2019
DOI: 10.1016/j.expthermflusci.2018.12.033
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An experimental investigation on pool boiling heat transfer enhancement using sol-gel derived nano-CuO porous coating

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Cited by 40 publications
(6 citation statements)
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“…Design of experiments is a collection of tools used mainly to interpret the influence of process parameters on output response [41]. Among the various tools in DoE, response surface methodology was employed [21] in the present study to analyse the influence of variation in were generated using the Design Expert software, as shown in Table 1.…”
Section: Preparation Of Sio2/ag-cuo Nanofluidmentioning
confidence: 99%
“…Design of experiments is a collection of tools used mainly to interpret the influence of process parameters on output response [41]. Among the various tools in DoE, response surface methodology was employed [21] in the present study to analyse the influence of variation in were generated using the Design Expert software, as shown in Table 1.…”
Section: Preparation Of Sio2/ag-cuo Nanofluidmentioning
confidence: 99%
“…High porosity and roughness and low wettability were the causes for such enhancement in HTC. 27 The critical heat flux investigation results revealed that the capillary wicking momentum was due to high wettability and altered surface roughness which were significant factors for the enhancement of CHF at minimum wall superheat. [28][29][30][31][32] The CHF augmentation of 61% and HTC of 198% have been achieved on microporous copper surfaces due to larger nucleation site density, increased bubble departure frequency, and reduced bubble diameter during departure.…”
Section: Introductionmentioning
confidence: 98%
“…High porosity and roughness and low wettability were the causes for such enhancement in HTC. 27 The critical heat flux investigation results revealed that the capillary wicking momentum was due to high wettability and altered surface roughness which were significant factors for the enhancement of CHF at minimum wall superheat. 2832…”
Section: Introductionmentioning
confidence: 98%
“…Design of experiments (DoE), fuzzy logic and artificial neural network (ANN) are the most preferred tools for finding the interaction of input parameters on the output response. Out of these, DoE will provide an insight into the dependence of response on input parameters in a minimum number of experiments [17]. Esfe et al [18] optimized the rheological and thermal properties of Al2O3-EG/water nanofluid by using response surface methodology (RSM).…”
Section: Introductionmentioning
confidence: 99%
“…For obtaining the optimum composition that yields maximum optical absorption, response surface methodology (RSM) in Design Expert 10 was employed. RSM provides a clear insight of input variables interaction on output response using a minimum number of experimental runs[17]. The parameters considered for optimization are the concentrations of nanoparticle and surfactant.…”
mentioning
confidence: 99%