Undergraduate Programme and Module Handbook 2024-2025
Module ENGI1151: COMPUTATIONAL TOOLS FOR ENGINEERS AND SCIENTISTS
Department: Engineering
ENGI1151: COMPUTATIONAL TOOLS FOR ENGINEERS AND SCIENTISTS
| Type | Open | Level | 1 | Credits | 20 | Availability | Available in 2024/2025 | Module Cap | Location | Durham |
|---|
Prerequisites
- A-level Mathematics at Grade A
Corequisites
- None
Excluded Combination of Modules
- None
Aims
- To equip students with fundamental techniques in the use of computational tools in Engineering.
- To give an awareness of the importance of computational tools in the modern world and the impact it has on technological advances and in research practise both within and outside Engineering.
- To introduce students to the application of computational tools in a range of settings across Engineering.
Content
- Introduction to a high-level programming language for Engineering application. This is a language primarily intended for numerical computations. Typically MATLAB would be used but other languages may be selected by the course leader.
- Using library functions or toolboxes, how to build on the work of others.
- Data acquisition. This will typically be carried out using a system-design platform and development environment with a visual programming language.
- Data manipulation and analysis.
- Using computational tools for Engineering analysis. This will typically be an optimisation problem.
Learning Outcomes
Subject-specific Knowledge:
- An understanding of how a Engineering analysis is carried out using a variety of tools
- An appreciation of the role of Engineering and computational tools in the modern world
- An understanding of several approaches to analysing Engineering data
- An appreciation of the practical limitations of computational tools in Engineering
Subject-specific Skills:
- On completion of the module, students will be able to write software programs to analyse Engineering data
- On completion of the module, students will be able to use off-the-shelf programs to analyse Engineering data
- On completion of the module, students will be able to select the appropriate computational tool for the problem at hand and be able to discuss the merits of their chosen approach
- On completion of the module, students will be able apply off-the-shelf or bespoke programs to carry out Engineering analysis
Key Skills:
- Structured presentation of information in written form
Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module
- Lectures enable the students to learn new material and provide structure and guidance to the student’s own activity.
- Practical classes enable the students to put into practice learning from lectures and strengthen their understanding through application.
- Students are assessed using coursework as this allows suitably complex problems to be presented to them.
Teaching Methods and Learning Hours
| Activity | Number | Frequency | Duration | Total/Hours | |
|---|---|---|---|---|---|
| Lectures | 19 | 1 per week | 1 hour | 19 | |
| Practical Classes | 19 | 1 per week | 1 hour | 19 | |
| Preparation, reading and self study | 160 | ||||
| Total | 200 |
Summative Assessment
| Component: Coursework | Component Weighting: 100% | ||
|---|---|---|---|
| Element | Length / duration | Element Weighting | Resit Opportunity |
| Assignment | 100% | none | |
Formative Assessment:
Examples and exercises are given throughout the course, to be undertaken and then discussed in practical sessions. Formative Laboratory Report.
■ Attendance at all activities marked with this symbol will be monitored. Students who fail to attend these activities, or to complete the summative or formative assessment specified above, will be subject to the procedures defined in the University's General Regulation V, and may be required to leave the University