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Prediction of Electropulse-Induced Nonlinear Temperature Variation of Mg Alloy Based on Machine Learning
기계 학습을 활용한 마그네슘 합금의 통전 비선형 온도 예측
Jinyeong Yu, Myoungjae Lee, Young Hoon Moon, Yoojeong Noh, Taekyung Lee
유진영, 이명재, 문영훈, 노유정, 이태경
Korean J. Met. Mater. 2020;58(6):413-422.   Published online 2020 May 19
DOI: https://doi.org/10.3365/KJMM.2020.58.6.413

Abstract
Electropulse-induced heating has attracted attention due to its high energy efficiency. However, the process gives rise to a nonlinear temperature variation, which is difficult to predict using a traditional physics model. As an alternative, this study employed machine-learning technology to predict such temperature variation for the first time. Mg alloy..... More

                           Cited By 2
Enhanced Resistance to Delayed Cracking in Deep-drawn Lean Duplex Stainless Steel: the Role of Residual Stress
Seok Hwan Jung, Taekyung Lee, Seok Weon Song, Young Jin Kwon, Hyung-Gu Kang, Dongchul Chae, Chong Soo Lee
Korean J. Met. Mater. 2017;55(8):544-549.   Published online 2017 Aug 1
DOI: https://doi.org/10.3365/KJMM.2017.55.8.544

Abstract
The delayed cracking behavior of deep-drawn lean duplex stainless steel (LDSS) was investigated, and compared with that of conventional metastable austenitic stainless steels (MASS). Hydrogen charging was performed by electrochemical method, and the hydrogen-charged specimens were subjected to the slow-strain-rate test. Fractures occurred along the phase boundaries in the LDSS,..... More

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