2023/24 Undergraduate Module Catalogue

MECH1010 Computers in Engineering Analysis

20 creditsClass Size: 350

Module manager: Professor Peter Culmer
Email: P.R.Culmer@leeds.ac.uk

Taught: Semesters 1 & 2 (Sep to Jun) View Timetable

Year running 2023/24

Module replaces

MECH 1220 Computers in Engineering Analysis

This module is not approved as a discovery module

Objectives

On completion of this module, students should be able to:
1. Appreciate the importance of computers and computational instruments to the development of engineering science in analytical and communication roles.
2. Understand the concepts of simple programming including logical structures, decision making, loops, subroutines and be able to develop simple programmes to solve engineering science problems.
3. Acquire, analyse and present a range of experimental data using graphical techniques.
4. Process data from a range of sources and display appropriate output.
5. Understand the practicalities of data acquisition.
6. Apply quantitative methods and computer software to solve engineering problems.
7. Ability to work with technical uncertainty.

Learning outcomes
At the end of this module, students will have learnt to:
1. Develop basic electronic circuits to interface sensors to computerised measurement hardware.
2. Understand existing programmes written using industry standard packages. Embedded microprocessors e.g. Arduino, Matlab and Mathworks.
3. Write their own computer programmes for the acquisition, analysis and visualisation of engineering processes.
4. Design and implement computer algorithms for the analysis of data.
5. Understand best practice in development, organisation and documentation of computer programmes.

Upon successful completion of this module the following UK-SPEC learning outcome descriptors are satisfied:

Knowledge and understanding of mathematical and statistical methods necessary to underpin their education in their engineering discipline and to enable them to apply a range of mathematical and statistical methods, tools and notations proficiently and critically in the analysis and solution of engineering problems (SM2m)
Ability to apply quantitative and computational methods, using alternative approaches and understanding their limitations, in order to solve engineering problems and implement appropriate action (EA3m)
Understanding of engineering principles and the ability to apply them to undertake critical analysis of key engineering processes (EA1m)
Understanding of contexts in which engineering knowledge can be applied (eg operations and management, application and development of technology, etc) (P1)
Knowledge of characteristics of particular equipment, processes or products, with extensive knowledge and understanding of a wide range of engineering materials and components (P2m)
Ability to work with technical uncertainty (P8)
Apply their skills in problem solving, communication, information retrieval, working with others and the effective use of general IT facilities (G1).

Skills outcomes
Matlab

Syllabus

Matlab
Students should be able to use Matlab to:
1. Understand generic concepts of programming including: input and output / mathematical syntax / conditional statements / for and while loops / subroutines.
2. Use Matlab to display 2D and 3D plots.
3. Manipulate matrices/ vectors.
4. Develop simple engineering programs.

Microprocessor Systems
The students will learn how to use microprocessor systems to:
Interface their computer to measure/control real-world signals
Troubleshoot and Debug Programs
Develop their own programs
Understand Data and File I/O
Develop Modular Systems
Measure and control real-world hardware

Teaching methods

Delivery type	Number	Length hours	Student hours
Lecture	22	1.00	22.00
Practical	22	2.00	44.00
Private study hours			134.00
Total Contact hours			66.00
Total hours (100hr per 10 credits)			200.00

Private study

- Planning assignments 20 hours
- Solving Assignments 60 hours
- Reading material for lecture preparation 20 hours
- Undertaking formative work 34 hours

Opportunities for Formative Feedback

Weekly quiz (Minerva) after each topic.
Weekly formative script-check feedback on self-study exercises.

Methods of assessment

Coursework

Assessment type	Notes	% of formal assessment
In-course Assessment	Matlab Class Test Formative	0.00
In-course Assessment	Matlab Individual Assessment	50.00
In-course Assessment	Microprocessor Systems Assessment	50.00
Total percentage (Assessment Coursework)		100.00

Resit - Microprocessors and Matlab assessment coursework offered. Students must satisfy certain threshold conditions of competence in order to be awarded the credits for this module. These additional competences relate to certain UK-SPEC Engineering Council learning outcomes required for accreditation that are uniquely assessed in this module, and that are satisfied by participation in practical activities.

Reading list

The reading list is available from the Library website

Last updated: 14/09/2023

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