CE2NMP-Numerical modelling and programming

Module Provider: School of Construction Management and Engineering, School of Built Environment
Number of credits: 20 [10 ECTS credits]
Level:5
Terms in which taught: Autumn / Spring term module
Pre-requisites:
Non-modular pre-requisites:
Co-requisites:
Modules excluded:
Current from: 2021/2

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 flows 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.ÌýThis module introduces the required knowledge for the formulation of equations, approaches to solve them numerically and ways in which the performance of the developed numerical model can be evaluated. This module also uses computer programming tools such as Matlab or Python to apply the numerical models and find the numerical solutions. A key characteristic of this module is that it builds upon knowledge gained in the module of Engineering Mathematics 1 (CE1EMA) and integrates and applies the knowledge obtained in the module of Fluids Mechanics (CE2FMT), Engineering Mathematics2 (CE2EMA) and Building Services 2 (CE2BSF).Ìý

Aims:

The aim of this module is to provide students with principals of numerical modelling and programming and enable them to formulate, 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:

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


• Conduct Iterative methods to solve numerical models,


• Design numerical models for physical phenomena including heat transfer and fluids flow,


• Implement numerical models by programming in MATLAB or Python,


• Evaluate the performance of the numerical models,


• Apply probability theory to evaluate numerical models of engineering problems,


• Apply optimisation algorithm to solve simple engineering problems,

Additional outcomes:

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


• To discuss limitations of numerical modelling,


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

Outline content:

• Numerical solutions of ODEs, first and second order,


• Iterative methods such as conjugate gradients for solving elliptic differential equations,


• Stiff ordinary differential equation solvers for solving the heat equation,


• Finite difference schemes for differential equations and their stability,


• The relation between the relative error of the scheme and the conditioning number,


• convergence criteria of rec ursive numerical schemes,


• Stability and perform basic stability analysis,


• Fourier series,


• Visualisation of the results of numerical models,


• Probability-based models,


• Optimisation algorithms,


• Agent-based modellingÌý

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.