References
- Ravi S, Balasubramanian V, Nematnasser S. Influences of post weld heat treatment on fatigue life prediction of strength mis-matched HSLA steel welds. Int. J. Fatigue. 2005;27:547–553.10.1016/j.ijfatigue.2004.09.006
- Lu F, Liu P, Ji H, et al. Dramatically enhanced impact toughness in welded 10%Cr rotor steel by high temperature post-weld heat treatment. Mater. Charact. 2014;92:149–158.10.1016/j.matchar.2014.03.014
- Japanese Industrial Standards and Japan Welding Engineering society. Methods of post weld heat treatment. 2009, JIS Z 3700 (in Japanese).
- Japanese high pressure power technology association – Stress-strain (SR) committee. Post weld heat treatment standard and commentary. 1994 (in Japanese).
- Vasudevan M, Venkadesan S, Sivaprasad PV, et al. Use of Larson–Miller parameter to study the influence of ageing on the hardness of cold worked austenitic stainless steel. J. Nucl. Mater. 1994;211:251–255.10.1016/0022-3115(94)90355-7
- Yu L, Nakabayashi Y, Saida K, et al. Quantitative consideration for the tempering effect during multi-pass thermal cycle in HAZ of low-alloy steel. Q. J. Jpn. Weld. Soc. 2011;29:107–113 (in Japanese).10.2207/qjjws.29.107
- Samuel KG, Ray SK. Larson–Miller correlation for the effect of thermal ageing on the yield strength of a cold worked 15Cr–15Ni–Ti modified austenitic stainless steel. Int. J. Pres. Ves. Pip. 2006;83:405–408.10.1016/j.ijpvp.2006.02.032
- Virtanen E, Van Tyne CJ, Levy BS, et al. The tempering parameter for evaluating softening of hot and warm forging die steels. J. Mater. Process. Technol. 2013;213:1364–1369.10.1016/j.jmatprotec.2013.03.003
- Sreenivasan PR. Hot-tensile data and creep properties derived there-from for 316L(N) stainless steel with various nitrogen contents. Procedia Eng. 2013;55:82–87.
- Deng D, Murakawa H, Shibahara M. Investigations on welding distortion in an asymmetrical curved block by means of numerical simulation technology and experimental method. Comput. Mater. Sci. 2010;48:187–194.
- Yu L, Nakabayashi Y, Sasa M, et al. Neural network prediction of hardness in HAZ of temper bead welding using the proposed thermal cycle tempering parameter (TCTP). ISIJ Int. 2011;51:1506–1515.
- Yu L, Sasa M, Ohnishi K, et al. Neural network-based hardness and toughness prediction in HAZ of temper bead welding repair technology. Q. J. Jpn. Weld. Soc. 2013;31:173s–177s.