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ENGI1151: COMPUTATIONAL TOOLS FOR ENGINEERS AND SCIENTISTS

Please ensure you check the module availability box for each module outline, as not all modules will run in each academic year. Each module description relates to the year indicated in the module availability box, and this may change from year to year, due to, for example: changing staff expertise, disciplinary developments, the requirements of external bodies and partners, and student feedback. Current modules are subject to change in light of the ongoing disruption caused by Covid-19.

Type Open
Level 1
Credits 20
Availability Available in 2024/2025
Module Cap
Location Durham
Department Engineering

Prerequisites

  • A-level Mathematics at Grade A

Corequisites

  • None

Excluded Combinations 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 students 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

ActivityNumberFrequencyDurationTotalMonitored
Lectures191 per week1 hour19 
Practical Classes191 per week1 hour19 
Preparation, reading and self study160 
Total200 

Summative Assessment

Component: CourseworkComponent Weighting: 100%
ElementLength / DurationElement WeightingResit Opportunity
Assignment 100none

Formative Assessment

Examples and exercises are given throughout the course, to be undertaken and then discussed in practical sessions. Formative Laboratory Report.

More information

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