Thermal Analysis | Thermal Modeling is a key part of any thermal design. These days, one can model almost anything using the state-of-the-art analysis and modeling tools available in the market. When used correctly, these tools can give you accurate results quickly and cost-effectively. Gone are the days when thermal engineers labored for weeks, or even months, designing thermal experiments to get limited information on a given layout. Now, one can build a model with a few clicks and see results almost instantly. Many of these tools such as the Ansys Thermal Analysis tool have made great progress over the years in robustness, accuracy, and ease of use. The best part is you don’t have to be a CFD (Computation Fluid Dynamics) specialist to use them. In many cases, a good knowledge of heat and mass transfer is sufficient.
However, regardless of how sophisticated these analysis tools have become, it is important that we use them properly for the scenario at hand. Otherwise, it will be “garbage in, garbage out,” as is often termed in the industry. Since thermal design is controlled by many variables, there are many things that can go wrong (or specified incorrectly) as well. When errors are made with a couple of inputs, the results can be totally invalid even when everything else is done correctly. Therefore, it is important that the experienced thermal analysis engineer follow some key steps meticulously, so their thermal simulation exercise is successful.
Thermal analysis requires a great deal of organization. The end result is the outcome of several activities combined. To begin, the thermal model has to have a physical model built within the analysis tool itself or imported from a CAD system. The physical model must closely represent the real system being modeled. The thermal model must also have numerous properties and boundary conditions assigned to it. These properties and boundary conditions define the nature of the system and its connection with its environment. Unrealistic boundary conditions give unrealistic results. Then the entire model must be discretized and analyzed to achieve a stable and accurate solution. In many cases, the final solution is obtained after a series of steps or iterations. At first, it is common to aim for a preliminary solution, based on basic inputs and a coarse mesh. After the first solution, we may refine the model by adding more details and mesh and re-run the model for another solution. The process continues until we are satisfied with our solution and the design is complete. All of this requires a step by step approach so the whole process is done correctly.
The above description is a broad outline of the CFD modeling experience. However, the thermal modeling exercise involves several more steps, which we would like to discuss here in greater detail. At the minimum, the modeling process includes the following nine steps: basic parameters setting, domain sizing, boundary conditions, physical model details, thermal properties, power loading, meshing, solving, and post-processing. These steps are discussed below.
The basic parameters of a thermal analysis | thermal modeling are things like ambient temperature, the variables to be solved (temperature and/or flow variables), gravity effects, radiation parameters, whether the flow is laminar or turbulent, steady or transient, transient settings, etc. These parameters define the nature of the thermal system we would like to model. In a conduction-only model, we turn off flow-related specifications. In a highly convective environment with fans and the like, the effects of natural convection (gravity) and radiation may be neglected (and hence turned off). If modeling transient, we need to specify additional parameters such as time steps, start time and end times.
As part of basic parameters specification, we may also specify how the governing equations are to be solved, such as discretization schemes and relaxation factors. Relaxation factors control the speed by which the solution is achieved. Relaxation factors are necessary because the governing thermo-fluid equations are highly non-linear and cannot be solved in a few steps. Although the default settings are OK in most cases, we may need to adjust the relaxation factors for more complicated cases, so our solution does not diverge.
All of the forms where the basic parameters are specified must be checked properly to make sure that the model or the problem we are trying to solve is well-defined. Otherwise, we will not get accurate results from our thermal modeling exercise.
Thermal systems can be broadly classifieds into two groups: passively-cooled systems and actively-cooled systems.
In passively-cooled systems, there are no air or fluid moving devices, such as fans or blowers. The system is cooled due to air or fluid movement as a result of temperature differences with the ambient. This is called natural convection cooling. Here, the amount of heat loss to the ambient is proportional to the product of the exposed surface areas of the system and the temperature differences with the ambient fluid. In addition to natural convection cooling, passively-cooled systems also lose heat by radiation. In radiation, heat transfer takes place due to temperature differences between the surfaces of the system and the surroundings (walls, air, etc.). Here, as in natural convection, the extent of heat transfer depends on the exposed surface area of the system and its temperature difference with the ambient. In passively cooled systems, the effect of radiation is typically 25-50 percent, depending on how high the system temperature is relative to the surroundings and its surface conditions.
In actively-cooled systems, there is a fluid moving device inside or around the system. Fans, blowers, and pumps are all examples of fluid movers. In such systems, the effects of radiation and natural convection are generally small and may be neglected. In modeling actively-cooled systems, it is important that the flow is modeled accurately. The thermal analysis engineer must know whether the flow is predominantly laminar or turbulent, as these two flows are modeled somewhat differently. It is also important that the physical components, especially around high flow areas, are modeled in sufficient detail – so flow obstructions and turns are captured accurately, including in the vicinity of the air or fluid mover.
