Burnout Conditions for Round Tubes at Elevated Pressures

Becker, K.M.; Djursing, D.; Lindberg, K.; Eklind, O.; Österdahl, C.

doi:10.1016/b978-0-08-017035-0.50009-4

Cited by 10 publications

(2 citation statements)

References 3 publications

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“…Applied to high-pressure CHF databank for water as listed in Table 1, the mean error and RMS error of CHF prediction models are summarized in Table 4. As exhibited, mean error of Levitan correlation (Levitan and Lantsman, 1975), Chernobai correlation (Chernobai, 1980), Becker correlation (Becker et al, 1972), Vijayarangan correlation (Vijayarangan et al, 2006), and Shah correlation (Mohammed Shah, 1987) are above ±50%. Although only applied to 414 subcooled data points, the RMS error of Hall correlation (Hall and Mudawar, 2000) and Katto's sublayer dryout model (Katto, 1992) is still up to 42.4% and 89.1%, respectively.…”

Section: Assessment Of High-pressure Chf Prediction Methodsmentioning

confidence: 89%

“…Shah correlation (Mohammed Shah, 1987) is developed from 23 different fluids including water, halocarbon refrigerants, chemicals, liquid metals, helium, and other cryogens. Chen correlation (Chen et al, 2017), Becker correlation (Becker et al, 1972), Lombardi correlation (Lombardi, 1995), Vijayarangan correlation (Vijayarangan et al, 2006), and Shah correlation (Mohammed Shah, 1987) require known inlet quality x in or the distance from the start of heated section to the boiling crisis point L c , which cannot be provided in some experimental tests. Katto (1992) developed a semitheoretical model based on sublayer dryout mechanism.…”

Section: Existing Chf Prediction Methods For High-pressure Conditionmentioning

confidence: 99%

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Assessment of CHF and Post-CHF Heat Transfer Models for High-Pressure Condition

Song

Liu

2021

Front. Energy Res.

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Supercritical heat transfer systems may undergo trans-critical procedures and work at subcritical conditions during startup, shutdown, or some accidents. However, well-validated heat transfer models for the high-pressure condition (P/Pc>0.7) are still missing. In the present work, with exhaustive literature review, extensive experimental databanks of CHF and post-dryout heat transfer under high-pressure condition are established, respectively. Existing prediction models for the high-pressure condition are also summarized from all over the world. Thereby, with the aid of the high-pressure experimental databank, prediction models get evaluated. It has been demonstrated that CHF correlation developed by Song et al. shows good predictive capability. Post-dryout heat transfer could get well predicted by the Song correlation. These recommended prediction models could be implemented to upgrade safety analysis codes for simulation of trans-critical transients.

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