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This course provides a detailed introduction to numerical methods used in chemical engineering. The course includes an introduction to the theory of numerical methods as well as practical guidance on the implementation of these tools to a variety of problems. The course is about 2/3 on numerical methods for simulation and 1/3 on computational fluid dynamics (CFD).
"Numerical methods for the simulation of chemical processes (Matthew Watson)• methods for solution of non-linear, poorly scaled, algebraic equations• solution of large systems of ODEs• modelling and solution of differential-algebraic equation (DAE) systems• modelling of distributed parameter systems• solution of partial differential equation systems using the method of lines• using sparsity for speedOptimisation and parameter estimation (Luke Schneider)• optimisation• optimisation for non-linear curve fitting• design and analysis of experiments using non-linear models• parameter uncertainty in linear models• modelling uncertainty in systems• optimisation of dynamic systems, including parameter estimationPython (Alfred Herritsch)• Introduction to scientific programming with Python• time series analysis• Python classes and applications for solving problems• useful Python packages for chemical engineers
1. Develop and numerically solve models of chemical engineering processes.2. Identify and apply the numerical tools appropriate to a particular problem.3. Apply optimisation and parameter estimation to problems in chemical engineering.4. Formulate and solving chemical engineering problems using an open source programming language.5. Critique results to estimate the accuracy and help guide design.
ENCH391 Process Systems and Control
Workload36 contact hours and completion of all assessments. If required there will be dedicated computer lab sessions.
Matt James Watson
3 Assignments Total: Assignment 1 due 16 March. Assignment 2 due 4 May. Assignment 3 due 29 May.
Beveridge, Gordon S. G. , Schechter, Robert Samuel;
Optimization: theory and practice
Canter and Schimmel;
(3 volume set).
Quantum Publishers, 1975.
Recommended Reading:Hangos, K. and Cameron, I.T. (2001) Process Modelling and Model Analysis, Academic Press.Beers, K.J. (2007) Numerical Methods for Chemical Engineers: Applications in Matlab, Cambridge University Press, Cambridge, UK.Schiesser, W.E. (2009) A Compendium of Partial Differential Equation Models: Method of Lines Analysis with Matlab, Cambridge University Press, Cambridge, UK.Chapra, S.C. and Canale, R.P. (2010) Numerical Methods for Engineers, 6th ed., McGraw-Hill, Boston.
ConcernsStudents with concerns about the course should contact the course coordinator or the 3rd Pro Director of Studies, Dr Alex Yip.General Policies of the DepartmentStudents may obtain the general policies of the University on matters such as the special considerations, appeals procedures, reconsideration of grades and special provision for students with disabilities from the University Calendar. The Department assessment details, Departmental Safety Handbook, Electrical Safety Supplement and Disposal of Chemical Wastes Policy are distributed to the students at the beginning of the new year.
Prerequisite: ENCH391. In addition good mathematics and Matlab skills are recommended. This course is an optional 3rd Professional depth elective.
Lectures encouraged but not mandatory
Late submission gathers a 10% penalty per day
4th floor of LINK building.
Domestic fee $975.00
International fee $5,500.00
* All fees are inclusive of NZ GST or any equivalent overseas tax, and do not include any programme level discount or additional course-related expenses.
This course will not be offered if fewer than 10 people apply to enrol.
For further information see
Chemical and Process Engineering