Overview

Computational methods are of paramount importance for solving real-world problems in applied mathematics.This unit teaches widely used numerical methods for problems from science, engineering, biology and finance that are modeled by partial differential equations (PDEs). The unit covers numerical methods for PDEs of elliptic, parabolic and hyperbolic type, as well … For more content click the Read More button below.

Offerings

S1-01-CLAYTON-ON-CAMPUS
S1-FF-CLAYTON-FLEXIBLE

Rules

Enrolment Rule

Contacts

Chief Examiner(s)

Dr Tiangang Cui

Unit Coordinator(s)

Dr Tiangang Cui

Learning outcomes

On successful completion of this unit, you should be able to:
1.

Explain the mathematical theory behind a selection of important numerical methods for PDEs, including the derivation of the methods and the analysis of their properties.

2.

Explain and apply notions of accuracy, stability and computational cost when solving PDE problems numerically.

3.

Demonstrate proficiency in numerical methods for PDEs and linear system solving, and apply them to problems in science, engineering, biology and finance.

4.

Implement advanced numerical PDE methods, and demonstrate the correctness and efficiency of the implementations in systematic computational tests.

5.

Apply critical thinking and demonstrate written and oral communication skills in the field of computational mathematics.

Assessment summary

Examination (3 hours and 10 minutes): 60% (Hurdle)

Continuous assessment: 40%

Hurdle requirement: If you would otherwise have passed the unit but who do not achieve at least 45% of the marks available for the end-of-semester examination will receive a Hurdle Fail (NH) grade and a mark of 45 on your transcript.

Workload requirements

Workload

Other unit costs

Costs are indicative and subject to change.
Miscellaneous items required (Printing, Stationery)- $100.

Availability in areas of study

Master of Mathematics