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 38Subbaian Jayabal, S. Rajamuneeswaran, R. Hari Ramprasath · Transactions of the Indian Institute of Metals · 2013
Wear of A380M Aluminum Alloy Under Reciprocating Load
被引 18Md. Aminul Islam, Zoheir N. Farhat · Journal of Materials Engineering and Performance · 2010
Wire and arc additive manufactured steel: Tensile and wear properties
被引 281Christina Viau Haden, Guosong Zeng, F.M. Carter · Additive manufacturing · 2017
此处列出前 3 条
引用本文 9
Machine learning in tribology: A review on framework, case studies, and future perspectives
被引 11Yadong LI, Bing Liu, Zhenghua Chang · Journal of Manufacturing Processes · 2026
A state of the art review of wire arc additive manufacturing (WAAM) - part2: process improvements and industrial applications
被引 7Francesco Lambiase, Phanidra Babu Yanala, Francesco Pace · The International Journal of Advanced Manufacturing Technology · 2026
WAAM 2015–2025: A review of technological advancements, material applications, and emerging directions
被引 7Parveen Kumar, Satish Kumar Sharma, Ratnesh Kumar Raj Singh · International Journal on Interactive Design and Manufacturing (IJIDeM) · 2025
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