An approach to estimate the low cycle fatigue probabilistic curves of PBF-LB/M 316L steel from small size datasets using the remora optimization algorithm-Reference-Cited by-同舟云学术

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An approach to estimate the low cycle fatigue probabilistic curves of PBF-LB/M 316L steel from small size datasets using the remora optimization algorithm

Published:2024-08 Issue: Volume:185 Page:108375
ISSN:0142-1123
Container-title:International Journal of Fatigue
language:en
Short-container-title:International Journal of Fatigue

Author:

Chen Yefeng,Wang Xiaowei,Zhang Zhen,Zhou Dewen,Jiang Yong,Weng Jian,Walther Frank,Gong Jianming

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Reference49 articles.

1. The role of side-branching in microstructure development in laser powder-bed fusion[J];Pham;Nat Commun,2020

2. Additively manufactured hierarchical stainless steels with high strength and ductility[J];Wang;Nat Mater,2018

3. Metal additive manufacturing: a review of mechanical properties[J];Lewandowski;Annu Rev Mat Res,2016

4. Low cycle fatigue life prediction of 316 L (N) stainless steel based on cyclic elasto-plastic response[J];Roy;Nucl Eng Des,2012

5. Understanding low cycle fatigue and creep–fatigue interaction behavior of 316 L (N) stainless steel weld joint[J];Shankar;Int J Fatigue,2016

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