Taking into consideration that nowadays the aerospace industry focuses a lot on safety, more durable and stable systems are developed. While the system itself is safer, there is another element that can have a high impact on the overall safety of a flight, namely the human factor. Pilot physiological parameters were measured during a full flight in a fixed cockpit environment using application-specific equipment. The recorded or calculated parameters are used to compute a performance envelope model with the scope of determining the degradation of the pilot’s condition during different flight phases or events. Several standardized tests were realized/performed on subjects who were given flight instructions before the test, without knowing beforehand the scenario and events that will occur/take place. This study helps in identifying the limits of pilots in different flight scenarios and the impact on their presumed performance.
One way to improve the measurements of the PSR (Primary Surveillance Radar) is to utilize the cinematic model of the aircraft (A/C) in a Kalman filter. Another newly developed method would be to implement multilateration using a large number of ground-based ADS-B (Automatic Dependent Surveillance-Broadcast) receivers. Originating in airport surveillance, multilateration grew to become the primary system for ATM (Air Traffic Management) in airspaces without PSR coverage. Given that each of the systems has its own advantages and limitations, we propose an evaluation of an alternative approach that uses data from multiple ADS-B receivers to implement a data fusion algorithm between PSR acquired position and MLAT (Multilateration) estimated position. Among the many ways to implement data fusion, have chosen to analyze two possible solutions: the direct fusion of the two available positions provided by the two systems using a traditional Kalman Filter and a linearization approach for the multilateration solution that does not require position computation. In both cases, these will improve the Kalman filter and lower the position estimation errors. The evaluation takes into consideration the possible sources of inaccuracies and provides sensibility analyses in regards to the number and positioning of ADS-B receivers involved in multilateration. This paper will conclude with a discussion of the computational power required for the two implementations.
In the space sector reducing the cost through innovative designs, can be achieved through mass reduction and shorter development time. Additive layer manufacturing (ALM) is a process which enables, not only a new cycle of optimization in terms of mass and performance, but also a minimum lead time for small series production of complex parts. The objective of this paper is to design a part as light as possible while respecting the specific requirements. Specialized optimization tools were used in order to significantly reduce the number of design iterations. In order to cut down the mass furthermore, while increasing the stiffness, a hollow structure was considered. Internal cavities may raise a problem of powder evacuation in case of powder fusion processes. Concerning contamination problems of the spacecraft's (S/C) components, a powder removal procedure was closely developed with the manufacturer. As an outcome, a lighter space component with a lower production cost and fewer points of potential failure was obtained.
In the robotics sector, inverse kinematics is one of the most typical research areas in design, trajectory planning, and dynamic analysis of robots. In this paper, an efficient algorithm for the inverse kinematics of a six degree of freedom robot manipulator for different aerospace applications is proposed. The proposed inverse kinematics algorithm is the Broyden-Fletcher-Goldfarb-Shanno algorithm, used for solving unconstrained nonlinear optimization problems. The developed algorithm is validated using simulation in Robotic toolbox. A separate MATLAB script is provided for a 3D visualization of the robot arm.
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