摘要
由一名新闻记者兼机器人与机器学习每日新闻编辑每日新闻-关于人工智能ce的详细数据已经呈现。根据NewsRx编辑在洛斯阿拉莫斯国家实验室的新闻报道，研究表明，“在添加剂制造(AM)中，诸如小孔孔等工艺缺陷很难预测，影响了AM生产材料的质量和完整性。因此，通过使用声发射等被动测量方法训练机器学习(ML)模型，有相当大的效果来预测这些工艺缺陷。”这项研究的财政支持者包括Lanl Ldrd；科学办公室；Ems L，PNL；Nsf；LNL。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Data detailed on artificial intelligen ce have been presented. According to news reporting out of the Los Alamos Nation al Laboratory by NewsRx editors, research stated, “In additive manufacturing (AM ), process defects such as keyhole pores are difficult to anticipate, affecting the quality and integrity of the AM-produced materials. Hence, considerable effo rts have aimed to predict these process defects by training machine learning (ML ) models using passive measurements such as acoustic emissions.” Financial supporters for this research include Lanl Ldrd; Office of Science; Ems l, Pnnl; Nsf; Llnl.
NETL
NSTL