With the ever-increasing power densities in electronic systems, it is important that your system is designed not only for core functions but also for thermals. Thermal engineering is a critical part of modern electronic systems. Often, thermal management is seen as an after-thought in design considerations until it is determined that there is a problem somewhere in a system due to excessive heating and malfunction. Poorly designed thermal management systems lead to all kinds of problems, including sub-optimal functions, poor mechanical aspects, high failure rates, and shorter lives. This is completely preventable, especially when handled early in the design cycle using in-house seasoned thermal engineers or expert thermal management consultants. Sometimes, the thermal design solutions can be as simple as addressing thermal interface solutions, selecting better materials, heat sink modification, or redirecting airflow to where it should be in the case of active cooling. At other times, it may require extensive [thermal analysis](https://www.thermalds.com/thermal-analysis-thermal-modeling/) and testing to determine the root problem, and hence the solution. In some cases, it may require a totally brand-new approach involving some serious research and development.
Thermal Modelling is the analysis of junctions in your building. These junctions arise where there is a change in building materials, where two different components meet, or where there is a change thickness or direction of adjoining materials.
Thermal Modelling is used to analyse these junctions to examine for performance and provide recommendations on best practice to make sure you get the best from your building.
With the ever-increasing power densities in electronic systems, it is important that your system is designed not only for core functions but also for thermals. Thermal engineering is a critical part of modern electronic systems. Often, thermal management is seen as an after-thought in design considerations until it is determined that there is a problem somewhere in a system due to excessive heating and malfunction. Poorly designed thermal management systems lead to all kinds of problems, including sub-optimal functions, poor mechanical aspects, high failure rates, and shorter lives. This is completely preventable, especially when handled early in the design cycle using in-house seasoned thermal engineers or expert thermal management consultants. Sometimes, the thermal design solutions can be as simple as addressing thermal interface solutions, selecting better materials, heat sink modification, or redirecting airflow to where it should be in the case of active cooling. At other times, it may require extensive [thermal analysis](https://www.thermalds.com/thermal-analysis-thermal-modeling/) and testing to determine the root problem, and hence the solution. In some cases, it may require a totally brand-new approach involving some serious research and development.
Thermal Modelling is the analysis of junctions in your building. These junctions arise where there is a change in building materials, where two different components meet, or where there is a change thickness or direction of adjoining materials.
Thermal Modelling is used to analyse these junctions to examine for performance and provide recommendations on best practice to make sure you get the best from your building.
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.
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.
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.
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.
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.
