  In global efforts to reduce harmful greenhouse gas emissions from the
transport sector, novel bio-hybrid liquid fuels from renewable energy and
carbon sources can be a major form of energy for future propulsion systems due
to their high energy density. A fundamental understanding of the spray and
mixing performance of the new fuel candidates in combustion systems is
necessary to design and develop the fuels for advanced combustion concepts. In
the fuel design process, a large number of candidates is required to be
screened to arrive at potential fuels for further detailed investigations. For
such a screening process, three-dimensional (3D) simulation models are
computationally too expensive and hence unfeasible. Therefore, in this paper,
we present a fast, reduced-order model (ROM) for inert sprays. The model is
based on the cross-sectionally averaged spray (CAS) model derived by Wan (1997)
from 3D multiphase equations. The original model was first tested against a
wide range of conditions and different fuels. The discrepancies between the CAS
model and experimental data are addressed by integrating state-of-the-art
breakup and evaporation models. A transport equation for vapor mass fraction is
proposed, which is important for evaporation modeling. Furthermore, the model
is extended to consider polydisperse droplets by modeling the droplet size
distribution by commonly used presumed probability density functions, such as
Rosin-Rammler, lognormal, and gamma distributions. The improved CAS model is
capable of predicting trends in the macroscopic spray characteristics for a
wide range of conditions and fuels. The computational cost of the CAS model is
lower than the 3D simulation methods by up to 6 orders of magnitude depending
on the method. This enables the model to be used not only for the rapid
screening of novel fuel candidates, but also for other applications, where ROMs
are useful.
