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Advanced Tutorial: Natural Convection of a LED Spotlight

This tutorial shows how to perform a natural convection simulation on a LED spotlight, aiming to satisfy maximum temperature requirements.

led cht simulation streamilines temperature distribution
Figure 1: Streamlines and temperature distribution on an LED

This tutorial teaches how to:

  • Set up and run a natural convection simulation using the Conjugate heat transfer v2.0 solver;
  • Assign boundary conditions, material, and other properties to the simulation;
  • Mesh with the SimScale standard meshing algorithm.

We are following the typical SimScale workflow:

  1. Prepare the CAD model for the simulation.
  2. Set up the simulation.
  3. Create the mesh.
  4. Run the simulation and analyze the results.

Did you know?

For applications with LEDs, it’s important to control the temperatures developing on the chips. A poor design, with high temperatures, is harmful to the lifetime of a LED package.

In this tutorial, we will simulate how effective natural convection is in cooling our geometry:

resulting natural convection led geometry
Figure 2: The hot air next to the LED rises and draws cold air from the surroundings, generating a natural convection.

1. Prepare the CAD Model and Select the Analysis Type

As a first step, please click on the button below. It will import the tutorial project directly into your Workbench.

The following picture demonstrates what should be visible after importing the tutorial project:

import led model simscale workbench
Figure 3: A quarter of the LED spotlight geometry in the SimScale Workbench.

Note that the project contains two geometries. The first one consists of the complete LED spotlight geometry, and the second one consists of a 90 degrees slice.

Did you know?

It’s possible to use the symmetrical nature of the LED spotlight geometry in our favor. Since we expect the flow to be mirrored along the symmetry planes, we can use just a quarter of the geometry. This brings a series of benefits, such as:

– Allows faster meshing operations and simulation runs
– Possibility to use finer cells, thus improving the domain discretization

symmetry plane led geometry cooling electronics
Figure 4: Top view, highlighting the symmetry planes (in red), and the quarter geometry used in this tutorial.

1.1. Create an Enclosure

The initial CAD geometry only contains the LED spotlight parts. Therefore, it’s necessary to create an external air domain. In SimScale, this is possible with an enclosure operation.

To do that, please right-click on the LED Spotlight – Quarter Geometry and select an ‘Enclosure‘ operation.

enclosure creation simscale
Figure 5: The enclosure operation will create the external air domain, to simulate natural convection.

The enclosure should be large enough to prevent the boundary conditions from interfering with the results. In Figure 6, you will find a good rule of thumb for the enclosure dimensions:

rule of thumb for enclosure creation natural convection led
Figure 6: Rule of thumb for the enclosure dimensions in natural convection of electronics.
  • Top: 6 times the height of the LED spotlight
  • Down: 4 times the height of the geometry
  • Sides: 8 times the width of the geometry

Please set up the enclosure dimensions as in Figure 7:

enclosure dimensions flow volume extraction operation domain
Figure 7: Enclosure dimensions for the present tutorial.
  1. Enable Keep existing parts. This step is important for conjugate heat transfer simulations. This way, the solid parts won’t get deleted during the enclosure operation.
  2. Set the enclosure dimensions to the following:
    • Minimum (x) value: 0 meters
    • Minimum (y) value: -0.3 meters
    • Minimum (z) value: 0 meters
    • Maximum (x) value: 0.25 meters
    • Maximum (y) value: 0.4 meters
    • Maximum (z) value: 0.25 meters
  3. ‘Start’ the operation.

1.2. Imprint Operation

Another important step is to run an Imprint operation. In our LED geometry, a series of interfaces between solid/solid and solid/flow regions are present. The imprint operation improves the automatic detection of such interfaces.

Using Figure 5 as a reference, create an Imprint operation and click ‘Start’.

1.3. Create the Simulation

Figure 8 shows the Workbench once the Imprint operation finishes running. Click on the ‘Create Simulation’ button to proceed.

creating a new simulation led geometry
Figure 8: Result of the enclosure and imprint operations.

