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APP MTH 3021 - Modelling with Ordinary Differential Equations III

North Terrace Campus - Semester 1 - 2015

Differential equation models describe a wide range of complex problems in biology, engineering, physical sciences, economics and finance. This course focuses on ordinary differential equations (ODEs) and develops students' skills in the formulation, solution, understanding and interpretation of coupled ODE models. A range of important biological problems, from areas such as resource management, population dynamics, and public health, drives the study of analytical and numerical techniques for systems of nonlinear ODEs. A key aim of the course is building practical skills that can be applied in a wide range of scientific, business and research settings. Topics covered are: analytical methods for systems of ODEs, including vector fields, fixed points, phase-plane analysis, linearisation of nonlinear systems, bifurcations; general theory on existence and approximation of ODE solutions; biological modelling; explicit and implicit numerical methods for ODE initial value problems, computational error, consistency, convergence, stability of a numerical method, ill-conditioned and stiff problems.

  • General Course Information
    Course Details
    Course Code APP MTH 3021
    Course Modelling with Ordinary Differential Equations III
    Coordinating Unit Applied Mathematics
    Term Semester 1
    Level Undergraduate
    Location/s North Terrace Campus
    Units 3
    Contact Up to 3 contact hours per week.
    Available for Study Abroad and Exchange Y
    Prerequisites (MATHS 2101 and MATHS 2102) or MATHS 2201 and MATHS 2202)
    Incompatible APP MTH 3013, APP MTH 3004
    Assumed Knowledge MATHS 2104
    Assessment Ongoing assessment: 30%, Exam 70%
    Course Staff

    Course Coordinator: Professor Yvonne Stokes

    Course Timetable

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

  • Learning Outcomes
    Course Learning Outcomes
    Students who successfully complete the course should:
    1. understand how to model time-varying systems using ordinary differential equations
    2. be able to identify and analyse stability of equilibrium solutions
    3. be able to numerically solve ordinary differential equations
    4. be able to analyse how the structure of solutions can change depending on a parameter
    5. understand the analytical solution theory for linear systems of ordinary differential equations
    6. appreciate the necessity of numerical and qualitative methods for analysing solutions for nonlinear systems
    7. have a detailed understanding of several ordinary differential equations models arising in physics, biology and chemistry, namely oscillator models, Lotka-Volterra competition and predator-prey models, Michaelis-Menton kinetics and SIR epidemic 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)
    Knowledge and understanding of the content and techniques of a chosen discipline at advanced levels that are internationally recognised. all
    The ability to locate, analyse, evaluate and synthesise information from a wide variety of sources in a planned and timely manner. 1
    An ability to apply effective, creative and innovative solutions, both independently and cooperatively, to current and future problems. 2,3,4,5,6,7
    A proficiency in the appropriate use of contemporary technologies. 3,7
    A commitment to continuous learning and the capacity to maintain intellectual curiosity throughout life. all
  • Learning Resources
    Required Resources
    None.
    Recommended Resources
    1. Butcher, John. Numerical Methods for Ordinary Differential Equations (Wiley, 2008)
    2. Chicone, Carmen. Ordinary Differential Equations with Applications (Springer, 2006)
    3. Dahlquist, Germund and Bjorck, Ake. Numerical Methods (Dover, 2003)
    4. de Vries, Gerda et al. A Course in Mathematical Biology (SIAM, 2006)
    5. Edelstein-Keshet, Leah. Mathematical Models in Biology (SIAM, 2005)
    6. Strogatz, Steven. Nonlinear Dynamics and Chaos (Perseus, 2001)
    Online Learning
    This course uses MyUni exclusively for providing electronic resources, such as lecture notes, assignment papers, sample solutions, discussion boards, etc. It is recommended that the students make appropriate use of these resources. Link to MyUni login page: https://myuni.adelaide.edu.au/webapps/login/
  • Learning & Teaching Activities
    Learning & Teaching Modes
    This course relies on lectures as the primary delivery mechanism for the material. Tutorials supplement the lectures by prov