How do you optimize the thermal design of your product with CAE tools?

Using thermodynamic analysis can also be a good way to start, particularly if paired with empirical data, to then modulate your problem. Nevertheless, make sure to include safety factors and work to the worst case scenario, so you can outperform the minimum requirements.

Usually, problem statement to optimize thermal design starts with defining the objective. Sometimes this could be simply a single objective or a multi-objective statement many a time, when it is a industrial application. It is also important to define the constraints, without which no engineering application exists. The next important aspect in optimization is identification of sensitive design parameters which impact the output using sensitivity analysis study. With this designer can choose the type of optimization strategy (local or global) based on the requirement and feasibility.

The thermal problem refers to the challenge of managing heat within a system or component. It involves analyzing and optimizing the distribution of heat to ensure that temperatures stay within acceptable limits. This includes considering factors such as material properties, geometric design, and environmental conditions. Solutions often leverage thermal simulations and engineering tools to predict and enhance heat dissipation, preventing overheating and ensuring the reliable operation of devices or systems.

KPI should be clearly defined and could go across different physics. It's quite common that flow fields interact with the structures.

When using CAE tools to optimize thermal design, start by clearly defining your thermal problem. Identify where heat comes from and goes in your product. Set the boundary conditions and constraints, considering external factors like ambient temperature and internal factors like material properties. Define your goals, whether it’s to reduce temperature, increase heat transfer efficiency, or balance the thermal load. Finally, identify key parameters like temperature profiles and heat fluxes to evaluate your design’s performance.

Also to consider, simpler models are often a good indicator of bigger problems at an early stage, and are easier to modulate. Use it as a guide to base safeguards on. Consider also using generative design to overcome design bias.

I think we're biased to jumping right to CFD, FEA, and other 3-D or 1-D CAE tools. Your first step, almost without fail, should be a hand calculation with the most complex tool you use being Excel or equivalent. Let that bound the problem for you.

If you are doing a transient analysis’ don’t forget that the run time depends strongly on the smallest element. Don’t create a mesh with any fine elements to start with .. it’s better to start with a coarser mesh and see how it goes. This gives a rapid appreciation of the problem and gives an early feedback to the design process.

Keep in mind when comparing with experimental data to ensure values are within the range of the different probes used and check what tolerance they have.

Geometry optimization usually is conducted at two different stages. Topological optimisation is very useful at early design stage to select among possible architectures the best one. Shape optimisation follows and allows to fine change the shape of the components. Even small shape modifications can substantially change the thermal stress at hot spots and the flow field and the thermal exchange efficiency. High fidelity multi-physics simulations are typically adopted at this final stage (CFD models of the flow field interacting with CSM models of the structure).

An interesting application is the design of an engine head. It requires attention for the intake and exhaust ports flow which substantially influence the engine performance, for the coolant channels and at the same time the thermal fatigue effects have to be controlled to get a proper component life.