Validation of the SU2 Flow Solver for Classical Non Ideal Compressible Fluid Dynamics

Abstract

The validation of SU2 for modelling classical non-ideal
compressible fluid dynamics will advance the research into efficient ORC
turbomachinery design. This study determines the validity of the
two-dimensional flow solver for predicting the isentropic expansion of Siloxane
MM through a converging-diverging nozzle using compressible Euler equations,
adiabatic flow, and the Peng-Robinson equation of state. Two flows with an
inlet stagnation temperature of 525K were considered: an expansion from 18.4
bar to 2.1 bar, and an expansion from 11.1 bar to 1.3 bar.  Mach number along the centreline and static
pressure along the nozzle surface were used as the direct system response
quantities used in the analysis. Experimental data and uncertainty came from
the ORCHID, model input uncertainty was quantified using stochastic
collocation, and the numerical uncertainty was calculated using the Richardson
extrapolation. The conclusions were based on a hybrid of the ASME V&V 20 and
Real Space validation metrics, with a novel Engineering Response Quantity
analysis based on determining the effects of system uncertainty on performance
parameters. The studied SU2 model provide valid predictions for Mach number,
and invalid predictions for static pressure. The largest error is in the kernel
region, where E_Mach=0.111 and E_Pressure = 112 kPa. Mach
number has a maximum simulation uncertainty of 2% at the transition to the
reflex region. Pressure has a maximum uncertainty of 3% at the throat. In the
context of turbomachinery the simulation uncertainties translate to +/-0.001
and +/-0.02 on a loss coefficient calculated across a theoretical normal shock,
for Mach and pressure respectively. Considering +/-0.01 as significant for a
loss coefficient the Mach uncertainty is negligible. Input uncertainty is the
largest component of the pressure uncertainty, while experimental uncertainty
is dominant for Mach. The input parameters which provide the highest
contribution to the uncertainty are critical pressure and temperature. The
developed infrastructure can be used for expanding the validation of SU2 to
different flow cases.