2021
DOI: 10.1088/2631-8695/ac3b2a
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A numerical-experimental analysis of qualification assessment for mono-block plasma-facing component with flat heat sink

Abstract: The heat removal capacity of a flat heat sink was studied using subcooled flow boiling experiments, to address the thermal peaking problem. Based on the Bowring criteria, the boiling curve is divided into a partially developed nucleate boiling regime (PDB) and fully developed nucleate boiling regime (FDB), and the existing heat transfer correlations for each flow regime are evaluated. In the PDB regime, the Baburajan correlation exhibited the highest prediction rate with an average error rate of 10.92%; howeve… Show more

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Cited by 15 publications
(7 citation statements)
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“…A solenoid valve with on-off function is installed under the accumulator to discharge all used water out of the loop after the experiment. Detailed information on the experimental equipment or loop design process can be found in previous papers [39][40][41]. Table 1 summarizes the ranges of the system parameters and uncertainties of the measured variables of the sub-cooled flow boiling experiment conducted in this study.…”
Section: Experimental Methods 21 Test Loopmentioning
confidence: 99%
“…A solenoid valve with on-off function is installed under the accumulator to discharge all used water out of the loop after the experiment. Detailed information on the experimental equipment or loop design process can be found in previous papers [39][40][41]. Table 1 summarizes the ranges of the system parameters and uncertainties of the measured variables of the sub-cooled flow boiling experiment conducted in this study.…”
Section: Experimental Methods 21 Test Loopmentioning
confidence: 99%
“…Additionally, an AlN plate with a very low HTC was installed on top of the FeCrAl heater to prevent heat loss over the channel. Detailed information on the heater development process and material selection can be found in a previous papers [10,20,23].…”
Section: One-side Joule Heating Assemblymentioning
confidence: 99%
“…A rechecking of the 5% of outlier data left after the development process confirmed that most were the result of incorrect machining of the channel's thermocouple holes or measurement errors by other measuring equipment. More detailed information about Python code can be found from previous papers [10,20,23,56].…”
Section: Python Code Developmentmentioning
confidence: 99%
“…Here, SSE (error sum of squares) is the sum of squares of the difference between the values that are not explained by the regression model and the values predicted by the regression model; SSR (regression sum of squares) is the sum of squares of the mean differences between the values predicted by the regression model and the observations; and SST (total sum of squares) is the total variation or the sum of SSE and SSR. SST, SSR and SSE can be obtained from (15), (16), and (17), respectively [34][35][36].…”
Section: Assessment Of Existing Ofi Correlationsmentioning
confidence: 99%