Module Catalogue 2024/25

CME1026 : Computing and Numerical Methods

CME1026 : Computing and Numerical Methods

  • Offered for Year: 2024/25
  • Module Leader(s): Dr Chris O'Malley
  • Owning School: Engineering
  • Teaching Location: Newcastle City Campus

Your programme is made up of credits, the total differs on programme to programme.

Semester 1 Credit Value: 5
Semester 2 Credit Value: 5
ECTS Credits: 5.0
European Credit Transfer System

Modules you must have done previously to study this module

Pre Requisite Comment



Modules you need to take at the same time

Co Requisite Comment



This module comprises two parts: “Numerical Methods” and “Programming in MATLAB” and is delivered over two semesters. In semester 1 the module aims to provide students with an introduction to theory and principles associated with some common numerical methods for engineering problem solving. In semester 2 the module aims to provide an introductory course in computer programming in MATLAB and Simulink.

Outline Of Syllabus

Key themes for semester 1: Analytical solutions versus numerical solutions; Root finding algorithms; Numerical integration; Numerical solutions of ODEs; Solutions of set of algebraic equations; Least-squares approximation; Use of the SIMULINK to solve these types of problems

Key themes for semester 2: Introduction to the MATLAB software environment; matrix handling; basic MATLAB commands; MATLAB scripts and functions; flow controls; plotting; program debugging; flowcharts and problem solving .

Learning Outcomes

Intended Knowledge Outcomes

To learn how to make use of the computing systems in the School of Engineering.

To recognise the basis of root finding algorithms, numerical integration techniques, numerical solutions of ODEs and algorithms for solving sets of algebraic equations, and how these may be used to solve Chemical Engineering problems (C2, C3).

To learn the basic principles of computer programming in MATLAB and SIMULINK.
To understand the difference and relationships between analytical and numerical methods in problem solving (C13).

Appreciation of the why numerical solutions are favoured over analytical solutions for solving complex engineering problems.

Demonstrate the ability to identify the computational characteristics of a model and in choosing an appropriate solution strategy based on the information available.

Develop understanding how to model dynamic systems using SIMULINK.

Intended Skill Outcomes

Capabilities in problem analysis and flowcharts.

Capability in MATLAB programming for engineering problem solving.

To gain experience of using commercial software to simulate a process.

To develop a working knowledge of MATLAB and SIMULINK.

To be able to apply the numerical techniques covered in the syllabus.

Solving of unseen Chemical Engineering problems.

Teaching Methods

Teaching Activities
Category Activity Number Length Student Hours Comment
Guided Independent StudyAssessment preparation and completion110:0010:00Semester 1 Examination
Guided Independent StudyAssessment preparation and completion110:0010:00Semester 2: Completion of the MATLAB & Simulink Assignment
Scheduled Learning And Teaching ActivitiesLecture101:0010:00Semester 1 Lectures
Scheduled Learning And Teaching ActivitiesLecture101:0010:00Semester 2 Lectures
Structured Guided LearningAcademic skills activities73:0021:00Semester 1 (asynchronous): Watch video example calculations. Completion of tutorial sheets.
Scheduled Learning And Teaching ActivitiesWorkshops12:002:00Semester 1: Simulink Workshop (50% of Cohort per session)
Scheduled Learning And Teaching ActivitiesWorkshops71:007:00Semester 1: Tutorial sessions to help with student problems from the tutorial sheets
Scheduled Learning And Teaching ActivitiesWorkshops83:0024:00Semester 2: Computing Labs (50% of Cohort per session)
Guided Independent StudyIndependent study16:006:00General reading around MATLAB functions and associated material
Teaching Rationale And Relationship

Lectures and lecture materials introduce basic knowledge and techniques. Tutorial work sheets reinforce acquired knowledge and sharpen problem solving skills. Assignments develop software skills and ability to use knowledge in problem solving tasks. Practical classes support the learning introduced in lectures through hands on experience with software. Examination with test the ability of the students to tackle unseen problems and select appropriate techniques to solve them. The students gain practical experience of applying the concepts introduced throughout the course to a number of problems varying in terms of complexity.

Reading Lists

Assessment Methods

The format of resits will be determined by the Board of Examiners

Description Length Semester When Set Percentage Comment
Written Examination901A50Closed Book Exam.
Other Assessment
Description Semester When Set Percentage Comment
Computer assessment2M50Computing assessment includes solving Euler’s method problems by hand and validating the results using software (both Simulink and MATLAB).
Assessment Rationale And Relationship

Examination will test the learning outcomes around problem solving of Chemical Engineering type problems.
Learning outcomes are more programming skills based in semester 2 therefore a summative assignment is the most appropriate manner to assess this content.


Past Exam Papers

General Notes


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The information contained within the Module Catalogue relates to the 2024 academic year.

In accordance with University Terms and Conditions, the University makes all reasonable efforts to deliver the modules as described.

Modules may be amended on an annual basis to take account of changing staff expertise, developments in the discipline, the requirements of external bodies and partners, and student feedback. Module information for the 2025/26 entry will be published here in early-April 2025. Queries about information in the Module Catalogue should in the first instance be addressed to your School Office.