Module Catalogue 2021/22

CME1026 : Computing and Numerical Methods

  • Offered for Year: 2021/22
  • Module Leader(s): Dr Chris O'Malley
  • Owning School: Engineering
  • Teaching Location: Newcastle City Campus
Semester 1 Credit Value: 5
Semester 2 Credit Value: 5
ECTS Credits: 5.0
Pre Requisites
Pre Requisite Comment


Co Requisites
Co Requisite Comment



To introduce the use of MATLAB-based computer programming and develop capabilities in problem analysis for computer-based solution.
To introduce the use of Excel for data analysis and presentation of results/information.
To learn the principles associated with some of the common computer-based techniques used to solve chemical and process engineering problems
This module comprises two parts: Numerical Methods and Programming in MATLAB and is delivered over two semesters.
Semester 1: The first part introduces the theory and principles associated with some of the common computer-based techniques used to numerically solve chemical and process engineering problems.
Semester 2: The second part provides an introductory course in computer programming for the solution of engineering problems. Students will be required to put into practice the theory learnt in Semester 1. MATLAB, a high-level computing language is used extensively. The learning objectives are delivered predominantly through "hands-on" laboratory problem solving sessions.

Outline Of Syllabus

Numerical Methods (Semester 1): Analytical solutions versus numerical methods; 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

Computing (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 solution strategies.

Learning Outcomes

Intended Knowledge Outcomes

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

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.
Appreciate the power of numerical techniques and computer-based solutions.

To understand 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.

Knowledge of how to identify the computational characteristics of a model and in choosing an appropriate solution strategy

To learn how to model dynamical systems using SIMULINK

Intended Skill Outcomes

Capabilities in problem analysis and flowcharts.
Capability in MATLAB programming for engineering problem solution.
To gain experience of using commercial software to simulate a process.
To develop a working knowledge of SIMULINK.
To be able to apply the numerical techniques covered in the syllabus.
Problem Solving.

Teaching Methods

Teaching Activities
Category Activity Number Length Student Hours Comment
Scheduled Learning And Teaching ActivitiesLecture101:0010:00Semester 1
Guided Independent StudyAssessment preparation and completion15:005:00Semester 1 Time limited (1hr) summative CANVAS test with preparation time (1.5hr)
Scheduled Learning And Teaching ActivitiesLecture101:0010:00Semester 2 lectures
Guided Independent StudyAssessment preparation and completion19:009:00Semester 2 Completion of the MATLAB & Simulink Assignment
Structured Guided LearningAcademic skills activities74:0028:00Semester 1 Watch asynchronous example calculations. Completion of tutorial sheets of 7 problems.
Scheduled Learning And Teaching ActivitiesWorkshops71:007:00Semester 1 Tutorial sessions to help with student problem from the tutorial sheets
Scheduled Learning And Teaching ActivitiesWorkshops73:0021:00Semester 2 Computing Labs
Guided Independent StudyIndependent study101:0010:00General reading around MATLAB functions and associated material
Teaching Rationale And Relationship

Rationale of Teaching Methods and Relationship to Learning Outcomes

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. The students gain practical experience of applying the concepts introduced throughout the course to a number of problems varying in terms of complexity.

Scenario Planning should lockdowns or restrictions be imposed:

Semester 1

Lecture Sessions

Plan A lectures present in person (PiP)

Plan B Asynchronous delivery of lecture content and 3 Synchronous Online (SO) to support

Workshop / Tutorial sessions

Plan A sessions to be PiP (whole cohort)

Plan B support to be provided through discussion boards and SO zoom tutorial sessions

Semester 2

Lecture Sessions

Plan A lectures present in person (PiP)

Plan B Asynchronous delivery of lecture content and 3 Synchronous Online (SO) to support

Workshop / Tutorial sessions

Plan A Computing cluster sessions PiP (Monday & Fridays 50% of the cohort per session); completion of worksheets

Plan B SO sessions to support self study completion of worksheets

Reading Lists

Assessment Methods

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

Other Assessment
Description Semester When Set Percentage Comment
Computer assessment1M20Canvas Test - x 4 Root finding techniques
Computer assessment1M20Canvas Test - x2 approaches to solving sets of equations
Computer assessment2M60Solving Euler’s method problems by hand and validating the results using software (both Simulink and MATLAB).
Assessment Rationale And Relationship

Semester 1
2 x 1hr limited summative Canvas quizzes focussed on 2 topics:
Test 1 - approximately week 3/4 of semester
Test 2 - approximately week 6/7 of semester
Semester 2
Assignment enables testing of simulation, programming and flow chart capabilities and will assess learning outcomes on solving ODEs and operating software.
Assignment release approximately week 4/5 of semester


Past Exam Papers

General Notes


Disclaimer: The information contained within the Module Catalogue relates to the 2021/22 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 2022/23 entry will be published here in early-April 2022. Queries about information in the Module Catalogue should in the first instance be addressed to your School Office.