Setting up a simulation for Electronic enclosure model using Ansys Icepak

Objective :

The main objective of this challenge, we have created the mesh model for assignment-1 that has been provided in the week-3. The total solver parameters were set accordingly to the requirements that have been provided in the geometry and the simulation has been done accordingly.

Introduction :

All electronic devices and circuitry generate excess heat and thus require thermal management to improve reliability and prevent premature failure. The amount of heat output is equal to the power input if there are no other energy interactions. There are several techniques for cooling including various styles of heat sinks, thermoelectric coolers, forced air systems, and fans, heat pipes, and others. In cases of extreme low environmental temperatures, it may actually be necessary to heat the electronic components to achieve satisfactory operation.

This is usually quoted as the thermal resistance from the junction to the case of the semiconductor device. The units are °C/W.

For example, a heatsink rated at 10 °C/W will get 10 °C hotter than the surrounding air when it dissipates 1 Watt of heat. Thus, a heatsink with a low °C/W value is more efficient than a heatsink with a high °C/W value. Given two semiconductor devices in the same package, a lower junction to ambient resistance indicates a more efficient device.

However, when comparing two devices with different die-free package thermal resistances their junction to ambient or junction to case resistance values may not correlate directly to their comparative efficiencies. Different semiconductor packages may have different die orientations, different copper(or other metal) mass surrounding the die, different die to attach mechanics, and different molding thickness, all of which could yield significantly different junction to the case or junction to ambient resistance values, and could thus obscure overall efficiency numbers.

Mesh Generation:

Mesh generation is the practice of creating a mesh, a subdivision of a continuous geometric space into discrete geometric and topological cells. Often these cells form a simplicial complex. Usually, the cells partition the geometric input domain. Mesh cells are used as discrete local approximations of the larger domain. Meshes are created by computer algorithms, often with human guidance through a GUI, depending on the complexity of the domain and the type of mesh desired. The goal is to create a mesh that accurately captures the input domain geometry, with high-quality (well-shaped) cells, and without so many cells to make subsequent calculations intractable. The mesh should also be fine (have small elements) in areas that are important for the subsequent calculations.

Meshes are used for rendering to a computer screen and for physical simulation such as finite element analysis or computational fluid dynamics. Meshes are composed of simple cells like triangles because, e.g., we know how to perform operations such as finite element calculations (engineering) or ray tracing (computer graphics) on triangles, but we do not know how to perform these operations directly on complicated spaces and shapes such as a roadway bridge. We can simulate the strength of the bridge, or draw it on a computer screen, by performing calculations on each triangle and calculating the interactions between triangles.

Cut plane through the x-axis:

Cut plane through the y-axis:

Cut plane through the z-axis:

Mesh surface for the domain:

Numerical setting:

Use problem set up wizard :

A software wizard or setup assistant is a user interface type that presents a user with a sequence of dialog boxes that lead the user through a series of well-defined steps. Tasks that are complex, infrequently performed or unfamiliar may be easier to perform using a wizard.

The general setup for basic parameters :

Basic parameters and choose the Zero equation turbulence model for the flow regime in the General setup tab.

Set up the gravity vector :

Gravity acts in the negative x-direction in this problem. To set up the effects of gravity, toggle on the Gravity vector in the General setup tab. Enter the new values for the gravity vector as x = 0, y = -9.80665 and z =0.

Defaults parameters :

In the default parameters, the temperature and the radiations were set to default as required for the simulation as provided in the challenge.

Transient setup parameters

A steady-state simulation is used to investigate the steady-state behavior of a system, where the simulation continues until the system reaches a steady-state. Otherwise, the simulation results can be significantly different from the true results

A steady-state simulation was considered in the simulation.

Advanced parameters in basic settings:

For many natural-convection flows, you can get faster convergence with the Boussinesq model than you can get by setting up the problem with a fluid density as a function of temperature. This model treats density as a constant value in all solved equations, except for the buoyancy term in the momentum equation.

Set no of iterations and convergence criteria:

The total number of iteration was set to be 500 iterations and coming to the convergence criteria the flow was set to 0.0001 and joule heating, the energy was 1e-7, and the turbulent kinetic energy and turbulent dissipation rate were 1e-7

Parallel setting:

Parallel exchanging messages between multiple computers running a parallel program across distributed memory. In parallel computing, multiple computers or even multiple processor cores within the same computer are called nodes.

Advanced solver setup:

In applied mathematics, discretization is the process of transferring continuous functions, models, variables, and equations into discrete counterparts. This process is usually carried out as a first step toward making them suitable for numerical evaluation and implementation on digital computers.

Select the Basic settings panel from the Solution settings branch of the tree and set the number of iterations to 300. Go to Advanced settings and specify Under-relaxation factors for Pressure, Momentum, and Temperature as 0.3, 0.7, and 1.0, respectively. Select Double for the Precision drop-down list. The recommended basic settings and advanced solver setup for this model are shown above.

Set up monitor points in the model:

And monitor points were considered at the plates and blocks, and the red color is the temperature monitor points and blue color are the velocity monitor

There are no universal metrics for judging convergence, a good indicator is when the solution no longer changes with more iterations, and when the residuals have decreased to a certain degree. The default criterion is that each residual will be reduced to a value of less than 10^-3 except the energy residual, for which the default criterion is 10^-7. It is a good idea to judge convergence not only by examining residuals levels but also by monitoring relevant integrated quantities.

