UnitLevel 3Undergraduate

MTH3340 Numerical methods for partial differential equations

Faculty of Science

MTH3340 Numerical methods for partial differential equations is a level 3, 6-credit-point, undergraduate unit from the Faculty of Science, offered in 2024 in Semester 2 at Clayton. It has no prerequisites.

Credit points
6
Offered in 2024
Semester 2
Clayton
Assessment
Exam 60%
and 1 other task

This is the 2024 handbook entry. See the 2027 entry.

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Requisites

Before MTH3340

No prerequisites or corequisites besides the enrolment rules below.

After MTH3340

No unit lists MTH3340 as a prerequisite in the 2024 handbook.

Enrolment rules

COREQUISITE: MTH2051 or MTH3051, unless MTH2040 or ENG2005 have been passed.

PREREQUISITES: You must have passed one unit from MTH2032 or MTH2040 or ENG2005 or be enrolled in the Master of Mathematics.

Overview

Partial differential equations are ubiquitous in many domains of sciences and industry, as they model phenomena with spatial and temporal variations. Most of these models are too complex to be exactly solved, and numerical methods are the only way to gather quantitative behaviour on the solutions. This unit covers the design, analysis and implementation of numerical methods for partial differential equations. Topics covered can include finite difference methods, finite element methods, finite volume methods, error analysis, elliptic equations, parabolic equations, implementation in dynamic languages (such as Python or Julia). The focus will be on the design of the methods, their mathematical analysis, and their implementation and numerical testing.

Offerings in 2024

Teaching periodCampusMode
Second semesterClaytonOn campus

Assessment

  • Continuous assessmentOther
    40%
  • Final assessment - Exam (3 hours and 10 minutes)ExamThreshold hurdle
    60%

Learning outcomes

When you finish this unit, you should be able to:

  1. 1

    Demonstrate understanding of the need for numerical methods to gather quantitative information on the solutions to partial differential equations.

  2. 2

    Design and analyse the convergence and stability of numerical methods for a range of partial differential equations.

  3. 3

    Select appropriate discretisation techniques based on their particular features, and the features of the considered model.

  4. 4

    Implement specific numerical methods in a high-level language (such as Python or Julia), and interpret numerical outputs.

  5. 5

    Demonstrate advanced skills in the written and oral presentation of theoretical and practical numerical problems involving partial differential equations.

Workload and teaching

  • Seminars36 hours
  • Applied sessions22 hours
  • Teaching approachActive learning
  • Three 1-hour seminars;
  • One 2-hour applied class (in weeks 2-12) and
  • 7 hours of independent study per week

We will use a blend of lectures, applied classes and labs. Lectures will enable us, as usual in mathematics, to deliver the main content of the unit – albeit in an interactive way, questioning student’s understanding and welcoming questions from students. Applied classes revolve around students actively solving exercises, putting in practice the content covered in the lectures; this is an essential way of assimilating that content. Labs will be focused around practical implementation of the methods, the issues around those and the interpretation of the numerical outputs.

Where it fits

MTH3340 is part of 8 areas of study in the 2024 handbook.

Contacts

Chief Examiners
Professor Santiago Badia
Unit Coordinators
Professor Santiago Badia

Common questions

What are the prerequisites for MTH3340?

MTH3340 has no prerequisites, but enrolment rules apply.

When is MTH3340 offered?

In 2024, MTH3340 runs in Semester 2 at Clayton.

Does MTH3340 have an exam?

Yes. The exam is worth 60% of the final mark, alongside 1 other task.

Which majors and minors include MTH3340?

MTH3340 is part of Applied mathematics, Mathematical statistics, Mathematics and Pure mathematics.

More details

Credit points
6
Level
3
Study level
Undergraduate
Faculty
Faculty of Science
Organisational unit
School of Mathematics
Type
Coursework
EFTSL
0.125
Student contribution
SCA Band 1
Study abroad
Available
Handbook years
202220232024202520262027