Available in 2024
Course code

MATH3700

Units

10 units

Level

3000 level

Course handbook

Description

Partial differential equations arise from the mathematical modelling of a wide range of problems in biology, engineering, physical sciences, economics and finance. Therefore, they form an essential part of the mathematical background required for engineering and physical sciences. This course introduces students to the modern theory and methods of partial differential equations. It provides the students with the skills to formulate partial differential equations for modelling real-world problems, the knowledge to solve them using fundamental analytical and numerical methods, and the ability to interpret the results in the relation to the modelling context.


Availability2024 Course Timetables

Callaghan

  • Semester 2 - 2024

Learning outcomes

On successful completion of the course students will be able to:

1. Build mathematical models of relevant real-world problems based on partial differential equations in studying differential equations.

2. Classify second order partial differential equations, apply analytical methods to solve them, and physically interpret the solutions.

3. Apply numerical methods to solve practical partial differential equations and implement them in computers.

4. Interpret and communicate solutions in relation to the underlying modelling problem.

5. Analyse the consistency, stability and convergence properties of numerical methods.


Content

  • Modelling with partial differential equations.
  • Classical solution techniques: method of characteristics, separation of variables and Fourier series, transform methods.
  • Numerical methods for partial differential equations: consistency, stability and convergence.

 


Assumed knowledge

MATH2310


Assessment items

Quiz: Quiz

Written Assignment: Assignments

Formal Examination: End of Semester Exam


Contact hours

Semester 2 - 2024 - Callaghan

Lecture-1
  • Face to Face On Campus 3 hour(s) per week(s) for 13 week(s) starting in week 1
  • Tutorial and computer lab work will be integrated with lecture material as required.

Course outline