Simulation of Boiling Heat Transfer at Different Reduced Temperatures with an Improved Pseudopotential Lattice Boltzmann Method

Abstract

The pseudopotential Lattice Boltzmann Method has attracted much attention in the recent years for the simulation of boiling heat transfer. Many studies have been published recently for the simulation of the bubble cycle (nucleation, growth and departure from a heated surface). This paper puts forward two-dimensional simulations of bubble nucleation, growth and departure using an improved pseudopotential Lattice Boltzmann Model from the literature at different reduced temperatures, Tr=0.76 and Tr=0.86. Two different models using the Bhatnagar–Gross–Krook (BGK) and the Multiple-Relaxation-Time (MRT) collision operators with appropriate forcing schemes are used. The results for pool boiling show that the bubbles exhibit axial symmetry during growth and departure. Numerical results of departure diameter and release period for pool boiling are compared against empirical correlations from the literature by varying the gravitational acceleration. Reasonable agreement is observed. Nucleate boiling trends with heat flux are also captured by the simulations. Numerical results of flow boiling simulations are compared by varying the Reynolds number for both reduced temperatures with the MRT model. It was found that the departure diamenter and release period decreases with the increase of the Reynolds number. These results are a direct effect of the drag force. Proper conclusions are commented at the end of the paper.

Pseudopotential Lattice Boltzmann Method for boiling heat transfer: a mesh refinement procedure

“…Equation ( 20) is discretized through a FD method along the lattices discrete values and weights as described in Li et al (2018b); Guzella et al (2020) regardless of the type of boundary condition for (Dirichlet or heat flux). No special treatment is needed at the boundaries since the wet-node approach is used for the LBM (Zou and He, 1997).…”

“…Moreover, solid-liquid-vapor interparticle interaction may take place, which has been proved to have an important influence in quantities of interest like the heat transfer coefficient (Wang and Dhir, 1993). For that reason, several researchers have dedicated themselves to better understanding these phenomena, either experimentally, theoretically, or numerically (Lienhard et al, 1973;Haramura and Katto, 1983;Kandlikar, 2001;Guan et al, 2011;Gong and Cheng, 2015a;Kim et al, 2016;Liang and Mudawar, 2018;Fariñas Alvariño et al, 2019;Guzella et al, 2020).…”

“…Recently, a numerical method that has drawn attention is the Lattice Boltzmann Method (LBM) due to its potential to simulate a variety of complex phenomena such as flow in porous medium (Guo and Zhao, 2002;Liu et al, 2016), turbulence (Yu et al, 2005;Chen et al, 2004), particle suspensions (McCullough et al, 2016;Safaei et al, 2016) and others (Gong and Cheng, 2012, 2015bGuzella et al, 2020). One of the LBM advantages for simulating interfacial dynamics lies in the fact that it does not involve front-tracking, as is the case on more traditional methods such as VOF and level-set.…”

Simulação numérica da formação de bolhas em superfícies aquecidas utilizando o método de >i<Lattice>/i< Boltzmann dos pseudopotenciais

“…Nas Equações 2.141 e 2.142, P SC é o tensor pressão original do modelo dos pseudopotenciais. Uma importante consequência dos diferentes tensores de pressão é que, para uma determinada simulação do mesmo problema com os mesmos parâmetros, a tensão superficial obtida por cada modelo será diferente (GUZELLA et al, 2020).…”

“…Dos parâmetros da Equação 4.1, tem-se que R ini = 50 é o raio inicial da gota, (x 0 , y 0 ) é a coordenada do centro do domínio computacional e W = 5 é a espessura da interface (GUZELLA et al, 2020). O critério de convergência da simulação é definido por meio do erro relativo do campo de densidade entre iterações consecutivas, considerando um resíduo de 10 −8 .…”