Supporting researchers conducting qualitative research into sensitive, challenging, and difficult topics: Experiences and practical applications.

Qualitative researchers often engage in work addressing challenging, difficult, or sensitive topics and are consequently exposed to the participants’ narratives which may be emotionally charged, distressing, or compromising. These narratives occasionally rest heavy on a researcher’s conscience or may linger in the mind. Much literature has assessed how best to keep participants safe, but less attention has been given to how we keep researchers safe. We therefore document the following: (1) Our experiences of the issues presented by undertaking qualitative research involving challenging, difficult, or sensitive topics; and (2) Practical principles devised to overcome these issues, ensuring safety and wellbeing amongst researchers engaging in these types of qualitative research. We provide guidance for qualitative researchers of all levels of experience and expertise on how best to protect and support themselves, their colleagues, and other collaborating research staff, when undertaking qualitative research which might otherwise feel uncomfortable or overwhelming to tackle

Modified State Observer for Atmospheric Reentry Uncertainty Estimation

Novel techniques, known as the Modified State Observer (MSO) and Reduced Order Modified State Observer (RMSO), are implemented to estimate system states and uncertainty due to unmodeled or unknown phenomena in a system. The MSO and RMSO utilize neural networks to calculate the system uncertainty online. A useful application of these observers is the state and uncertainty estimation during atmospheric entry or reentry. Uncertainty is inherent during atmospheric reentry due to variations in atmospheric density and the attitude of the reentering object. The ability of the MSO and RMSO to estimate system uncertainty online helps to provide more accurate state estimates in systems with large uncertainty. To demonstrate the applicability and validity of the MSO and RMSO to these systems, a simulation is performed assuming no a priori knowledge of reentry dynamics to a nonlifting atmospheric reentry and the results of extended Kalman Filters are presented for comparison. The MSO and RMSO are then applied to a tumbling reentry scenario for comparison to the nonlifting reentry scenario. Results are presented that demonstrate the ability of the MSO and RMSO to accurately estimate both the system states and the system uncertainty during an atmospheric reentry. © 2012 by IST-Rolla LLC. Published by the American Institute of Aeronautics and Astronautics, Inc