Experimental investigation on heat transfer characteristics of a novel hypervapotron channel for divertor target in nuclear fusion reactors

Abstract

In the further development of nuclear fusion energy, managing the high heat flux on a divertor target remains a significant issue. To address this, the development of innovative cooling channels capable of efficiently managing high heat loads is essential. Among various cooling techniques, the hypervapotron (HV) method stands out for its exceptional heat transfer capabilities. This study undertakes an in-depth analysis of a novel HV cooling channel, evaluating its heat transfer performance via an electron beam high heat flux testing system. The focus was on subcooled flow boiling, observing that the novel HV channel displayed varied flow patterns with increasing heat flux. Additionally, a comparative investigation was conducted to assess the heat transfer efficiency of this novel HV channel against traditional ITER-like HV channel and smooth channel. The analysis incorporated various system parameters, such as mass flow rate and system pressure, to understand their effects on heat transfer. To effectively predict the heat transfer performance of the novel HV channel, efforts have been made to evaluate existing and develop new heat transfer correlations for the channel. Furthermore, Artificial Neural Networks (ANNs) have also been utilized as a crucial approach in this predictive endeavor. The outcomes of this study hold significant implications for understanding and optimizing the design of cooling channels for divertor target in nuclear fusion reactors.

Keywords

• Heat transfer characteristic
• Hypervapotron channel
• Heat transfer correlation
• Artificial Neural Network
• Nuclear fusion