Fatigue life prediction in presence of mean stresses using domain knowledge‐integrated ensemble of extreme learning machines

L Gan, H Wu, Z Zhong - Fatigue & Fracture of Engineering …, 2022 - Wiley Online Library
… An accurate and stable data-driven model is proposed in this work for fatigue life prediction
fatigue lives. Meanwhile, the theoretical prediction, as a representation of domain knowledge

On the integration of domain knowledge and branching neural network for fatigue life prediction with small samples

L Gan, H Wu, Z Zhong - International Journal of Fatigue, 2023 - Elsevier
… integrating domain knowledge and DNNs is proposed in this section for fatigue life prediction
… of data requirements and the improvement of prediction performance. The proposed model …

A novel fatigue and creep-fatigue life prediction model by combining data-driven approach with domain knowledge

HH Gu, XC Zhang, K Zhang, KS Li, ST Tu… - … Journal of Fatigue, 2024 - Elsevier
… is developed to predict fatigue and creep-fatigue life under strain-… with domain knowledge.
A dataset comprising 224 groups of high-temperature low-cycle fatigue and creep-fatigue

Fatigue life prediction of aluminum alloy via knowledge-based machine learning

Z Lian, M Li, W Lu - International Journal of Fatigue, 2022 - Elsevier
… 2b indicates that the high content of Mg, Zn, Zr, Cr, Mn, and Cu favors the increase of fatigue
life, which is consistent with the domain knowledge that Mg-Al-Zn and Al-Si-Cu-Mg-Zr are …

Fatigue life prediction of the FCC-based multi-principal element alloys via domain knowledge-based machine learning

L Xiao, G Wang, W Long, PK Liaw, J Ren - Engineering Fracture …, 2024 - Elsevier
… Furthermore, we analyze the factors that affect fatigue life and provide the … a domain
knowledge-based fatigue life prediction model for various MPEA systems. Firstly, 203 fatigue data …

High-cycle fatigue life prediction of L-PBF AlSi10Mg alloys: a domain knowledge-guided symbolic regression approach

H Yu, Y Hu, G Kang, X Peng… - … Transactions of the …, 2024 - royalsocietypublishing.org
life with the geometric parameters of critical defects. This study proposes a new fatigue life
prediction … and morphology) in terms of domain knowledge-guided symbolic regression (SR). …

Machine learning-based fatigue life prediction of metal materials: Perspectives of physics-informed and data-driven hybrid methods

H Wang, B Li, J Gong, FZ Xuan - Engineering Fracture Mechanics, 2023 - Elsevier
Fatigue life prediction is critical for ensuring the safe service … have been proven effective in
predicting fatigue life, the lack of … The fatigue life prediction in this paper is the fatigue life of …

A frequency-domain enhanced multi-view network for metal fatigue life prediction

S Chen, X Zhou, Y Bai - arXiv preprint arXiv:2405.07507, 2024 - arxiv.org
… -domain analysis for fatigue life prediction is proposed. The model consists of two main
analytical components: one for analyzing multiaxial fatigueknowledge based features to predict

A unified prediction approach of fatigue life suitable for diversified engineering materials

C Feng, M Su, L Xu, L Zhao, Y Han - Engineering Fracture Mechanics, 2023 - Elsevier
… the integration of symbolic regression and domain knowledge, which exhibited good … to
comprehensively analyze the fatigue behavior and realize the fatigue life prediction of welded …

Fatigue life prediction considering mean stress effect based on random forests and kernel extreme learning machine

L Gan, H Wu, Z Zhong - International Journal of Fatigue, 2022 - Elsevier
… models, are proposed to predict the fatigue life in presence of mean … and fatigue properties
as well as the cyclic stress–strain responses of materials are employed to map the fatigue life