首页|New Data from East China University of Science and Technology Illuminate Findings in Machine Learning [Microstructural Featuredriven Machine Learning for Predicting Mechanical Tensile Strength of Laser Powder Bed Fusion (L-pbf) Additively ...]
New Data from East China University of Science and Technology Illuminate Findings in Machine Learning [Microstructural Featuredriven Machine Learning for Predicting Mechanical Tensile Strength of Laser Powder Bed Fusion (L-pbf) Additively ...]
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NETL
NSTL
Elsevier
New research on Machine Learning is the subject of a report. According to news reporting from Shanghai, People’s Republic of China, by NewsRx journalists, research stated, “The rapid solidification inherent in laser powder bed fusion (L-PBF) additive manufacturing (AM) introduces segregation phenomena and formation of non-equilibrium phases in duplex titanium alloy components, thereby impeding their suitability for high-reliability engineering applications. Consequently, heat treatment becomes indispensable for optimizing both the microstructure and mechanical properties to meet application requirements.” Funders for this research include National Natural Science Foundation of China (NSFC), National Key R&D Program of China, Fundamental Research Funds for the Central Universities in China.
ShanghaiPeople’s Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine LearningEast China University of Science and Technology
NETL
NSTL
Elsevier
