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European Congress of Chemical Engineering - 6
Copenhagen 16-21 September 2007

Abstract 3375 - The Function of Functional Modelling in (Bio-)Chemical Engineering

The Function of Functional Modelling in (Bio-)Chemical Engineering

Systematic methods and tools for managing the complexity

Advances in Computational & Numerical Methods (T4-4)

Prof Sten Bay Jørgensen
Technical University of Denmark
CAPEC, Dpt. of Chemical Engineering
Building 229
DK-2800 Lyngby
Denmark

Prof Morten Lind
Technical University of Denmark
Oersted
Dk2800 Lyngby
Denmark

Asc. Prof Niels Jensen
Department of Chemical Engineering - DTU
CAPEC
Søltofts Plads, Building 229
DK-2800 Kgs. Lyngby
Denmark

Dr Johannes Petersen
Technical University of denmark
Oersted
Dk2800 Lyngby
Denmark

Keywords: Functional Modelling, Systematic model development, Multiscale modelling, Reasoning in models

Functional modelling links the system purpose with its physical/chemical implementations. This linkage is achieved by systematically representing the system purpose and the derived sub goals and subsequently connecting these to the means through which the (sub-) purposes are achieved in a multilevel abstraction framework. By assigning causality to the model it is possible to reason in functional models. Thus functional models constitute a meta-model class from which conventional mathematical models may be derived. To facilitate functional model development and usage a modelling framework may be implemented in a computer environment wherein the reasoning can be carried out.

Functional models may be used for many different functions/purposes in chemical engineering. A number of these have been illustrated recently and a few will be elucidated in this paper.

One example where functional modelling may be advantageously used is to facilitate an automated HAZOP analysis of an integrated chemical process plant. To illustrate this application a case study has been carried out using the Indirect Vapour Recompression Distillation Plant (IVaRDiP) at DTU. This case illustrates that it is possible in a flexible manner to reveal both local and quite remote cause and effect relations and to analyse the potential malfunctions. Functional modelling of the IVaRDiP with its control system also directly reveals the importance of being able to model the purposes of the control system for designing the plant operation. Thus this application points at a potential future usage of functional modelling is represent a process design and its potential control design thereby enabling reasoning on plant operability early-on during simultaneous process and control design.

Another example where process and control functions are intimately related is modelling of metabolic and regulatory networks in microorganisms where functional modelling enables simultaneous representation of the dual functionalities, thereby facilitating the understanding of the different modes of control in microorganisms. A basic study of the possible elementary control functions reveals that only a limited set of functions exist. These functions are all shown to be present in microorganism regulatory networks.

Combining mathematical models and knowledge within their systems and knowledge system purposes seem to be intuitively obvious; however this link is usually not explicitly available in traditional mathematical models. Instead mathematical models may be developed from a functional model provided the means for obtaining the desired physical functionality are specified.

Thus functional modelling may be used in many different functions in (bio-)chemical processes. In fact engineering is all about developing systems to achieve a desired functionality, hence functional modelling can be used advantageously in many aspect of engineering design.

Presented Tuesday 18, 15:40 to 16:00, in session Advances in Computational & Numerical Methods (T4-4).

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