Colloquia

Samenvatting

Corrosion prevention in radar systems is critical for ensuring operational reliability, particularly in high-humidity naval environments. To mitigate corrosion risks, radar systems make use of air dryers that supply dry air to prevent condensation. However, challenges persist in accurately predicting condensation events due to varying environmental conditions and internal dynamics. This study aims to develop a dynamic model that forecasts moisture dynamics and condensation onset within multi-compartment radar systems, with applications to Thales Nederland’s radar products.

Using Simulink, a modular and graphical modeling approach, the model simulates transient humidity and temperature behaviors under a range of conditions. Experiments were conducted to validate the model’s accuracy. However, challenges arose while making the experimental setups function properly, making finalizing the results impossible. Therefore, future steps must involve further experimental validation of model predictions under complex airflow and condensation scenarios to extend its applicability. These future experiments are expected to enhance the model’s accuracy in simulating the onset and progression of condensation in intricate compartmentalized environments.

The experimental limitations were identified throughout the process, including inadequate insulation, non-adjustable compressed air supply, sensor placement challenges, and equipment constraints, all of which influenced measurement precision. Recommendations are made to improve future experiments through enhanced thermal insulation, adjustable air dryers, optimized sensor placement, and additional airflow monitoring equipment. Despite these challenges, the dynamic model showed strong potential, in forecasting humidity dynamics and condensation behavior within complex system environments. This research contributes to the onset of a valuable tool for the proactive management of moisture dynamics in radar systems, supporting Thales Nederland’s efforts in optimizing system integrity and longevity under variable environmental conditions