# NUMERICAL AND STATISTICAL METHODS - 2019/0

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

Civil and Environmental Engineering

HAGEN-ZANKER Alex (Civl Env Eng)

## Overall student workload

Independent Learning Hours: 113

Lecture Hours: 22

Laboratory Hours: 15

Semester 1

## Module content

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

• Programming in MATLAB: Programming techniques to implement and use numerical methods as encountered in this module

• 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 GROUP COURSEWORK 40
School-timetabled exam/test WEEKLY COMPUTER BASED ASSESSMENTS 20
Examination EXAMINATION- 2 HOURS 40

## Alternative Assessment

• The alternative assessment for the Group Coursework is an Individual Coursework.
• The alternative assessment for the Weekly Computer Based Assessments is a Single Computer Based Assessment that covers the same material, but in fewer questions and shorter time than the combined weekly assessments.

## Assessment Strategy

The assessment strategy is designed to provide students with the opportunity to demonstrate their understanding of main numerical and statistical methods in Civil Engineering, their ability to apply these in a programming environment and their ability to independently apply methods beyond those taught in the lectures.

Thus, the summative assessment for this module consists of: coursework in groups of four students (40%) assessing the element of independent problem solving; a two-hour exam (40%) assessing the element of theoretical understanding of numerical and statistical methods; weekly computer based tests (20%) assessing the development of programming skills.

Formative assessment and feedback

The computer lab based tutorial use class sizes of 20-25 students to allow discussion and time to address individual questions related to the exercises. There will also be opportunity for groups working on coursework to show and discuss their progress.

## Module aims

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

## Learning outcomes

 Ref Attributes Developed 001 Proficiently and critically use a range of numerical and statistical methods in the analysis and solution of engineering problems, including an understanding of alternative approaches and their limitations KC SM2B, SM2M, SM5M, EA3B, EA3B, P2B 002 Use MATLAB and programming as a tool to help solve engineering problems KC SM2B, SM4M, EA3B, P2B 003 Move towards independent research, application and analysis of numerical methods for engineering problems KCT P4, G1 004 Convey technical information in a written report to a professional standard PT D6 005 Collaborate effectively in a small team and exercise initiative and individual responsibility P P11B, P11M, G4

Attributes Developed

C - Cognitive/analytical

K - Subject knowledge

T - Transferable skills

P - Professional/Practical skills

## Methods of Teaching / Learning

The intended learning outcomes of this module emphasize the ability to interpret and apply numerical and statistical methods over the theoretical knowledge of numerical methods and programming concepts. Students will gain an understanding of the main methods in computational Civil Engineering practice and be able to apply those in a programming environment.

The learning and teaching strategy is aligned with these learning outcomes in several ways:

1. By running computer lab tutorials for two hours per week for the initial four weeks. In these labs students are introduced to the MATLAB language and software and develop the fundamental programming skills required for the practical engagement with numerical methods. The programming skills are developed by working on a set of practical exercises.

2. Students will work in groups of four to develop further numerical problem-solving skills by solving a set of coursework exercises that require independent research into the application of methods that are not covered in the lectures,

3. It is not expected that tutorial exercises will be completed during the tutorials; the main mode of independent learning is to work on these exercises and the coursework at home or on campus.

4. The lectures introduce key numerical and statistical methods from Civil Engineering practice with sufficient detail and theoretical background for students to apply these in their own programs. Practically all theory introduced in the lectures will be applied in the tutorial exercises.

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.