Note: This unit version is currently under review and is subject to change!

CHNG9202: Applied Mathematics for Chemical Engineers (2019 - Semester 1)

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Unit: CHNG9202: Applied Mathematics for Chemical Engineers (6 CP)
Mode: Normal-Day
On Offer: Yes
Level: Postgraduate
Faculty/School: School of Chemical and Biomolecular Engineering
Unit Coordinator/s: Dr Montoya, Alejandro
Session options: Semester 1
Versions for this Unit:
Site(s) for this Unit:
Campus: Camperdown/Darlington
Pre-Requisites: None.
Prohibitions: CHNG2802 OR CHNG5702.
Brief Handbook Description: Virtually every aspect of a chemical engineer's professional life will involve some use of mathematical techniques. Not only is the modern chemical engineer expected to be proficient in the use of these techniques, but they are also expected to be able to utilise computer-based solutions when analytical solutions are unfeasible. This unit of study aims to expose students to an appropriate suite of techniques and enable them to become proficient in the use of mathematics as a tool for the solution of a diversity of chemical engineering problems.

Specifically, this unit consists of two core modules: MODULE A: Applied Statistics for Chemical Engineers and MODULE B: Applied Numerical Methods for Chemical Engineers. These modules aim at furthering knowledge by extending skills in statistical analysis and Chemical Engineering Computations. This unit will also enable the development of a systematic approach to solving mathematically oriented Chemical Engineering problems, which will help with making sound engineering decisions.

In addition, there will be considerable time spent during the semester on advanced topics related to mathematical analysis techniques in engineering and recent associated developments.
Assumed Knowledge: Enrolment in this unit of study assumes that first year undergraduate core maths, science and engineering UoS (or their equivalent) have been successfully completed.
Lecturer/s: Dr Montoya, Alejandro
Timetable: CHNG9202 Timetable
Time Commitment:
# Activity Name Hours per Week Sessions per Week Weeks per Semester
1 Lecture 2.00 1 13
2 Tutorial 2.00 1 13
3 Independent Study 5.00 1 13
T&L Activities: This course uses a variety of teaching and learning activities. These activities consist of lectures, tutorials, PC lab activities and essay examinations. The tutorials and PC lab activities complement the theory and applications presented in the lectures and represent a significant ingredient for realizing the aims of the course. We make use of Excel and Matlab.

Each week a new tutorial will be given and you are highly encouraged to attempt this prior to attending the tutorial session. This will promote discussion and interaction during the tutorial deepening on your learning. The primary goal of the tutorials is not to serve as items of assessment (i.e.| as hand-in assignments to earn marks). Rather, the aim of the tutorial sessions will continue to give you a chance to work through a guided number of problems. You will be able to get feedback on your progress from the lecturer, the tutors and your fellow students. Through this process, you will develop understanding and confidence in handling the material.

Learning outcomes are the key abilities and knowledge that will be assessed in this unit. They are listed according to the course goal supported by each. See Assessment Tab for details how each outcome is assessed.

(7) Project and Team Skills (Level 1)
1. Effectively communicate both technical and non-technical material in written, electronic, graphics, and spoken forms
(2) Engineering/ IT Specialisation (Level 2)
2. Propose experimental and computational approaches to bring together and apply knowledge to numerically characterise, analyse and solve a wide range of engineering problems
3. Use the standard techniques of statistical design of experiments to evaluate the effect of input variables in the response of chemical engineering processes
4. Apply computational methods to get insights into steady and non-steady conditions of Chemical Engineering processes
(1) Maths/ Science Methods and Tools (Level 3)
5. Be able to fit polynomials to experimental data
6. Use numerical procedures to solve typical engineering equations with multiple variables
7. Write computer codes in Matlab to numerically integration and differentiate data obtained from experimental observations
Assessment Methods:
# Name Group Weight Due Week Outcomes
1 Quiz one No 20.00 Week 6 2, 3,
2 Quiz two No 20.00 Week 12 2, 4, 5,
3 Online Assessments No 10.00 Multiple Weeks 2, 3, 4, 5, 6,
4 Project 1: Design of Experiments Yes 25.00 Week 13 1, 2,
5 Project2:Numerical analysis of Experimental Data Yes 25.00 Week 13 4, 6, 7,
Assessment Description: Paper and computer-aided examinations will be part of the assessment. It is aimed to allow you to reflect on your learning and to gauge your performance in the course. You are highly encouraged to treat and use these as learning situations rather than examination exercises.

