ANN Modeling for Prediction of Fatigue Crack Growth Rate
Saurabh Kumar Gupta
Sold by AHA-BUCH GmbH, Einbeck, Germany
AbeBooks Seller since August 14, 2006
New - Soft cover
Condition: Neu
Quantity: 1 available
Add to basketSold by AHA-BUCH GmbH, Einbeck, Germany
AbeBooks Seller since August 14, 2006
Condition: Neu
Quantity: 1 available
Add to basketnach der Bestellung gedruckt Neuware - Printed after ordering - Fatigue crack growth is one of the most important factors in the design of the different mechanical structures. Different models were developed to predict the fatigue crack growth rate. These models cannot be used for different materials to predict the fatigue crack growth rate and examine the effect of different parameters.The neural network is a complicated nonlinear dynamic system with the ability of prediction based on real time information. It is a good tool to develop quantitative predictive method for the fatigue crack growth rate based on experimental data. The prediction of crack retardation using ANN shows greater accuracy as compared to the wheeler model. The overload application reduces the crack growth and results in enhanced fatigue life.
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