Course coordinator
Associate Professor Rowan Gollan
Consultation can be arranged via email.
Course overview
- Study period
- Semester 2, 2025 (28/07/2025 - 22/11/2025)
- Study level
- Undergraduate
- Location
- St Lucia
- Attendance mode
- In Person
- Units
- 2
- Administrative campus
- St Lucia
- Coordinating unit
- Mech & Mine Engineering School
Computational Fluid Dynamics (CFD) for engineering applications. Development of computational techniques for analysis of complex engineering processes by bringing together the knowledge gained in one or more of the following disciplines: fluid mechanics, thermodynamics, heat/mass transfer and numerical methods.
The student is introduced to the modelling and simulation techniques that are part of modern computational fluid dynamics (CFD) software. A CFD package is used to analyse compressible flow situations.
You should plan to spend at least 10 hours per week on this course in order to obtain a passing grade.
Course requirements
Assumed background
This course is based on a working knowledge of Fluid Mechanics, an understanding of numerical methods, and a good knowledge of the Python programming language. To successfully complete this course assumes knowledge in the following:
• Advanced Fluid Mechanics
• Numerical Methods: Completion of courses that cover matrix methods, interpolation, numerical integration and methods for solution of ordinary differential equations.
• Python programming:
Experience with other engineering programming language (e.g. matlab, C, C++, C#, D, etc) and then learning python in your own time has proven effective also. Please discuss with Course Coordinator.
Prerequisites
You'll need to complete the following courses before enrolling in this one:
MECH3400 and (MECH2410 or MECH3410) and (MECH2700 or MECH3750 or MECH3780)
Companion or co-requisite courses
You'll need to complete the following courses at the same time:
If MECH3410 (or equivalent) not previously completed, MECH3410 must be taken as companion.
Incompatible
You can't enrol in this course if you've already completed the following:
MECH4480, MECH7480
Course contact
Course staff
Lecturer
Timetable
The timetable for this course is available on the UQ Public Timetable.
Additional timetable information
No workshop on Wednesday 13 August due to Royal Queensland Show Holiday.
Aims and outcomes
The purpose of this course is to introduce you to the principles of Computational Fluid Dynamics along with associated tools, and to show you how to apply these in an engineering context. The goal is that you will be able to generate high quality simulations of flow fields to inform engineering design and decision making.
Learning outcomes
After successfully completing this course you should be able to:
LO1.
Demonstrate competence in the formulation and implementation of numerical methods for modelling dynamic fluid systems, including general transport processes.
LO2.
Apply the principles of verification and validation in CFD modelling to assess the quality and trustworthiness of simulation results.
LO3.
Apply the principles of best-practice CFD to generate high quality simulations, including considerations of physical model selection, numerical convergence and appropriateness of boundary conditions.
LO4.
Design, develop and implement analysis workflows to process CFD flow field results into engineering quantities of interest.
LO5.
Apply CFD for engineering analysis, design and decision making, and appraise the quality of simulation results.
LO6.
Evaluate the strengths, weaknesses and assumptions of CFD analysis for engineering design and decision making.
Assessment
Assessment summary
| Category | Assessment task | Weight | Due date |
|---|---|---|---|
| Computer Code, Tutorial/ Problem Set | Homework exercises | 10% |
4/08/2025 - 27/10/2025
Homework exercises are due on Mondays at 1:00pm weekly, excluding Week 4 because of the interruption to teaching due to the Exhibition holiday in Week 3. Mondays are chosen to follow the previous week's applied class on the Friday. |
| Computer Code, Paper/ Report/ Annotation | 2-D Flow Solver | 20% |
16/09/2025 2:00 pm |
| Paper/ Report/ Annotation | Simulation of compressible Flow | 20% |
31/10/2025 5:00 pm |
| Examination |
Final exam
|
50% |
End of Semester Exam Period 8/11/2025 - 22/11/2025 |
A hurdle is an assessment requirement that must be satisfied in order to receive a specific grade for the course. Check the assessment details for more information about hurdle requirements.
Assessment details
Homework exercises
- Mode
- Written
- Category
- Computer Code, Tutorial/ Problem Set
- Weight
- 10%
- Due date
4/08/2025 - 27/10/2025
Homework exercises are due on Mondays at 1:00pm weekly, excluding Week 4 because of the interruption to teaching due to the Exhibition holiday in Week 3. Mondays are chosen to follow the previous week's applied class on the Friday.
- Learning outcomes
- L01, L02, L03, L04, L05, L06
Task description
The homework exercises for submission will be noted on the weekly worksheets. The submissions will take the form of computer source code, text responses and figures/graphs.
Each submission is worth 1%, but your total marks are capped at 10%. Your overall mark for homework exercises will be computed as the best 10 out of 11 submissions over the semester.
