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In this work, flow boiling heat transfer coefficients of deionized water and copper oxide water-based nanofluids at different operating conditions have been experimentally measured and compared. The liquid flowed in an annular space. According to the experiments, two distinguished heat transfer regions with two different mechanisms can be seen namely forced convective and nucleate boiling regions. Results demonstrated that with increasing the applied heat flux, flow boiling heat transfer coefficient increases for both of test fluids at both heat transfer regions. In addition to, by increasing the flow rate of fluid, the heat transfer coefficient dramatically increases at both regions. Influence of inlet temperature of fluid to the annulus as a complicated parameter has been investigated and briefly discussed. Results showed that inlet temperature of fluid displaces the boundary between forced convection and nucleate boiling areas such that with increasing the inlet temperature, nucleation mechanism become dominant mechanism at lower heat fluxes. Furthermore, higher heat transfer coefficient can be obtained due to interactions of bubbles and local agitations. Also, Chen type model was modified in terms of thermo-physical properties and examined to experimental data. Results showed that experimental data are in a good agreement with those of obtained by the correlation with deviation up to 30%.

In this paper, a new method for enhancing the pool boiling heat transfer coefficient of pure liquid, based on the gas injection through the liquids has been introduced. Hence, the effect of gas dissolved in a stagnant liquid on pool boiling heat transfer coefficient, nucleation site density, and bubble departure diameter has experimentally been investigated for different mole fractions of SO2 and various heat fluxes up to 114 kW/ m2. The presence of SO2 in captured vapor inside the bubbles, particularly around the heat transfer surface increases the pool boiling heat transfer coefficient. The available predicted correlations are unable to obtain the reasonable values for pool boiling heat transfer coefficient in this particular case. Therefore, to predict the pool boiling heat transfer coefficient accurately, a new modified correlation based on Stephan-Körner relation has been proposed. Also, during the experiments, it is found that nucleation site density is a strictly exponential function of heat flux. Accordingly, a new correlation has been obtained to predict the nucleation site density. The major application of the nucleation site density is in the estimating of mean bubble diameters as well as local agitation due to the rate of bubble frequency.

Determining the solubility of gases in solvents and considering non-idealities at different operating conditions are essential to design a cost-effective and energy-efficient absorption process. In this work, using a lab-made set-up, solubility of ethylene in N-methyl-2-pyrrolidone (NMP) was measured at different temperatures (278.15, 298.15, and 328.15 K) and pressures up to 14 bar, and the kinetic and equilibrium data were obtained. Accordingly, Henry’s law constants are calculated at various temperatures. Then, thermodynamic modeling was accomplished by applying Peng-Robinson equation of state (PR-EOS) and Wilson activity coefficient model, and the binary interaction parameters were estimated. By the thermodynamic modeling, positive deviation from ideal behavior was apparently observed. Due to low absolute average deviation of < 7.7%, the correlated model was able to predict the ethylene solubility in NMP with a reliable accuracy.

Influence of Al2O3 nanoparticles on nucleate pool boiling heat transfer of diluted binary water-glycerol mixtures has been experimentally measured up to heat flux 91 kW/m2 at diluted volume fractions of 1% to 5% of glycerol into pure water at volumetric concentrations 0.5%, 1% and 1.5% of Al2O3 nanoparticles. Obtained results indicate that presence of nanoparticles into the mixtures result in increasing the pool boiling heat transfer coefficient values and also result in decreasing the wall superheat temperature of surface. Increased values of heat transfer are increased with increasing the volume fractions of Al2O3 too. Generally, it is concurred that Al2O3 nanoparticles typically enhance the pool boiling heat transfer coefficient of binary water-glycerol mixture in comparison with absence of nanoparticles circumstances, up to 25% at 1.5% Al2O3. Additionally, new simple semi - mathematical model has been proposed for a rough estimating of enhanced values with uncertainty about 8%.