Convegni ATI - Accesso riservato soci CTI

Autore: M. Grigiante, P. Baggio, G. Scalabrin, G. Cristofoli

Collana: CA - 56 - Napoli 2001

Note:
In the study and design of components and systems for refrigeration and heat pumps the prediction of thermodynamic properties of pure refrigerants is required with an high accuracy level over a wide range of pressure and temperature. A very accurate thermodynamic model for a pure fluid can be generally obtained from a wide number of precise experimental data on which setting up specific parameters of complex generalised models or fitting over them the parameters of multiparameter equations of state.
Each fluid can then be represented only after a long and expensive experimental work.
More often the study of the thermodynamic properties of pure fluids are limited to the components of a same family of compounds so that, the development of accurate thermodynamic models, valid only for the fluids of the same family, looks as a slightly simplifying task. Limiting the analysis of the thermodynamic properties to the new generation refrigerant fluid family, an appropriate conformality approach can be deduced, which allows to set up predictive models of high accuracy level on a wide
range of the density, enthalpy and entropy surfaces.

As tested in this work, the utilization of modelling techniques based on a corresponding-states format

can yield interesting advantages and get a high level of accuracy when utilized inside the same group

of conformal fluids.

According to this analysis, new three parameters Corresponding States (CS) models are developed in

particular for saturated and compressed liquid, enthalpy and entropy. These new models are based on

original scaling factors determined only on a limited saturated experimental values or on coexisting

phase conditions. Making use of two accurate dedicated equations as references, the same structure of

the Teja CS model is maintained, substituting the classical acentric factor ? with new defined scaling

parameters.

The reached results are compared with those obtained with the most advanced models available and,

considering their predictive nature, the proposed models can be considered an improved tool for the

advanced technological applications.