Validation of Proposed Correlation with Other CHF Results from Open

Literature

In this section, the proposed CHF prediction correlation is validated with open literature CHF data obtained in various operating conditions. The empirical CHF prediction correlation proposed in chapter 4 is based on only current experimental conditions. Thus the validation for empirical CHF correlation is excluded due to lack of applicability for different operating conditions. However, the proposed analytical CHF prediction correlation based on the bubble force balance method developed in previous section possesses the universal application feasibility over large range of operating conditions. In order to evaluate applicability of the proposed correlation, it is noted that operating conditions (i.e., system pressure, mass flux, inlet sub-cooling temperature, and type of fluids) is required to predict the CHF value. Including current CHF test in flow boiling, other 5 researcher’s CHF data in flow boiling condition in literature are selected for the validation work.

Due to lack of flexibility of the current experimental apparatus, hydraulic diameter effects on CHF were not examined. Even though proposed CHF prediction correlation does not contain hydraulic diameter information, this correlation can be expanded for different geometry by using equation (2-7) which is widely used in the CHF look up table (refer to chapter 2.4). The proposed CHF prediction correlation for the current experimental condition can be improved by adding more CHF data with a wider range of key parametric conditions. In this validation work, 36 current CHF measure value are selected for the comparative study between author’s proposed

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CHF correlation and most well accepted Katto CHF prediction correlation. Katto proposed a revised generalized correlation applicable for a range of fluids (i.e. water, R-12, R134a). The correlation is a non-local correlation that consists of four equations (refer chapter 5.1.1). The effect of inlet sub-cooling on the CHF is included in the correlation. The correlation requires an inlet sub-cooled enthalpy, a system pressure, mass flux, and geometry of heating section.

Figure 5.5 The comparative study between proposed correlation prediction and Katto (1984) CHF prediction correlation

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Figure 5.5 shows the comparison between the prediction accuracy of proposed correlation and that of Katto CHF correlation. The maximum deviation for both correlations (author, and Katto) under the identical operating input parameters (system pressure, mass flux, inlet sub-cooled enthalpy) are 7% and 20% respectively. In the calculation of proposed correlation, the static contact angle value for copper surface is measured and utilized as 80° in proposed correlation. It is found that the Katto correlation generally under predicts the CHF value in given condition, which is also consistent with other researcher founding (Chang et al., 2005).

For the applicability study in proposed correlation, a total of 105 data points of CHF in flow boiling of either water or R-134a as working fluid were collected from 5 researcher’s CHF value in open literature. Experimental CHF measurement data used here are those presented by Lee et al. (2008), Bang et al. (2002), Van Der Mollen et al. (1978), Kim et al. (2009), Kim et al. (2010), and author CHF data. The data used in the present analysis are pre-screen data via heat balance methods, and they are comprised of 25 data from Lee et al. (2008), 12 data from Bang et al. (2004), 12 data from Van Der Mollen et al. (1978), 20 data from Kim et al. (2009), 36 data from author. The ranges of the collected experimental data are 1 bar P (pressure) 20 bar, 100 kg/m2-s G (mass flux) 2512 kg/m2-s, 11kJ/kg ∆ (inlet sub-cooled enthapy) 249.kJ/kg, respectively. The detail information of range of each group’s operating conditions is summarized in Appendix A.

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Figure 5.6 The comparison between CHF predictions by proposed correlation and 5 other researcher’s CHF measurement (105 CHF data).

To improve feasibility of the proposed CHF correlation, it is required to collect more CHF data points with extended experimental condition as well as, to include static contact angle information in flow boiling condition. Unfortunately a few flow boiling CHF enhancement tests with static contact angle measurements have been found in the literature. The literature of surface modification by nanoparticle deposition in flow boiling condition is in the early stage of investigation of CHF enhancement with surface feature (Kim et al., 2005). The conclusion from

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nanoparticle deposition studies in flow boiling condition (Kim et al., 2009) is that addition of nanoparticles in the working fluid provides the nanoparticle deposition by boiling process at the interface between liquid and solid surface and generates a surface with enhanced wettability and reduced the contact angles. Kim et al. (2009) reported the 35~55% CHF enhancement by using nanoparticle inserted fluid of water. In addition static contact angle are measured for experimental CHF test.

Figure 5.7 The comparative study between CHF prediction by the author’s proposed correlation with contact angle and CHF prediction without contact angle.

0 1x106 2x106 3x106 4x106 5x106 6x106 7x106 8x106 0 1x106 2x106 3x106 4x106 5x106 6x106 7x106 8x106 +20% -20%

Water without contact angle (Kim, 2009) Water with contact (Kim, 2009)

Pred ic ted CH F, q '' CH F (W /m 2 ) Meausred CHF, q''_CHF (W/m2)

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Therefore, we conduct the validation work of our proposed correlation with Kim et al. (2011) with consideration of surface wettability on CHF enhancement. The figure 5.7 shows the comparison between the CHF prediction by proposed correlation for Kim’s CHF data with considering contact angle measurement and without considering contact angle measurement. The maximum deviations of CHF prediction is calculated as 20% without contact angle parameter (inserting the reference contact angle of 80°) and 7% with contact angle parameter (inserting the measured contact angle 10°~15° . It is found that the proposed correlation shows better

prediction accuracy when the surface is modified. Furthermore, the enhancements of CHF results are observed both in experimental result and analytic correlation prediction.