Developing Surrogates for Liquid Transportation Fuels: The Role of Spherically Symmetric Droplet Combustion - Novel Combustion Concepts for Sustainable Energy Development - page 375

component hydrocarbon (e.g., n-heptane = #2 diesel fuel (Wang et al. 2013 )or
combining the kinetic mechanism of methyl butanoate with heptane for a soybean
biodiesel (Lee et al. 2013 ).
A step-up from a single component hydrocarbon is a binary blend which have
been used as surrogates (i.e., a n-dodecane/iso-octane = a multicomponent paraf-

c mixture (mole) fraction of [i.e., 0.519/0.481 (Dooley et al.
2012 )]). Three and four component blends have been successfully developed for
some transportation fuels (Dooley et al. 2010 , 2012 ). Higher-order surrogates have
been formulated with eight components to represent a certi

finic jet fuel in a speci

cation gasoline and
reference diesel fuel (Mueller et al. 2012 ). It is clearly advantageous to have a
surrogate with as few components as possible to enable predictions of physical and
thermodynamic properties with minimal effort.
This paper reviews the development of surrogates from the perspective of liquid
fuels and the role that droplet combustion dynamics can play in this process.
Experimental results are presented that show the ef cacy of a simpli ed droplet

burning con guration for evaluating the performance of gasoline and jet fuel. Some

results related to detailed numerical simulation of droplet combustion of biofuel
surrogates are also included.

2 The Canonical Configuration for Liquid Fuel
Combustion

Developing a surrogate involves several tasks: (1) determining the broad chemical
classes of the real fuel; (2) selecting the surrogate components; (3) calculating the
fractional amounts of the surrogate components through a process that minimizes
the difference between selected combustion targets of the surrogate and real fuel
(e.g., by various optimization methods (Narayanaswamy et al. 2013 ; Dooley et al.
2010 , 2012 )); (4) comparing combustion properties of the surrogate to the real fuel
as measured in a suitable combustion con guration; and (5) assessing the ef cacy

of the surrogate to produce high fidelity predictions of combustion properties

measured in a suitable combustion con guration.

Considering combustion properties pertinent to liquid fuels, at one extreme is the
stochastic environment of a piston engine (Fig. 3 ), with its swirling and turbulent
motion, spray dynamics, and radiation.
Ab initio models for engines do not exist. The KIVA code (Amsden 1999 ) is one
of the more advanced solvers of the transport equations for in-cylinder combustion
dynamics that includes models for spray injection. Nonetheless, detailed numerical
modeling of spray combustion is also beyond current capabilities (i.e., when
including, simultaneously, detailed combustion kinetics, radiative and unsteady
effects, droplet formation, evaporation). This leaves processes at the level of indi-
vidual droplets to consider. Here too, there are signi

cant challenges.