Course coordinator
Professor Anh Nguyen
Course overview
- Study period
- Semester 1, 2025 (24/02/2025 - 21/06/2025)
- Study level
- Postgraduate Coursework
- Location
- St Lucia
- Attendance mode
- In Person
- Units
- 2
- Administrative campus
- St Lucia
- Coordinating unit
- Chemical Engineering School
This course builds on CHEE3007 Process Modelling and Dynamics and considers a range of techniques required to model complex and unfamiliar processes. Students use advanced features of relevant modelling and programming software. Large scale experimental data from processes or experiments are used to build 'data driven' models for a range of applications. Following this, students integrate data-driven and mechanistic models to develop and apply hybrid modelling to model industrial or experimental processes. The projects are derived from current industry applications.
Modern chemical engineering is "model centric", meaning that the decision making taken in design and operations is highly informed through a wide range of models that possess various characteristics. A range of models are investigated in this course. Their nature and origin, as well as their formulation and solution are covered, starting with the analysis of complex, dynamic industrial data and then using that data for model building or validation of mechanistic or grey box models. The use of approaches such as system identification and principal component analysis are emphasised. The course uses industrial projects to drive knowledge, skill development and decision making.
Course requirements
Assumed background
Completion of the 4 year BE degree in Chemical Engineering with good understanding of process principles, programming skills and prior modelling expertise via CHEE3007 and CHEE4009.
Prerequisites
You'll need to complete the following courses before enrolling in this one:
CHEE3007
Companion or co-requisite courses
You'll need to complete the following courses at the same time:
CHEE7113
Restrictions
Permission is required from the HoS to enrol, please contact studentenquiries@chemeng.uq.edu.au
Course contact
Course staff
Lecturer
Dr Felix Egger
Professor Anh Nguyen
Dr Christian Zuluaga Bedoya
Dr Lars Puiman
Tutor
Mr Greg Siemon
Mr Braden Fritz
Timetable
The timetable for this course is available on the UQ Public Timetable.
Aims and outcomes
To extend the knowledge and skills acquired from CHEE3007 Process Modelling and Dynamics and CHEE4009 Transport Phenomena. The goal is to address advanced modelling techniques, applied to industrial designs and operation, which can have a significant impact on decision making. The course will address the underlying characteristics of process systems as represented in very large dynamic data sets to build insights into the underlying system dynamics. It will provide skills in evaluating the quality of the data and its use in building empirical models. Data-driven, mechanistic and hybrid modelling ﾠwill be investigated. Practical use of modelling and solution environments will be emphasized, along with the fundamentals of good modelling practice. The fundamental nature of multiscale models will be examined. Students will develop their critical thinking and communication skills, such that they can ask essential questions in model development and application, such as What is the purpose of the model? How can the model be used for decision making? What are the key limitations of the model? What reliability/confidence/accuracy/uncertainty is required or expected from a specific model? What additional information would improve your predictions? What insights can you glean from the model?
Learning outcomes
After successfully completing this course you should be able to:
LO1.
Clean, tidy, explore, visualize, analyze and develop models to provide insight into large industrial datasets
LO2.
Explain the opportunities and challenges for advanced modelling approaches in a wide range of system applications, across research, design and operations
LO3.
Evaluate, select and apply appropriate modelling methodologies for particular outcomes, including both mechanistic and empirical models, and hybrid systems
LO4.
Critically assess the validity of the assumptions underpinning your model, using data, logic and mechanistic knowledge; assess whether the model is fit for purpose; evaluate the reliability of model output; identify what information is required to improve confidence in model predictions
LO5.
Apply critical thinking skills to analyze, synthesize and effectively communicate technical information
LO6.
Demonstrate professional conduct in engaging with industry, including an appreciation of sustainability
LO7.
Improve teamwork skills through practice, reflection, feedback and change
Assessment
Assessment summary
| Category | Assessment task | Weight | Due date |
|---|---|---|---|
| Participation/ Student contribution | Non-Disclosure Agreement | Compulsory |
24/02/2025 1:00 pm |
| Paper/ Report/ Annotation |
Individual exercises
|
20% Hurdle |
24/03/2025 3:00 pm 2/05/2025 3:00 pm |
| Paper/ Report/ Annotation, Presentation |
Project Presentation and Project Part A
|
25% |
31/03/2025 4:00 pm 11/04/2025 3:00 pm
Single combined submission for CHEE7111 and CHEE7113 |
| Paper/ Report/ Annotation, Presentation |
Project Presentation and Project Part B
|
25% |
19/05/2025 4:00 pm 30/05/2025 3:00 pm
Single combined submission for CHEE7111 and CHEE7113. |
| Examination |
Exam During Exam Period (School) - Individual Oral defence
|
30% Hurdle |
End of Semester Exam Period 7/06/2025 - 21/06/2025 |
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
Non-Disclosure Agreement
- Mode
- Activity/ Performance
- Category
- Participation/ Student contribution
- Weight
- Compulsory
- Due date
24/02/2025 1:00 pm
- Learning outcomes
- L06
Task description
This course uses real industrial data in project work and assessment.
