Development of the Temperature Profile Optimization Method for Thermal Conditioning of Large Bodies

The performance of various systems, such as electronic cards, avionics, and propulsion systems, is highly depend on thermal effects and the system’s temperature. As the operational temperatures of these systems undergo changes throughout their life cycles, the characterization of temperature-dependent performances necessitates different tests, including performance tests under controlled temperature conditions. Obtaining desired temperature distribution for smaller components, such as avionics or electronic components can be achieved within several hours or even minutes inside the industrial furnaces. Conversely, temperature conditioning for larger structures, such as propulsion systems, may require several days or even weeks. The process of temperature conditioning, conducted under a constant furnace temperature is a time-consuming operation when it is considered in terms of project workflow. In an effort to decrease the duration of these last long and inefficient constant furnace temperature processes, a time optimization study is proposed which is aiming to obtain varying furnace temperature profile to acquired needed temperature distribution throughout these large structures. Three-dimensional, two-dimensional, and axisymmetric finite element models are established for a comprehensive examination of a large-scale system by considering the nature of the problem. Outcomes from these distinct finite element models leads to the determination that the axisymmetric model is most suited for the ensuing optimization study. The constraints and the objective of the optimization are clearly defined. An iterative procedure is conducted between the optimization tool and heat transfer analysis solver. As a result of the study, required time for the temperature conditioning is decreased by almost 50% by using the obtained varying furnace temperature profiles instead of using constant furnace temperature. It is noteworthy that diverse constraints and objectives may be implemented within the developed model to accommodate case-specific exigencies.