Short fiber reinforced composite material design based on artificial neural network
In order to guide the design of short fiber reinforced composites,a method based on artificial neural network is proposed.First,a mathematical model is established by combining orientation averaging method and self-consistent hypothesis,to calculate the elastic properties of SFRCs under different volume fractions.Then,two different artificial neural networks are built,and the data sets obtained from the mathematical model are trained.The elastic properties of SFRCs can be quickly predicted from the volume fraction of SFRCS.The fiber volume fraction can also be inversely derived from the known elastic properties of SFRCs.Compared with the traditional method,it can effectively reduce the number of repeated experiments,reduce the cost and cycle,and has certain reference significance for the setting of composite experiments.
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