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A Fundamental Equation of State for 2-propanol (C3H8O) in the Extended Equation of State Format

J. Phys. Chem. Ref. Data 38, 127 (2009); doi:10.1063/1.3112608

Published 13 May 2009

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G. Scalabrin and P. Stringari
Dipartimento di Fisica Tecnica, Università di Padova, via Venezia 1, I-35131 Padova, Italy
An innovative method for the regression of a fundamental equation of state of a pure fluid was recently proposed. This technique, called an extended equation of state, adopts a framework similar to the extended corresponding states method but uses a cubic equation for the target fluid instead of the equation of state for the reference fluid, and shape functions are expressed through a multilayer feedforward neural network. The use of a neural network assures very high flexibility of the functional forms to be regressed, allowing the resulting model to represent the thermodynamic properties of a pure fluid with an accuracy comparable to that attained by state-of-the-art multiparameter equations of state. The technique is applied here to 2-propanol to derive a dedicated equation of state in a heuristic mode directly from the available experimental data. The majority of the data cover the range of temperatures from 280  to  600  K and pressures up to 50  MPa; this is also the validity range of the developed equation. For the present case, primarily due to the unfavorable situation of the data, all of the available thermodynamic properties have been used for the regression procedure in order to get the expected accuracy. The model has been validated with data for coexistence states, density, isobaric and isochoric heat capacities, and speed of sound. The obtained results are satisfactory because the proposed equation of state represents the available data within their mean experimental uncertainties. ©2009 American Institute of Physics
History: Received 15 January 2009; accepted 11 March 2009; published 13 May 2009
Permalink: http://link.aip.org/link/?JPCRBU/38/127/1
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KEYWORDS and PACS

Keywords
PACS
  • 64.30.Jk
    Equations of state of nonmetals
  • 84.35.+i
    Neural networks (circuit implementations)
  • YEAR: 2009

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0047-2689 (print)   1529-7845 (online)
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