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Applied Mathematical Modelling (MAST30030)
Undergraduate level 3Points: 12.5Dual-Delivery (Parkville)
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About this subject
- Overview
- Eligibility and requirements
- Assessment
- Dates and times
- Further information
- Timetable(opens in new window)
Contact information
Semester 1
Dr Douglas Brumley
Overview
Availability | Semester 1 - Dual-Delivery |
---|---|
Fees | Look up fees |
This subject demonstrates how the mathematical modelling process naturally gives rise to certain classes of ordinary and partial differential equations in many contexts, including the infectious diseases, the flow of traffic and the dynamics of particles and of fluids. It advances the student’s knowledge of the modelling process, as well addressing important mathematical ideas in deterministic modelling and the challenges raised by system nonlinearity.
- Infectious disease models and other contexts leading to systems of autonomous first-order differential equations; initial value problem, phase space, critical points, local linearization and stability; qualitative behaviour of plane autonomous systems, structural stability; formulation, interpretation and critique of models.
- Conservation laws and flux functions leading to first-order quasilinear-linear partial differential equations; characteristics, fans, shocks and applications including modelling traffic flow.
- Introduction to continuum mechanics: basic principles; tensor algebra and tensor calculus; the ideal fluid model and potential flow; the Newtonian fluid, Navier-Stokes equations and simple solutions.
Intended learning outcomes
On completion of this subject, students should be able to:
- Evaluate the nature of deterministic mathematical modelling, including model formulation, selection of appropriate mathematical formalism, solution strategies and interpretation of results;
- Appraise contexts in which systems of autonomous ordinary differential equations or quasilinear first-order partial differential equations provide relevant models, and describe the general features of such models and what may be learned from them;
- Investigate and classify critical points in two-dimensional autonomous ODE problems, and be able to infer qualitative behaviour in the phase plane.
Generic skills
In addition to learning specific skills that will assist students in their future careers in science, they will have the opportunity to develop generic skills that will assist them in any future career path. These include:
- mathematical modelling skills: the ability to formulate a mathematical model, select an appropriate solution strategy and interpret solutions;
- analytical skills: the ability to construct and express logical arguments and to work in abstract or general terms to increase the clarity and efficiency of analysis;
- time-management skills: the ability to meet regular deadlines while balancing competing commitments.
Last updated: 31 January 2024
Eligibility and requirements
Prerequisites
Code | Name | Teaching period | Credit Points |
---|---|---|---|
MAST20030 | Differential Equations | Semester 2 (Dual-Delivery - Parkville) |
12.5 |
One of
Code | Name | Teaching period | Credit Points |
---|---|---|---|
MAST20009 | Vector Calculus |
Semester 2 (Dual-Delivery - Parkville)
Semester 1 (Dual-Delivery - Parkville)
|
12.5 |
MAST20032 | Vector Calculus: Advanced | Semester 1 (Dual-Delivery - Parkville) |
12.5 |
Corequisites
None
Non-allowed subjects
None
Inherent requirements (core participation requirements)
The University of Melbourne is committed to providing students with reasonable adjustments to assessment and participation under the Disability Standards for Education (2005), and the Assessment and Results Policy (MPF1326). Students are expected to meet the core participation requirements for their course. These can be viewed under Entry and Participation Requirements for the course outlines in the Handbook.
Further details on how to seek academic adjustments can be found on the Student Equity and Disability Support website: http://services.unimelb.edu.au/student-equity/home
Last updated: 31 January 2024
Assessment
Description | Timing | Percentage |
---|---|---|
Three written assignments, due at regular intervals during semester
| Throughout the semester | 30% |
Written examination
| During the examination period | 70% |
Last updated: 31 January 2024
Dates & times
- Semester 1
Coordinator Douglas Brumley Mode of delivery Dual-Delivery (Parkville) Contact hours 36 one-hour lectures (three per week); 12 one-hour practice classes (one per week) Total time commitment 170 hours Teaching period 28 February 2022 to 29 May 2022 Last self-enrol date 11 March 2022 Census date 31 March 2022 Last date to withdraw without fail 6 May 2022 Assessment period ends 24 June 2022 Semester 1 contact information
Dr Douglas Brumley
Time commitment details
170 hours
Last updated: 31 January 2024
Further information
- Texts
Prescribed texts
There are no specifically prescribed or recommended texts for this subject.
- Related Handbook entries
This subject contributes to the following:
Type Name Informal specialisation Applied Mathematics Informal specialisation Science Discipline subjects - new generation B-SCI Informal specialisation Applied Mathematics Informal specialisation Applied Mathematics specialisation Major Applied Mathematics - Available through the Community Access Program
About the Community Access Program (CAP)
This subject is available through the Community Access Program (also called Single Subject Studies) which allows you to enrol in single subjects offered by the University of Melbourne, without the commitment required to complete a whole degree.
Entry requirements including prerequisites may apply. Please refer to the CAP applications page for further information.
- Available to Study Abroad and/or Study Exchange Students
This subject is available to students studying at the University from eligible overseas institutions on exchange and study abroad. Students are required to satisfy any listed requirements, such as pre- and co-requisites, for enrolment in the subject.
Last updated: 31 January 2024