Add to ORKGLow cycle fatigue (LCF) behaviour of normalized and tempered modified 9Cr-1Mo steel has been studied at various temperatures, strain amplitudes, increase in strain amplitude, decrease in strain rate and with an increase in the duration of hold time in tension. The capability of artificial neural network (ANN) approach of life prediction under LCF and creep-fatigue interaction conditions has been assessed by using the data from National Institute of Materials Science, Japan and that generated in our laboratory. It is demonstrated that the predictions are well within a factor of two
The current financial climate is driving a move towards increased use of computer modelling techniqu...
In this study, deep learning approach was utilized for fatigue behavior prediction, analysis, and op...
Low cycle fatigue (LCF) and creep fatigue interaction (CFI) loadings are the main factors resulting ...
Low cycle fatigue (LCF) behavior of solutionized 316L(N) stainless steel (SS) has been studied at va...
Low cycle fatigue (LCF) behavior of solutionized 316L(N) stainless steel (SS) has been studied at va...
The applicability of artificial neural networks (ANN) in predicting the strain-life fatigue properti...
In the present study an Artificial Neural Network (ANN) model is developed for fatigue life predicti...
The ASME Boiler and Pressure Vessel Code contains rules for the construction of nuclear power plant ...
Available from British Library Document Supply Centre-DSC:DXN023771 / BLDSC - British Library Docume...
Low cycle fatigue (LCF) and creep fatigue interaction (CFI) loadings are the main factors resulting ...
In this study, fatigue life predictions for the various metal matrix composites, R ratios, notch geo...
In this study, an artificial neural network model was developed to predict the thermal-mechanical fa...
Creep rupture stresses at temperatures between 723-923 K have been estimated at a rupture life of 2....
In this study, an artificial neural network model was developed to predict the thermal-mechanical fa...
An artificial neural network has been proved to be a sufficient tool for modelling fatigue life of m...
The current financial climate is driving a move towards increased use of computer modelling techniqu...
In this study, deep learning approach was utilized for fatigue behavior prediction, analysis, and op...
Low cycle fatigue (LCF) and creep fatigue interaction (CFI) loadings are the main factors resulting ...
Low cycle fatigue (LCF) behavior of solutionized 316L(N) stainless steel (SS) has been studied at va...
Low cycle fatigue (LCF) behavior of solutionized 316L(N) stainless steel (SS) has been studied at va...
The applicability of artificial neural networks (ANN) in predicting the strain-life fatigue properti...
In the present study an Artificial Neural Network (ANN) model is developed for fatigue life predicti...
The ASME Boiler and Pressure Vessel Code contains rules for the construction of nuclear power plant ...
Available from British Library Document Supply Centre-DSC:DXN023771 / BLDSC - British Library Docume...
Low cycle fatigue (LCF) and creep fatigue interaction (CFI) loadings are the main factors resulting ...
In this study, fatigue life predictions for the various metal matrix composites, R ratios, notch geo...
In this study, an artificial neural network model was developed to predict the thermal-mechanical fa...
Creep rupture stresses at temperatures between 723-923 K have been estimated at a rupture life of 2....
In this study, an artificial neural network model was developed to predict the thermal-mechanical fa...
An artificial neural network has been proved to be a sufficient tool for modelling fatigue life of m...
The current financial climate is driving a move towards increased use of computer modelling techniqu...
In this study, deep learning approach was utilized for fatigue behavior prediction, analysis, and op...
Low cycle fatigue (LCF) and creep fatigue interaction (CFI) loadings are the main factors resulting ...