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- W2381746146 abstract "The bending life of polyester glass fiber reinforced polyester(GFRP) under xenon arc lamp accelerated aging was predicted by BP neural network.The relationship between aging time and bending strength was tested.And models on the relationship between aging time and bending strength were built by BP neural network.Based on MATLAB,the aging life of polyester FRP was analyzed and forecast.The simulation results were compared with those by least square method.The results show that if the decrease in the bending strength by 50% is considered as failure,then the aging life of polyester is 813 d,that of GFRP with filler is 1 031 d and the GFRP without filler is 1 065 d.It is shown that the BP neural network can predict the aging life of FRP.The error between the predicted results by the BP neural network and those by least square method is less than 8%,and the predicted results is in accordance with the practical change of the material property." @default.
- W2381746146 created "2016-06-24" @default.
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- W2381746146 date "2011-01-01" @default.
- W2381746146 modified "2023-09-25" @default.
- W2381746146 title "Accelerated Aging Life Prediction for GFRP Based on BP Neural Network" @default.
- W2381746146 hasPublicationYear "2011" @default.
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