Function chain neural network prediction on heat transfer performance of oscillating heat pipe based on grey relational analysis

来源期刊:中南大学学报(英文版)2011年第5期

论文作者:鄂加强 李玉强 龚金科

文章页码:1733 - 1737

Key words:oscillating heat pipe; grey relational analysis; function chain neural network; heat transfer

Abstract:

As for the factors affecting the heat transfer performance of complex and nonlinear oscillating heat pipe (OHP), grey relational analysis (GRA) was used to deal with the relationship between heat transfer rate of a looped copper-water OHP and charging ratio, inner diameter, inclination angel, heat input, number of turns, and the main influencing factors were defined. Then, forecasting model was obtained by using main influencing factors (such as charging ratio, interior diameter, and inclination angel) as the inputs of function chain neural network. The results show that the relative average error between the predicted and actual value is 4%, which illustrates that the function chain neural network can be applied to predict the performance of OHP accurately.

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