02_Modelling_E2009 - 1 28150. Introduction to proces...

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Unformatted text preview: 1 28150. Introduction to proces control 2. First principles process modelling Krist V. Gernaey 31 August 2009 28150 Learning objectives At the end of this lesson you should be able to: Create, in a structured step-wise fashion, a first-principles dynamic model for a process Implement and simulate the model (exercises, next week!) 31 August 2009 28150 Outline Introduction Model development principles Degrees of freedom analysis A systematic model development approach Modelling examples 31 August 2009 28150 Outline Introduction Model development principles Degrees of freedom analysis A systematic model development approach Modelling examples 2 31 August 2009 28150 What is a model? A model (M) for a system (S) and an experiment (E) is anything to which E can be applied in order to answer questions (P) about S (Minsky, 1965) S P M E 31 August 2009 28150 Different models Physical model of a system Pilot plant Mathematical model of a system Equations Graphs Linguistic model of a system Example: If substrate is available, dissolved oxygen consumption of the biomass will increase 31 August 2009 28150 What is a first principles model? A model developed using the principles of chemistry, physics and biology (conservation laws) first engineering principles model, theoretical model, deterministic model, white box model Steady-state model versus unsteady-state model ( dynamic model ) 31 August 2009 28150 Model classification First engineering principles models Empirical (black Box )models Semi- empirical (grey box) models Process data Process knowledge Neural network, ARX, ARMAX, etc. 3 31 August 2009 28150 Properties of first principles models Model complexity must be determined (assumptions), depends on model purpose Can be computationally expensive (not real-time) May be expensive/time-consuming to obtain Good for extrapolation, scale-up Does not require experimental data to obtain (data required for validation and fitting) 31 August 2009 28150 Properties of black-box models Large number of unknown parameters Can be obtained quickly (e.g., linear regression) Model structure is subjective Dangerous to extrapolate 31 August 2009 28150 Properties of grey-box models Compromise of first two approaches Model structure may be simpler Good versatility, can be extrapolated Can be run in real-time 31 August 2009 28150 The use of a model Real world problem Mathematical problem Mathematical solution Interpretation of solution 4 31 August 2009 28150 Outline Introduction Model development principles Degrees of freedom analysis A systematic model development approach Modelling examples 31 August 2009 28150 Model development principles Conservation of mass Conservation of component i { } { } out mass of rate in mass of rate mulation mass of accu rate- =...
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This note was uploaded on 11/20/2009 for the course CHME DTU-abroad taught by Professor Rafiqulgani during the Fall '09 term at Rensselaer Polytechnic Institute.

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02_Modelling_E2009 - 1 28150. Introduction to proces...

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