Published December 2018 | Version v1
Journal article

Simulation of transcritical fluid jets using the PC-SAFT EoS

  • 1. School of Mathematics, Computer Science & Engineering, Department of Mechanical Engineering & Aeronautics, City University London, Northampton Square, EC1V 0HB (United Kingdom)
  • 2. Department of Chemical and Life Science Engineering, 601 West Main Street, Richmond, VA 23284 (United States)

Description

Highlights: • Coupling of the PC-SAFT and the Navier-Stokes equations. • Conservative and quasi-conservative formulations. • Advection test cases and shock tube problems. • Planar two-dimensional simulations of supercritical and transcritical jets. The present paper describes a numerical framework to simulate transcritical and supercritical flows utilising the compressible form of the Navier–Stokes equations coupled with the Perturbed Chain Statistical Associating Fluid Theory (PC-SAFT) equation of state (EoS); both conservative and quasi-conservative formulations have been tested. This molecular model is an alternative to cubic EoS which show low accuracy computing the thermodynamic properties of hydrocarbons at temperatures typical for high pressure injection systems. Liquid density, compressibility, speed of sound, vapour pressures and density derivatives are calculated with more precision when compared to cubic EoS. Advection test cases and shock tube problems are included to show the overall performance of the developed framework employing both formulations. Additionally, two-dimensional simulations of nitrogen and dodecane jets are presented to demonstrate the multidimensional capability of the developed model.

Availability note (English)

Available from http://dx.doi.org/10.1016/j.jcp.2018.07.030

Additional details

Identifiers

DOI
10.1016/j.jcp.2018.07.030;
PII
S0021999118304911;

Publishing Information

Journal Title
Journal of Computational Physics (Print)
Journal Volume
374
Journal Page Range
p. 444-468
ISSN
0021-9991
CODEN
JCTPAH

Optional Information

Copyright
Copyright (c) 2018 Elsevier Inc. All rights reserved.