ENG1014 - Engineering numerical analysis

Overview

This unit introduces engineering computing fundamentals in the contexts of data analysis and modelling of physical systems. The Python programming language will be introduced, including techniques for importing/exporting data and communicating results from computational analysis. Programming structures such as loops, conditional statements and functions will be introduced. You will use … For more content click the Read More button below.

You will use programming to examine a range of complex engineering systems, including performing basic analysis on large data sets and modelling systems that do not exhibit analytical solutions. Problems related to these systems will be solved using various numerical methods for linear regression, root-fiding, numerical integration and numerical solutions to ordinary differential equations. The underlying assumptions, complexities and uncertainties associated with the models and numerical methods will be emphasised.

Offerings

S1-01-CLAYTON-FLEXIBLE

S1-01-MALAYSIA-ON-CAMPUS

S2-01-CLAYTON-FLEXIBLE

S2-01-MALAYSIA-ON-CAMPUS

Requisites

Prohibition

Rules

Enrolment Rule

Contacts

Chief Examiner(s)

Dr Andrew Rodda

Unit Coordinator(s)

Associate Professor Ooi Ean Hin

Dr Lim Lam Ghai

Dr Andrew Rodda

Notes

Optional Peer Assisted Study Sessions (PASS) run in this unit.

Learning outcomes

On successful completion of this unit, you should be able to:

Identify appropriate programming structures and functions to solve simple computational tasks.

Discern mathematical and computational information in prose descriptions of diverse engineering problems, and incorporate this into computed solutions.

Select and use appropriate programming structures and functions to solve engineering problems.

Select and use appropriate text or graphical formats to communicate the solutions to engineering problems.

Describe uncertainties and errors associated with numerical models and methods and their implications on the computed results.

Teaching approach

Active learning

This unit uses a blended-flipped active learning approach that introduces you to topics via online written and video material. You are expected to prepare for the week by studying this content, then attending an expert-led workshop where the concepts are reviewed and where activities are provided to apply students' knowledge on the activity within the class. You will gain further practical experience via hands-on practical classes.

Assessment summary

Continuous assessment: 50%
Final assessment: 50%

This unit contains threshold hurdle requirements that you must achieve to be able to pass the unit. You are required to achieve at least 45% in the total continuous assessment component and at least 45% in the final assessment component. The consequence of not achieving a hurdle requirement is a fail grade (NH) and a maximum mark of 45 for the unit.

Assessment

1 - Quizzes and tests

2 - Computer labs

3 - Assignment

4 - Final assessment

Scheduled and non-scheduled teaching activities

Assessments

Laboratories

Workshops

Workload requirements

Workload

The minimum total expected workload to achieve the learning outcomes for this unit is 144 hours per semester typically comprising a mixture of 3-6 hours of scheduled learning activities and 6-9 hours of independent study per week. Scheduled activities may include a combination of teacher-directed learning, peer-directed learning and online engagement. Independent study may include associated readings, assessment and preparation for scheduled activities.

Availability in areas of study

E3001 Bachelor of Engineering (Honours)