A parametric study of the heat flux partitioning model for nucleate boiling of nanofluids

Simulation of pool boiling of nanofluids by using Eulerian multiphase model

“…Due to near molecular mixing between the dilute concentration of nanoparticles and the base fluid, a nanofluid hydro dynamically behaves as it is pure base fluid, and therefore, single-phase modeling of nanofluid is reasonable to assume. On another hand, it was also believed that the vapor-phase is not dense enough to hold the nanoparticles within so, we assumed that the thermal properties of the vapor phase were not influenced by stable nanoparticles, as suggested by [16][17][18]26].…”

“…It is widely known that the boiling of pure liquids complex and the presence of ultrafine particles increase this degree of complexity due to the interaction between exist phases, their interfaces and the heating surface [15]. Some new investigations show that many factors were affecting the pool boiling of nanofluids such as particle size, concentration, heating surface structure and bubbles dynamic; hence, studying such mechanisms theoretically need further investigations to build an accurate predictive model [16][17][18]. One of the most critical sub-phenomena involved in pool boiling of nanofluids is bubble dynamics during the nucleate regime; therefore, studying the bubble parameters with the presence of those ultrafine particles could result in an accurate predictive model for such mechanism.…”

Numerical simulation of pool boiling on smooth, vertically aligned tandem tubes

“…To model pool boiling on smooth tubes, which are inherently a two-phase flow with phase change, the Eulerian-Eulerian framework is adopted such that each phase is treated as a continuum. In the Eulerian-Eulerian method, mass, momentum and energy conservation equations are given as follows for each phase [32][33][34]:…”

A theoretical model for nucleate boiling of nanofluids considering the nanoparticle Brownian motion in liquid microlayer

“…For a given wall roughness, different ratios of R a /d np could be realized by using various d np values (Section 3.2). More detailed investigation on the effects of wall roughness relative to nanoparticle size on nucleate boiling of nanofluids is available in our recent study [35]. For the purpose of comparison, computations were also conducted using the classic HFP model.…”