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22대 대한민국 국회 국회정보길라잡이 국회의원검색
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In this study, fracture toughness with the base metal of 9% Ni steel, a cryogenic steel, was evaluated under conditions without hydrogen charging (WO-H) and with hydrogen charging (W-H). Hydrogen charging was performed using an electrochemical cathodic charging method in a electrolyte of 3% NaCl + 0.3% NH4SCN at 19℃ with a current density of 50 A/m². Fracture toughness was assessed at -80℃, -100℃, -130℃, and -160℃ using CTOD (Crack Tip Opening Displacement) tests. The results for WO-H indicated a decrease in fracture toughness values with decreasing temperature, while the results for W-H showed an increase in fracture toughness values as the temperature decreased. In addition, the fracture surfaces and fracture toughness of WO-H and W-H became increasingly similar as the temperature decreased, as observed through scanning electron microscopy (SEM). At -80℃, there was a significant difference in fracture toughness between the WO-H and W-H conditions. WO-H was influenced only by the low temperature, whereas W-H was affected by both low temperature and hydrogen, showing combined effects that led to a decrease in fracture toughness due to hydrogen embrittlement. However, at -160℃, the fracture toughness values for both WO-H and W-H conditions were nearly identical. This suggests that the temperature effect on fracture toughness reduction is greater than hydrogen embrittlement at very low temperatures.

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Review on welding process monitoring based on deep learning using time-series data = 시계열 데이터를 이용한 딥러닝 기반 용접 공정 모니터링 리뷰 Jaeheon Lee, Hwani Hwang, Taesoon Jeong, Dukyong Kim, Jeongbin Ahn, Gyuchan Lee, Seung Hwan Lee p. 333-344, [1-12]

다중 센서 기반 딥러닝 모델을 이용한 6000계열 알루미늄 합금의 고온 균열 진단 = Detection of hot cracking for 6000 series aluminum alloys using a multi-sensor based deep learning model 김건민, 이재헌, 이승환 p. 345-356

Review of recent additive manufacturing and welding research with application of physics-informed neural networks = 물리 기반 인공 신경망의 적층 및 용접 연구 적용 Taehwan Ko, Heuisu Kim, Yeoungcheol Shin, Dukyong Kim, Young Hoon Lee, Jinsu Hong, Seung Hwan Lee p. 357-365, [1-9]

590 MPa급 고강도강과 6xxx계 알루미늄 합금의 Flow Drilling Screw 접합품질 예측 알고리즘 개발 = Quality prediction algorithm for flow drilling screw joining of 590 MPa high-strength steel and 6xxx series aluminum alloy 최유리, 김동윤, 장준명, 유지영, 이승환 p. 366-377

Bonding properties of package-on-package stack interconnection using by 150 ㎛ height copper posts = 1150 ㎛ 높이 구리기둥 적용 패키지-온-패키지 적층 접합 특성 Mi-Song Kim, So-Hee Hyun, Joo Young Bae, Won Sik Hong p. 378-387, [1-10]

Thermal and frequency response analysis on friction stir welding tool with different materials by using FEA method Rohit Pandey, Himanshu Shukla, Balendra Bhaskar, Ashish Shrivastava p. 388-395

Modelling for temperature distribution calculation using surface scattering of free electrons in finite metal solid = 자유전자의 표면산란 원리를 활용한 금속체의 온도예측 모델 Woo-Jae Seong p. 396-405, [1-9]

Effect of welding process on microstructure and mechanical properties of boron containing modified 9Cr-1Mo steel Gopa Chakraborty, P. Vasantharaja, B. Shashank Dutt, M. Nani Babu, C.R. Das, A. Moitra, M. Vasudevan p. 406-413

파괴인성에 영향을 미치는 액화수소 특성 = Liquid hydrogen properties affecting fracture toughness 성대희, 조원준, 노지선, 박중구, 박정웅, 최동현, 안규백 p. 414-427

마이크로 솔더링을 위한 레이저 및 Laser-Assisted Bonding (LAB) 기술의 최근 발전과 Mini-LED에의 적용 = Recent advences in laser and laser-assisted bonding (LAB) technologies for micro-soldering and applications to mini-LED 구준호, 정재필 p. 428-436

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