Surrogate Mixtures Developed to Represent Real Fuel Properties

Capability Title Surrogate mixtures developed to represent real fuel properties
Laboratory Lawrence Livermore National Laboratory (LLNL)
Capability experts Scott Wagnon (LLNL), Russell Whitesides (LLNL)
Description Surrogate mixtures are needed to represent real fuels in engine simulations and engine experiments. A surrogate optimizer tool is used to target over 30 properties and metrics to match real fuels with surrogate fuel mixtures. Surrogates for gasoline, diesel, and their mixtures with new fuels are developed to match desired fuel properties including RON, MON, cetane number, distillation curve, H/C ratio, density, carbon types, chemical classes, PMI and yield-sooting index (YSI). RON and MON are predicted in the surrogate optimizer using a chemical kinetic model for the surrogate mixture and machine learning.
Limitations Kinetic models for components in the surrogate mixture are needed RON and MON prediction.
Unique aspects
Availability Surrogate fuel development capabilities are limited by availability of staff.
Citations/references 1. Scott Wagnon, “Development of an Optimized Gasoline Surrogate Formulation for PACE Experiments and Simulations” 2020 DOE VTO Merit Review, slide 10,
2. C. L. Druzgalski, S. Lapointe, R. Whitesides and M. J. McNenly, “Predicting octane number from microscale flame dynamics,” Combust. Flame 208 (2019) 5-14.
3. G. Fioroni, L. Fouts, J. Luecke, D. Vardon, N. Huq, E. Christensen, X. Huo, T. Alleman, R. McCormick, M. Kass, E. Polikarpov, G. Kukkadapu and R. A. Whitesides, “Screening of Potential Biomass-Derived Streams as Fuel Blendstocks for Mixing Controlled Compression Ignition Combustion,” SAE International, (2019).