Simulation of copper–water nanofluid in a microchannel in slip flow regime using the lattice Boltzmann method

Karimipour, Arash; Nezhad, Alireza Hossein; D’Orazio, Annunziata; Esfe, Mohammad Hemmat; Safaei, Mohammad Reza; Shirani, Ebrahim

doi:10.1016/j.euromechflu.2014.08.004

Cited by 240 publications

(79 citation statements)

References 64 publications

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“…Thus, the Nu decreases by increasing x, regardless of the volume concentration. Most of the previous reports ignored the temperature jump [18], [34] and [35] except [36].…”

Section: Resultsmentioning

confidence: 99%

LBM Analysis of Micro-Convection in MHD Nanofluid Flow

Sunil

Kumar

2017

Stroj. vest. - Jour. Mech. Eng.

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“…Thus, the Nu decreases by increasing x, regardless of the volume concentration. Most of the previous reports ignored the temperature jump [18], [34] and [35] except [36].…”

Section: Resultsmentioning

confidence: 99%

LBM Analysis of Micro-Convection in MHD Nanofluid Flow

Sunil

Kumar

2017

Stroj. vest. - Jour. Mech. Eng.

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“…The lattice Boltzmann method (LBM) is a powerful numerical technique based on kinetic theory for simulating fluid flows and modeling the physics in fluids and nanofluids (Succi, 2001;Yu et al, 2003;Karimipour et al, 2015). In comparison with the conventional CFD methods, the advantages of LBM include simple calculation procedure, simple and efficient implementation for parallel computation, easy and strong handling of complex geometries, and others.…”

Section: Introductionmentioning

confidence: 99%

A Double Multi-Relaxation-Time Lattice Boltzmann Method for Simulation of Magneto Hydrodynamics Natural Convection of Nanofluid in a Square Cavity

Rahmati

Najjarnezami

2016

JAFM

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In this work, for the first time, a double multi-relaxation-time lattice Boltzmann method (2-MRT-LBM) is proposed to simulate MHD natural convection of nanofluid in a two-dimensional square cavity. The cavity is filled with TiO 2 -water nanofluid and is get under a uniform magnetic field at different angles with respect to horizontal plane. The proposed numerical scheme is solved the flow field and the temperature field using MRT-D2Q9 and MRT-D2Q5 lattice model, respectively. So, the main objective of this work is to show the effectiveness of this model to predict the effects of pertinent parameters such as the Rayleigh number (10 3 < Ra < 10 7 ), the solid volume fraction (0 % <  < 5 %), the Hartmann number (0 < Ha < 60) and the magnetic field angle (0 < < 90) on the flow field and temperature field and the heat transfer performance of the cavity. The obtained results indicate that the proposed method is a powerful approach to simulate the MHD natural convection of nanofluids in a square cavity. Also the numerical results show that for Ra = 10 5 and for the range of Hartmann number of this study, the heat transfer and fluid flow depend strongly upon the direction of magnetic field. Furthermore, the magnetic field influence on the effect of nanoparticles on the heat transfer enhancement is not significant.

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“…Boltzmann method, which is utilized for the numerical simulation of flow and heat transfer, was used to study the convection heat transfer of nanofluids in an enclosure by Karimipour et al [3][4][5][6][7]. The CFD model was used by Skovgaard and Nielsen [8] to simulate indoor air flow, and CFD technology was adopted in air conditioning engineering.…”

Section: Mathematical Problems In Engineeringmentioning

confidence: 99%

Optimization of Indoor Thermal Comfort Parameters with the Adaptive Network‐Based Fuzzy Inference System and Particle Swarm Optimization Algorithm

Yin

Shi

et al. 2017

Mathematical Problems in Engineering

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The goal of this study is to improve thermal comfort and indoor air quality with the adaptive network-based fuzzy inference system (ANFIS) model and improved particle swarm optimization (PSO) algorithm. A method to optimize air conditioning parameters and installation distance is proposed. The methodology is demonstrated through a prototype case, which corresponds to a typical laboratory in colleges and universities. A laboratory model is established, and simulated flow field information is obtained with the CFD software. Subsequently, the ANFIS model is employed instead of the CFD model to predict indoor flow parameters, and the CFD database is utilized to train ANN input-output "metamodels" for the subsequent optimization. With the improved PSO algorithm and the stratified sequence method, the objective functions are optimized. The functions comprise PMV, PPD, and mean age of air. The optimal installation distance is determined with the hemisphere model. Results show that most of the staff obtain a satisfactory degree of thermal comfort and that the proposed method can significantly reduce the cost of building an experimental device. The proposed methodology can be used to determine appropriate air supply parameters and air conditioner installation position for a pleasant and healthy indoor environment.

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Simulation of copper–water nanofluid in a microchannel in slip flow regime using the lattice Boltzmann method

Cited by 240 publications

References 64 publications

LBM Analysis of Micro-Convection in MHD Nanofluid Flow

LBM Analysis of Micro-Convection in MHD Nanofluid Flow

A Double Multi-Relaxation-Time Lattice Boltzmann Method for Simulation of Magneto Hydrodynamics Natural Convection of Nanofluid in a Square Cavity

Optimization of Indoor Thermal Comfort Parameters with the Adaptive Network‐Based Fuzzy Inference System and Particle Swarm Optimization Algorithm

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