A Conjugate Heat Transfer analysis on Exhaust Port Manifold using ANSYS Fluent
Introduction:
The analysis type of Conjugate Heat Transfer allows the simulation of the heat transfer between solid and fluid domains by exchanging thermal energy at the interface between them. Typical applications of this analysis type are the simulation of the heat exchanger, cooling of electronic equipment, and general-purpose cooling and heating system.
In most cases, heat transfer in solids, if only due to conduction, is described by Fourier\'s law of heat conduction.
`q=-k*gradT`
In most cases, heat transfer in fluids, if only due to convection, is described by Newton\'s law of cooling.
`q=h*gradT`
where,
q= heat flux
k=Thermal conductivity
h= Convective heat transfer coefficient
The Conjugate Heat transfer corresponds with the combination of heat transfer in solids and heat transfer in fluids.
Conjugate Heat Transfer Applications:
1) Heat exchanger - It exchanges heat from one fluid to another. The forced convection is the most common way to achieve a high heat transfer coefficient. The separation layers are made of solid. The conduction occurs through the separation layer.
2) Thermal insulators (eg. Polyurethane foam) - Polyurethane foam contains cavities of air which gives the insulation property to the material.
3) Heat sink - It dissipates the heat from electronic devices through convection.
4) Exhaust port manifold- It transfers the burned air mixture from all cylinders to exhaust system. the solid part of manifold takes heat from hot gas through convection. then the heat conducted through the solid part of the manifold. Finally, the heat dissipated through the outer surface of the manifold.
Fig. Exhaust port manifold for 4 cylinders in-line engine
Mesh details:
| Baseline Mesh | Refined Mesh | |
| Number of elements | 137385 | 442238 |
| Element size | 0.15 m |
0.01 m (solid domain), 0.1 m (fluid domain) |
| Number of Inflation Layers | Nil | 5 |
The Academic version of Ansys has an element count limit of 0.5 million. Hence, the maximum number of elements have been limited to 0.45 million.
Fig. Mesh details
The above pictures show that the mesh details of inflation layers, Fluid and solid domain.
Simulation details:
Type of simulation: Steady-state
Type of model: K-epsilon (Turbulence model)
Material Properties:
The material of Exhaust manifold: Aluminum
Working fluid: Air
Air:
Density = 1.225 `(Kg)/(m^3)`
Specific heat `c_p`=1006.43 `J/(Kg*K)`
Thermal conductivity = 0.0242 `W/(m*K)`
Viscosity = 1.7894e-5 `(Kg)/(m*s)`
Aluminum:
Density = 2719 `(Kg)/(m^3)`
Specific heat `c_p` = 871 `J/(Kg*K)`
Thermal conductivity = 202.4 `W/(m*K)`
Boundary condition:
Inlet air velocity = 5 m/s
Inlet air temperature = 700 K
Outlet pressure = 0 Pa
Outer suface of Exhaust manifold: Wall
Thermal condition = Convection
Heat transfer coefficient = 20 `W/(m^2*K)`
Solution method: Pressure-Velocity coupling
The above details are used to simulate the problem for both baseline mesh condition and refined mesh condition.
Results from Baseline simulation:
1)
From the above residual plot, it was evident that residuals from all the equations start making repetitive profile after the 250th iteration. Hence, the solution has converged at 250th iteration.
2)
The above picture shows that the velocity streamlines of flow. The flow has the highest velocity at throat region of the outlet manifold.
3)
The above velocity contour shows the velocity distribution of the outlet manifold region. The maximum velocity was 37.7 m/s at near to the throat region.
4)
The above contour shows that temperature contour of the outer surface of the exhaust manifold.
5)
The above temperature contour shows the temperature distribution of the outlet manifold region.
6)
The above contour shows the heat transfer coefficient of the outlet manifold region. The heat transfer coefficient value was varied from 0 to 101.1 `W/(m^2*K)`.
Results from the refined simulation:
1)
From the above residual plot, it was evident that residuals from all the equations start making repetitive profile after the 80th iteration. Hence, the solution has converged at 80th iteration.
2)
The above picture shows that the velocity streamlines of flow. The flow has the highest velocity at throat region of the outlet manifold.
3)
The above velocity contour shows the velocity distribution of the outlet manifold region. The maximum velocity was 40.13 m/s at near to the throat region.
4)
The above contour shows that temperature contour of the outer surface of the exhaust manifold.
5)
The above temperature contour shows the temperature distribution of the outlet manifold region.
6)
The above contour shows the heat transfer coefficient of the outlet manifold region. The heat transfer coefficient value was varied from 0 to 208.7 `W/(m^2*K)`.
Verification of HCT prediction from simulation results:
1) For fully developed turbulent flow in a smooth circular tube, the local Nusselt number may be obtained from the well-known Dittus-Boelter equation. This equation is easy to solve but less accurate when there is a large temperature difference across the fluid and is less accurate for the rough tube.
Correlation: `Nu_(Dh)=0.023*Re_(Dh)^0.8*Pr^(0.4)`
Where,
Dh - Hydraulic diameter
Re - Reynolds number
Pr - Prandtl number
Nu - Nusselt number
Validity: `0.6<=Pr<=160`
`Re_(Dh)>10000`
`L/D>10`
In our case, the Nusselt number was 353.6. It was obtained from using the maximum velocity of flow.
`Nu_(Dh)=(h*D_h)/k`
From the above equation, the value of heat transfer coefficient was 50.336. In simulation results, the heat transfer coefficient varied from 0 to 208.7. The results obtained from solving the Dittus-Boelter equation is within the range of results from the simulation.
2) Grid dependence test
Conclusions:
1) The results obtained from baseline mesh and refined mesh followed the same pattern of contour. But the magnitude of the temperature and velocity are slightly varied.
2) The simulation results obtained from simulation were verified using the Dittus-Boelter equation.
3) The accuracy of the prediction depends on mesh quality, Number of elements, usage of Inflation layers.