| Unit name | Mathematical and Data Modelling 3 |
|---|---|
| Unit code | EMAT30005 |
| Credit points | 30 |
| Level of study | H/6 |
| Teaching block(s) |
Teaching Block 4 (weeks 1-24) |
| Unit director | Professor. Champneys |
| Open unit status | Not open |
| Pre-requisites |
EMAT22220 Mathematical and Data Modelling 2 EMAT20200 Engineering Mathematics 2 EMAT20920 Numerical Methods with Matlab |
| Co-requisites |
None |
| School/department | School of Engineering Mathematics and Technology |
| Faculty | Faculty of Engineering |
This unit will build on the Mathematical and Data Modelling 1 and 2 units in the first two years of the engineering mathematics degree programmes and complete our students' thorough grounding in team-based mathematical modelling and problem solving applied to real world problems.
The unit will be divided into 3 project phases each taking 7 term-time weeks. At the start of each phase real world projects will be presented to the students mostly drawn from external stakeholders. Students will then be allocated to groups of 4-6 to work on each project.
During each project students will be trained in the problem solving approach, and work on and be guided towards and through particular mathematical/computational solution methodologies by the supervising academics. At the end of the phase each group of students will present their results and submit a written technical report.
Aims:
To give students a thorough grounding in mathematical modelling and problem solving applied to real world engineering / applied science problems. The course will cover both model-centric and data-centric paradigms.
At the end of the course students will:
1) Have mathematically modelled a range of real world problems drawn from engineering, economics, and the physical, chemical and biological sciences.
2) Have experience of finding, reading and interpreting technical information.
3) Understand the mathematical modelling cycle, of model, analysis, prediction/interpretation, and iterative refinement.
4) Understand the differences between and relative merits of model-centric and data-centric paradigms.
5) Be able to identify and draw upon a range of appropriate mathematical and computational methodologies when presented with new and unfamiliar problems.
6) Have practised teamwork and time management.
7) Have learnt how to present and interpret mathematical results to/for a non-mathematical engineering audience.
8) Have experience of writing substantial technical reports
Computer laboratory sessions and group meetings with an academic.
This unit will be assessed by the three projects and an individual writing analysis. Each of the three projects will be mainly marked on the final technical report but will also have an additional smaller group assessment:
Group report 1: 25% -- (ILOs 1-8)
Group report 2: 25%
Group report 3: 25%
Group interim report 1: 5% -- (ILOs 7-8)
Group presentation 2: 5% -- (ILO 7)
Group poster 3: 5% -- (ILO 7)
Individual writing analysis: 10% -- (ILO 7-8)
Individual marks for the group reports will be moderated by peer feedback from the students in each group.
There is no standard set of textbooks for this course. Each problem presented will typically be accompanied by a couple of references. However, students will be encouraged to use the library and internet to discover any missing technical information not included in the problem presentation.
