MEC3456 - Engineering computational analysis

Overview

This unit conveys the fundamentals of numerical analysis techniques for root-finding, interpolation, integration, the solution of ordinary differential equations and data analysis, and Python/Matlab is employed to demonstrate their implementation. The role computers play in both the solution of engineering problems and the acquisition and analysis of data is explored … For more content click the Read More button below.

This unit conveys the fundamentals of numerical analysis techniques for root-finding, interpolation, integration, the solution of ordinary differential equations and data analysis, and Python/Matlab is employed to demonstrate their implementation. The role computers play in both the solution of engineering problems and the acquisition and analysis of data is explored through consideration of common partial differential equations in mechanics, and their solution via finite difference, finite volume, and finite element methods.

Offerings

S1-01-CLAYTON-FLEXIBLE

S1-01-MALAYSIA-ON-CAMPUS

Requisites

Prerequisite

Prohibition

Rules

Enrolment Rule

Contacts

Chief Examiner(s)

Dr Juxi Leitner

Unit Coordinator(s)

Associate Professor Ooi Ean Hin

Dr Juxi Leitner

Learning outcomes

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

Apply appropriate mathematical and numerical techniques to solve common engineering problems.

Construct algorithms and programs that can solve engineering problems by integrating multiple numerical techniques.

Apply these programs to engineering problems in order to generate solutions.

Analyse and interpret data using numerical techniques.

Assess algorithms, programs and solutions for error, stability and accuracy.

Teaching approach

Problem-based learning

The main theory and concepts that form the core of this unit are introduced in a set of short online videos that should be watched prior to class. The ideas in these videos will be consolidated by explaining them in more detail in class and via the application of theory to specific examples and developing algorithms for their implementation. You will then individually develop Python/MATLAB code to implement these methods and solve problems, with particular attention being paid to errors, accuracy and stability.

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 - Computer-based assignments

2 - Moodle quizzes

3 - Final assessment

Scheduled and non-scheduled teaching activities

Laboratories

Practical activities

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.

Learning resources

Required resources

Other unit costs

The following item is mandatory for practical aspects of the unit and should be purchased at your own cost as you will be reusing them throughout your course.

Calculator

Availability in areas of study

E3001 Bachelor of Engineering (Honours) - Specialisation: Aerospace engineering
E3001 Bachelor of Engineering (Honours) - Specialisation: Mechanical engineering
E6011 Master of Professional Engineering - Specialisation: Mechanical engineering