Book of Abstracts
European Congress of Chemical Engineering (ECCE-6)
Copenhagen, 16-20 September 2007
The Function of Functional Modelling in (Bio-)Chemical
Engineering
Sten Bay Jørgensen,a Niels Jensen, a Morten Lind,b
a
Department of Chemical Engineering, Technical University of Denmak, DK-2800 Lyngby, Denmark
Ørsted_DTU, Technical University of Denmak, DK-2800 Lyngby, Denmark
c
Research Centre, Address, Zip-code City, Country
b
1. Summary
Functional modelling links the modelling purpose with its physical/chemical
implementations. Thereby this modelling methodology, which has been developed
within computer science sems to provide a systematic basis for spolving many of the
challenging problems related to multiple scales and multiple abstartion levels in
process and product engineering.
Keywords: , multiscale modelling, modelling networks, complexity, Automated
HAZOP, regulatory networks
2. Extended Abstract
Functional modelling links the modelling purpose with its physical/chemical
implementations. This linkage is achieved by systematically representing the
modelling purposes and their derived sub-goals and subsequently connecting these to
the means through which the (sub-)purposes are achieved. These connection may be
made within a multilevel abstraction framework called functional modelling. By
assigning cause and effect to the means it is also possible to reason in functional
models. To facilitate model development a functional modelling framework may be
implemented in a computer environment wherein also the reasoning can be carried
out. Clearly functional modelling provides a natural basis for integrating design over
many different scales which constitutes a fundamental problem in chemical
engineering.
Functional models may be directly used in design, e.g. when a separation (or reaction)
agent is desired for the execution of a specific separation (or reaction). Here
functional modelling may be used to facilitate reverse engineering such that the
process may be optimally designed assuming the availability of the proper ideal agent
and in a subsequent step then the (nearly) ideal agent may be designed in a separate
S.B. Jørgensen et al.
step. If design of a nearly ideal agent indeed is feasible then an optimal design has
been achieved, if however a suboptimal design must be settled for, then however this
may be rather easily verified as a neraly optimal solution can be provided as a starting
point. Eden et al (2004).
Functional models clealrly may be used for many different purposes. A number of
these have been illustrated recently. One example is to model the function of
regulatory networks in microorganisms thereby illustrating how information at many
different abstraction levels may be combined to achieve a desired functionality. Here
functional modelling enables simultaneous representation of multiple functionalities,
thereby facilitating the understanding of the different modes of control in microorganisms, Gernaey et al (2006). Another example is to automate HAZOP analysis of
an integrated chemical plant again based upon afunctional model of the plant
combined with the causal roles which permit reasoning about consequences of
deviations in process plants.. This methodology has been developed and implemented
as a prototype in a JESS based system. The automated HAZOP methodology has been
demonstrated in a case study performed on 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 which
normally are quite difficult to uncover for unexperineced personel. Thereby the
autokmated HAZOP may provide a highly desirable assistance during Hazard
identification, Jensen et al (2006).
Functional modelling of a process plant with its control system also directly reveals
the importance of being able to model the functionality of the control system for
designing the (optimal) plant operation. Thus a potential future usage of functional
modelling may be to represent a process design and its potential control design
thereby enabling reasoning on simultaneous process and control design including
paying proper regard to the results of a HAZOP analysis as reflected in the
requirements to the control system. Thus pointing to development of a suitable
(optimal) operations managemnet system specification.
Combining mathematical models and their purposes, i.e. as expressed in Functional
Models seem to be intuitively obvious, however this link is usually not explicitly
available in traditional mathematical models. Instead mathematical models may be
developed form a Functional Model once the means for achieving the desired
functionality are specified and suitably classified.
Thus functional modelling indeed 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. With the dual notion of abstratction hierarchies
and means end relationships then functional modelling provides a systematic
framework and thereby a scientific basis for managing complexity. Therefore it can
be highly advantageous for cheimcal) engineering to develop functional modelling as
a separate discipline more explicitly.
Funcction of Functional Modelling in (Bio-)Chemical Engineering
3
References:
1. M.R. Eden, S.B. Jørgensen, R. Gani, M. El-Halwagi, 2004, “A novel
framework for simultaneous separation process and product design”,
Chemical Engineering & Processing, 43, pp. 595-608
2. Gernaey K.V., Lind M. and Jørgensen S.B., 2006 “Towards understanding the
role and function of regulatory networks in microorganisms” in, Puigjaner L.
and Heyen G. (Eds.) Computer Aided Process & Product Engineering. WileyVCH, Weinheim (Germany), vol. 1, Chapter 7, pp. 223-264
3. Netta Liin Rossing, Morten Lind, Johannes Petersen, Sten Bay Jørgensen and
Niels Jensen, 2006, “A Functional approach to HAZOP studies”, Chemical
Engineering Transactions (AIDIC), Volume 9: Proceedings of 2nd
International Conference on Safety & Environment in Process Industry, Editor
S.S. Buratti, pp. 49-54