Using artificial neural networks to predict the fatigue life of carbon and low-alloy steels

Author:

Pleune T.Todd,Chopra Omesh K

Publisher

Elsevier BV

Subject

Mechanical Engineering,Waste Management and Disposal,Safety, Risk, Reliability and Quality,General Materials Science,Nuclear Energy and Engineering,Nuclear and High Energy Physics

Reference13 articles.

1. Caudill, M., Butler, C., 1990. Backpropagation networks. In: Naturally Intelligent Systems. MIT Press, Cambridge, MA, 1990, pp. 183–195.

2. Chopra, O.K., 1996. PVRC meeting. Orlando FL, April.

3. Chopra O.K., Shack, W.J., 1995. Effects of material and loading variables on fatigue life of carbon and low-alloy steels in LWR environments. In: Rocha, M.M., Riera, J.D. (Eds.), Transactions of the Thirteenth International Conference on Structural Mechanics in Reactor Technology (SMiRT 13), Vol. II. Escola de Engenharia-Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil, pp. 551–562.

4. Chopra, O.K., Shack, W.J., 1997. Evaluation of effects of LWR coolant environments on fatigue life of carbon and low-alloy steels. In: Van der Sluys, W.A. (Ed.), Proceedings of the Symposium on Effects of the Environment on the Initiation of Crack Growth, ASTM STP 1298. American Society for Testing and Materials, Philadelphia, 1997.

5. Chopra, O.K., Shack, W.J., 1998. Fatigue crack initiation in carbon and low-alloy steels in light water reactor environments — mechanism and prediction. In: Mehta, H.S. (Ed.), Fatigue, Environmental Factors, and New Materials, PVP-Vol. 374, pp. 155–168.

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