In order to access this Confidential Information, students are required to sign a Non-Disclosure Agreement, in which they agree not to disclose confidential information to any external party, unless required to do so by law. At the end of the course, students are required to permanently erase or physically destroy (by shredding) all received Confidential Information covered by the Non-Disclosure Agreement.
The Confidential Information can be described as Process Flow Sheets, Piping and Instrumentation Diagrams, plant operating manuals and process descriptions, plant data and standard operating procedures, regardless of whether such information is designated as “Confidential Information” at the time of its disclosure.
Submission guidelines
Signed and returned to course-coordinator in hardcopy, or scanned and emailed.
Deferral or extension
You cannot defer or apply for an extension for this assessment.
Individual exercises
- Hurdle
- Online
- Mode
- Activity/ Performance
- Category
- Paper/ Report/ Annotation
- Weight
- 20% Hurdle
- Due date
24/03/2025 3:00 pm
2/05/2025 3:00 pm
- Learning outcomes
- L01, L03, L04, L05
Task description
Individual exercise 1 Due 24 Mar 15:00 Weight: 10%
Performance on nominated individual case studies and set tasks, from Part A content.
Individual exercise 2 Due 2 May 15:00 Weight: 10%
Performance on nominated individual case studies and set tasks from Part B content.
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.
Hurdle requirements
For an overall grade of 4 or higher in this course, students require an overall grade >=50 % AND an average grade across the individual assignments >=50 % AND grade >=50 % on individual oral defence.Submission guidelines
Submitted through Turnitin, via the course Blackboard site.
Deferral or extension
You may be able to apply for an extension.
The maximum extension allowed is 28 days. Extensions are given in multiples of 24 hours.
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.
Assessments must be submitted on or before the due date. Late submissions of assessment items will only be accepted if approval for late submission has been obtained prior to the due date.
Penalties Apply for Late Submission
Refer PPL Assessment Procedure Section 3 Part C (48)
A Student Access Plan (SAP) can only be used for a first extension. Extensions based on an SAP may be granted for up to seven (7) days, or the maximum number of days specified in the Course Instance (CI), if it is less than seven (7) days. Any further extensions will require additional supporting documentation, such as a medical certificate.
Project Presentation and Project Part A
- Identity Verified
- In-person
- Online
- Mode
- Oral, Written
- Category
- Paper/ Report/ Annotation, Presentation
- Weight
- 25%
- Due date
31/03/2025 4:00 pm
11/04/2025 3:00 pm
Single combined submission for CHEE7111 and CHEE7113
- Learning outcomes
- L01, L03, L04, L05, L06, L07
Task description
Project presentation Part A Due 31/03 16:00 Weight: 5%
Presentation to students, staff and industry personnel. A single, combined presentation will be completed for both the CHEE7111 and CHEE7113 components of the project. Students will be required to mark and respond to presentations by other groups, as well as present their own work.
Each group will upload a presentation to Blackboard prior to the scheduled presentation time, then either play a recording of their presentation or present live, and then respond live to questions and comments from teaching staff, classmates and industry partner.
Exact timing will depend on availability of industry clients, estimated due date is class time on this date.
Project report Part A Due 11/04 15:00 Weight: 20%
A team-based project focussed on a process system of complex nature. It will involve both written submission and team-based presentation to the client(s).
The single project report will cover Part A projects from both CHEE7111 and CHEE7113.
Submissions will be through Blackboard. A Turnitin link will be made available before the due date.
This assessment task evaluates students' abilities, skills and knowledge without the aid of generative Artificial Intelligence (AI) or Machine Translation (MT). Students are advised that the use of AI or MT technologies to develop responses is strictly prohibited and may constitute student misconduct under the Student Code of Conduct.
Submission guidelines
Submit presentation files via Blackboard. Presentations will be held during class time.
Deferral or extension
You may be able to apply for an extension.
The maximum extension allowed is 28 days. Extensions are given in multiples of 24 hours.
Late submission
A penalty of 1 grade for each 24 hour period from time submission is due will apply for up to 7 days. After 7 days you will receive a mark of 0.
Assessments must be submitted on or before the due date. Late submissions of assessment items will only be accepted if approval for late submission has been obtained prior to the due date.