Artificial Intelligence (AI) and Machine Translation (MT) are emerging tools that may support students in completing this assessment task. Students may appropriately use AI and/or MT in completing this assessment task. Students must clearly reference any use of AI or MT in each instance.
A failure to reference generative AI or MT use may constitute student misconduct under the Student Code of Conduct.
Submission guidelines
Submit on Gradescope (with link on Blackboard).
Deferral or extension
You cannot defer or apply for an extension for this assessment.
The best 10 out of 11 submissions over the semester will be counted and results/answers are released soon after the due date, no extensions are permitted.
Late submission
You will receive a mark of 0 if this assessment is submitted late.
Results released promptly to permit students to progress with follow up submissions. This has been approved by the Associate Dean (Academic).
2-D Flow Solver
- Mode
- Written
- Category
- Computer Code, Paper/ Report/ Annotation
- Weight
- 20%
- Due date
16/09/2025 2:00 pm
- Learning outcomes
- L01, L02, L03, L04
Task description
This assignment will assess content in Modules 1 and 2 through implementation and application of a two-dimensional flow solver. The full assignment specification and criteria will be available on the Blackboard course page.
This task has been designed to be challenging, authentic and complex. Whilst students may use AI and/or MT technologies, successful completion of assessment in this course will require students to critically engage in specific contexts and tasks for which artificial intelligence will provide only limited support and guidance.
A failure to reference generative AI or MT use may constitute student misconduct under the Student Code of Conduct.
To pass this assessment, students will be required to demonstrate detailed comprehension of their written submission independent of AI and MT tools.
Submission guidelines
Submit via Gradescope (with link provided on Blackboard).
Deferral or extension
You may be able to apply for an extension.
The maximum extension allowed is 14 days. Extensions are given in multiples of 24 hours.
Feedback is provided to students following 14 calendar days.
Late submission
A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.
Simulation of compressible Flow
- Mode
- Written
- Category
- Paper/ Report/ Annotation
- Weight
- 20%
- Due date
31/10/2025 5:00 pm
- Learning outcomes
- L02, L03, L04, L05, L06
Task description
This assignment will assess you ability to perform and interpret simulations of compressible flows. You will use the Eilmer compressible flow tool. The submission format is a short report. The full assignment specification will be released on the Blackboard course page.
This task has been designed to be challenging, authentic and complex. Whilst students may use AI and/or MT technologies, successful completion of assessment in this course will require students to critically engage in specific contexts and tasks for which artificial intelligence will provide only limited support and guidance.
A failure to reference generative AI or MT use may constitute student misconduct under the Student Code of Conduct.
To pass this assessment, students will be required to demonstrate detailed comprehension of their written submission independent of AI and MT tools.
Submission guidelines
Submit on Gradescope (with link on Blackboard).
Deferral or extension
You may be able to apply for an extension.
The maximum extension allowed is 14 days. Extensions are given in multiples of 24 hours.
Feedback is provided to students following 14 calendar days.
Late submission
A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.
Final exam
- Hurdle
- Identity Verified
- Mode
- Written
- Category
- Examination
- Weight
- 50%
- Due date
End of Semester Exam Period
8/11/2025 - 22/11/2025
- Learning outcomes
- L01, L02, L03, L04, L05, L06
Task description
The final exam is a paper-based handwritten examination that assesses the concepts presented in all modules (1, 2 & 3) of the course.
This assessment task is to be completed in-person. The use of generative Artificial Intelligence (AI) or Machine Translation (MT) tools will not be permitted. Any attempted use of AI or MT may constitute student misconduct under the Student Code of Conduct.
Hurdle requirements
You will require 45% or higher in the final exam in order to get a grade of 4 or above in the course.Exam details
| Planning time | 10 minutes |
|---|---|
| Duration | 120 minutes |
| Calculator options | (In person) Casio FX82 series only or UQ approved and labelled calculator |
| Open/closed book | Closed book examination - no written materials permitted |
| Exam platform | Paper based |
| Invigilation | Invigilated in person |
Submission guidelines
Deferral or extension
You may be able to defer this exam.
