首页|Investigators from Department of Chemical Engineering Have Reported New Data on Machine Learning (Analysis of Cohesive Particles Mixing Behavior In a Twin-paddl e Blender: Dem and Machine Learning Applications)
Investigators from Department of Chemical Engineering Have Reported New Data on Machine Learning (Analysis of Cohesive Particles Mixing Behavior In a Twin-paddl e Blender: Dem and Machine Learning Applications)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Data detailed on Machine Learning have been prese nted. According to news originating from Toronto, Canada, by NewsRx corresponden ts, research stated, “This research paper presents a comprehensive discrete elem ent method (DEM) examination of the mixing behaviors exhibited by cohesive parti cles within a twin-paddle blender. A comparative analysis between the simulation and experimental results revealed a relative error of 3.47%, demon strating a strong agreement between the results from the experimental tests and the DEM simulation.” Financial support for this research came from CGIAR.
TorontoCanadaNorth and Central Ameri caCyborgsEmerging TechnologiesMachine LearningMathematicsPolynomialD epartment of Chemical Engineering
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