Thermal Mathematical Models (TMMs) are used to predict the thermal behavior of satellite structures in orbit. However, due to inherent uncertainties in these models, physical testing is necessary to achieve reliable predictions. While these tests are critical, they often introduce uncontrolled uncertainties, such as heat leaks and measurement errors, making the correlation process complex and time-consuming. To address these challenges, this thesis proposes an alternative testing methodology that reduces uncertainties in thermal test data by using the phase shifts between temperature responses from oscillatory heat loads for TMM correlation. By comparing the measured and predicted phase shifts, thermal model parameters such as conductance or capacitance can be effectively correlated. The results demonstrate that this methodology is largely insensitive to uncontrolled conductive heat leaks, allowing the correlation process to focus only on key thermal parameters. This approach improves the reliability of thermal test data and streamlines the correlation process. Moreover, its potential application in ambient conditions offers a promising testing solution for early-phase model correlation.

The Last Hope drone will autonomously find a clear path into the sky from the ground and ascend to an altitude of up to two thousand meters. Within 20 minutes it transmits a call for help with exact location information to rescue operators via the Iridium satellite network...

This work is a part of the Automated Rotor Blade Inspection (ARBI) project. ARBI aims to improve the rotorcraft RTB process with novel rotor blade measurement equipment. The objective of this research is to investigate how the variation in structural properties of the rotor blades composite structure affects the dynamical response during the RTB process. It is hypothesized that the variation in stiffness and shift in the center of gravity of the structure is caused by in-service defects and repairs.
The results of the NDI inspections give a detailed overview of what type of non-uniformities are found in CH-47 rotor blades. A 2D analytical model is developed to quantify structural blade properties of blades that contain non-uniformities. This model provides the ability to determine the impact of these non-uniformities on the structural parameters based on NDI results and helps to improve the FEM model that is used for RTB simulation.

Digital Image Correlation is a powerful tool with which full-field strains can be extracted from a series of digital images. If applied on the micro-scale of composites, the fiber-matrix interaction can be studied. To do so, different challenges have to be overcome. First, composite specimens have to be prepared for microscopy. Then, a speckle pattern for the DIC algorithm has to be applied, for which different methods are examined and optimized. Next, digital microscopic imaging systems are compared and characterized. Finally, a relation between parameters of the DIC algorithm (such as subset shape and size) and the accuracy is determined.