Robotics & Machine Learning Daily News2024,Issue(Dec.3) :31-32.

Investigators at University of Shanghai for Science and Technology Detail Findin gs in Machine Learning (Thermal-fluid Modeling and Physics-informed Machine Lear ning for Predicting Molten Pool Depth In Single-layer Multi-track Fiber Laser .. .)

上海科技大学的研究人员详细研究了机器学习(热流体建模和物理信息机器学习,用于预测单层多轨道光纤激光器熔池深度。 .)

Robotics & Machine Learning Daily News2024,Issue(Dec.3) :31-32.

Investigators at University of Shanghai for Science and Technology Detail Findin gs in Machine Learning (Thermal-fluid Modeling and Physics-informed Machine Lear ning for Predicting Molten Pool Depth In Single-layer Multi-track Fiber Laser .. .)

上海科技大学的研究人员详细研究了机器学习(热流体建模和物理信息机器学习,用于预测单层多轨道光纤激光器熔池深度。 .)

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摘要

由一名新闻记者-机器人与机器学习日报的工作人员新闻编辑每日新闻-一项关于机器学习的新研究现在可用。根据消息来源在中华人民共和国上海,由NewsRx记者报道,研究表明:“理解”熔池的动态特性及其几何形状的准确预测是激光凝固的关键。熔池深度对s层之间的冶金结合至关重要,但仍难以确定确定。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – A new study on Machine Learning is now available. According to news originatingfrom Shanghai, People’s Republic of Ch ina, by NewsRx correspondents, research stated, “Understandingthe molten pool d ynamics and accurately predicting its geometry are critical aspects of laser cla dding.The molten pool depth is crucial for the metallurgical bond between layer s, yet it remains difficult todetermine.”

Key words

Shanghai/People’s Republic of China/As ia/Cyborgs/Emerging Technologies/Machine Learning/University of Shanghai for Science and Technology

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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