研究论文
Advanced ensemble machine learning and response surface methodology for optimizing and predicting tribological performance of CMT-WAAM fabricated Al5356 alloy
M.K. Nagarajan, Manikandan Arumugam
SRM Institute of Science and Technology
来源International Journal on Interactive Design and Manufacturing (IJIDeM)
年份2025
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工程Additive Manufacturing Materials and Processes
Metal and Thin Film Mechanics · Advanced materials and composites
参考文献 65
Artificial Neural Network Modeling of Mechanical Properties of Calcium Carbonate Impregnated Coir-Polyester Composites
被引 38S. Jayabal, S. Rajamuneeswaran, R. Ramprasath · Transactions of the Indian Institute of Metals · 2013
Wear of A380M Aluminum Alloy Under Reciprocating Load
被引 18Md. Aminul Islam, Zoheir Farhat · Journal of Materials Engineering and Performance · 2010
Wire and arc additive manufactured steel: Tensile and wear properties
被引 279Christina V. Haden, Guosong Zeng, F.M. Carter · Additive manufacturing · 2017
此处列出前 3 条
引用本文 8
WAAM 2015–2025: A review of technological advancements, material applications, and emerging directions
被引 5Parveen Kumar, Satish Kumar Sharma, Ratnesh Kumar Raj Singh · International Journal on Interactive Design and Manufacturing (IJIDeM) · 2025
Machine learning in tribology: A review on framework, case studies, and future perspectives
被引 5Yadong LI, Bing Liu, Zhenghua Chang · Journal of Manufacturing Processes · 2026
Abrasive waterjet machining characteristics of nylon 6 polymer matrix reinforced with seashell biofillers: experimental analysis, optimization, and prediction
被引 4P. Vasanthkumar, Gopinath Perumal, B. Deepanraj · International Journal on Interactive Design and Manufacturing (IJIDeM) · 2025
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