首页|Researchers from Beihang University Report Findings in Machine Learning (Develop ment of a Novel Continuum Damage Mechanicsbased Machine Learning Approach for V ibration Fatigue Assessment of Fastener Clip Subjected To High-frequency Vibrati on)
Researchers from Beihang University Report Findings in Machine Learning (Develop ment of a Novel Continuum Damage Mechanicsbased Machine Learning Approach for V ibration Fatigue Assessment of Fastener Clip Subjected To High-frequency Vibrati on)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on Machine Learn ing have been published. According to news reporting originating in Beijing, Peo ple’s Republic of China, by NewsRx journalists, research stated, “This paper pro poses a novel method based on continuum damage mechanics (CDM) and machine learn ing (ML) models to evaluate the vibration fatigue behavior of W1-type railway fa stener clips subjected to high-frequency vibration. Firstly, static and fatigue tests are conducted on 60Si2Mn spring steel to acquire elastic modulus, tensile strength, and P-S-N curves.” Financial supporters for this research include National Natural Science Foundati on of China (NSFC), China Academy of Railway Sciences Co., Ltd..
BeijingPeople’s Republic of ChinaAsi aCyborgsEmerging TechnologiesMachine LearningBeihang University
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