CE1NMP-Numerical modelling and programming 1

Module Provider: School of Construction Management and Engineering, School of Built Environment
Number of credits: 10 [5 ECTS credits]
Level:4
Terms in which taught: Spring term module
Pre-requisites:
Non-modular pre-requisites:
Co-requisites:
Modules excluded:
Current from: 2020/1

Module Convenor: Dr Stefan Smith

Email: s.t.smith@reading.ac.uk

Type of module:

Summary module description:

Numerical models are central to solve complex engineering problems, including assessment of thermal behaviour of environmental systems, heat transfer and fluid flow in the built environment. Numerical modelling and programming helps to find approximate solutions for complex, nonlinear problems where analytic solutions are not available such as the study of microclimates. This module introduces the principal knowledge for the formulation of model equations, approaches to solve them numerically and ways in which the performance of the developed numerical model can be evaluated. This module also introduces the basics of commuter programming using either Matlab or Python programs. A key characteristic of this module is that it is designed to integrate and apply the knowledge obtained in the module of Building Services 1 (CE1BSP), thermodynamics and heat transfer (CE1THT) and Engineering Mathematics (CE1EMA). 

Aims:

The aim of this module is to provide students with principles of numerical modelling and programming and enable them to formulate, numerically model and evaluate the performance of the developed models to solve engineering problems.

Assessable learning outcomes:

On successful completion of this module the student should be able to:

• Explain the need for numerical modelling and programming to solve engineering problems,  


• Recognise sources of numerical error and derive and measure order of accuracy,


• Design numerical models for physical phenomena including heat transfer,


• Implement numerical models by programming in MATLAB or Python,


• Evaluate the perform ance of the numerical models.

Additional outcomes:

• To describe the terminology used in numerical modelling and programming,


• To discretise an equation in a consistent way, and assess the accuracy of the discretisation,


• To discuss limitations of numerical modelling,


• To understand the difference and relationships between analytical and numerical methods in problem-solving.

Outline content:

• Introduction to numerical modelling and programming,


• Programming flowcharts,


• Programming techniques in a scripting language, e.g., variables, loops, conditionals, functions, arithmetic


• Root finding algorithms, such as Newton-Raphson, and Runge-Kutta,


• Numerical solutions of set a of algebraic equations,


• Models, continuous and discrete,


• Rule and knowledge-based models,


• Le ast-squares approximation,


• Numerical Solution of differential and Integral Equations

Global context:

The skills and knowledge that students will acquire from this module have global applications.

Brief description of teaching and learning methods:

Teaching in this module will be by means of lectures, tutorials and practical classes using facilities available in the computer laboratory. These sessions will be complemented by project activities and guided independent study.

Independent study hours needed depend on the learning style of each individual. The following guide for independent study hours is just an example.

Contact hours:

	Autumn	Spring	Summer
Lectures		20
Tutorials		5
Practicals classes and workshops		5
Guided independent study:
Wider reading (independent)		5
Wider reading (directed)		5
Peer assisted learning		5
Advance preparation for classes		12
Preparation for tutorials		5
Preparation of practical report		30
Revision and preparation		6
Reflection		2
Total hours by term	0	100	0
Total hours for module	100

Summative Assessment Methods:

Method	Percentage
Project output other than dissertation	70
Set exercise	30

Summative assessment- Examinations:

Summative assessment- Coursework and in-class tests:

There will be a set exercise test which will be assessed summatively and should be submitted online by the end of week 9 of the spring term. In addition, the outcomes of project work should be prepared as a report (2000-2500 words) and should be submitted online by the end of week 11 of spring term. 

Formative assessment methods:

This module includes formative assessment of exercises and problem-solving practices about numerical modelling and programming that will be discussed in tutorial sessions, practical classes and workshops.

Penalties for late submission:

The Module Convenor will apply the following penalties for work submitted late:

• where the piece of work is submitted after the original deadline (or any formally agreed extension to the deadline): 10% of the total marks available for that piece of work will be deducted from the mark for each working day[1] (or part thereof) following the deadline up to a total of five working days;
• where the piece of work is submitted more than five working days after the original deadline (or any formally agreed extension to the deadline): a mark of zero will be recorded.

The University policy statement on penalties for late submission can be found at: http://www.reading.ac.uk/web/FILES/qualitysupport/penaltiesforlatesubmission.pdf
You are strongly advised to ensure that coursework is submitted by the relevant deadline. You should note that it is advisable to submit work in an unfinished state rather than to fail to submit any work.

Assessment requirements for a pass:

A mark 0f 40%

Reassessment arrangements:

Students who have failed in their first attempt will be provided with an assignment brief related to numerical modelling and programming and they should prepare a report (2000-2500 words) that should be submitted online.

Additional Costs (specified where applicable):

Last updated: 31 July 2020