Thermal modelling software

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. 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.

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.

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. 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. These variables, called Symbols, allow models to be rapidly manipulated with a few keystrokes, meaning updating or maintaining the model is easy, as is performing sensitivity studies and investigating what-if scenarios.

You can visualize the temperatures and heat flows to understand all the nuances of your thermal system. Powerful post-processing tools include automatically determining maximum and minimum temperatures, plotting component temperatures, exporting results to a file for Excel, and even creating a video of a temperature plot through time.

Two seamlessly integrated modules are available with Thermal Desktop. RadCAD calculates radiation heat transfer between components within the model and between the model and the environment. FloCAD adds the capability to model flow circuits, including fans and convective heat transfer. These fluid models integrate with the thermal models and are solved together, enabling accurate modeling of devices such as radiator systems or cryogenic lines.

Thermal Desktop's capabilities can be expanded even more by adding TD Direct , our advanced meshing software that is easily integrated into Thermal Desktop. TD Direct is ideal for complex geometry in virtually any CAD format , rapid design interations, fluid volumes for Compartments, pipe centerlines, and many other functions.

Thermal Desktop is used by thermal engineers around the globe. It is not a compromise of many disciplines rolled into a single product; this is nothing but the very best of thermal and fluids analysis. Should you need help learning our software, you will find CRTech is staffed by thermal and fluids engineers who understand your needs and concerns.

Thermo-electrochemical analysis of lithium ion batteries for space applications using Thermal Desktop, W. Walker, H. Ardebili Associated paper can be download here. Gasbarre, Ruth M. Work is also underway to incorporate other types of energy transformations e. Hence, in cases that involve convection and radiation, Energy2D results should be considered as qualitative. The pictures to the right show a comparison of the results of Energy2D simulations with images from infrared thermography for a simple model house.

The thermal patterns predicted by Energy2D roughly match those from a thermal camera. More than 40 scientific papers have used Energy2D as a research tool not just a citation , demonstrating its wide applications across science and engineering. How many books have recommended it? Toggle navigation. Customer Login. Apart from that, there is really no need to create an account to use this website. Remember Me. Log in.

Not registered yet? Create an account Forgot your username? Forgot your password? Heat Conduction multi-layered composite shell elements solid elements connectivity elements and thermal contact definitions temperature-dependent material properties anisotropic heat conduction internal heat generation phase-changes.

Thermal Radiation models for solar radiation and all sorts of other sources of light and thermal radiation material properties depending on wavelength and angle of incidence intra-model surface-to-surface radiation considers absorption, reflection and transmission as well as refraction diffuse and specular reflection tool for generating representative solar and cloudiness environmental data for any place and time on earth.

Different types of thermal boundary conditions can be applied such as: heat exchange by convection at surfaces thermal radiation between surfaces and external solar loads direct spatial contact of surface areas various types of heat sources and sinks coupling of component part temperatures to adjacent air Most boundary conditions can be time-dependent or temperature-dependent.

The numerical solver itself allows for fixed and adaptive time stepping for efficient solution progress restarting a simulation based on previous results a wide range of expert solver options for fine-tuning of result precision and convergence behaviour.