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ANN-based prediction of Nusselt number in PCM heat exchanger for solar heat storage
Thi Nhan Nguyen(응웬티난),Byungryun Kim(김병련),Thanh Phuong Nguyen(응웬탄풍),Van Cong Le(레반콩),Chanwoo Park(박찬우) 대한기계학회 2021 대한기계학회 춘추학술대회 Vol.2021 No.11
In this study, heat transfer during the melting process of paraffin wax as a phase change material (PCM) is researched. To predict Nusselt number, the melting characteristic of PCM, an artificial neural network (ANN) model is built. Datasets from experiment are used for training and testing the ANN model in the ratio of 80% and 20%, respectively. Rayleigh, Fourier and Stefan numbers are set as input parameters of the network. The accuracy of developed model is evaluated by Mean square error (MSE). The optimal structure of ANN based on minimum MSE has high accuracy in predicting the heat transfer characteristics during PCM melting.