CHE5884 · Process modelling and optimisation

Overview

The unit will cover the purpose and methods of modelling chemical and biochemical processes. It includes the development of constitutive relations, model building, evaluation and sensitivity analysis. Numerical techniques will include the solution of systems of linear, non-linear and algebraic equations. Models are subjected to optimisation. The basic principles of optimisation including the types of variables, linear and non-linear models, constraints and objective functions will be covered. Various optimisation algorithms for linear, non-linear problems and mixed integer problems are presented in the context of chemical process design. Multi-objective optimisation is used to explore trade-offs involved with sustainable process development.

Areas of study: E6009 Master of Industrial Chemical Engineering (Monash-SEU Double Masters) E6011 Master of Professional Engineering - Specialisation: Chemical engineering

Offerings

Assessment

The Handbook lists an examination for this unit.

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 details may change. Please refer to the assessment information in Moodle closer to the start of the teaching period.

Requisites

The Handbook lists no prerequisite, corequisite or prohibition for this unit.

Learning outcomes

1. Generate models of chemical and biological processes respecting conservation laws, applying suitable constraints and constitutive relations and determine an appropriate solution algorithm.
2. Assess complex models of chemical processes with an understanding of the mathematical structure of the model and the convergence methods used to obtain the model solution.
3. Assess the appropriate optimisation strategy for linear, non-linear, unconstrained, constrained and mixed integer models from a fundamental understanding of functional and constraint convexity, or determine the appropriate evolutionary solution strategy when convexity is not assured.
4. Demonstrate both single objective and multi-objective optimisation of process models to improve the process objective(s), which assess the sustainability of chemical processes using the life cycle assessment methodology.

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.

Student experience, not official rules. Nothing here changes what the Handbook says.