首页|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)
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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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)."
ShanghaiPeople's Republic of ChinaAs iaCyborgsEmerging TechnologiesMachine LearningMathematicsNumerical Mod elingShanghai Jiao Tong University
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