Robotics & Machine Learning Daily News2024,Issue(Dec.2) :136-136.

University of Surrey Researchers Have Published New Study Findings on Machine Le arning (Machine learning powered predictive modelling of complex residual stress for nuclear fusion reactor design)

萨里大学的研究人员发表了关于Machine Le Arning(用于核聚变反应堆设计的基于机器学习的复杂残余应力预测模型)的新研究结果

Robotics & Machine Learning Daily News2024,Issue(Dec.2) :136-136.

University of Surrey Researchers Have Published New Study Findings on Machine Le arning (Machine learning powered predictive modelling of complex residual stress for nuclear fusion reactor design)

萨里大学的研究人员发表了关于Machine Le Arning(用于核聚变反应堆设计的基于机器学习的复杂残余应力预测模型)的新研究结果

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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新闻-调查人员讨论人工智能的新发现。根据来自…的消息英国萨里郡,由News Rx编辑报道,该研究称,“容器内聚变组件,组装激光焊接是最有发展前途的焊接技术之一,其制备的材料呈现出明显的非均匀分布残余应力、显微组织和材料性能。残余应力会影响结构关键部件的完整性和寿命"。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews - Investigators discuss new findings in artificial intelligence. According to news originating fromSurrey, United Kingdom, by News Rx editors, the research stated, “Fusion In-vessel components, assembledand mai ntained using laser welding, one of the most promising techniques, exhibit compl ex distributions ofresidual stress, microstructures, and material properties. T hese residual stresses can compromise structuralintegrity and lifespan of criti cal components.”

Key words

University of Surrey/Surrey/United Kin gdom/Europe/Cyborgs/Emerging Technologies/Machine Learning/Nuclear Fusion/Physics

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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