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Using uncertainty quantification and machine learning techniques to study the evolution of odor capture

Description: Data management plan for the research grant, "Using uncertainty quantification and machine learning techniques to study the evolution of odor capture." This research proposes the application of uncertainty quantification (UQ) and machine learning (ML) to a CFD model of odor capture to understand the role of hair-array morphology, kinematics, and fluid environment in odor capture. The combination of CFD modeling and UQ&ML techniques can map out the performance space under which these chemosensor… more
Date: 2022-04-01/2025-03-31
Creator: He, Yanyan & Waldrop, Lindsay D.
Item Type: Refine your search to only Text
Partner: UNT College of Science
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