S. LAUGIER ET AL.
Copyright © 2011 SciRes. OJPC
353.11 2.8887 906.09 357.02 3.0532 807.50 362.88 3.47 691.30 362.88 9.9964 1107.95
and 3 of original paper [3]. Other trustable data (about
10500 over the 48000 original raw data) are available
from corre s ponding author: laugier@enscbp.fr.
4. Conclusions
Through the present study we have pointed out the im-
portance of reliable and accurate data and the usefulness
of simple data consistency tests. These simple tests jus-
tify the development of various performing techniques
such as tho s e based on neur a l ne twork.
Density of gases and gas mixtures must tend to zero
when pressure tends to zero and additionally the virial
law must be followed.
Neural network based approach presently used to as-
sess the quality of experimental hexafluoropropylene
densities gives encouraging results.
For supercritical HFP only one isotherm has been
conserved from previous work [3]. Due to high thermal
effects in the vicinity of critical po int, it would have been
certainly necessary to be more careful and more patient
recording the data (very small pressure changes are re-
quested as a function of time).
Finally, we conclude neural network modeling is
worth in the assessment of data consistency.
As far as high pressure vibrating tube densimeters are
used, vapor densities at very low pressures are better
determined through extrapolation of higher pressure val-
ues using virial equation of state.
Only trustable densities for the three vapor, liquid and
supercritical physical states have been reported herein.
Supporti ng Informa tion Availab l e:
Density values of HFP at various temperatures and in
its various states: vapor, liquid and supercritical. This
material is available upon demand to corresponding au-
thor: laugier@enscbp.fr. It has to be used preferably to
the material presented in Coquelet et al.’s paper [3] that
unfortunately contains inaccurate and erroneous data.
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