ANSYS Icepak will begin to calculate a solution for the model, and a separate window will open where the solver will print the numerical values of the residuals. ANSYS Icepak will also open the Solution residuals graphics display and control window, where it will display the convergence history for the calculation.

Examine and post-process the results:

Residual plot:

Select the Basic settings panel from the Solution settings branch of the tree and set the number of iterations to 100. Go to Advanced settings and specify Under-relaxation factors for Pressure, Momentum, and Temperature as 0.3, 0.7, and 1.0, respectively. Select Double for the Precision drop-down list.

From the residual plot provided above it is clear that the simulation has reached the converged stage and also obtained the convergence, and they are no fluctuations in the plot.

Temperature monitoring points:

The temperature points have been placed at five separate components where the temperature of the components is seen. Components display the temperature because we have provided power to certain components.

From the above plot, Temperature patterns are constantly decreasing, which ensures that at the start of the components, the temperature is indicated by the power supplied manually. After the forced air passes through the openings to the domains, the components tend to cool down and set at a temperature and decrease in temperature by reference to the forced convection.

Velocity monitoring points:

Velocity sensor points often allow for the estimation of the input velocity and other velocity control points at the other end openings at the openings on one side of the structure to track the velocity of the air entering the domain.

Here, the control point at the opening of the air inlet displays a steady temperature of 0.5m / sec in the simulation, which is a reference to the system, whereas the other curve indicates a change in velocity. It implies that the velocity at the center is small since the strong components are there at the top, the velocity is gradual that as the gap is there.

Plane cut:

The cut plane was created for the Electronic enclosure model and the axis for the cut-plane used was the z plane through the center.

Pressure contour representation for the cut-plane:

For the cut plane representation, we have shown the pressure contour on the Z-plane for the model.

Vector plot:

The Vector plot was set to the Z-plane through the plane and it is clearly seen that the inlet velocity was at the initial value of 0.06m/sec and a maximum velocity was at the value of 0.543m/sec was obtained in the domain and the velocity inside the domain was nearly at 0.20m/sec.

Animation for the Velocity Vector profile on the Cut plane in the X-axis:

The vector animation which represents the flow of the velocity magnitude over the Electronic enclosure model surface was shown in the above animation.

Temperature contour:

The Temperature Contour was set to position accordingly to the Z plane through the plane and it is clearly seen that the initial temperature for the opening was at the 20°C and a maximum temperature of 95.59°C was obtained in the domain and the temperature inside the solid domain was nearly at 67.8°C.

Animation for the Temperature profile on the Cut plane in the Z-axis:

The Temperature animation which represents the temperature magnitude over the Electronic enclosure model surface was shown in the above animation.

Velocity contour:

The Velocity Contour was set to position accordingly to the Z-plane through the plane and it is clearly seen that the initial velocity for the opening was at the initial value of 0.06m/sec and a maximum velocity was at the value of 0.54 m/sec was obtained in the domain and the velocity inside the domain was nearly at 0.13 m/sec.

Animation for the Velocity profile on the Cut plane in the X-axis:

The velocity animation which represents the velocity magnitude over the Electronic enclosure model surface was shown in the above animation.

Pressure contour:

The Pressure Contour was set to position accordingly to the Z-plane through the plane and it is clearly seen that the initial pressure for the opening was at the initial value of 0.05 N/m^2 and a maximum pressure was at the value of 0.21N/m^2 was obtained in the domain and the pressure inside the domain was nearly at 0.09 N/m^2.

Negative pressure would mean that air is being sucked into your case from all the tiny gaps you can't control and don't have filters on, which means less efficient cooling over time. Aim for slightly positive-pressure, with slightly higher intake CFM than exhaust CFM.

Animation for the Pressure profile on the Cut plane in the X-axis:

The Pressure animation which represents the velocity magnitude over the Electronic enclosure model surface was shown in the above animation.

Stream particles profile:

A streamline is a path traced out by a massless particle as it moves with the flow. It is easiest to visualize a streamline. The stream-lines profile was shown below on the total domain in the hanging node.

Animation for the stream particles profile on the domain:

The Streamline animation which represents the temperature magnitude over the Electronic enclosure model was shown in the above animation.

Object face:

An object-face view allows you to examine the distribution of a solution variable on one or more faces of an object in the model. To generate an object-face view, you must select the object and specify both the variable to be displayed (e.g., temperature, Velocity, Pressure) and the attributes of the view (e.g., shading type).

Object face to display temperature contour on overall Electronic enclosure Model:

The overall temperature distribution throughout the Electronic enclosure model was shown in the above Figure.

Object face to display velocity contour on overall Electronic enclosure Model:

The overall velocity distribution throughout the Electronic enclosure model was shown in the above Figure.

Object face to display Pressure contour on overall Electronic enclosure Model:

The overall Pressure distribution throughout the Electronic enclosure model was shown in the above Figure.

Conclusion:

We have successfully performed the simulation analysis for an Electronic enclosure model and obtained the results by post-processing. And separately meshed assemblies have been employed to reduce the overall mesh count in the domain. Parameters like temperature, pressure, and velocity were plotted. And monitor points were considered at the plates and blocks to obtain the temperature and velocity that has generated in the model.