A boiling surface with different initial roughness and under various nanoparticles volume fractions was studied in present work. Develop a correlation and sensitivity analysis. The results showed that for small (7.3 nm) and much larger (about 2,000 nm) surface roughness, compared to nanoparticle size of around 25 nm, the heat transfer rate of nanofluid diminishes relative to that of base fluid. The results also demonstrated that the boiling heat transfer rate is reduced by increasing the concentration of nanoparticles. For larger boiling surface roughness (480 nm) and nanoparticles volume fractions of less than 0.1 Vol.%, the value of heat transfer increases with the increase of nanoparticles concentration; and for those of more than 0.1 Vol.%, heat transfer rate decreases by adding more nanoparticles, significantly. Finally, an equation was presented for estimating the wall superheat and the C_sf coefficient in terms of mentioned parameters.

Purpose: The purpose of this paper is to improve the lattice Boltzmann method’s ability to simulate a microflow under constant heat flux. Design/methodology/approach: Develop the thermal lattice Boltzmann method based on double population of hydrodynamic and thermal distribution functions. Findings: The buoyancy forces, caused by gravity, can change the hydrodynamic properties of the flow. As a result, the gravity term was included in the Boltzmann equation as an external force, and the equations were rewritten under new conditions. Originality/value: To the best of the authors’ knowledge, the current study is the first attempt to investigate mixed-convection heat transfer in an inclined microchannel in a slip flow regime.

This paper aims to propose a new nonlinear function estimation fuzzy system as a novel statistical approach to estimate nanofluids’ thermal conductivity. A fuzzy system having a product inference engine, a singleton fuzzifier, a center average defuzzifier and Gaussian membership functions is proposed for this purpose. Results indicate that the proposed fuzzy system can predict the thermal conductivity of Al₂O₃/paraffin nanofluid with appropriate precision and generalization and it also outperforms the classic interpolation methods. A new nonlinear function estimation fuzzy system was introduced as a novel statistical approach to estimate nanofluids’ thermal conductivity for the first time.