Module Catalogue 2019/20

CME1026 : Computing and Numerical Methods

  • Offered for Year: 2019/20
  • Module Leader(s): Dr Chris O'Malley
  • Lecturer: Dr Mark Willis
  • Owning School: Engineering
  • Teaching Location: Newcastle City Campus
Semesters
Semester 1 Credit Value: 5
Semester 2 Credit Value: 5
ECTS Credits: 5.0
Pre Requisites
Pre Requisite Comment

N/A

Co Requisites
Co Requisite Comment

N/A

Aims

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 Techniques 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 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 Techniques (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 simulate dynamical systems

MATLAB (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.
Excel-based data analysis and charting.

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 using Excel and MATLAB.
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 bases 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.
Capability in data analysis using EXCEL.
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
Guided Independent StudyAssessment preparation and completion112:0012:00Exam Revision
Guided Independent StudyAssessment preparation and completion12:302:30MATLAB assessment
Guided Independent StudyAssessment preparation and completion11:301:30Exam
Guided Independent StudyAssessment preparation and completion11:001:00Exam
Scheduled Learning And Teaching ActivitiesLecture241:0024:00N/A
Scheduled Learning And Teaching ActivitiesPractical103:0030:00Computing practice
Scheduled Learning And Teaching ActivitiesPractical121:0012:00Numerical practice (tutorials)
Guided Independent StudyIndependent study117:0017:00Preparation and review of lecture material
Total100:00
Teaching Rationale And Relationship

Lectures introduce basic knowledge and techniques. Tutorials reinforce acquired knowledge and practical 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.

Reading Lists

Assessment Methods

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

Exams
Description Length Semester When Set Percentage Comment
Written Examination901A50Closed Book exam.
Written Examination602A30Open Book Exam
Other Assessment
Description Semester When Set Percentage Comment
Computer assessment2M20Matlab assignment
Assessment Rationale And Relationship

Computer-based programming skills are best assessed by demonstration of the capability, and the lab-based assignment serves to assess the level of achievement of the learning outcomes. The assignment is completed with the use of MATLAB and Excel to demonstrate that appropriate levels of skills in the use of these applications have been gained. The examinations enable the assessment of whether the students have understood the methodologies and whether they are sufficiently conversant with the application of the techniques to real world scenarios.

Timetable

Past Exam Papers

General Notes

N/A

Disclaimer: The information contained within the Module Catalogue relates to the 2019/20 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 2020/21 entry will be published here in early-April 2019. Queries about information in the Module Catalogue should in the first instance be addressed to your School Office.