Composition Analysis and
Viscosity Prediction of Complex
Fuel Mixtures Using a Molecular-Based Approach
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Abstract
The automobile industry currently faces the challenge
of developing
a new generation of diesel motor engines that satisfy both increasingly
stringent emission regulations and reduces specific fuel consumption.
The performance of diesel engines, seen in terms of emissions and
specific fuel consumption, generally improves with increasing fuel-injection
pressure. The design of the next generation of diesel fuel injection
systems requires the knowledge of the thermophysical properties, in
particular viscosity, of a wide-type of diesel fuels at pressures
up to 300 MPa or more. The objective of the present work is to demonstrate
that it is possible to predict the viscosity of any petroleum-based
diesel fuel, using, exclusively, its molar fraction distribution as
provided by multidimensional gas chromatography techniques. The precise
knowledge of the fuel chemical constituents allows the understanding
of the influence of the different hydrocarbon families on the fluid
viscosity by means of molecular dynamics simulations. The accuracy
of the Anisotropic United Atom force-field was tested and was found
to be in agreement with experimental viscosities obtained with a new
vibrating wire device at different temperatures and pressures up to
300 MPa. Finally, the experimental and simulated viscosities have
been compared with improved group contribution method that has been
coupled with gas chromatography experimental measurements for a viscosity
prediction that was estimated to be of less than 18% of mean absolute
deviation