Fatigue modeling using neural networks: A comprehensive review
Neural network (NN) models have significantly impacted fatigue‐related engineering
communities and are expected to increase rapidly due to the recent advancements in …
communities and are expected to increase rapidly due to the recent advancements in …
[HTML][HTML] Machine learning for predicting fatigue properties of additively manufactured materials
Fatigue properties of materials by Additive Manufacturing (AM) depend on many factors
such as AM processing parameter, microstructure, residual stress, surface roughness …
such as AM processing parameter, microstructure, residual stress, surface roughness …
Probabilistic physics-guided machine learning for fatigue data analysis
Abstract A Probabilistic Physics-guided Neural Network (PPgNN) is proposed in this paper
for probabilistic fatigue SN curve estimation. The proposed model overcomes the limitations …
for probabilistic fatigue SN curve estimation. The proposed model overcomes the limitations …
Fatigue property prediction of additively manufactured Ti-6Al-4V using probabilistic physics-guided learning
The probabilistic fatigue properties of additively manufactured (AM) Ti-6Al-4V using
selective laser melted (SLM) process is analyzed considering the effects of process …
selective laser melted (SLM) process is analyzed considering the effects of process …
Research on fatigue reliability assessment of engine cylinder head based on neural network
G Jing, S Li, S Xiao, T Ma, Z Lyu, S Sun… - International Journal of …, 2023 - Elsevier
Fatigue reliability (FR) evaluation is crucial for extending the service life and improving the
reliability of automotive engines. This study proposed a general framework for assessing …
reliability of automotive engines. This study proposed a general framework for assessing …
Multiaxial low-cycle fatigue life model for notched specimens considering small sample characteristics
S Wu, J Liu, Y Wang, J Lu, Z Zhang - International Journal of Structural …, 2024 - emerald.com
Purpose Sufficient sample data are the necessary condition to ensure high reliability;
however, there are relatively poor fatigue test data in the engineering, which affects fatigue …
however, there are relatively poor fatigue test data in the engineering, which affects fatigue …
Multi-fidelity data aggregation using convolutional neural networks
Multi-fidelity data exist in almost every engineering and science discipline, which can be
from simulation, experiments, and a hybrid form. High fidelity data are usually associated …
from simulation, experiments, and a hybrid form. High fidelity data are usually associated …
Uncertainty quantification and reduction in aircraft trajectory prediction using Bayesian-Entropy information fusion
Eliminating accidents while maintaining the integrity of the National Airspace System is one
of the central objectives of the Next Generation Air Transportation System. This paper …
of the central objectives of the Next Generation Air Transportation System. This paper …
Bayesian model averaging for probabilistic SN curves with probability distribution model form uncertainty
Q Zou, J Wen - International Journal of Fatigue, 2023 - Elsevier
Reliability analysis of engineering components or structures heavily relies on accurately
estimating the fatigue properties of materials. However, significant uncertainty exists …
estimating the fatigue properties of materials. However, significant uncertainty exists …
Probabilistic fatigue life prediction model of natural rubber components based on the expanded sample data
X Liu, WB Shangguan, X Zhao - International Journal of Fatigue, 2022 - Elsevier
A novel method for determine the probabilistic distribution model of natural rubber (NR)
fatigue life is proposed. Uniaxial tension fatigue tests are carried out on dumbbell-shaped …
fatigue life is proposed. Uniaxial tension fatigue tests are carried out on dumbbell-shaped …