The basic parameter input forms must be checked periodically for accuracy in any thermal simulation tool, whether it is Ansys thermal analysis or FloTherm.
A thermal model must have a domain within which the analysis must be conducted. The domain should include the key elements of the system that is being modeled, including the device itself. The domain also determines how the system being modeled interacts with the environment. Therefore, it is critical that we use the right domain size and shape for our model to include the device we are modeling as well as its immediate environment. In general, domain boundaries are chosen so that either a given variable has a fixed value at the boundary, or the spatial change of a variable is close to zero at the boundary (adiabatic or symmetry boundary conditions). Therefore, when we establish a domain, we must ensure that such assumptions are realistic and do not deviate from the real system, at least not by a whole lot.
In domain sizing, we must also strike a balance between unnecessarily large domain size and model accuracy. Often, larger domain size means bigger mesh count and longer run time. This can be a problem when you would like to know whether you are on the right track or not quickly, especially in the early stages of thermal modeling. Unnecessarily large mesh sizes will also be a problem in transient simulations, where the wait time can be a lot longer. The seasoned thermal analysis experienced engineer or thermal simulation consultants would know the appropriate domain size by experience, typically from prior models. Otherwise, one may conduct sensitivity analysis with 2-3 variations of domain sizes to see the effect of domain size on key variables.
By model details, we mean the physical details of the system being analyzed. If we are modeling a laptop computer, for example, the model will have the key components such as the enclosure, display, PCB with components, Hard Drive and/or SSD, wireless components, power supply, interface materials, cooling solutions, etc. Today’s thermal analysis tools can import the physical model in its entirety. However, it important that we exclude minor details from the model so that the mesh size is not too large. In many cases, small pins, protrusions, and curves do not matter much in thermal modeling, especially when they are far away from the main heat sources inside the system being modeled and/or when they are away from the main flow paths.
When building a model, a special attention must be given to areas in and around major heat sources, such as PCB and IC packages. The model must have the right details in these areas to capture the expected large gradients of the key variables in these areas. The larger the gradients, the finer the mesh should be in those areas as well.
The physical system may be modeled suspended in air or sitting on (or next to) some surface with the appropriate gap or boundary conditions. Whatever components we include, our assumptions must be realistic and the boundary conditions consistent with the real situation we are trying to analyze.
Thermal properties include variables like thermal conductivity, specific heat, and density. In a steady-state analysis, thermal conductivity is the main variable to consider. In transient analysis, density and specific heat will also be important, in addition to thermal conductivity. All components in the thermal model must be assigned the right thermal properties. These properties govern how heat is transferred from one component to the other, and ultimately to the environment. Poor choice of thermal properties will, therefore, lead to poor results as well.
In some cases, the thermal property of a component or space may vary spatially. It may also depend on another variable, such as temperature. In those cases, we may define the appropriate profile of that property and assign it to the components in question. In some cases, such as in PCB modeling or thermal interface solutions, we may need to break up the component itself into layers or parts, so we can specify more exact properties for each part or layer.
An electronic device becomes hot because heat is generated within some components of this device. This heat comes from the power each component draws from the power supply. Almost all power consumed by a given component within an electronic system is converted into heat. Therefore, it is very important that we know the exact power load on every component in our system. Our solution is as good as the accuracy of these inputs. In case of uncertainty, it is customary to err on the side of more conservative inputs. At times, we may also establish plots or contours for a range of power loads to see thermal scenarios for different loads.
In addition to the overall power loads, it is also important that we know the exact location where each power load is being dissipated. In IC Packages, for example, the power consumed by the die is not distributed throughout the die. Rather, much of the power comes from a few regions within the die. In general, the power is dissipated on one side or surface of the die. Within that surface, there are areas where power dissipation is high, such as logic areas, and there are areas where the power density is low. So, it is important that we specify the exact power load based on location. In today’s thermal analysis tools, these inputs are relatively easy to specify, provided one has the right data.
Our thermal modeling consultants can help you get the right power data for your components from the right sources, which, at times, can take considerable time assemble.
Thermal analysis | thermal modeling is conducted by digitizing the entire model domain into small areas and volumes called mesh elements or cells. Essentially, we break up the entire domain into thousands of small volumetric cells. Within each cell, we assume an average value for each variable such as temperature. The variables are supposed to vary between neighboring cells according to an assumed profile and governed by partial differential equations. The partial differential equations are, in turn, influenced by the thermal properties we discussed above, such as thermal conductivity, density, specific heat, etc.
