ABSTRACT: Spectrally-integrated Raman scatter imaging for quantitative mixing measurements in methanol sprays under elevated pressure and temperature
This study presents the development and application of a Raman scatter imaging diagnostic for quantitative characterization of fuel–air mixing in evaporative methanol sprays under high-pressure, high-temperature conditions. Traditional diagnostics such as Rayleigh scattering and laser-induced fluorescence (LIF) face significant limitations when applied to fluids featuring low scattering cross-sections or non-fluorescent properties. To address these challenges, we implemented a spectrally-integrated Raman imaging technique using a single high-speed CMOS camera and a pulsed, burst-mode Nd:YAG laser. The method captured Raman scattered signals from both fuel and ambient species, enabling time-resolved mapping of the mixture fraction field without requiring complex absolute calibration. An in-situ calibration strategy was employed to relate Raman intensity ratios to fuel concentration, simultaneously accounting for the various species’ cross-sections and for spectral variations in optical efficiency. The diagnostic demonstrated quantitative measurements of mixture fraction at high-speed in evaporative methanol sprays, with performance on par with similar measurements using Rayleigh scattering under optimal conditions. The technique offers a robust and practical alternative to conventional diagnostics and provides valuable validation data for modeling fuel sprays in advanced combustion systems.
BIO: Dr. Lyle Pickett
Dr. Lyle Pickett is a Senior Scientist at Sandia National Laboratories, where he has been employed since 2000. His research expertise is in optical diagnostics of spray combustion in chambers that provide engine-relevant conditions at high pressure and temperature. He founded and leads an international experimental and modeling collaboration to share spray combustion datasets online through the Engine Combustion Network (https://ecn.sandia.gov), encouraging the improvement of computational codes used for engine design. The research enables engines with increased efficiency, reduced emissions, and the use of low carbon-intensity fuels.
