Week 6: Conjugate Heat Transfer Simulation
Objective: To simulate the flow through the solid pipe "Conjugate Heat transfer" and understand super cycling.
We have to perform the following tasks:
Baseline configuration
- Setup a flow simulation through a pipe
- Inlet Reynolds number should be 7,000
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Hint: Use the below formula to calculate velocity for the corresponding value of REYNOLD NUMBER and give DIRICHLET BC for the velocity at the inlet and specify the value for velocity calculated at Inlet BC using the below formula,
Re = (rho*V*D)/(Dynamic viscosity)
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- Turbulence modeling - K-Epsilon
- Super cycling parameters - same as in the video
Additional 3D outputs
- Add Y+ to your post.in file
Grid dependence test
- Start with an initial base grid
- Run grid dependence test on 3 grids and show that the outlet temperature converges to a particular value
Effect of supercycle stage interval
- Set supercycle stage interval to 0.01,0.02 and 0.03
- For these three values, how does the total simulation time compare against the baseline configuration
Brief description of why and where a CHT analysis is used.
The term conjugate heat transfer (CHT) is used to describe processes that involve variations of temperature within solids and fluids, due to thermal interaction between the solids and fluids. The exchange of thermal energy between the two physical bodies is called the study of Heat Transfer, the rate of transferred heat is directly proportional to the temperature difference between the bodies. A typical example is the heating or cooling of a solid object by the flow of air in which it is immersed and some other example includes conduction through solids, free and forced convection in the gases/fluids, and thermal radiation. Typical applications of this analysis type exist as, but are not limited to, the simulation of heat exchangers, cooling of electronic equipment, and general-purpose cooling and heating systems.
Conjugate heat transfer corresponds with the combination of heat transfer in solids and heat transfer in fluids. In solids, conduction often dominates whereas, in fluids, convection usually dominates. Efficiently combining heat transfer in fluids and solids is the key to designing effective coolers, heaters, or heat exchangers. Forced convection is the most common way to achieve a high heat transfer rate. In some applications, the performances are further improved by combining convection with phase change (for example liquid water to vapor phase change).
Heat transfer in solids and heat transfer in fluids are combined in the majority of applications. This is because fluids flow around solids or between solid walls and because solids are usually immersed in a fluid.
Modes of heat transfer
- Conduction: diffusion of heat due to temperature gradients. A measure of the amount of conduction for a given gradient is heat conductivity.
- Convection: when heat is carried away by moving fluid. The flow can either be caused by external influences, forced convection; or by buoyancy forces, natural convection. Convective heat transfer is tightly coupled to the fluid flow solution.
- Radiation: transfer of energy by electromagnetic waves between surfaces with different temperatures, separated by a medium that is at least partially transparent to the (infrared) radiation. Radiation is especially important at high temperatures, e.g. during combustion processes, but can also have a measurable effect at room temperatures.
An accurate description of heat transfer modes, material properties, flow regimes, and geometrical configurations enables the analysis of temperature fields and heat transfer.
Typical design problems involve the determination of:
- Overall heat transfer coefficient, e.g. for a car radiator.
- The highest (or lowest) temperature in a system, e.g. in a gas turbine, chemical reaction vessels, food ovens.
- Temperature distribution (related to thermal stress), e.g. in the walls of a spacecraft.
- Temperature response in time-dependent heating/cooling problems, e.g. engine cooling, or how fast does a car heat up in the sun and how is it affected by the shape of the windshield?
The fluid flow and heat transfer problems can be tightly coupled through the convection term in the energy equation and when physical properties are temperature dependent. While analytical solutions exist for some simple problems, we must rely on computational methods to solve most industrially relevant applications.
CHT can be performed to improve the cooling performance of the water jacket and increase engine life. Advancements in cooling for applications such as gas turbine components require an improved understanding of the complex heat transfer mechanisms and the interactions between those mechanisms, which our engineers can perform without hassle. Critical cooling applications often rely on multiple thermal protection techniques, including internal cooling, external film cooling, etc. which are efficiently used by our analysis to cool components and limit the use of coolant. We do extensive support for Motor and Battery CHT Analysis to get the optimized design for High voltage systems. Conjugate Heat Transfer analysis provides the temperature distribution in solid and coolant of the engine and clear insight on velocity distribution and mechanism of heat transfer of coolant. Results of CHT analysis become input to structural simulations as thermal loads.
We have a wide experience in Engine CHT Analysis for various types of engines like Bikes, Passenger Cars, Racing cars, Commercial Vehicles, Marine, Agricultural equipment and Earth-moving equipment, etc.
