A smoothed particle hydrodynamics approach for numerical simulation of nano-fluid flows

Application to forced convection heat transfer over a horizontal cylinder
  • Hossein Nasiri
  • Mohammad Yaghoub Abdollahzadeh Jamalabadi
  • Reza Sadeghi
  • Mohammad Reza Safaei
  • Truong Khang Nguyen
  • Mostafa Safdari Shadloo
Article
  • 41 Downloads

Abstract

Nano-fluidic flow and heat transfer around a horizontal cylinder at Reynolds numbers up to 250 are investigated by using weakly compressible smoothed particle hydrodynamics (WCSPH). To be able to simulate enhanced nanoparticle heat transfer, this manuscript describes for the first time a development that allows conductive and convective heat transfer to be modelled accurately for the Eckert problem using WCSPH. The simulations have been conducted for Pr = 0.01–40 with nanoparticle volumetric concentrations ranging from 0 to 4%. The velocity fields and the Nusselt profiles from the present simulations are in a good agreement with the experimental measurements. The results show that WCSPH is appropriate method for such numerical modelling. Additionally, the results of heat transfer characteristics of nano-fluid flow over a cylinder marked improvements comparing with the base fluids. This improvement is more evident in flows with higher Reynolds numbers and higher particle volume concentration.

Keywords

Smoothed particle hydrodynamics (SPH) Weakly compressible Nanoparticles Nano-fluid Forced convection 

List of Symbols

Mathematical Characters

B

Constant in equation of state

co

Artificial speed of sound

Cp

The specific heat at constant pressure

Cv

The specific heat at constant volume

D

Cylinder diameter

e

Energy of a given particle

f

Arbitrarily function

h

Smoothing length or support dimension

H

Computational domain height

k

Thermal conductivity of fluid

L

Computational domain length

m

Mass of a given particle

Nu

Nusselt number

P

Pressure acting on the particle

Pr

Prandtl number

Q

Heat flux terms in energy equation

r

Distance between the centres of a couple of particles

r

Position vector identifying the equilibrium state

Re

Reynolds number

t

Time

T

Temperature

u

Velocity component along x-axis

v

Velocity component along y-axis

V

Volume of the particle i

W

Kernel or smoothing function

x

The first Cartesian coordinate axis

y

The second Cartesian coordinate axis

Greek Symbols

δ

Dirac delta function

σ

Stress tensor

μ

Viscosity coefficient

ρ

Mass density

ν

Kinematic viscosity

γ

Constant in state equation

φ

Nanoparticle volume fraction

ε

Parameter of artificial viscous heating

Subscripts

0

Value for reference condition

Cut

Cutting radius

i

Particle of interest

j

Neighbour particle

f

Fluid

nf

Nano-fluid

s

Solid nanoparticle

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Copyright information

© Akadémiai Kiadó, Budapest, Hungary 2018

Authors and Affiliations

  • Hossein Nasiri
    • 1
  • Mohammad Yaghoub Abdollahzadeh Jamalabadi
    • 2
  • Reza Sadeghi
    • 3
  • Mohammad Reza Safaei
    • 4
    • 5
  • Truong Khang Nguyen
    • 4
    • 5
  • Mostafa Safdari Shadloo
    • 6
  1. 1.Department of Mechanical EngineeringDaneshpajoohan Higher Education InstituteIsfahanIran
  2. 2.Department of Mechanical, Robotics and Energy EngineeringDongguk UniversitySeoulRepublic of Korea
  3. 3.Department of Mechanical EngineeringUniversity of TehranTehranIran
  4. 4.Division of Computational Physics, Institute for Computational ScienceTon Duc Thang UniversityHo Chi Minh CityVietnam
  5. 5.Faculty of Electrical and Electronics EngineeringTon Duc Thang UniversityHo Chi Minh CityVietnam
  6. 6.CORIA-UMR 6614, Normandy University, CNRS-University & INSA of RouenRouenFrance

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