The analysis type choice widget opens up. From the options, pick ‘Conjugate heat transfer v2.0’ and ‘Create the Simulation’:

conjugate heat transfer 2.0 analysis type
Figure 9: Analysis type choice widget.

As a result of a strongly coupled energy equation, the Conjugate heat transfer v2.0 analysis type provides much faster convergence rates, in comparison to the conventional Conjugate heat transfer (CHT).

Did you know?

The analysis type you choose within the simulation library depends on what results you are interested in, and what given parameters you have.

  • With a Conjugate Heat Transfer (CHT or CHT v2.0) analysis type, it’s possible to simulate heat transfer between solids and also between the solid and fluid domains. This is the common choice for electronics cooling.
  • If you are only interested in the heat transfer within solids, you can simplify the simulation process by performing a Heat Transfer analysis.
  • Lastly, for simulating heat transfer only in the fluid domain, the appropriate analysis type is a Convective Heat Transfer.

After creating a simulation, the simulation tree will be visible in the left-hand side panel. It’s necessary to set up all entries to be able to run the simulation. At this point, SimScale will also automatically detect all Contacts within the geometry. In our case, there are a total of 64 interfaces.

The global simulation settings remain as default, as in Figure 10. Since it’s a natural convection simulation, the velocities in the domain are small, and a ‘Laminar’ turbulence model is appropriate.

simulation tree set up entries led geometry
Figure 10: The left-hand side panel contains the simulation tree.

Did you know?

In natural convection simulations, where the temperature gradients in the air domain are small, it’s common to use the Boussinesq approximation to account for buoyancy.

In Figure 10, one can use the Boussinesq approximation by keeping Compressible toggled off. For further information, please check this documentation page about buoyancy.

2. Assigning the Material and Boundary Conditions

In the following sections, we will set up the physics of the simulation.

2.1. Model

In the Model tab, it’s possible to define the direction and magnitude of gravity:

gravity definition simscale natural convection led
Figure 11: The gravity direction is based on the orientation cube, in the bottom-right of the viewer.

Please define gravity as ‘-9.81’ \(m/s^2\) in the y-direction.

2.2. Defining the Materials

In conjugate heat transfer simulations, it’s necessary to define both solid and fluid materials. Let’s first go through the fluid domain.

Important

Each volume in the domain needs to receive one material assignment.

Assigning more than one material to a volume or leaving parts without any assignments will result in an error.

2.2.1 Fluid Materials

To add a fluid material, please click on the ‘+ button’ next to Fluid:

adding fluid material in simscale
Figure 12: Adding a new fluid material.

The fluid material library pops up. From the list, choose ‘Air‘:

library of fluid materials
Figure 13: Library of fluid materials.

The geometry contains two air regions: one internal to the LED, and the external flow region. You can use the right-hand side panel to quickly select the volumes.

assigning fluid materials led geometry
Figure 14: Using the right-hand side panel to assign materials.

Did you know?

For this tutorial, we will use the default values for the air properties. It’s possible, however, to edit each one of the values from Figure 14 by clicking on them. Find more details about using custom materials in this article.

2.2.2 Solid Materials

Let’s now add the solid materials. First, click on the ‘+ button’ next to Solids, as in figure 12. This time, a library of solid materials appear.

From the list, please choose ‘PVC’, which is a common material for circuit boards:

library of solid materials
Figure 15: Library of solid materials.

The materials library contains common properties for PVC. In this tutorial, PVC is used in a circuit board, so we will adjust the material properties to account for the circuits. Figure 16 shows the changes:

custom materials in simscale
Figure 16: Custom properties for PVC. Click on the fields to edit them.
  • Set \((\kappa)\) Thermal conductivity to 2.5 \(\frac {W}{m.K}\).
  • The new Specific heat is 1004 \(\frac {J}{kg.K}\).
  • Set \((\rho)\) Density to 1900 \(\frac {kg}/{m^3}\).
  • Lastly, assign the Board volume.

All the remaining solid materials maintain the default settings. Find below a list of materials and the respective assignments.

