Effects of fuel and soot characteristics on the inception and development of contrails
Amitesh Roy, Rajat Sawanni, Yash T. Rajan, Isaac Jahncke, Taye Taddesse, Clinton P. T. Groth, Swetaprovo Chaudhuri, Ömer L. Gülder
Abstract
Fundamental questions related to the roles of fuel type, combustion parameters, and turbulence transport interactions in the inception and growth of contrails have remained intractable in remote sensing and in-flight measurements. Consequently, we developed a novel laboratory-scale facility for studying the inception, growth and persistence of contrails for aircraft-relevant conditions. The exhaust gas generated using an inverted co-flow soot generator at a set of global equivalence ratios for two fuels - ethylene and propane is supplied to the contrail tunnel, which then mixes with an ambient flow emulating long-haul aircraft cruise conditions (20.8 kPa and 190 K). Detailed soot characterization using a scanning mobility particle sizer and transmission electron microscopy is coupled with measurements of instantaneous and averaged scattering intensities from the generated contrails. The experimental results are complemented by numerical simulations of the contrail tunnel using solutions of the Favre-averaged Navier-Stokes (FANS) equation and a two-equation model for handling particulate matter, including soot and ice. Results show, for the first time, the cross-section of a contrail, and the interaction of turbulent mixing and microphysical growth scales involved in ice nucleation across the shear layers. The average scattering cross sections of contrails increase with equivalence ratio, due to higher soot number concentrations and water vapor content. Comparisons between ethylene and propane exhausts indicate that the scattering propensity of contrails is more sensitive to exhaust water vapor content than to soot concentrations. Finally, depolarization measurements are used to show asphericity in ice crystal habits. Thus, our study present a unique window into contrail formation, theoretical modeling and simulation.
