Prediction of constant amplitude fatigue crack growth life of 2024 T3 Al alloy with R-ratio effect by GP

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@Article{Mohanty:2015:ASC,

• author = "J. R. Mohanty and T. K. Mahanta and A. Mohanty and D. N. Thatoi",
• title = "Prediction of constant amplitude fatigue crack growth life of 2024 {T3 Al} alloy with R-ratio effect by {GP}",
• journal = "Applied Soft Computing",
• volume = "26",
• pages = "428--434",
• year = "2015",
• keywords = "genetic algorithms, genetic programming, Artificial neural network, Fatigue crack growth life, Fatigue crack growth rate, Load ratio",
• ISSN = "1568-4946",
• DOI = "doi:10.1016/j.asoc.2014.10.024",
• URL = "http://www.sciencedirect.com/science/article/pii/S1568494614005353",
• abstract = "The objective of this study is to develop a genetic programming (GP) based model to predict constant amplitude fatigue crack propagation life of 2024 T3 aluminium alloys under load ratio effect based on experimental data and to compare the results with earlier proposed ANN model. It is proved that genetic programming can effectively interpret fatigue crack growth rate data and can efficiently model fatigue life of the material system under investigation in comparison to ANN model.",

}

Genetic Programming entries for J R Mohanty T K Mahanta A Mohanty D N Thatoi

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