講演情報
[2C18]Developing correlation for prediction of DNB heat flux in subcooled flow boiling using artificial neural network-aided framework
*Nguyen Thanh Binh1, Akira Satou1, Yoshiyasu Hirose1, Satoshi Abe1, Yasuteru Sibamoto1 (1. JAEA)
キーワード：
DNB、Subcooled flow boiling、Artificial neural network
To avoid failure in heating devices, knowledge about DNB heat flux is essential for ensuring the safety of light water reactors. Due to complexity of this phenomenon, accurate prediction method for DNB heat flux remains a challenging issue. In this study, six dimensionless numbers that would have effect on DNB heat flux were gathered from available resources. Artificial neural network (ANN) was used to study about the inter-relationship between parameters on the DNB heat flux. The minimum number of most important non-dimensional quantities were extracted by ANN. A simple correlation was constructed using only dimensionless mass flux, channel diameter and subcooling. The calculated result of the proposed correlation is compared with existing models to evaluate its performance. It is proven that the proposed model has superior features such as robustness, simplicity, applicability over wide range of operating conditions and independent on thermo-hydraulic conditions.