  • Aluminium: Core
  • Brass: Connector Base
  • Copper: Connector Pin
  • Glass: Glass
  • Silicon: 0.25 W Chip, 0.5 W Chip, and 1 W Chip

2.3. Initial Conditions

In CFD simulations, it’s a good practice to initialize the parameters close to the expected solution. With this approach, it’s possible to improve the convergence rate of a simulation, achieving the final result faster.

In this tutorial, we will change the initialization of temperature and velocity.

Did you know?

In SimScale, there are two ways to define the initialization of a parameter:

  • Uniform initialization, which initializes a parameter in the entire domain with the same value
  • Subdomain initialization, which initializes a parameter in specific volumes within the domain

For additional information on domain initialization, please visit this documentation page.

2.3.1 Temperature

The LED geometry contains three chips, which are dissipating heat. From a design perspective, it’s important to keep the chip temperatures under control, otherwise, the lifetime of the LED gets shorter.

Usual temperatures on the chips are around 100°C, thus, initializing the LED parts at 75°C is a good initial guess. Figure 17 shows the initial steps for initialization with subdomains.

subdomain initialization simscale temperature
Figure 17: Initializing the temperature of the LED parts via subdomains.
  1. Add a new subdomain by clicking on the ‘+ button’ next to Subdomains.
  2. Input the initialization value, in this case, 75°C.

We want to assign all the LED parts to this subdomain. The quickest way to do that is by using an Invert visible assignment function. Please proceed as below:

invert visible assignments simscale
Figure 18: Using the invert visible assignment feature to quickly select the 9 LED volumes.
  1. Select the Flow region volume.
  2. By right-clicking in the viewer, a window with options appears.
  3. Click on Invert visible assignment. This way, the 9 LED volumes are assigned.

2.3.2 Velocity

As a result of the high temperatures on the LED geometry, a natural convection plume develops. Therefore, we strongly recommend initializing the velocity field around the LED, which enhances the convergence rate of the simulation.

natural convection plume
Figure 19: Natural convection plume on the LED geometry.

In this tutorial, we will initialize the velocity field using a cylinder geometry primitive, which is a good option for the shape of the LED geometry. Figure 20 shows the initial steps:

natural convection initialization for velocity
Figure 20: Subdomain initialization for velocity.
  1. Add a new subdomain by clicking on the ‘+ button’ next to Subdomains.
  2. Using the orientation cube as a reference, initialize the velocity in the y-direction with 0.05 \(m/s\).
  3. Click on the ‘+ button’ next to Geometry primitives and select a Cylinder.

Now, a window opens up, where the user can define the cylinder orientation and dimensions. Using a cylinder slightly wider than the LED geometry yields good results. Therefore, please input the values from Figure 21:

cylinder initialization geometry primitives
Figure 21: Cylinder dimensions for the velocity initialization. The cylinder extends from the bottom to the top of the domain.

After saving the cylinder primitive, make sure to assign it to the subdomain initialization.

Important

The optimal value for the velocity initialization may vary from case to case. For natural convection applications, initializing velocity with velocities between 0.05 and 0.2 m/s provides a very good convergence in most cases.

2.4. Boundary Conditions

For boundary condition definition, we will use Figure 22 as reference:

boundary condition overview domain for natural convection led
Figure 22: Overview of the boundary conditions for the LED geometry.

2.4.1 Natural Convection Inlet/Outlet

The natural convection inlet/outlet boundary condition is exclusive to SimScale. This boundary condition allows fluid to go in and out of the domain, therefore it’s a good option when it’s not clear what the flow behavior will be. For more details on the mathematical implementation, see this dedicated documentation page.

To create a new boundary condition, click on the ‘+ button’ next to Boundary conditions, and select the desired type from the drop-down menu.

boundary condition creation
Figure 23: Creating a new boundary condition in the SimScale Workbench.

Using figure 22 as a reference, the top, bottom, and both side faces will receive a natural convection inlet/outlet boundary condition.

natural convection inlet/outlet set up
Figure 24: With this configuration, the flow entering the domain via the boundaries is at 19.85 K.

2.4.2 Symmetry

Please create a second boundary condition, as in figure 21. This time, however, select a Symmetry condition:

symmetry boundary condition flow field
Figure 25: Symmetry boundary condition assignment.

