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Content archived on 2024-04-16

Advanced flow modelling for industrial applications


To assess the utility of current Computational Fluid Dynamic (CFD) approaches, appropriately amended and elaborated, to predict the performance of spray dryers and packed bed adsorbers/regenerators.

CFD is now an important tool for the design and development of equipment in the fields of mechanical, nuclear and aeronautical engineering. It has great potential for application in the process industries, but so far the number of applications in this field has been relatively limited. The primary field of application has been the design of power generation furnaces and process heaters.

The study focusses on two areas of process engineering which have been identified as priorities, namely spray dryers and packed beds. CFD is applied to these areas to assess the utility of this approach to predict their performance for improved energy efficiency.

More specifically, the study combines the acquisition of good experimental data and the improvement of mathematical models in order to develop sound computational tools for spray dryers and adsorbers which would be useful for the prediction of performance and the development of improved designs.

Spray dryers

The study contains experimental work to be carried out at the University of Erlangen and the IST, and a combined effort on modelling involving the groups mentioned above and those at Cranfield and Imperial College.

Adsorbers / Regenerators

The work to performed contributes to the overall objectives of the project by :

improving specific models, such as the porosity and wall models;
predicting micro-scale effects in industrial adsorbers;
simulating numerically heat and mass transfer in adsorbers (regenerators under steady-state and transient conditons;
validating the numerical results obtained by direct comparison with experimental measurements from literature and industry and with analytical solutions.


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Call for proposal

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EU contribution
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9,Heroon Polytechniou 9
15780 ATHENS

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Total cost
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Participants (7)