Investigators from University of South Carolina Target Machine Learning (Explain able and Reduced-feature Machine Learning Models for Shape and Drag Prediction o f a Freely Moving Drop In the Sub-critical Weber Number Regime)

Robotics & Machine Learning Daily News2024，Issue(Dec.16) ：59-60.

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Investigators from University of South Carolina Target Machine Learning (Explain able and Reduced-feature Machine Learning Models for Shape and Drag Prediction o f a Freely Moving Drop In the Sub-critical Weber Number Regime)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Current study results on Machine Learn ing have been published. According tonews reporting originating from Columbia, South Carolina, by NewsRx correspondents, research stated,“Accurately predictin g the shape and drag of a moving drop is crucial in many spray applications. However, due to the complex interaction between the drag force and drop shape defor mation, accurateprediction of drop shape and drag from Computational Fluid Dyna mics (CFD) simulation requires largecomputational resources and time.”

Key words

Columbia/South Carolina/United States/North and Central America/Computational Fluid Dynamics/Cyborgs/Emerging Tech nologies/Fluid Mechanics/Machine Learning/University of South Carolina

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出版年

2024

Robotics & Machine Learning Daily News

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