Ziel
In recent years several studies have demonstrated the great potential of the supercritical fluid technology (SFT). The design of these process requires simulation software whose reliability depends mainly on the knowledge of the behavior of the chemical mi xture. The real behavior depends on chemical and thermodynamic properties continuously changing during the unit operations. They can then be reliably represented only by continuous thermodynamic models as an equations of state (EoS). To generate these EoS a large number of experimental data need to be produced which requires very time consuming procedures. The main object of this project is to develop a new method to obtain an EoS for mixtures by only a minimum experimental effort. This will be achieved by integrating inside a cubic EoS a Neural Networks (NN) function approximator trained on selected data sets of the mixture. The required data sets can be obtained only at the qualified highly thermodynamic laboratory of the host Institution. This tool is ad dressed to the following urgent needs: to improve thermodynamics properties predictive methods by involving new fluids as alternative to the traditional CO2, to optimize the unit operations, to achieve the optimal design by minimizing the total energy cost . These aspects are still the effective limiting factors to the diffusion of the SFT technology in spite of the growing number of applications and the wealth of experimental works available. By this model the potentiality of the SFT can investigate strateg ic applications as extractive processes, treatment of wastes, energetic applications. This requires further research efforts enlarging the applicant expertise for a long term benefit. Considering the very outstanding level of the host partner and the appli cant scientific experience, the development of this project, besides meeting one of the priority areas of the FP6 enhances the strategic knowledge and competitiveness of the EU on SFT in the years to come
Wissenschaftliches Gebiet
Schlüsselbegriffe
Aufforderung zur Vorschlagseinreichung
FP6-2002-MOBILITY-5
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