Note

Please note that all 16 faces in the symmetry plane receive a symmetry boundary condition. This includes all faces shown in Figure 26.

symmetry faces boundary condition cfd
Figure 26: All faces in the symmetry planes receive a symmetry boundary condition.

2.5. Advanced Concepts

Additionally, the geometry contains three chips, which will be defined as power sources. Figure 27 contains further details:

power source led
Figure 27: The quarter of LED geometry contains three chips, ranging from 0.25 to 1 watt

In SimScale, there are two types of Power sources:

  • Absolute power source: the user defines the heat flux in \(W\) or \(\frac {btu}{s}\)
  • Specific power source: the definition of the flux is in \(W/m^3\) or \(\frac {btu}{s.in^3}\)

Hence, the Absolute power source works best in our case, as we already know the exact heat flux in each chip.

Please proceed to set up the first power source, as in Figure 28:

power source creation steps
Figure 28: Creating a new power source in SimScale
  1. Create a new power source by clicking on the ‘+ button’ next to Power sources.
  2. Select an Absolute power source and set the heat flux to 1 watt.
  3. Assign the 1 W Chip volume to this power source, which can be done using the right-hand side geometry panel in the Workbench.

Please create two new power sources, for the 0.5 W Chip and the 0.25 W Chip volumes. Follow the same steps outlined above, remembering to adjust the Heat flux accordingly.

2.6. Numerics & Simulation Control

The default settings in the Numerics tab work well for most simulations. In this tutorial, no changes are required.

In the Simulation control tab, it’s possible to define a series of parameters that control the simulation process, including the number of iterations to perform, and the maximum runtime for the simulation run. Figure 29 highlights the changes in the simulation control tab:

simulation control settings
Figure 29: End time controls the number of iterations to perform in the simulation.
  • Define an End time of 750 iterations and a Write interval of 750 iterations. With these settings, only the result set from the last iteration will be written, which is a common practice for steady-state simulations.
  • Change the Maximum runtime of the simulation to 30000 seconds.

Did you know?

In a steady-state simulation, the End time and Delta t parameters control the number of iterations to be performed.

For more notes on the simulation control settings, please visit the following page: How to set up simulation control parameters in a steady-state CFD analysis.

2.7. Results Control

Setting up result controls is a crucial step in a simulation. Since they help us to assess convergence, it’s important to set meaningful result controls for our parameters of interest.

For a LED simulation, some parameters of interest are, for example, the temperature on the chips. Therefore, we will set Area average result controls on them. To do that, please proceed as in Figure 30:

area average result control led chip
Figure 30: As an output of this result control, we will receive average levels of the parameters on selected faces.
  1. Create a new Area average control by clicking on the ‘+ button’ next to Surface data.
  2. Define a Write interval of 5 iterations. This way, the algorithm will plot the area averages every 5 iterations, which is good enough for steady-state.
  3. To make the face selection easier, please hide the Board volume, by clicking on the ‘eye icon’ next to it.
  4. For the first result control, please select the top face of the 1-watt chip.

Afterward, following the same procedure, please create two additional area average controls, for the top faces of the 0.5 W Chip and the 0.25 W Chip.

3. Mesh

For the meshing operation, we recommend using the standard algorithm, which is a good choice in general, as it is quite automated and delivers good results for most geometries.

After clicking on Mesh in the simulation tree, a setup window opens. The main default settings are good for an initial study. Under Advanced settings, please set the Number of gap elements to 3.

standard mesh main settings led geometry
Figure 31: Main settings for the standard mesher.

Did you know?

In CHT simulations, oftentimes the solid parts will have thin sections. It’s important to add at least 2 or 3 cells to correctly resolve the temperature gradients within these small parts.

gap elements benefits standard mesher
Figure 32: Thin gaps in the LED geometry.

By defining the Number of gap elements to 3, the meshing algorithm will ensure at least 3 elements capturing the small sections.

With these mesh settings, we already have a good mesh that allows us to run a successful simulation.

In the box below, we will show optional steps to configure a region refinement for the mesh, which allows us to capture the convection plume more accurately. If you would like to proceed without region refinements, please skip to section 4.

