Robotics & Machine Learning Daily News2024,Issue(Oct.7) :144-145.

New Machine Learning Study Findings Have Been Reported from Shanghai Jiao Tong U niversity (Machine Learning and Numerical Simulation Research On Specific Energy Consumption for Gradated Coarse Particle Two-phase Flow In Inclined Pipes)

Robotics & Machine Learning Daily News2024,Issue(Oct.7) :144-145.

New Machine Learning Study Findings Have Been Reported from Shanghai Jiao Tong U niversity (Machine Learning and Numerical Simulation Research On Specific Energy Consumption for Gradated Coarse Particle Two-phase Flow In Inclined Pipes)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily NewsInvestigators discuss new findings in Machine Lea rning. According to news reporting out of Shanghai, People's Republic of China, by NewsRx editors, research stated, "In deep-sea mining engineering, accurately predicting the energy required per unit length of pipeline to transport a unit m ass of solids (dimensionless specific energy consumption, DSEC) is crucial for e nsuring energy conservation and efficiency in the project. Based on our previous work, we utilized the machine learning (ML) and the computational fluid dynamic s (CFD)-discrete element method (DEM) method to study the transport characterist ics and flow field variations of gradated coarse particles in inclined pipes (gr adated particles refer to solid particles mixed in specific size and quantity ra tios)."

Key words

Shanghai/People's Republic of China/As ia/Cyborgs/Emerging Technologies/Machine Learning/Mathematics/Numerical Mod eling/Shanghai Jiao Tong University

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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