Penalties Apply for Late Submission
Refer PPL Assessment Procedure Section 3 Part C (48)
A Student Access Plan (SAP) can only be used for a first extension. Extensions based on an SAP may be granted for up to seven (7) days, or the maximum number of days specified in the Course Instance (CI), if it is less than seven (7) days. Any further extensions will require additional supporting documentation, such as a medical certificate.
Project Presentation and Project Part B
- Online
- Mode
- Oral, Written
- Category
- Paper/ Report/ Annotation, Presentation
- Weight
- 25%
- Due date
19/05/2025 4:00 pm
30/05/2025 3:00 pm
Single combined submission for CHEE7111 and CHEE7113.
- Learning outcomes
- L01, L03, L04, L05, L06, L07
Task description
Project presentation Part B Due 19/05 16:00 Weight: 5 %
Presentation to students, staff and industry personnel. A single, combined presentation will be completed for both the CHEE7111 and CHEE7113 components of the project. Students will be required to mark and respond to presentations by other groups, as well as present their own work.
Each group will upload a presentation to Blackboard prior to the scheduled presentation time, then either play a recording of their presentation or present live, and then respond live to questions and comments from teaching staff, classmates and industry partner.
Exact timing will depend on availability of industry clients, estimated due date is class time on this date.
Project report Part B Due 30/05 15:00 Weight: 20%
A second project dealing with course content and skills applied to a process design or operational issue. It will involve both written submission and team-based presentation to the client(s).
The single project report will cover Part B projects from both CHEE7111 and CHEE7113.
Submissions will be through Blackboard. A Turnitin link will be made available before the due date.
This assessment task evaluates students' abilities, skills and knowledge without the aid of generative Artificial Intelligence (AI) or Machine Translation (MT). Students are advised that the use of AI or MT technologies to develop responses is strictly prohibited and may constitute student misconduct under the Student Code of Conduct.
Submission guidelines
Submit presentation files via Blackboard. Presentations will be held during class time.
Deferral or extension
You may be able to apply for an extension.
The maximum extension allowed is 28 days. Extensions are given in multiples of 24 hours.
Late submission
A penalty of 1 grade for each 24 hour period from time submission is due will apply for up to 7 days. After 7 days you will receive a mark of 0.
Assessments must be submitted on or before the due date. Late submissions of assessment items will only be accepted if approval for late submission has been obtained prior to the due date.
Penalties Apply for Late Submission
Refer PPL Assessment Procedure Section 3 Part C (48)
A Student Access Plan (SAP) can only be used for a first extension. Extensions based on an SAP may be granted for up to seven (7) days, or the maximum number of days specified in the Course Instance (CI), if it is less than seven (7) days. Any further extensions will require additional supporting documentation, such as a medical certificate.
Exam During Exam Period (School) - Individual Oral defence
- Hurdle
- Identity Verified
- In-person
- Mode
- Oral
- Category
- Examination
- Weight
- 30% Hurdle
- Due date
End of Semester Exam Period
7/06/2025 - 21/06/2025
- Learning outcomes
- L01, L03, L04, L05, L06
Task description
This is an oral assessment: you will speak on a topic of your choosing for 3 minutes, then defend your comments on that topic and respond to other questions related to the course.
This assessment task evaluates students' abilities, skills and knowledge without the aid of generative Artificial Intelligence (AI) or Machine Translation (MT). Students are advised that the use of AI or MT technologies to develop responses is strictly prohibited and may constitute student misconduct under the Student Code of Conduct.
Hurdle requirements
For an overall grade of 4 or higher in this course, students require an overall grade >=50 % AND an average grade across the individual assignments >=50 % AND grade >=50 % on individual oral defence.Exam details
| Planning time | no planning time minutes |
|---|---|
| Duration | 30 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 | Other |
| Invigilation | Invigilated in person |
Submission guidelines
Deferral or extension
You may be able to apply for an extension.
The maximum extension allowed is 28 days. Extensions are given in multiples of 24 hours.
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.
Assessments must be submitted on or before the due date. Late submissions of assessment items will only be accepted if approval for late submission has been obtained prior to the due date.
Penalties Apply for Late Submission
Refer PPL Assessment Procedure Section 3 Part C (48)
A Student Access Plan (SAP) can only be used for a first extension. Extensions based on an SAP may be granted for up to seven (7) days, or the maximum number of days specified in the Course Instance (CI), if it is less than seven (7) days. Any further extensions will require additional supporting documentation, such as a medical certificate.
