An artificial neural network modeling approach for short and long fatigue crack propagation
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Title
An artificial neural network modeling approach for short and long fatigue crack propagation
Authors
Keywords
Short crack, Long crack, Machine learning, Neural network, Crack growth rate
Journal
COMPUTATIONAL MATERIALS SCIENCE
Volume 185, Issue -, Pages 109962
Publisher
Elsevier BV
Online
2020-08-06
DOI
10.1016/j.commatsci.2020.109962
References
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- A generalized fatigue damage parameter for multiaxial fatigue life prediction under proportional and non-proportional loadings
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- (2013) Sara Ghandehari et al. SEPARATION SCIENCE AND TECHNOLOGY
- A modification of Morrow and Smith-Watson-Topper mean stress correction models
- (2011) A. INCE et al. FATIGUE & FRACTURE OF ENGINEERING MATERIALS & STRUCTURES
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- (2010) Jamal A. Abdalla et al. JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
- Evaluation of multilayer perceptron and self-organizing map neural network topologies applied on microstructure segmentation from metallographic images
- (2009) Victor Hugo C. de Albuquerque et al. NDT & E INTERNATIONAL
- A new solution for automatic microstructures analysis from images based on a backpropagation artificial neural network
- (2008) Victor Hugo C. de Albuquerque et al. Nondestructive Testing and Evaluation
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