Papers by Keyword: Extra-Low Cycle

Abstract: The fracture problems of medium carbon steel under extra-low cycle bend torsion fatigue loading were studied using artificial neural networks (ANN) in this paper. The ANN model exhibited excellent comparison with the experimental results. It was concluded that predicted fracture design parameters by the trained neural network model seem more reasonable compared to approximate methods. It is possible to claim that, ANN is fairly promising prediction technique if properly used. Training ANN model was introduced at first. And then the Training data for the development of the neural network model was obtained from the experiments. The input parameters, the presetting deflection and notch open angle, and the output, the cycle times of fracture were used during the network training. The neural network architecture is designed. The ANN model was developed using back propagation architecture with three layers jump connections, where every layer was connected or linked to every previous layer. The number of hidden neurons was determined according to special formula. The performance of system is summarized at last. In order to facilitate the comparisons of predicted values, the error evaluation and mean relative error are obtained. The result show that the training model has good performance, and the experimental data and predicted data from ANN are in good coherence.

Abstract: The fracture problems of medium carbon steel (MCS) under extra-low cycle bend torsion loading were studied using artificial neural networks (ANN) in this paper. The training data were used in the formation of training set of ANN. The ANN model exhibited excellent comparison with the experimental results. It was concluded that predicted fracture design parameters by the trained neural network model seem more reasonable compared to approximate methods. It is possible to claim that, ANN is fairly promising prediction technique if properly used. Training ANN model was introduced at first. And then the Training data for the development of the neural network model was obtained from the experiments. The input parameters, notch depth and tip radius of the notch, and the output, the cycle times of fracture were used during the network training. The neural network architecture is designed. The ANN model was developed using back propagation architecture with three layers jump connections, where every layer was connected or linked to every previous layer. The number of hidden neurons was determined according to special formula. The performance of system is summarized at last. In order to facilitate the comparisons of predicted values, the error evaluation and mean relative error are obtained. The result show that the training model has good performance, and the experimental data and predicted data from ANN are in good coherence.

Abstract: The fracture problems of ecomaterial (aluminum alloyed cast iron) under extra-low cycle rotating bending fatigue loading were studied using artificial neural networks (ANN) in this paper. The training data were used in the formation of training set of ANN. The ANN model exhibited excellent in results comparison with the experimental results. It was concluded that predicted fracture design parameters by the trained neural network model seem more reasonable compared to approximate methods. It is possible to claim that, ANN is fairly promising prediction technique if properly used. Training ANN model was introduced at first. And then the Training data for the development of the neural network model was obtained from the experiments. The input parameters, notch depth, the presetting deflection and tip radius of the notch, and the output parameters, the cycle times of fracture were used during the network training. The neural network architecture is designed. The ANN model was developed using back propagation architecture with three layers jump connections, where every layer was connected or linked to every previous layer. The number of hidden neurons was determined according to special formula. The performance of system is summarized at last. In order to facilitate the comparisons of predicted values, the error evaluation and mean relative error are obtained. The result show that the training model has good performance, and the experimental data and predicted data from ANN are in good coherence.

Abstract: The fracture problems of medium carbon steel under extra-low cycle axial fatigue loading were studied using artificial neural network in this paper. The training data were used in the formation of training set of artificial neural network. The artificial neural network model exhibited excellent comparison with the experimental results. It was concluded that predicted fracture design parameters by the trained neural network model seem more reasonable compared to approximate methods. Training artificial neural network model was introduced at first. And then the Training data for the development of the neural network model was obtained from the experiments. The input parameters, notch depth and tip radius of the notch, and the output, the cycle times of fracture were used during the network training. The neural network architecture is designed. The artificial neural network model was developed using back propagation architecture with three layers jump connections, where every layer was connected or linked to every previous layer. The number of hidden neurons was determined according to special formula. The performance of system is summarized at last. The result show that the training model has good performance, and the experimental data and predicted data from artificial neural network are in good coherence.

Abstract: The applied investigation of regular fracture for low carbon steel under extra-low cycle inverse rotating bending fatigue was studied in this paper. The principle of inverse rotating bending fatigue was explained at first. The effect of experimental parameters on cycle times of fracture, such as the relations of presetting deflection to quality of blanking and cycle times of fracture were discussed through the experiments. The effects of geometrical parameters of notch, such as tip radius, depth and open angle, on cycle times of fracture were studied. The results show that low carbon steel can be regular fractured through inverse rotating bending fatigue. The quality of blanking is depended on presetting deflection of inverse rotating bending.

Abstract: The application of regular blanking for brass under extra-low cycle rotating bending fatigue was studied. The experiments of rotating bending fatigue have been made in special equipment designed by us. Several problems, the relations of the cycle times of fracture, the strain amplitude near the tip of notch and fracture toughness of fatigue to the presetting deflection, the effects of depth and tip radius of notch to the cycle times of fracture, were discussed through the experiments. The formulae of stress amplitude at the tip of notch and fracture toughness of brass to presetting deflection were obtained. The suitable parameters of fracture in rotating bending fatigue for blanking of brass under extra-low cycle times have been proposed.

Abstract: Rotating bending and inverse rotating bending are the two different forms of fatigue. The application of regular blanking for brass under extra-low cycle inverse rotating bending fatigue was investigated. The principle of inverse rotating bending fatigue was explained at first. And then the experiment of inverse rotating bending fatigue was made in special equipment designed by the authors. Several problems, i.e. the relations of the quantities such as cycle times of fracture, the strain amplitude near the notch tip and fracture toughness of fatigue to the presetting deflection, the effects of depth and tip radius of notch on the cycle times of fracture, were discussed with the helps of experiment. Finally, The relation of depth of crack propagation to cycle times were discussed also. The suitable parameters of inverse rotating bending fatigue for blanking of brass were obtained.

Abstract: Safety designs and fracture designs are the two important fields of crack theory. The fracture problems of middle carbon steel under extra-low cycle rotating bending fatigue loading are studied in this paper. The experiments have been made in special rotating bending fatigue fracture machine designed by us. Several problems, the relations of the cycle times of fracture and the strain amplitude near notch tip to the deflection, the effects of depth and tip radius of notch to the cycle times of fracture, are discussed through the experiments. The mathematical expression of fracture toughness to the cycle times of fracture is obtained. The suitable parameters of rotating bending fatigue fracture model for middle-carbon steel in extra-low cycle times has been proposed.

Abstract: The rotating bending and the inverse rotating bending are the two different forms of fatigue fracture. Some fracture problems for middle carbon steel in extra-low rotating bending fatigue loading are studied in this paper. The experiments of inverse rotating bending fatigue have been made in special equipment designed by us. Several problems, the relations of the cycle times of fracture and the strain amplitude near notch tip to the deflection, the relations of the depth of crack propagation to the cycle times of fracture, are discussed through the experiments. The effects of depth and tip radius of notch to the cycle times of fracture are studied also in this paper. The suitable parameters of inverse rotating bending fatigue fracture model for middle-carbon steel in extra-low cycle times has been proposed.