Environmental Engineering Reference
In-Depth Information
figuration of Fig. 4 is obviously not the same as the stochastic envi-
ronment of an engine, though it does serve as a building block for a progression of
complexities that lead to relevance to an engine environment. Even for the con-
The con
figuration of Fig. 4 , the same basic mechanisms of combustion present in an engine
exist in the spherical droplet
guration. Its greatest virtue for developing
surrogate fuels is that it is amenable to detailed numerical modeling (Liu et al.
2013a ; Farouk et al. 2013 ; Fahd et al. 2014 ) which allows for a more rigorous test
of the surrogate fuel chemical kinetics with combustion properties that include
vaporization and liquid-phase multicomponent effects. For these reasons, the iso-
lated droplet burning geometry can be viewed as a canonical con
fl
ame con
guration for
liquid fuel combustion.
3 Developing a Surrogate for Liquid Transportation Fuels
Surrogate components are selected with reference to broad chemical classes of the
real fuel (Dooley et al. 2010 , 2012 ; Huber et al. 2010 ; Mueller et al. 2012 ;
Narayanaswamy et al. 2013 ). Once identi
ed, their fractional amounts need to be
determined. A simple approach involves sweeping through compositions to identify
ones where the real and surrogate fuel targets match. This primitive approach looses
its appeal for more than one target or binary system (Avedisian 2008 ).
For a general multicomponent surrogate, constrained optimization or regression
techniques are used to identify the fractional amounts that reduce the difference
between the real and surrogate fuel targets (Dooley et al. 2010 , 2012 ; Narayanaswamy
et al. 2013 ; Mueller et al. 2012 ; Huber et al. 2010 ). There is no universal set of targets
for developing a surrogate. They are linked to the application (Pitz et al. 2007 ).
Targets that have been considered for transportation fuels include various combina-
tions of the hydrogen-to-carbon (H/C) ratio, derived cetane number (DCN), threshold
sooting index (TSI), average molecular weight (MW ave ), liquid density, and advanced
distillation curve to characterize the phase behavior of the fuel. Typically, four targets
are involved in the matching process.
In the next sections, we discuss the performance of several surrogates for liquid
transportation fuels from the perspective of the spherical droplet
guration.
We begin with a brief discussion of the experimental designs for creating
near-spherically symmetric droplet burning conditions. We then present some
experimental results and include discussion of the performance of a surrogate
developed using the optimization process mentioned above. Some results are also
discussed for detailed numerical modeling of the spherical droplet
fl
ame con
fl
ame con
gu-
ration for a biodiesel surrogate.
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