When it comes to meshing, one thing is critical: mesh refinement. In general, a model will have areas where the mesh is fine and areas where the mesh is coarse. We need a fine mesh in areas where the changes in variables (gradients) are high, and a coarse mesh in areas where the variations are low. This is because, using large cells, we cannot capture rapidly changing variables in a given space or time. In general, we should have much finer mesh close to solid objects or surfaces, as these areas are likely to have high gradients of the variables being solved.
Mesh refinement is easily handled in modern computational tools. It is usually a matter of just specifying some values and growth metrics inside a few forms. By changing these values one can see how the mesh changes in focus areas.
We may embed one mesh cluster within another to take care of components with highly disparate sizes, e.g. IC Packages on a PCB. It is possible to have a cascade of mesh clusters as can be seen in the GIF image shown on this page. The mesh lines do not have to conform at boundaries since almost all modern analysis tools have non-conformal meshing capability. In a non-conformal mesh, one cell can interface with two or more cells in the same direction. The values of variables at such cells are determined based on the appropriate interpolation of its neighboring cell values.
When we mesh a model, it is always a good idea to examine the mesh on planes and surfaces, so the mesh looks consistent with our expectations. Any areas where the mesh needs improvement must be addressed promptly, including areas where the mesh is too coarse or too fine, or when the cells are too distorted – elements with bad aspect ratios (very long on one side and short on the other, etc.).
The experienced thermal analysis engineer uses various mesh refinement levels and meshing strategies in his/her analysis. For quick runs or rough estimates, one may use coarse meshes. For the final results, we may use fine meshes. Run times are directly proportional to the number of mesh elements we have in a model. Whereas smaller models may take minutes to run, models with tens of millions of mesh elements may take days or even weeks to finish runs on a modern server.
Solving or running for a solution is one of the last two steps in thermal modeling. Here, the model will go through iterations to arrive at the final solution. As indicated above, the partial differential equations that govern fluid flow and heat transfer are highly none-linear. A closed-form solution is, therefore, not possible in one or two steps. Hence, we must arrive at the solution iteratively, beginning from some guessed values for all the cells inside the computational domain. This iterative process can involve tens, hundreds, or even thousands of iterations before the solution converges – meaning the values at all cell points cease to change appreciably.
The iterative process is controlled by ‘relaxation factors.’ Relaxation factors are numbers between 0 and 1. These factors control how much of the ‘corrections’ suggested by the CFD tool we take when moving from one iteration level to the next. For example, if the relaxation factors for temperature is 1, the cell temperature at the end of a given iteration is updated by the full ‘correction value’ obtained in that iteration. However, in almost all cases, taking the full correction value at the end of each iteration will lead to divergence – meaning, the solution will blow up and becomes worthless. So it is essential that we use values lower than 1, but higher than 0, for each variable being solved (such as flow, pressure, temperature, etc.).
In thermal simulations, one solution run is rarely sufficient to get the end result we want. Typically, our thermal modeling consultants go through a series of runs using a given model. In subsequent runs, we may add more details, adjust basic parameters, mesh refinement levels, domain sizes and run times, until we are satisfied with the final results.
The last step in thermal modeling exercise is post-processing. When a model finishes solving, it is time to check the solution. With today’s state-of-the-art thermal analysis tools, there are numerous ways to display results. One can display contours of temperature (or any other variable) on a point, plane, or surface. We may also build derivatives or functions of variables and display them on points, planes, and surfaces. There is no limit to how much we can slice and dice the thermal solution. In transient simulations, we can also make animations to show how the thermal profile of a system develops over time, which is especially useful to explain things to the uninitiated, including upper management and general customers.
While examining thermal simulation results, in general, the thermal engineer should view the results critically. It is very easy to get excited and carried away with pretty pictures and take their accuracy for granted. This can be a big mistake, especially in the early stages of thermal modeling. Therefore, we must check our solution for consistency and against our expectations to make sure that our solution is not erroneous.
There are several thermal analysis | thermal modeling software packages in the market today. Some are more comprehensive than others. However, the main general-purpose thermal analysis tools widely used in the electronics industry today are Icepak, the Ansys Thermal Analysis package, and FloTHERM, from Mentor Graphics. You can use any of these two packages to do pretty much any thermal analysis tasks you may have. Both have come a long way from what they used to be several years ago to what they are today in accuracy, ease of use and automation.
In addition to the above two general-purpose thermal analysis tools, there are also other tools especially geared to solve certain aspects of thermal simulations, such as pure conduction or phase change. Others serve niche industries, such as data centers and power plants. Almost all CAD solid modeling packages have some aspect of thermal analysis capability built inside them.
If you have any questions about this article or if you are looking for thermal simulation consultants, and need thermal analysis consulting, please contact us at firstname.lastname@example.org. Our thermal modeling consultants will get back to you promptly.
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