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Effective Drag Coefficient Prediction On Single-View 2d Images Of Snowflakes, Cameron Hudson
Effective Drag Coefficient Prediction On Single-View 2d Images Of Snowflakes, Cameron Hudson
Graduate College Dissertations and Theses
The drag coefficient of snowflakes is an crucial particle descriptor that can quantify the relationships with the mass, shape, size, and fall speed of snowflake particles. Previous studies has relied on estimating and improving empirical correlations for the drag coefficient of particles, utilizing 3D images from the Multi-Angled Snowflake Camera Database (MASCDB) to estimate snowflake properties such as mass, geometry, shape classification, and rimming degree. However, predictions of the drag coefficient with single-view 2D images of snowflakes has proven to be a challenging problem, primarily due to the lack of data and time-consuming, expensive methods used to estimate snowflake shape …