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APP MTH 7049 - Applied Mathematics Topic D

North Terrace Campus - Semester 2 - 2025

This course is available for students taking a Masters degree in Mathematical Sciences. The course will cover an advanced topic in applied mathematics. For details of the topic offered this year please refer to the Course Outline.

  • General Course Information
    Course Details
    Course Code APP MTH 7049
    Course Applied Mathematics Topic D
    Coordinating Unit Mathematical Sciences
    Term Semester 2
    Level Postgraduate Coursework
    Location/s North Terrace Campus
    Units 3
    Available for Study Abroad and Exchange Y
    Assessment Ongoing assessment, exam
    Course Staff

    Course Coordinator: Dr Edward Green

    Course Timetable

    The full timetable of all activities for this course can be accessed from .

  • Learning Outcomes
    Course Learning Outcomes
    This year, the topic of this course is Mathematical modelling using perturbations methods.

    Synopsis

    Many different physical problems can be modelled using differential equations with applicable initial and boundary conditions, which feature a small parameter. This course concerns the development and solution of simplified models for such problems using perturbation methods which exploit this small parameter. The solution is represented as an asymptotic expansion in the small parameter, of which a few terms are determined, somewhat like approximating a function by a few terms of its Taylor series. Perturbation methods will be considered in the context of some different applications such as laser drilling and fibre drawing. It will be seen that the solutions obtained give excellent understanding, not readily obtained by brute force numerical simulation.

    Use will be made of analytical and numerical solution techniques. Ability to use Matlab ODE solvers and graphical tools will be beneficial.

    The course will be run mainly on active learning principles; in-person attendance is expected and there will be no video recordings of lectures.

    Assumed knowledge for the course is a basic understanding of ODEs and PDEs, e.g. as covered in Differential Equations II, Modelling with ODEs III, PDEs & Waves III, or similar.


    Learning Outcomes

    On successful completion of this course, students will be able to:
    1. Identify the type of problems for which perturbation methods are applicable;
    2. Derive simplified models from more complex ones using appropriate asymptotic expansions;
    3. Obtain analytical/numerical solutions, as appropriate, to the models derived;
    4. Understand and explain the physical insight given by these models;
    5. Understand the limitations of these models.
    University Graduate Attributes

    This course will provide students with an opportunity to develop the Graduate Attribute(s) specified below:

    University Graduate Attribute Course Learning Outcome(s)

    Attribute 1: Deep discipline knowledge and intellectual breadth

    Graduates have comprehensive knowledge and understanding of their subject area, the ability to engage with different traditions of thought, and the ability to apply their knowledge in practice including in multi-disciplinary or multi-professional contexts.

    all

    Attribute 2: Creative and critical thinking, and problem solving

    Graduates are effective problems-solvers, able to apply critical, creative and evidence-based thinking to conceive innovative responses to future challenges.

    all

    Attribute 3: Teamwork and communication skills

    Graduates convey ideas and information effectively to a range of audiences for a variety of purposes and contribute in a positive and collaborative manner to achieving common goals.

    1,5

    Attribute 8: Self-awareness and emotional intelligence

    Graduates are self-aware and reflective; they are flexible and resilient and have the capacity to accept and give constructive feedback; they act with integrity and take responsibility for their actions.

    all
  • Learning Resources
    Required Resources
    Textbook: Thomas Witelsk and Mark Bowen, Methods of Mathematical Modelling, Continuous Systems and Differential Equations. Springer International Publishing AG Switzerland, 2015. Available online via the Barr Smith Library.

    Other course materials:
     provided via the course's MyUni site.
    Online Learning
    The course will have an active MyUni website. However in-person attendance at workshops is expected and these will not be recorded.
  • Learning & Teaching Activities
    Learning & Teaching Modes
    The learning in this course will be, predominantly, by active, discovery-based learning. Oral presentations and written assessments will also be employed.
    Workload

    The information below is provided as a guide to assist students in engaging appropriately with the course requirements.

    Activity Quantity Workload Hours
    Workshops (includes presentations, and prior work) 22 88
    Assignments 3 30
    Project 1 32
    Total 150
    Learning Activities Summary
    There will be two workshop sessions (i.e. 2 hrs) per week, run in student-centred mode, coupled with prior readings, working of problems and preparation of presentations.

    Formal assignments will also be submitted on which feedback will be given. A significant project will be completed in the seonc half of the semester.
  • Assessment

    The University's policy on Assessment for Coursework Programs is based on the following four principles:

    1. Assessment must encourage and reinforce learning.
    2. Assessment must enable robust and fair judgements about student performance.
    3. Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
    4. Assessment must maintain academic standards.

    Assessment Summary
    A guide is given below; this will be finalised before commencement of the course.

    Assessment Task Type Weighting Learning Outcomes
    Assignments (3) Formative and Summative    30% All
    Presentations and active participation Formative and Summative    20% All
    Project Formative and Summative 50% All
    Assessment Detail

    No information currently available.

    Submission

    No information currently available.

    Course Grading

    Grades for your performance in this course will be awarded in accordance with the following scheme:

    M10 (Coursework Mark Scheme)
    Grade Mark Description
    FNS   Fail No Submission
    F 1-49 Fail
    P 50-64 Pass
    C 65-74 Credit
    D 75-84 Distinction
    HD 85-100 High Distinction
    CN   Continuing
    NFE   No Formal Examination
    RP   Result Pending

    Further details of the grades/results can be obtained from Examinations.

    Grade Descriptors are available which provide a general guide to the standard of work that is expected at each grade level. More information at Assessment for Coursework Programs.

    Final results for this course will be made available through .

  • Student Feedback

    The University places a high priority on approaches to learning and teaching that enhance the student experience. Feedback is sought from students in a variety of ways including on-going engagement with staff, the use of online discussion boards and the use of Student Experience of Learning and Teaching (SELT) surveys as well as GOS surveys and Program reviews.

    SELTs are an important source of information to inform individual teaching practice, decisions about teaching duties, and course and program curriculum design. They enable the University to assess how effectively its learning environments and teaching practices facilitate student engagement and learning outcomes. Under the current SELT Policy (http://www.adelaide.edu.au/policies/101/) course SELTs are mandated and must be conducted at the conclusion of each term/semester/trimester for every course offering. Feedback on issues raised through course SELT surveys is made available to enrolled students through various resources (e.g. MyUni). In addition aggregated course SELT data is available.

  • Student Support
  • Policies & Guidelines
  • Fraud Awareness

    Students are reminded that in order to maintain the academic integrity of all programs and courses, the university has a zero-tolerance approach to students offering money or significant value goods or services to any staff member who is involved in their teaching or assessment. Students offering lecturers or tutors or professional staff anything more than a small token of appreciation is totally unacceptable, in any circumstances. Staff members are obliged to report all such incidents to their supervisor/manager, who will refer them for action under the university's student鈥檚 disciplinary procedures.

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