Numerical Methods for Engineers and Scientists” by Singiresu S. Rao
“Computational Fluid Dynamics: A Practical Approach” by J Tu, GH Yeoh and C Liu.
Unit Schedule
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Week |
Topic |
Lecturer |
Laboratory/Tutorial |
Assessments |
|
1 |
Introduction to numerical methods |
Dr. Lee |
No tutorial |
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2 |
Applied Matlab programming |
Dr. Lee |
Matlab programming |
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3 |
Nonlinear equation |
Dr. Lee |
Linear and nonlinear problems |
Assignment 1 due |
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4 |
System of linear equation, Elimination methods, LU factorization |
Dr. Lee |
Linear and nonlinear problems |
Tutorial problem 1 due |
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5 |
Interpolation and polynomial approximation, curve fitting |
Dr. Lee |
Problem sets on interpolation |
Assignment 2 due |
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6 |
Numerical differentiation |
Dr. Lee |
Vibration analysis |
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7 |
Numerical integration Trapezoidal rule, simpson’s rule |
Dr. Lee |
Vibration analysis |
Assignment 3 due |
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8 |
Euler method, Runge-Kutta method |
Dr. Lee |
Thermofluid problems |
Tutorial problem 2 due |
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9 |
Boundary value ordinary differential equations |
Dr. Lee |
Thermofluid problems |
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10 |
Partial differential equations |
Dr. Lee |
ODE and PDE problem sets |
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11 |
Method of solutions |
Dr. Lee |
CFD pre processing |
Assignment 4 due |
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12 |
Computational Fluid Dynamics |
Dr. Lee |
CFD analysis |
Tutorial problem 3 due |
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13 |
Revision |
Dr. Lee |
CFD post processing |
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Policies and Procedures
Macquarie University policies and procedures are accessible from Policy Central. Students should be aware of the following policies in particular with regard to Learning and Teaching:
Academic Honesty Policy http://mq.edu.au/policy/docs/academic_honesty/policy.html
Assessment Policy http://mq.edu.au/policy/docs/assessment/policy.html
Grading Policy http://mq.edu.au/policy/docs/grading/policy.html
Grade Appeal Policy http://mq.edu.au/policy/docs/gradeappeal/policy.html
Grievance Management Policy http://mq.edu.au/policy/docs/grievance_management/policy.html
Disruption to Studies Policy http://www.mq.edu.au/policy/docs/disruption_studies/policy.html The Disruption to Studies Policy is effective from March 3 2014 and replaces the Special Consideration Policy.
In addition, a number of other policies can be found in the Learning and Teaching Category of Policy Central.
Student Code of Conduct
Macquarie University students have a responsibility to be familiar with the Student Code of Conduct: https://students.mq.edu.au/support/student_conduct/
Results
Results shown in iLearn, or released directly by your Unit Convenor, are not confirmed as they are subject to final approval by the University. Once approved, final results will be sent to your student email address and will be made available in eStudent. For more information visit ask.mq.edu.au.
Student Support
Macquarie University provides a range of support services for students. For details, visit http://students.mq.edu.au/support/
Learning Skills
Learning Skills (mq.edu.au/learningskills) provides academic writing resources and study strategies to improve your marks and take control of your study.
Student Services and Support
Students with a disability are encouraged to contact the Disability Service who can provide appropriate help with any issues that arise during their studies.
Student Enquiries
For all student enquiries, visit Student Connect at ask.mq.edu.au
IT Help
For help with University computer systems and technology, visit http://informatics.mq.edu.au/help/.
When using the University's IT, you must adhere to the Acceptable Use Policy. The policy applies to all who connect to the MQ network including students.
Graduate Capabilities
Creative and Innovative
Our graduates will also be capable of creative thinking and of creating knowledge. They will be imaginative and open to experience and capable of innovation at work and in the community. We want them to be engaged in applying their critical, creative thinking.
This graduate capability is supported by:
Learning outcomes
- Ability to develop techniques for accurate and efficient solution of models based on linear and nonlinear equations, ordinary differential equations and partial differential equations.
- Demonstrate skill in Matlab as the tool to implement numerical analysis for practical engineering problems.
Assessment task
- Assignments
Discipline Specific Knowledge and Skills
Our graduates will take with them the intellectual development, depth and breadth of knowledge, scholarly understanding, and specific subject content in their chosen fields to make them competent and confident in their subject or profession. They will be able to demonstrate, where relevant, professional technical competence and meet professional standards. They will be able to articulate the structure of knowledge of their discipline, be able to adapt discipline-specific knowledge to novel situations, and be able to contribute from their discipline to inter-disciplinary solutions to problems.
This graduate capability is supported by:
Learning outcomes
- Understand how engineering problems can be solved using basic mathematical models and numerical methods.
- Demonstrate skill in Matlab as the tool to implement numerical analysis for practical engineering problems.
Assessment tasks
- Assignments
- Tutorial Problem Solving
- Mid term Test
- Final Examination
Critical, Analytical and Integrative Thinking
We want our graduates to be capable of reasoning, questioning and analysing, and to integrate and synthesise learning and knowledge from a range of sources and environments; to be able to critique constraints, assumptions and limitations; to be able to think independently and systemically in relation to scholarly activity, in the workplace, and in the world. We want them to have a level of scientific and information technology literacy.
This graduate capability is supported by:
Learning outcomes
- Ability to identify risk associated with floating point computations and perform error analysis.
- Ability to develop techniques for accurate and efficient solution of models based on linear and nonlinear equations, ordinary differential equations and partial differential equations.
- Demonstrate skill in Matlab as the tool to implement numerical analysis for practical engineering problems.
Assessment tasks
- Assignments
- Tutorial Problem Solving
- Mid term Test
- Final Examination
Problem Solving and Research Capability
Our graduates should be capable of researching; of analysing, and interpreting and assessing data and information in various forms; of drawing connections across fields of knowledge; and they should be able to relate their knowledge to complex situations at work or in the world, in order to diagnose and solve problems. We want them to have the confidence to take the initiative in doing so, within an awareness of their own limitations.
This graduate capability is supported by:
Learning outcomes
- Ability to identify risk associated with floating point computations and perform error analysis.
- Ability to develop techniques for accurate and efficient solution of models based on linear and nonlinear equations, ordinary differential equations and partial differential equations.
- Demonstrate skill in Matlab as the tool to implement numerical analysis for practical engineering problems.
Assessment tasks
- Assignments
- Tutorial Problem Solving