Engineering Mathematics and Scientific Computing

Module title	Engineering Mathematics and Scientific Computing
Module code	INT1113
Academic year	2022/3
Credits	30
Module staff	Dawn Elizabeth Bird (Convenor)

Duration: Term	1	2	3
Duration: Weeks	10	10

Number students taking module (anticipated)	40

Description - summary of the module content

Module description

This module introduces modern engineering mathematics by teaching maths alongside programming. What you learn in this module will support mathematical content in core modules throughout your programme. You will be introduced to core mathematical tools for modelling engineering systems which will be developed further in Year 2. You will learn about statistical methods of analysis that are vital tools for experimental engineers.

An elementary introduction to programming in python will be provided which will equip you with valuable data processing and modelling skills. The teaching of python will mirror mathematical content, building on knowledge of specialist packages for matrices, differential equations and statistics.

Module aims - intentions of the module

This module aims to provide you with all of the mathematical tools to tackle modern engineering problems. It will allow you to develop strong quantitative skills, such that mathematical tools become second nature so you can focus directly on engineering challenges and concepts. An important aspect of this is to provide a solid foundation in programming.

Intended Learning Outcomes (ILOs)

ILO: Module-specific skills

On successfully completing the module you will be able to...

1. manipulate complex algebraic expressions (including Boolean algebra), functions and vectors [E1,C1]
2. demonstrate knowledge of analytical and numerical differentiation and integration [E1,C1]
3. solve ordinary differential equations [E1,C1]
4. demonstrate foundational knowledge of statistical and probabilistic techniques required for engineering [E1,C1]
5. manipulate matrices, and use them to solve systems of equations and simple eigenvalue problems [C1

ILO: Discipline-specific skills

On successfully completing the module you will be able to...

6. demonstrate knowledge of the key principles of object orientated programme [C1
7. structure, write and test computer programmes to solve engineering mathematical task [C1]
8. formulate engineering problems into mathematical statements [C1]
9. understand the application of new mathematical methods in the context of real engineering problems [C1]

ILO: Personal and key skills

On successfully completing the module you will be able to...

10. demonstrate strong quantitative and problem solving skills [E1,C1]
11. demonstrate a strong foundation in scientific computing in python [C1]

Syllabus plan

Algebra (Refresher Unit)
Functions
Vectors

Differentiation

Integration

Ordinary Differential Equations

Matrices

Statistics and Probability for Engineers

Transformations - Fourier & Laplace

Learning and teaching

Learning activities and teaching methods (given in hours of study time)

Scheduled Learning and Teaching Activities	Guided independent study	Placement / study abroad
220	80

Details of learning activities and teaching methods

Category	Hours of study time	Description
Scheduled learning and teaching activities (synchronous)	160	Lectures and tutorials
Scheduled learning and teaching activities (synchronous)	20	Computing laboratories
Scheduled Learning and Teaching Activities (asynchronous)	40	Online (ELE) activities
Tutorial preparation and guided independent study	80	Independent study

Assessment

Formative assessment

Form of assessment	Size of the assessment (eg length / duration)	ILOs assessed	Feedback method
Online ELE Quizzes	2 hours per week	1-11	Online feedback

Summative assessment (% of credit)

Coursework	Written exams	Practical exams
30	70

Details of summative assessment

Form of assessment	% of credit	Size of the assessment (eg length / duration)	ILOs assessed	Feedback method
Coursework (online)	30	2 worksheets, 10 hours each	1-11	Written feedback on formal submission
Written Examination (online)	20	2 hour mid-module exam	1-5, 8-10	Written feedback on formal submission
Written Examination (online)	50	2 hour end of module exam	1-5, 8-10	Written feedback on formal submission

Re-assessment

Details of re-assessment (where required by referral or deferral)

Original form of assessment	Form of re-assessment	ILOs re-assessed	Timescale for re-assessment
Written exam and coursework	Written exam (referral)	1-11	Next assessment period
Written exam	Written exam (deferral)	1-5, 8-10	Next assessment period

Re-assessment notes

The pass mark for award of credit in this module is 40%. Referral is the process whereby a further attempt at the module examination, following an initial failure, is permitted without the requirement to repeat any attendance. Referral will constitute one formal examination – coursework and component exams will not be included in the re-assessment.

Resubmission of coursework is impractical since coursework answers and feedback are given to students after marking.

The grade for the referred examination, and therefore the module grade, will be capped at 40%.

The grade for a deferral will combine grades awarded for coursework and deferred examinations.

Resources

Indicative learning resources - Basic reading

Author	Title	Edition	Publisher	Year	ISBN
Stroud, K.A	Engineering Mathematics	8th	Macmillan International	2020	987-1-352-01027-5 paperback 987-1-352-01028-2 ebook
Stroud K.A. & Booth Dexter J.	Advanced Engineering Mathematics	6th	Macmillan International	2020	978-1-352-01025-1 paperback 978-1-352-01026-8 ebook

Module has an active ELE page

Key words search

Engineering Mathematics, Programming, Computing, Python

Credit value	30
Module ECTS	15
Module pre-requisites	None
Module co-requisites	None
NQF level (module)	4
Available as distance learning?	Yes
Origin date	19/11/2019
Last revision date	09/07/2022