首页|Findings from Wuhan University in Machine Learning Reported (A Reality-augmented Adaptive Physics Informed Machine Learning Method for Efficient Heat Transfer P rediction In Laser Melting)
Findings from Wuhan University in Machine Learning Reported (A Reality-augmented Adaptive Physics Informed Machine Learning Method for Efficient Heat Transfer P rediction In Laser Melting)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Investigators publish new report on Ma chine Learning. According to news reportingout of Wuhan, People’s Republic of C hina, by NewsRx editors, research stated, “Physics informed neuralnetwork (PINN ) method is proposed to alleviate problems in many science and engineering scena rioswhen data-collection is difficult, or traditional numerical calculations ar e lack of convenience becausemore time-consuming numerical calculations are req uired whenever one or more parameters of the processis changed. However, for ad vanced manufacturing processes like laser melting (LM), a basis of lasermetal a dditive manufacturing, involve many complex physical phenomena (e.g. melting, co nvection,solidification, vaporization and interface evolution), the full equati ons of which are too complex to besolved by current PINN.”
WuhanPeople’s Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine LearningWuhan University
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