Robotics & Machine Learning Daily News2024,Issue(Jan.10) :74-75.

Findings in Machine Learning Reported from Pacific Northwest National Laboratory (Machine Learning Methods for Particle Stress Development In Suspension Poiseuille Flows)

Robotics & Machine Learning Daily News2024,Issue(Jan.10) :74-75.

Findings in Machine Learning Reported from Pacific Northwest National Laboratory (Machine Learning Methods for Particle Stress Development In Suspension Poiseuille Flows)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Investigators discuss new findings in Machine Learning. According to news originatingfrom Richland, Washington, by NewsRx correspondents, research stated, “Numerical simulations are usedto study the dynamics of a developing suspension Poiseuille flow with monodispersed and bidispersedneutrally buoyant particles in a planar channel, and machine learning is applied to learn the evolvingstresses of the developing suspension. The particle stresses and pressure develop on a slower time scalethan the volume fraction, indicating that once the particles reach a steady volume fraction profile, theyrearrange to minimize the contact pressure on each particle.”

Key words

Richland/Washington/United States/North and Central America/Cyborgs/Emerging Technologies/Machine Learning/Pacific Northwest National Laboratory

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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