Course grading
Full criteria for each grade is available in the Assessment Procedure.
| Grade | Cut off Percent | Description |
|---|---|---|
| 1 (Low Fail) | 0.00 - 29.99 |
Absence of evidence of achievement of course learning outcomes. |
| 2 (Fail) | 30.00 - 44.99 |
Minimal evidence of achievement of course learning outcomes. |
| 3 (Marginal Fail) | 45.00 - 49.99 |
Demonstrated evidence of developing achievement of course learning outcomes Course grade description: Falls short of satisfying basic requirements for a Pass. Overall grade: 45.00-49.99% or less than 45% in the IVA requirement explained below. |
| 4 (Pass) | 50.00 - 64.99 |
Demonstrated evidence of functional achievement of course learning outcomes. Course grade description: Satisfies all of the basic learning requirements for the course, such as knowledge of fundamental concepts and performance of basic skills; demonstrates sufficient quality of performance to be considered satisfactory or adequate or competent or capable in the course. Overall mark 50.00-64.99% and a minimum score of 45% in the final exam. |
| 5 (Credit) | 65.00 - 74.99 |
Demonstrated evidence of proficient achievement of course learning outcomes. Course grade description: Demonstrates ability to use and apply fundamental concepts and skills of the course, going beyond mere replication of content knowledge or skill to show understanding of key ideas, awareness of their relevance, some use of analytical skills, and some originality or insight. Overall mark 65.00-74.99% and a minimum score of 60% in the final exam. |
| 6 (Distinction) | 75.00 - 84.99 |
Demonstrated evidence of advanced achievement of course learning outcomes. Course grade description: Demonstrates awareness and understanding of deeper and subtler aspects of the course, such as ability to identify and debate critical issues or problems, ability to solve non-routine problems, ability to adapt and apply ideas to new situations, and ability to invent and evaluate new ideas. Overall mark 75.00- 84.99% and a minimum score of 70% in the final exam. |
| 7 (High Distinction) | 85.00 - 100.00 |
Demonstrated evidence of exceptional achievement of course learning outcomes. Course grade description: Demonstrates imagination, originality or flair, based on proficiency in all the learning objectives for the course; work is interesting or surprising or exciting or challenging or erudite. Overall mark 85.00 - 100% and a minimum score of 80% in the final exam. |
Additional course grading information
Grading Criteria
Specific grading criteria will be provided for each assessment item. These are available on Blackboard in the assessment folder.
Identity verified assessment
Identity verified assessment (IVA) will be through obtaining at least 45% of the available marks in the final exam.
Supplementary assessment
Supplementary assessment is available for this course.
Additional assessment information
Further details on assessment descriptions and the relevant criteria will be available on the course Blackboard site.
A failure to reference AI use may constitute student misconduct under the Student Code of Conduct.
Learning resources
You'll need the following resources to successfully complete the course. We've indicated below if you need a personal copy of the reading materials or your own item.
Library resources
Find the required and recommended resources for this course on the UQ Library website.
Additional learning resources information
BLACKBOARD: all course related information, lecture notes, applied class questions, and links to other course relevant material will be made available on the course Blackboard site.
EILMER:ﾠ In addition to the User Guide, direct access to the Eilmer project is available at http://gdtk.uqcloud.net/
TEXTBOOKS: Access to the recommended text books will be assumed. No additional material will need to be purchased.
Learning activities
The learning activities for this course are outlined below. Learn more about the learning outcomes that apply to this course.
Filter activity type by
Please select
| Learning period | Activity type | Topic |
|---|---|---|
Multiple weeks From Week 1 To Week 4 |
Workshop |
MODULE 1: CFD in a microcosm Introduction to CFD by building a simple one-d flow solver. This introduces: finite-volume method for Navier-Stokes equations; boundary conditions; discretisation; numerical stability; and measures of convergence. Learning outcomes: L01, L02, L03, L04 |
Multiple weeks From Week 2 To Week 13 |
Applied Class |
Applied Class Applied Classes: These sessions are structured around a worksheet and are self-paced. Staff may lead demonstrations on certain aspects of the worksheet exercises. Some of the worksheet exercises contribute towards the weekly homework assignments. In the weeks prior to major assignments, staff are available to give assignment advice in these sessions. Learning outcomes: L01, L02, L03, L04, L05, L06 |
Multiple weeks From Week 5 To Week 8 |
Workshop |
MODULE 2: D.I.Y Navier-Stokes solver Learn about numerical algorithms for Euler and Navier-Stokes equations through a Do-It-Yourself approach: by building your own flow solver. Also covered in this module is grid generation, and verification and validation. Learning outcomes: L01, L02, L03, L04 |
Multiple weeks From Week 9 To Week 13 |
Workshop |
MODULE 3: Compressible Flow Learn about solving compressible flows (Eilmer); Learn to write source code for compressible solvers Learning outcomes: L02, L03, L04, L05, L06 |
Policies and procedures
University policies and procedures apply to all aspects of student life. As a UQ student, you must comply with University-wide and program-specific requirements, including the:
- Student Code of Conduct Policy
- Student Integrity and Misconduct Policy and Procedure
- Assessment Procedure
- Examinations Procedure
- Reasonable Adjustments for Students Policy and Procedure
Learn more about UQ policies on my.UQ and the Policy and Procedure Library.