Mathematical Modeling
The flow of thermal energy from matter occupying one region in space to matter occupying a different region in space is known as heat transfer. Heat transfer can occur by three main methods:
- Conduction
- Convection
- Radiation
Physical models involving conduction and/or convection only are the simplest while buoyancy-driven flow or natural convection and radiation models are more complex.
Super Cycling Concept
Super cycling is a technique that is used in Converge studio in the case of conjugate heat transfer problems with solid and liquid regions. The main problem is that both solvers cannot run at the same speed since solving in the fluid domain is much faster owing to the time scale difference for heat transfer in liquids as compared to the solids. This causes problems during the solution given that the solid side solver would not have reached a steady state/convergence in the time the liquid solver does. This is where the concept of super cycling is based.
The basic idea of super cycling is that the solver for the fluid domain is paused until the solver for the solid domain converges. The following steps are involved in performing the super cycling
- Solve the fluid and the solid together with the transient solver. store the instantaneous Heat transfer coefficients and temperature on the interface during the process.
- Freeze the fluid solver. Time-averages the Heat transfer coefficients and temperatures and applies them as boundary conditions at the interface.
- Solves the solid temperature until it reaches a steady state.
- Update the solid temp field and unfreezes the fluid solver.
- Repeat until the solid temp converges.
Geometry:
Diagnosis result: (before case setup)
Boundary Flagging:
Simulation Case setup:
- Application type: Time based
- Materials:
(a) Predefined mixtures = Air
(b) Solid simulation
(c) Global transport parameters
(d) Species
- Simulation Parameters:
(a) Run Parameters
(b) Simulation Time Parameters:
(c) Solver Parameters [Transient-State]:
- Boundary Conditions:
(a) Solid outer wall
(b) Solid side
(c) Inlet
(d) Outlet
(e) Interface
- Regions and Initialization:
(a) Fluid region
(b) Solid region
- Physical Models:
Click on Physical Models and select Turbulence Modeling and Super-cycle modeling in this case.
- Turbulence modeling:
- Super-cycle modeling:
- Grid Control:
- Output Files:
Results:
Case 1:
For Mess size: 0.001
- Mess
- Pressure contour
- Velocity contour
- Y plus
- Temperature contour
- SC_AVG_HTC
- SC_AVG_Temp
Case 2:
For Mess size: 0.002
- Mess
- Pressure contour
- Velocity contour
- Y plus
- Temperature contour
- SC_AVG_HTC
- SC_AVG_Temp
Case 3:
For Mess size: 0.003
- Mess
- Pressure contour
- Velocity contour
- Y plus
- Temperature contour
- SC_AVG_HTC
- SC_AVG_Temp
Plots:
- Fluid side temperature
- Solid side temperature
- Supercycle at the monitor point (-0.0078, 0.015665, 0.18):
- Fluid Side Mean temperature
- Solid Side Mean Temperature
- Supercycle at the monitor point
Conclusion:
Results discussion of mesh independency:
- In this challenge, we performed the conjugate heat transfer analysis in a solid pipe.
- We have performed the grid independency test with 0.001m, 0.002m, and 0.003m. From the above plots, we can clearly say that as the mesh is finer, the accuracy of the results increases. But when the mesh goes finer and finer the computational cost has been increased.
| Mesh size | 0.001 | 0.002 | 0.003 |
| Fluid mean temperature(K) | 353.285 | 351.738 | 345.402 |
| Solid mean temperature(K) | 665.76 | 745.452 | 823.746 |
| Computational time used by the program(S) | 21389.769258 | 1287.318420 | 346.041404 |
Results discussion of the effect of supercycle stage:
We set the supercycle stage interval, i.e time length for each cycle stage from supercycle modeling is used 0.01, 0.02, and 0.03. And for a smaller value of supercycle stage interval, the convergence is achieved faster. A monitor point is also created in the solid thickness boundary to observe the effects of super cycling. The plot shows that the steady state solver is employed in the solid region at fixed intervals of time (i.e. the super-cycle stage interval) and the results are compared while the transient solver computing the fluid flow is temporarily paused. Super-cycling is done as the heat flow in the solids when depicted by a transient solver, is time-consuming. Hence it is better to apply steady-state analysis for the heat transfer through the solid while studying the behavior of fluid flow through the pipe.
The temperature profile in the solid region
As we mentioned above, the steady-state solver is employed in the solid region resulting in the sudden increase in temperature at various time intervals. This does not represent the actual temperature flow in the solid and only the steady-state temperature. Note that the increase in the temperature in the solid regions is due to the heat flux added to the solid outer wall.
The temperature profile in the fluid region
The transient solver is used to simulate the flow in the fluid region and hence the actual increase in the temperature is observed in this case. The increase in temperature is due to the transfer of heat from the solid to the fluid.