1. NUMERICAL STUDY OF AL2O3-WATER NANOFLUID IN LAMINAR JET IMPINGEMENT
Abanti Datta, Sonal Kumar, Pabitra Halder
Department of Aerospace Engineering & Applied Mechanics
Indian Institute of Engineering Science and Technology Shibpur
National Conference on Advances in Thermal Engineering
September 23-24, 2016, Jadavpur University, Kolkata

2. Outline What is Nanofluid? Introduction to jet impingement
Literature review
Governing equations
Thermo-physical properties
Problem statement
Results
Conclusion
Reference
Sonal Kumar, Abanti Datta, Pabitra Halder

3. What is Nanofluid?
Nanofluids are suspensions of nanometer-sized solid particles or fibers (with average size below 100nm) involving a base fluid.
Nature is full of nanofluids, like blood, a complex biological nanofluid where different nanoparticles (at molecular level) accomplish different functions.
Nanoparticle materials include:
Oxide ceramics – Al2O3, CuO
Metal carbides – SiC
Nitrides – AlN, SiN
Metals – Al, Cu
Nonmetals – Graphite, carbon nanotubes
Base fluids include:
Water
Ethylene- or tri-ethylene-glycols and other coolants
Oil and other lubricants
Bio-fluids
Polymer solutions
Sonal Kumar, Abanti Datta, Pabitra Halder

4. Why use Nanofluids?
Nanofluids clearly exhibit improved thermo-physical properties such as thermal conductivity, thermal diffusivity, viscosity and convective heat transfer coefficient.
Nanoparticles stay suspended much longer than micro-particles and, if below a threshold level and/or enhanced with surfactants/stabilizers, remain in suspension almost indefinitely.
Furthermore, the surface area per unit volume of nanoparticles is much larger (million times) than that of microparticles (the number of surface atoms per unit of interior atoms of nanoparticles, is very large).
Sonal Kumar, Abanti Datta, Pabitra Halder

5. Introduction to Jet Impingement
Impinging jets have been widely used in industrial applications because they provide high localized heat transfer coefficients
Drying paper and textile products, cooling of gas turbine equipment and walls of combustion chambers, cooling of electronic components, material and production processes and freezing of tissues during surgery operations are some of the different application areas of impinging jets
Sonal Kumar, Abanti Datta, Pabitra Halder

6. Heat transfer enhancement in Jet Impingement
In order to obtain heat transfer enhancement in jet impingement flows various techniques such as inserting fins or foams can be employed
These kinds of techniques require modification in the applied system, however using nanofluids in the working fluid is a simple way for improving heat transfer rate and it does not require any constructional modification in the application systems
Sonal Kumar, Abanti Datta, Pabitra Halder

7. Application areas
Sonal Kumar, Abanti Datta, Pabitra Halder

8. Literature review
Roy et al. [1] Numerical investigation Al2O3/water nanofuids in the laminar regime. Reported enhancement in heat transfer of 200% while using nanofluid consisting of 10% volume fraction at Re = 1200
Palm et al. [2] Numerically investigation laminar-forced convection flow of nanofluids using Al2O3/water. For 4% volume fraction of nanoparticle, reported an increase of 25% in average wall heat transfer coefficient.
Sonal Kumar, Abanti Datta, Pabitra Halder

9. Governing equations Eulerian-Eulerian Two phase mixture model
For incompressible steady flow, the continuity equation for the mixture is: (1)
The momentum equation for the mixture can be expressed as:
(2)
Sonal Kumar, Abanti Datta, Pabitra Halder

10. The energy equation for the mixture is: (3)
The drift velocity for the secondary phase is defined as the velocity of the dispersed phase relative to that of the mixture velocity:
(4)
The relative velocity is defined as the velocity of the secondary phase relative to the primary phase velocity:
(5)
The drift velocity is related to the relative velocity:
(6)
Sonal Kumar, Abanti Datta, Pabitra Halder

