# NUMERICAL AND STATISTICAL METHODS - 2021/2

Module code: ENG2106

## Module Overview

Civil Engineers routinely make use of software tools for calculations on physical systems, ranging from structural analysis, to soil mechanics and fluid dynamics. This module provides an introduction to the numerical and statistical methods underlying many of these tools, including Finite Element and Finite Difference Methods as well as linear regression.

The module is hands-on: students will be introduced to MATLAB and learn to write their own programs to apply the methods encountered in the module.

### Module provider

Sustainability, Civil & Env Engineering

HAGEN-ZANKER Alex (Civl Env Eng)

### Module cap (Maximum number of students): N/A

Independent Learning Hours: 50

Tutorial Hours: 15

Guided Learning: 60

Captured Content: 25

Semester 1

N/A

## Module content

The module sits within the core subject of mathematic and covers the following areas:

• Fundamental programming concepts: variables, functions, control structures, vector and matrix data structures

• Syntax, semantics and good programming practice.

• Using the MATLAB programming language and integrated development environment

• Solution of Ordinary Differential Equations by Runge-Kutta and associated methods

• Solution methods for simultaneous linear equations

• Principles and application of the Finite Difference Method for solving Ordinary and Partial Differential Equations

• Principles and application of the Finite Element Method applied on truss structures

• Principles and application of (multiple) linear regression, including confidence and significance

## Assessment pattern

Assessment type Unit of assessment Weighting
Coursework ASSIGNMENT 1: PROGRAMMING FUNDAMENTALS 30
Coursework ASSIGNMENT 2: PROGRAMMING APPLICATION 30
Examination Online ONLINE 24 HOUR (OPEN BOOK) EXAM 40

## Alternative Assessment

Not applicable

## Assessment Strategy

Summative assessment

The summative assessment for this module consists of two coursework assignment and an exam. In the first coursework assignment, students demonstrate fundamental programming skills in MATLAB, including the use of functions, variable, matrix and vector data structures, control structures and plotting (learning outcomes 003 and 005). In the second coursework, students apply their programming skills to implement a numerical method that they have independently researched (learning outcomes 004 and 005). The end-of-semester exam assesses the element of theoretical understanding of numerical and statistical methods (learning outcomes 001 and 002).

Formative assessment and feedback

During computer lab based tutorials students have an opportunity to receive verbal feedback on their work. Additionally, students can test their understanding and get immediate feedback through weekly multiple-choice tests.

## Module aims

• Knowledge and experience of the use of standard numerical and statistical methods to solve complex engineering problems
• Knowledge and experience of using computer programming as a tool to solve engineering problems

## Learning outcomes

 Ref Attributes Developed 001 Proficiently and critically use a range of numerical methods for the analysis and solution of engineering problems, including an understanding of alternative approaches and their limitations KC SM2B, SM2M, SM5M, EA3B, EA3B, P2B 002 Proficiently and critically use multiple linear regression for data analysis KC SM2B, SM2M, SM5M, EA3B, EA3B, P2B 003 Use MATLAB and programming as a tool to help solve engineering problems KC SM2B, SM4M, EA3B, P2B 004 Move towards independent research, application and analysis of numerical methods for engineering problems KCT P4, G1 005 Convey technical information in a written report to a professional standard PT D6

Attributes Developed

C - Cognitive/analytical

K - Subject knowledge

T - Transferable skills

P - Professional/Practical skills

## Methods of Teaching / Learning

Lectures – and supporting notes – are used to introduce key concepts and theoretical background. The main learning however, will take place as students complete weekly exercises that bring the newly learned concepts and knowledge to practice. Weekly tutorial sessions are used to provide feedback and discuss these exercises. The first four weeks of the module are dedicated to programming fundamentals. In these weeks the tutorials are longer than usual (two hours instead of one) because of the importance of feedback in this stage of learning. The coursework provides further exercise in developing programming skills and the ability to use these skills to solve numerical problems. A staggered approach is followed, where the first coursework assignment covers fundamentals and the second requires independent inquiry and application of techniques

Indicated Lecture Hours (which may also include seminars, tutorials, workshops and other contact time) are approximate and may include in-class tests where one or more of these are an assessment on the module. In-class tests are scheduled/organised separately to taught content and will be published on to student personal timetables, where they apply to taken modules, as soon as they are finalised by central administration. This will usually be after the initial publication of the teaching timetable for the relevant semester.