MATH6103 Scientific and Industrial Modelling

Offered By	Department of Mathematics
Academic Career	Graduate Coursework
Course Subject	Mathematics
Offered in	First Semester, 2009 and First Semester, 2010
Unit Value	6 units
Course Description	The use of mathematical models has grown rapidly in recent years, owing to the advent of cheap and powerful computers, expanding from applications in the physical and earth sciences to the biological and environmental sciences, and now into industry and commerce. In this course we study: The process of starting with an initial succinct non-mathematical description of a problem Formulate associated mathematical models. Introduce new mathematical techniques and then determine and interpret solutions that are useful in a real life context. General computational and mathematical techniques and strategies will be introduced by examining specific scientific and industrial problems. The topics to be covered in this course include: Model type selection and formulation Data analysis techniques (time/space and frequency domain) State Space and Transfer Function Models Model Structure Identification Testing and Sensitivity Analysis Computations will be done using modern high level scientific computing environments such as SCILAB or PYTHON. Note: Graduate students attend joint classes with undergraduates but are assessed separately.
Learning Outcomes	On satisfying the requirements of this course, students will have the knowledge and skills to: 1. Design a model based on the basic processes and behaviour of a system and different ways of representing them 2. Evaluate the issues in building and evaluating models, taking into account their purpose and prior knowledge 3. Explain and use some important modelling tools (transfer function, state space, frequency-domain and DE-based models as well as data analysis techniques) 4. Discuss the role of modelling in both industry and science 5. Explain sensitivity and uncertainty analysis techniques
Indicative Assessment	Assessment will be based on: Exam (40%; LO 1, 2, 3, 4, 5) Project designing and evaluating a model for a selected system (30%; LO 1, 2) Three assignments demonstrating ability to apply techniques (10% each; LO 2, 3, 5)
Course Classification(s)	AdvancedAdvanced courses are designed for students having reached 'first degree' level of assumed knowledge, which provide a deep understanding of contemporary issues; or 'second degree' and higher levels of knowledge; or for transition to research training programs. and SpecialistSpecialist courses are designed for students having reached 'first degree' level of assumed knowledge, which provide for the acquisition of specialist skills; or 'second degree' and higher level of knowledge; or for transition to research training programs; or knowledge associated with professional accreditation.
Areas of Interest	Mathematics
Eligibility	Bachelor degree; with second year Maths.
Requisite Statement	Requirtes undergraduate degree with suitable second year Maths (or equivalent)
Consent Required	Please contact MATHSadmin@maths.anu.edu.au for consent to enrol in this course.
Programs	Master of Mathematical Sciences and Master of Environment
Academic Contact	Dr Barry Croke

The information published on the Study at ANU 2009 website applies to the 2009 academic year only. All information provided on this website replaces the information contained in the Study at ANU 2008 website.