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Facial recognition software (FRS) is a form of biometric security that detects a face, analyzes it, converts it to data, and then matches it with images in a database. This technology is currently being used in vehicles for safety and convenience features, such as detecting driver fatigue, ensuring ride share drivers are wearing a face covering, or unlocking the vehicle. Public transportation hubs can also use FRS to identify missing persons, intercept domestic terrorism, deter theft, and achieve other security initiatives. However, biometric data is sensitive and there are numerous remaining questions about how to implement and regulate FRS in a way that maximizes its safety and security potential while simultaneously ensuring individual’s right to privacy, data security, and technology-based equality.

A method is presented here that detects aircraft tail surface icing that might normally be unobserved by the flight crew. Such icing can be detected through the action of highly computationally efficient signal processing of existing sensor signals using a so-called failure detection filter (FDF). The FDF creates a unique output signature permitting relatively early detection of tail surface icing. The FDF incorporates a stable state estimator from which the icing signature is created. This estimator is robust to analytical modeling errors or uncertainties, and to process noise (e.g. turbulence). Excellent performance of the method is demonstrated via simulation.

This paper presents further development of stall margin instrumentation designed for use in icing conditions. Initial work developing this instrumentation was conducted on a NACA 0018 wing model in Western Michigan University's wind tunnel.1 The results from this work showed promise and work continued on a NACA 23012 wing. The work on the NACA 23012 wing is presented here. The stall margin instrumentation system maintains accuracy independent of wing leading edge ice formations. The stall margin system uses four surface pressures, measured aft of the ice formation, from which the aircraft's normalized lift coefficient is determined. The pressure port locations are selected such that the calibration algorithm remains nearly constant as the leading edge ice shape and thickness change. This allows the normalized lift coefficient to be known for iced and non-iced conditions.

A method has been developed for calculating the internal temperature distribution in an aircraft tire while free rolling under load. The method uses an approximate stress analysis of each point in the tire as it rolls through the contact patch, and from this stress change the mechanical work done on each volume element may be obtained and converted into a heat release rate through a knowledge of material characteristics. The tire cross-section is then considered as a body with internal heat generation, and the diffusion equation is solved numerically with appropriate boundary conditions at the wheel and runway surface. Comparisons with buried thermocouples in actual aircraft tires shows good agreement.