Non-Intrusive Thermo-Structural Characterization of Water-Ice Clouds

Prime Photonics (Prime), in conjunction with Virginia Tech (VT), are proposing a novel approach to quantitative detection of airborne ice crystals and supercooled water droplets. The envisioned instrumentation system, dubbed the Temperature and Phase of Water via AI-based Detection using Raman scatteringmdash;or TAP WADR,nbsp; builds upon recent breakthroughs at Virginia Tech (VT) for incorporating machine learning-based classification and regression models for non-spherical particle sizing, while recognizing the value of spontaneous Raman scattering spectroscopy for temperature and phase measurements.In Phase I, Prime and VT will develop a library for both water structure/size and temperature and incorporate it into VTrsquo;s existing AI/machine learning architecture. A single-particle proof-of-concept experimental apparatus will be developed to characterize supercooled water droplets, and at least two forms of ice that will be used for AI model test and validation. Finally, a concept for TAP WADR system integration will be developed for a NASA facility.In Phase II, the TAP WADR system will be scaled up to perform thermo-structural measurements across a 4+ foot water-ice cloud test section. In the first year, risk reduction testing will occur at a VT wind tunnel. In the second year of Phase II, the instrument will be transitioned to a Glenn icing facility to validate performance for mixed phase icing clouds.