Optimization of MLP neural network for modeling effects of electric fields on bubble growth in pool boiling
Author:
Funder
National Science Foundation
Publisher
Springer Science and Business Media LLC
Subject
Fluid Flow and Transfer Processes,Condensed Matter Physics
Link
https://link.springer.com/content/pdf/10.1007/s00231-023-03434-z.pdf
Reference71 articles.
1. Bi J, Christopher DM, Zhao D, Xu J, Huang Y (2019) Numerical study of bubble growth and merger characteristics during nucleate boiling. Prog Nucl Energy 112:7–19. https://doi.org/10.1016/j.pnucene.2018.12.001
2. Kangude P, Srivastava A (2020) Understanding the growth mechanism of single vapor bubble on a hydrophobic surface: Experiments under nucleate pool boiling regime. Int J Heat Mass Transf 154:119775. https://doi.org/10.1016/j.ijheatmasstransfer.2020.119775
3. Tran N, Sajjad U, Lin R, Wang CC (2020) Effects of surface inclination and type of surface roughness on the nucleate boiling heat transfer performance of HFE-7200 dielectric fluid. Int J Heat Mass Transf 147:119015. https://doi.org/10.1016/j.ijheatmasstransfer.2019.119015
4. McHale JP, Garimella SV (2010) Bubble nucleation characteristics in pool boiling of a wetting liquid on smooth and rough surfaces. Int J Multiph Flow 36:249–260. https://doi.org/10.1016/j.ijmultiphaseflow.2009.12.004
5. Lamas MI, Jabardo JMS, Arce A, Fariñas P (2012) Numerical analysis of the bubble detachment diameter in nucleate boiling. J Phys Conf Ser. Institute of Physics Publishing. https://doi.org/10.1088/1742-6596/395/1/012174
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