Corresponding states correlation for maximum heat flux in two-phase closed thermosyphon

Golobič, Iztok; Gaspersic, B.

doi:10.1016/s0140-7007(97)00019-4

Cited by 18 publications

(6 citation statements)

References 9 publications

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“…Under this limitation, at the critical heat flux, vapor bubbles coalesce near the pipe wall that prohibits the contact of working liquid to wall surface resulting in rapid increase in evaporator wall temperature. Golobič and Gašperšič [31] have complied many CCFL and boiling limitation correlations available for closed two-phase thermosyphons. For Boiling Limitation, we make use of the correlation suggested by Imura et al [32] which provides a good estimate given by:…”

Section: Design Of Experimentsmentioning

confidence: 99%

Thermal performance of closed two-phase thermosyphon using nanofluids

Khandekar

Joshi

Mehta

2008

International Journal of Thermal Sciences

211

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Section: Design Of Experimentsmentioning

confidence: 99%

Thermal performance of closed two-phase thermosyphon using nanofluids

Khandekar

Joshi

Mehta

2008

International Journal of Thermal Sciences

211

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“…The boiling limit is more important at higher values of heat input to the evaporator, when the FR value is high. Many studies were carried out to find correlations for determining the maximum allowable heat input with considering this limitation . In the present work for estimating this limit, a correlation proposed by Imura et al has been used.…”

Section: Resultsmentioning

confidence: 99%

Effects of a Nanofluid and Magnetic Field on the Thermal Efficiency of a Two‐Phase Closed Thermosyphon

Salehi

Heris

Sharifi

et al. 2013

Heat Trans. Asian Res.

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Heat transfer of a CuO/water nanofluid in a two‐phase closed thermosyphon (TPCT) that is thermally enhanced by a magnetic field has been predicted by an optimized artificial neural network (ANN). The magnetic field strength, volume fraction of nanoparticles in water, and inlet power were used as input parameters and the thermal efficiency was used as the output parameters. The correlation coefficient (R2 = 0.924), mean square error (MSE = 0.000340231), mean absolute error (MAE = 0.012410941), and normalized mean‐squared error (NMSE = 0.112417498) between the measured and predicted thermal efficiency by the ANN model were developed. The results were compared with experimental data and it was found that the thermal efficiency estimated by the multi‐layer perception neural network is accurate. In this study, a new approach for the auto‐design of neural networks, based on a genetic algorithm, has been used to predict collection output of a TPCT. © 2013 Wiley Periodicals, Inc. Heat Trans Asian Res, 42(7): 630–650, 2013; Published online in Wiley Online Library (http://wileyonlinelibrary.com/journal/htj). DOI 10.1002/htj.21043

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“…Given that, for evaporator length to tube diameter ratios (le/din>5), the boiling limit is the less severe among the operational constraints (i.e. entrainment limit) for a standard thermosyphon [23], the general pool boiling CHF for FC-72 can be considered as the ideal maximum heat flux achievable. Furthermore, in order to compare the MELT technology with the closed Thermosyphon, the maximum heat flux is evaluated by means of existing correlations developed for the TS (Table 4).…”

Section: Thermal Characterization In Vertical Positionmentioning

confidence: 99%