Effect of Ti/N Ratio on Grain Growth Inhibition in the Coarse-Grained Heat-Affected Zone of Low Carbon Steels Simulated for Ultra-High Heat Input and Tandem Electro-Gas Welding

Seonghoon Yoo; Byungrok Moon; Myeonghwan Choi; Xian Guo; Junghoon Lee; Namhyun Kang

doi:10.1007/s12540-021-01157-6

추천

검색

자료유형: 학술저널

저자정보: Seonghoon Yoo (Pusan National University) Byungrok Moon (Pusan National University) Myeonghwan Choi (Pusan National University) Xian Guo (Pusan National University) Junghoon Lee (Yonsei University) Namhyun Kang (Pusan National University)

저널정보: 대한금속·재료학회 Metals and Materials International Metals and Materials International Vol.28 No.11

발행연도: 2022.11

수록면: 2,766 - 2,777 (12page)

DOI: 10.1007/s12540-021-01157-6

이용수

📌

연구주제

📖

연구배경

🔬

연구방법

🏆

연구결과

초록· 키워드

오류제보하기

In this study, the effect of the Ti/N ratio on the coarsening behaviour of (Ti, Nb)(C, N) precipitates and prior austenite grainsize (PAGS) in the coarse-grained heat-affected zone (CGHAZ) during the welding process was investigated. Oscillationand tandem electro-gas welding (EGW) were simulated using the finite element method to calculate the thermal history ofthe CGHAZ. The calculated thermal history was applied to the Gleeble specimens to simulate the CGHAZ of tandem EGW.As the Ti/N ratio decreased to ~1.5, and the amount of N increased, finer and more (Ti, Nb)(C, N) precipitates existed inthe as-rolled and CGHAZ specimens (peak temperature ~ 1335 °C), thereby producing a small PAGS. Comparing with theprevious studies regarding to the isothermal kinetics conducted by isothermal heat treatment of Ti(C,N), the athermal kinetics(simulation of tandem EGW) of (Ti,Nb)(C,N) showed the insignificant growth of PAGS. Furthermore, Nb-rich precipitateswere dissolved in the matrix above 1000 °C, and they did not contribute to the PAGS growth of the CGHAZ.

#Precipitate · Heat affected zone · Austenite grain size · (Ti #Nb)(C #N) complex particle · Electro–gas welding

참고문헌 (0)

참고문헌 신청

참고문헌이 DBpia에서 서비스 중이라면, [참고문헌 신청]을 통해 등록해보세요

함께 읽어보면 좋을 논문

논문 유사도에 따라 DBpia 가 추천하는 논문입니다. 함께 보면 좋을 연관 논문을 확인해보세요!