11. Thermo-physical property models
Ref
Density
[6]
Specific heat
Thermal conductivity
[7]
Viscosity
Sonal Kumar, Abanti Datta, Pabitra Halder

12. Problem statement
The steady-state numerical predictions of local surface Nusselt number values are undertaken using the FLUENT 6.3 CFD numerical code
The program GAMBIT is used to create the numerical mesh for the predictions, using a grid with a total of 6.3*104
Sonal Kumar, Abanti Datta, Pabitra Halder

13. Parameters studied Inlet Reynolds number (Re) Nozzle diameter (D)
D = 10mm
Nozzle height from plate (H/D)
H/D = 4,10
Nanoparticle concentration ()
 = 0%, 1%, 4%, 6%
Nanoparticle size
40 nm
Nanoparticle material
Al2O3
Sonal Kumar, Abanti Datta, Pabitra Halder

14. Stream function variation as function of Re at fixed H/W=10 & ϕ=4%
Results
Stream function variation as function of Re at fixed H/W=10 & ϕ=4%
Sonal Kumar, Abanti Datta, Pabitra Halder

15. Temperature profile as function of Re at fixed H/W=10 ϕ=4%
Results
Temperature profile as function of Re at fixed H/W=10 ϕ=4%
Sonal Kumar, Abanti Datta, Pabitra Halder

16. Results
Profiles of stagnation point convective heat transfer coefficients as a function of Re for H/W = 4 & H/W = 10.
Sonal Kumar, Abanti Datta, Pabitra Halder

17. Results
Profiles average convective heat transfer coefficients as a function of Re
Sonal Kumar, Abanti Datta, Pabitra Halder

18. Average Nusselt number as a function of Re
Results
Average Nusselt number as a function of Re
Sonal Kumar, Abanti Datta, Pabitra Halder

19. Average Nusselt number as a function of ϕ
Results
Average Nusselt number as a function of ϕ
Sonal Kumar, Abanti Datta, Pabitra Halder

20. Conclusion Increasing H/D, for same nozzle diameter
Near the impingement surface, temperature grows and tends to decrease at edge of plate
Heat transfer enhancement is evident
Increasing nanoparticle concentration, increases fluid bulk temperature which elevated heat transfer rate of mixture
Moreover it is again proved that increasing Reynolds number as well as concentration increases convective heat transfer coefficient and Nusselt number compare to base fluid
A maximum increase of 30% in terms of average heat transfer coefficients is detected at φ = 6% for H/W = 10
Sonal kumar, Abanti Datta, Pabitra Halder

21. Reference
[1] Roy, G., C. T. Nguyen, and P. Lajoie. “Numerical investigation of laminar flow and heat transfer in a radial flow cooling system with the use of nanofluids.” Superlattices and Microstructures 35, no. 3 (2004)
[2] S. J.Palm, G. Roy, C. T. Nguyen. “Heat transfer enhancement with the use of nanofluids in radial flow cooling systems considering temperature-dependent properties.” Applied Thermal Engineering 26, no. 17 (2006)
[3] Fluent 6.2 User Manual, Fluent Incorporated, 2006.
[4] B.Sagot, G. Antonini, A. Christgen, F. Buron. “Jet impingement heat transfer on a flat plate at a constant wall temperature.” International Journal of Thermal Sciences 47, no. 12 (2008)
[5] F. R. Menter, “Two-equation eddy-viscosity turbulence models for engineering applications.” AIAA journal 32, no. 8 (1994)
[6] J. Buongiorno, “Convective transport in nanofluids.” Journal of Heat Transfer 128, no. 3 (2006)
[7] M. Corcione, “Empirical correlating equations for predicting the effective thermal conductivity and dynamic viscosity of nanofluids.” Energy Conversion and Management 52, no. 1 (2011)
Sonal Kumar, Abanti Datta, Pabitra Halder

22. Sonal Kumar, Abanti Datta, Pabitra Halder