MATH3501 Scientific and Industrial Modelling
Later Year Course
| Offered By | Department of Maths |
|---|---|
| Academic Career | Undergraduate |
| Course Subject | Mathematics |
| Offered in | First Semester, 2010 and Second Semester, 2011 |
| 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.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. Computations will be done using modern high level scientific computing environments such as SCILAB or PYTHON. Topics to be covered 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. Honours Pathway Option (HPO):Students must have 12 units of Group B level Mathematics including MATH2405 or a mark of 60 or more in MATH2305 to choose this option. Students who choose this option will be expected to complete extra work of a more theoretical nature. At least one of the assignments worth 10% will be replaced by an alternative assignment, and the exam will contain alternative questions requiring deeper conceptual understanding |
| Learning Outcomes |
On satisfying the requirements of this course, students will have the knowledge and skills to: 1. Describe many of the basic processes and behaviours of different systems and different ways of representing them2. 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. Describe sensitivity and uncertainty analysis techniques |
| Indicative Assessment |
Assessment will be based on:
|
| Areas of Interest | Mathematics |
| Requisite Statement |
Requires MATH2305; or MATH2405; or 12 units of Group B Mathematics courses with a mark of 60 or better |
| Science Group | C |
| Academic Contact | Barry Croke |
The information published on the Study at ANU 2010 website applies to the 2010 academic year only. All information provided on this website replaces the information contained in the Study at ANU 2009 website.