(Optional) Region refinement for the convection plume

In natural convection simulations, a convection plume develops above the hot parts. To capture the plume more accurately, we can use finer mesh cells around that region.

natural convection plume led
Figure 33: Natural convection plume over a LED geometry

With the standard mesher, a region refinement is appropriate to capture the developing plume. Therefore, please click on the ‘+ button’ next to Refinements:


creating mesh refinements standard mesher
Figure 34: Adding a new region refinement

In the configuration window that opens, you can define the Maximum edge length for the cells inside the refinement region. In Figure 35, you will find the necessary steps:


region refinement set up
Figure 35: Configuration of the region refinement

1. Define a Maximum edge length of 0.0025 meters
2. Click on the ‘+ button’ next to Geometry primitives and choose a ‘Cartesian box’

Next, it’s necessary to define the dimensions of the cartesian box. Keeping the convection plume in mind, please input the following dimensions:


region refinement cartesian box definition led geometry
Figure 36: Region refinement dimensions, to enhance the plume resolution.

  • Minimum (x) value: 0 m
  • Minimum (y) value: -0.1 m
  • Minimum (z) value: 0 m
  • Maximum (x) value: 0.05 m
  • Maximum (y) value: 0.25 m
  • Maximum (z) value: 0.05 m

As a final step, return to the Region refinement previously created, and toggle on the cartesian box assignment.


cartesian box assignment for a mesh refinement
Figure 37: Assigning the cartesian box to the region refinement.

This concludes the configuration of the region refinement.

Did you know?

The CHTv2.0 solver uses a special kind of meshes, named conformal meshes. In a conformal mesh, the cells at the interface between two parts will match perfectly, which allows for a more robust setup and faster convergence.

conformal mesh conjugate heat transfer v 2
Figure 38: Comparison between a non-conformal mesh (left) and a conformal mesh (right)

For this reason, meshes created for other analysis types can’t be used in a CHTv2.0 simulation.

4. Start the Simulation

To start a new simulation, please click on the ‘+ button’ next to Simulation Runs.

new simulation run simulation tree
Figure 39: Creating a new simulation run.

This way, the mesh will be generated, and afterward the simulation run will start automatically. While the simulation results are being calculated, you can already have a look at the intermediate results in the post-processor. They are being updated in real-time! You will also find a link to the finished project at the end of the tutorial.

The simulation run takes from 110 to 150 minutes to finish. At this point, you can access the post-processing environment by clicking on ‘Solution Fields’ or ‘Post-process results’:

accessing the post-processing environment simulation
Figure 40: Accessing the post-processing environment for a finished simulation run.

5. Post-Processing

5.1 Result Controls

The average chip temperatures are available under the ‘Area averages’ tab:

temperature average result control
Figure 41: Average temperature on the half-watt chip. The temperature is just over 100 Celsius.

The plot shows how the chip temperature is evolving as the algorithm performs iterations. In a converged simulation, the temperatures will stabilize and no longer change between iterations. As a result of the strongly coupled formulation, the CHT v2.0 algorithm the temperature converges quickly, in just over 400 iterations.

For more notes on assessing convergence in CFD simulations, please refer to this article.

Did you know?

With SimScale, it’s possible to run multiple simulations in parallel for different LED designs. The aim is to obtain an optimized geometry, with lower temperatures on the chips.

This way, you can evaluate various geometries faster, speeding up the design process.

5.2 Post-Processing Pictures

After accessing the post-processor by clicking on ‘Solution Fields‘, you can use several post-processing filters to further analyze the results.

In the animation below, we can see the flow field that develops around the LED spotlight. Air is drawn from the bottom and the sides of the spotlight, due to the temperatures in the solid parts.

post-processed results of a led spotlight simulation simscale
Animation: Developing convection plume on a LED spotlight.

Have a look at our post-processing guide to learn how to use the post-processor for this simulation.

Congratulations! You finished the tutorial!

Note

If you have questions or suggestions, please reach out either via the forum or contact us directly.

Last updated: September 20th, 2020

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