This course extends the concepts of mass and energy balances introducing an incremental approach to the development of dynamic models of process units. Concepts presented in lectures is reinforced by a series of workshops from the initial tasks of specifying a modelling project to the final tasks of simulation and validation.
At the completion of the course, you will have developed the skills to construct process models that can be used to verify process and control system performance, test process operability and controllability and predict future process behaviour.
- Model Development 1 includes the uses of models, modelling goals and specifications, basic principles of conservation and constitutive equations.
- Model Development 2 includes model formulation from goals to specifying assumptions and writing equations, incremental modelling practice starting with overall mass, component mass, energy and then momentum.
- Analysis of and Solution Models includes degrees of freedom and index, controllability, observability and identifiability.
- Model Calibration and Validation includes strategies, data requirements, sensitivity analysis, regression and the evaluation of regression results.
- Empirical Models includes fitting simple models to step tests, the identification and regression steps for simple time-series models.
- Advanced Models includes a brief introduction to distributed parameter, discrete event and hybrid models, when they are needed and what is available for such modelling.
What Do You Get?
- Copy of "Process Modelling and Model Analysis" by Hangos and Cameron (a recent authoritative text on process modelling).
- Three-month trial license of software for dynamic simulation, time-series analysis and data analysis.
- Hands-On experience in developing, analysing and validating process models.
- Free advice from expert consultants in process modelling and simulation (bring along your current problem).
Who Should Enroll?
Engineers involved with the design and/or operation of processes who are interested in improving process performance through modelling and simulation.