Optimizing cooling and heating
Thermal behavior of a system can sometimes have a major influence of the operating life of a mechanism. The analysis is often very complex, due to flow around the structure, as well the effect of moving parts. 3D calculations on the thermal behavior of such a system can therefore become very complicated and time-consuming, while the accuracy of these type of calculations is sometimes doubtful. In situations like this, it can be time-effective to perform analytical 1D or 2D calculations in Mathcad or Python, converting complex convection, conduction or radiation problems to well-known empirical relations. The figure provides an example of such an approach. Heat exchange and heat build-up in the marine propulsor resulted in insight as to appropriate oil viscosity and appropriate cooling methods.
Besides performing analytical calculations, Huygens Engineers also simulates stationary and transient temperature profiles in solids. As heat is transported through (poor) conduction within solids, applications like plastic molding require active cooling and heating, which needs to be predicted accurately to ensure the product quality.
The conductivity can vary largely within one model and is not necessarily constant for the entire temperature range. For example, in case of plastic molding, a steel mold will conduct heat much faster than the plastic product. For organic materials, like meat, varying thermal properties are also very common, as freezing and boiling effects of the water and fat content will influence the specific heat and conductivity. An example of transient cooling in a low conductivity meat product and a video of transient cooling in a high conductivity mold can be viewed in the figure below.
In convection-oriented cases, Huygens Engineers determines convection coefficients through detailed simulation, validation and measurement of elements in a flow.
A specific phenomenon with regard to cooling and heating is that of a thermal shock and related material stress. A sensor utilized in a cyclical temperature environment did not reach the desired service-life targets when subjected to cycles where temperature rapidly increased from -30 °C to 60 °C.
Drum-motors in belting applications cool through cyclical contact of parts of the drum with the belt during rotation and subsequent transient thermal conduction. This cyclical process results in a long-term cyclical thermal equilibrium of the belt and the drum-motor, as each go through their periodic motion. The polymer of the belt conducts heat poorly, and belts may or may not be subjected to temperatures at which mechanical strength drops below specification.
Huygens Engineers developed a 2D finite-difference Python-simulation for hot product environments for application engineering. The figure below shows a simulation of finite difference implementation, thermal performance prediction and a discretized numerical model in Python.
