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Overview of common thermophysical property modelling approaches for cryogenic fluid simulations at supercritical conditions.

Author(s) : MADANA GOPAL J. V., MORGAN R., SERCEY G. de, VOGIATZAKI K.

Type of article: Periodical article, Review

Summary

Computational Fluid Dynamics (CFD) frameworks of supercritical cryogenic fluids need to employ Real Fluid models such as cubic Equations of State (EoS) to account for thermal and inertial driven mechanisms of fluid evolution and disintegration. Accurate estimation of the non-linear variation in density, thermodynamic and transport properties is required to computationally replicate the relevant thermo and fluid dynamics involved. This article reviews the availability, performance and the implementation of common Real Fluid EoS and data-based models in CFD studies of supercritical cryogenic fluids. A systematic analysis of supercritical cryogenic fluid (N2, O2 and CH4) thermophysical property predictions by cubic (PR and SRK) and non-cubic (SBWR) Real Fluid EoS, along with Chung’s model, reveal that: (a) SRK EoS is much more accurate than PR at low temperatures of liquid phase, whereas PR is more accurate at the pseudoboiling region and (b) SBWR EoS is more accurate than PR and SRK despite requiring the same input parameters; however, it is limited by the complexity in thermodynamic property estimation. Alternative data-based models, such as tabulation and polynomial methods, have also been shown to be reliably employed in CFD. At the end, a brief discussion on the thermophysical modelling of cryogenic fluids affected by quantum effects is included, in which the unsuitability of the common real fluid EoS models for the liquid phase of such fluids is presented.

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Pages: 30 p.

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  • Original title: Overview of common thermophysical property modelling approaches for cryogenic fluid simulations at supercritical conditions.
  • Record ID : 30031244
  • Languages: English
  • Subject: Technology
  • Source: Energies - vol. 16 - n. 2
  • Publishers: MDPI
  • Publication date: 2023/01
  • DOI: http://dx.doi.org/https://doi.org/10.3390/en16020885

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