Course grading
Full criteria for each grade is available in the Assessment Procedure.
| Grade | Description |
|---|---|
| 1 (Low Fail) |
Absence of evidence of achievement of course learning outcomes. Course grade description: Typically <20 %. As for grade 2. |
| 2 (Fail) |
Minimal evidence of achievement of course learning outcomes. Course grade description: Typically 20-44 %. Demonstrates clear deficiencies in understanding and applying fundamental concepts; communicates information or ideas in ways that are frequently incomplete or confusing and give little attention to the conventions of the discipline. Grade scores below 3 indicate lack of professional competence in the course material and/or students have failed to complete sufficient assessment items for these requirements to be assessed. |
| 3 (Marginal Fail) |
Demonstrated evidence of developing achievement of course learning outcomes Course grade description: Falls short of satisfying basic requirements for a Pass, due to not demonstrating required competence in assessment and/or failure to complete sufficient assessment for competence to be reasonably assessed. Overall grade typically 45-49% AND/OR grade <50 % across the individual assignments AND/OR grade <50 % on individual oral defence. |
| 4 (Pass) |
Demonstrated evidence of functional achievement of course learning outcomes. Course grade description: For an overall grade of 4 or higher in this course, students require an overall grade >=50 % AND an average grade across the individual assignments >=50 % AND grade >=50 % on individual oral defence. |
| 5 (Credit) |
Demonstrated evidence of proficient achievement of course learning outcomes. Course grade description: For an overall grade of 5 in this course, students typically require an aggregate score of 65-74% AND overall grade >60 % across individual assessment items. |
| 6 (Distinction) |
Demonstrated evidence of advanced achievement of course learning outcomes. Course grade description: For an overall grade of 6 in this course, students typically require an aggregate score of 75-84% AND overall grade >70 % across individual assessment items. |
| 7 (High Distinction) |
Demonstrated evidence of exceptional achievement of course learning outcomes. Course grade description: For an overall grade of 7 in this course, students typically require an aggregate score of at least 85% AND overall grade >80 % across individual assessment items. |
Supplementary assessment
Supplementary assessment is available for this course.
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
Library resources are available on the UQ Library website.
Additional learning resources information
See Blackboard site for CHEE7111.
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 |
Workshop |
Part A: Data analysis and data driven modelling ALL CHEE7111 AND CHEE7113 TIMETABLED CLASSES IN WEEK 1 WILL BE DEVOTED TO CHE7111, AND IN WEEK 2 ALL CHEE7111 & 7113 CLASSES WILL BE DEVOTED TO CHEE7113. FROM WEEK 3 ONWARD, CHEE7111 AND CHEE7113 CLASSES WILL RUN EACH WEEK. Students will be introduced to key aspects of data analysis and data-driven modelling during workshop sessions Learning outcomes: L01, L03, L04, L05, L06, L07 |
Problem-based learning |
Part A: Data analysis and data driven modelling Students will be introduced to key aspects of data analysis and data-driven modelling during workshop sessions, then apply these skills in workshops and mentoring sessions to complete an individual assignment and industry-based group project. Topics covered include: Introduction to systems modelling & data processing; Multivariate analysis; Time series analysis; Construction, application and interpretation of data driven models. Guest lectures and engagement with industry partner will take place in parallel with the workshop and mentoring sessions. Learning outcomes: L01, L03, L04, L05, L06, L07 |
|
Problem-based learning |
Part B: Modelling application to control Students will be introduced to the fundamental principles of good modelling practice in both empirical and mechanistic modelling, including appropriate methods of calibration, model assessment and communication of results, and application of models to process control. Content will be covered in workshops, followed by guided tutorial and mentoring sessions when students will work on individual assessment, and then applied industrial project in parallel with CHEE7113. Workshops will be complemented with guest lectures and engagement with industry partner. Learning outcomes: L01, L03, L04, L05, L06, L07 |
|
Workshop |
OPTIONAL Pre-semester Introductory Python workshop An OPTIONAL pre-semester workshop provides students with an introduction to basic coding in Python, the primary programming language used in CHEE7111 and CHEE7113. Students who attend can claim credit for Python learning activities (worth up to 5 % of Assignment 1) Learning outcomes: L02 |
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 - Students Policy and Procedure
Learn more about UQ policies on my.UQ and the Policy and Procedure Library.
School guidelines
Your school has additional guidelines you'll need to follow for this course:
- Safety Induction for Practicals
Course guidelines
Anyone undertaking courses with a practical component must complete the UQ Undergraduate Student Laboratory Safety Induction and pass the associated assessment.
Specific instructions, usage guidelines and rules for each of the undergraduate laboratories will be delivered as part of each course.
In some cases, students may be required to attend a specific face-to-face laboratory induction/training session.