首页|Findings on Machine Learning Discussed by Investigators at Lawrence Livermore Na tional Laboratory (Explosively Driven Richtmyer-meshkov Instability Jet Suppress ion and Enhancement Via Coupling Machine Learning and Additive Manufacturing)
Findings on Machine Learning Discussed by Investigators at Lawrence Livermore Na tional Laboratory (Explosively Driven Richtmyer-meshkov Instability Jet Suppress ion and Enhancement Via Coupling Machine Learning and Additive Manufacturing)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators discuss new findings in Machine Learning. According to news reportingfrom Livermore, California, by New sRx journalists, research stated, “The ability to control the behavior offluid instabilities at material interfaces, such as the shock-driven Richtmyer-Meshkov instability, is a grandtechnological challenge with a broad number of applicat ions ranging from inertial confinement fusionexperiments to explosively driven shaped charges. In this work, we use a linear-geometry shaped chargeas a means of studying methods for controlling material jetting that results from the Richt myer-Meshkovinstability.”
LivermoreCaliforniaUnited StatesNo rth and Central AmericaCyborgsEmerging TechnologiesMachine LearningLawre nce Livermore National Laboratory
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