Modelling systems defined by RTD curves

Abstract

The RIO theory is commonly used for describing flow patterns in a large class of applications, and par ticularly for ventilated enclosures. Experimental RIO curves are used for modelling these premises with an application in the nuclear industry for predicting the airbome pollutant transfers in order to prevent radiological risk. An approach based on a superstructure involving interlinked elementary flow patterns such as CS TRs, P FRs, recycles and by-passes is implemented. ln order to propose a generic and easy to use tool, the associated large-scale MI NLP problem is solved by using the GAMS package. After a vali dation phase on examples with known solutions, a laboratory enclosure, called MELANIE, used in the nuclear industry is modelled. The comparison between experimental RIO curve and the ones obtained from models extracted from superstructures shows good agreement. The superstructure-based solution procedure constitutes an efficient and intermediate way between numerical simulations using C FD codes and experimental determinations of characteristic parameters, which are both difficult to implement in the case of large and cluttered systems which are typic.al of the nuclear industry.

Compartmental Modelling in chemical engineering: A critical review

“…A known tracer distribution is injected in input and measurements of the output give the Residence Time Distribution (RTD) functions as explained in Danckwerts [21]. The analysis of RTD functions gives a possible network of "virtual" ideal reactors that is representative of the global fluid dynamics system (see Figure 1 left) (Hocine et al [37], Laquerbe et al [53]). The representative structure is not necessarily unique and could be improved by getting information such as geometry (reactor shape, size) or mixing device position and energy provided to the fluid.…”

Hydrodynamic modelling of complex fixed bed geometries in simulated moving bed adsorption processes

“…Other studies have been recently done to fill in the gaps of classical RTD methods, as Smart RTD (Simcik et al 2012) and the reactive-mixing index analysis (Yablonsky et al, 2009). Yet, Claudel et al (2002) and Hocine et al (2008) developed simple hydrodynamic models through the RTD by making some assumptions about the internal information of the systems in study.…”

Automatic reactor model synthesis with genetic programming

“…Two alternative approaches for the direct generation of reactor models worth mentioning have used genetic algorithms (Laquerbe et al 2001) or found a model by simplifying initially complex super-structures (Hocine et al 2008). Both approaches, however, require the measurement of the residence time distribution.…”