In this paper, a novel design method, which is different from the traditional and empirical one (i. e., taking p and pv as the basic checking parameters) is presented for the fatigue strength design of dynamically loa...In this paper, a novel design method, which is different from the traditional and empirical one (i. e., taking p and pv as the basic checking parameters) is presented for the fatigue strength design of dynamically loaded journal bearings. The method makes it possible that dynamically loaded bearings can be desed as same as other machine elements by stress-strength criterion. The practical design results show that the method has high accuracy and reliability, and may open a new visa in bearing fatigue designs.展开更多
With the method of neural network, the processes of fatigue stiffness decreasing and deflection increasing of reinforced concrete beams under cyclic loading were simulated. The simulating system was built with the giv...With the method of neural network, the processes of fatigue stiffness decreasing and deflection increasing of reinforced concrete beams under cyclic loading were simulated. The simulating system was built with the given experimental data. The prediction model of neural network structure and the corresponding parameters were obtained. The precision and results were satisfied and could be used to investigate the fatigue properties of reinforced concrete beams in complex environment and under repeating loads.展开更多
文摘In this paper, a novel design method, which is different from the traditional and empirical one (i. e., taking p and pv as the basic checking parameters) is presented for the fatigue strength design of dynamically loaded journal bearings. The method makes it possible that dynamically loaded bearings can be desed as same as other machine elements by stress-strength criterion. The practical design results show that the method has high accuracy and reliability, and may open a new visa in bearing fatigue designs.
基金Supported by Visiting Scholar Foundaion of Key Lab. in University and National Natural Science Foundation of China(5 0 0 780 0 9)
文摘With the method of neural network, the processes of fatigue stiffness decreasing and deflection increasing of reinforced concrete beams under cyclic loading were simulated. The simulating system was built with the given experimental data. The prediction model of neural network structure and the corresponding parameters were obtained. The precision and results were satisfied and could be used to investigate the fatigue properties of reinforced concrete beams in complex environment and under repeating loads.
