Nitrous oxide has recently entered violently the arena of space propulsion and gained interest, due to its high energy and gasification potential and despite its low oxygen content as an oxidizing chemical and its instability over some 600 C. However, its physical and chemical instability soon proved to be a potential hazard and led to a renewed interest in the study of its behavior as a fluid. In the present contribution computer simulation of the liquid phase flow of the nitrous oxide under high pressure is used to predict and avoid the cavitation into the feeding line tract of rocket engines, specifically of the compound rocket engines feeding line. The method involves a substantially simplified 1-D description of the fluid motion with sufficiently accurate determination of cavitation risk where the feeding duct suffers blunt variations of the cross area or steep turns and corners involving sensible static pressure variations of the fluid. A means of avoiding dangerous behaviors of the nitrous oxide is thus developed that could increase safety margins during the handling of this quite unpredictable oxidizer for the compound, combined or hybrid rocket engines.
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.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.