Your competency in the key concepts to be covered in this unit will be assessed as follows:

• Two quizzes: Module A (Desing of Experiments for Chemical Engineers) and Module B (Data Analysis for Chemical Engineers).

• Weekly assessments to complete over several weeks

• Project 1: Develop an experimental activity to practice your knowledge in the design of experiments and present the results in written form and orally in front of all students.

• Project 2: a problem-solving assignment in Numerical Computations to complete on week 13.
Assessment Feedback: Sufficient feedback to students is provided by the lecturer and tutors. The solution of tutorial examples, quizzes and project questions will be discussed with students in class, and individually on especially circumstances, if need it.
Grade Type Description
Standards Based Assessment Final grades in this unit are awarded at levels of HD for High Distinction, DI (previously D) for Distinction, CR for Credit, PS (previously P) for Pass and FA (previously F) for Fail as defined by University of Sydney Assessment Policy. Details of the Assessment Policy are available on the Policies website at . Standards for grades in individual assessment tasks and the summative method for obtaining a final mark in the unit will be set out in a marking guide supplied by the unit coordinator.
Policies & Procedures: See the policies page of the faculty website at for information regarding university policies and local provisions and procedures within the Faculty of Engineering and Information Technologies.
Recommended Reference/s: Note: References are provided for guidance purposes only. Students are advised to consult these books in the university library. Purchase is not required.
  • Applied Statistics and Probability for Engineers
  • Numerical Methods for Engineers
Online Course Content: Lecture slides and tutorial notes are available prior to the corresponding lecture section on the e-learning WebCT

(blackboard) site.

Note that the "Weeks" referred to in this Schedule are those of the official university semester calendar

Week Description
Week 1 Review: Introduction to Matlab, Statistical Distributions and their properties
Week 2 Basics of Design of Experiments
Week 3 Statistical quality control analysis
Week 4 Analysis of data obtained with a Design of Experiments scheme: Analysis of variance
Week 5 Analysis of data obtained with a Design of Experiments scheme: Surface response models
Week 6 Application of Design of Experiments in the Chemical Industry
Assessment Due: Quiz one
Week 7 Numerical procedures to solve typical engineering equations: Least-square techniques for maximising, minimising and finding roots of a set of equations with multiple variables
Week 8 Differential equations relevant to Chemical Engineering with initial conditions
Week 9 Differential equations relevant to Chemical Engineering with boundary conditions
Week 10 Application of partial differential equations in mass and energy balances
Week 11 Application of Laplace Transform in Chemical Engineering
Week 12 Application of Laplace Transform in Chemical Engineering
Assessment Due: Quiz two
Week 13 Review of Quiz two and Project
Assessment Due: Project 1: Design of Experiments
Assessment Due: Project2:Numerical analysis of Experimental Data

Course Relations

The following is a list of courses which have added this Unit to their structure.

Course Year(s) Offered
Master of Professional Engineering (Chemical & Biomolecular) 2015, 2016, 2017, 2018, 2019, 2020
Graduate Diploma in Complex Systems 2017, 2018, 2019, 2020
Master of Complex Systems 2017, 2018, 2019, 2020

Course Goals

This unit contributes to the achievement of the following course goals:

Attribute Practiced Assessed
(8) Professional Effectiveness and Ethical Conduct (Level 1) No 0%
(7) Project and Team Skills (Level 1) No 12.5%
(6) Communication and Inquiry/ Research (Level 1) No 0%
(2) Engineering/ IT Specialisation (Level 2) No 63%
(1) Maths/ Science Methods and Tools (Level 3) No 24.5%

These goals are selected from Engineering & IT Graduate Outcomes Table 2018 which defines overall goals for courses where this unit is primarily offered. See Engineering & IT Graduate Outcomes Table 2018 for details of the attributes and levels to be developed in the course as a whole. Percentage figures alongside each course goal provide a rough indication of their relative weighting in assessment for this unit. Note that not all goals are necessarily part of assessment. Some may be more about practice activity. See Learning outcomes for details of what is assessed in relation to each goal and Assessment for details of how the outcome is assessed. See Attributes for details of practice provided for each goal.