The space debris management and alleviation in the microgravity environment is a dynamic research theme of contemporary interest. Herein, we provide a theoretical proof of the concept of a lucrative energy conversion system that is capable of changing the space debris into useful powders in the International Space Station (ISS) for various bids. A specially designed broom is adapted to collect the space debris of various sizes. An optical sorting method is proposed for the debris segregation in the ISS by creating an artificial gravitational field.It could be done by using the frame-dragging effect or gravitomagnetism. An induction furnace is facilitated for converting the segregated metal-scrap into liquid metal. A fuel-cell aided water atomization method is proposed for transforming the liquid debris into metal powder. The high-energetic metal powders obtained from the space debris could be employed for producing propellants for useful aerospace applications, and the silicon powder obtained could be used for making soil for fostering the pharmaceutical-flora in the space lab in the future aiming for the scarce-drug discoveries for high-endurance health care management. The proposed energy conversion system is a possible alternative for the space debris extenuation and its real applications in orbiting laboratories through the international collaboration for the benefits to humanity.
The second-generation star tracker estimates pointing knowledge of a satellite without a-priori knowledge. But star trackers are larger in size, heavier, power hungry and expensive for nanosatellite missions. The Arcsecond Pico Star Tracker (APST) is designed based on the limitations of nanosatellites and estimated to provide pointing knowledge in an arcsecond. The APST will be used on the SNUSAT-2, Earth-observing nanosatellite. This paper describes the requirements of APST, trade-off for the selection of image sensor, optics, and baffle design. In addition, a survey of algorithms for star trackers and a comparison of the specifications of APST with other Pico star trackers are detailed. The field of view (FOV) estimation shows that 17°and 22°are suitable for APST and this reduces stray light problems. To achieve the 100% sky coverage, the FOV of 17°and 22°should able to detect the 5.85 and 5.35 visual magnitude of stars, respectively. It is validated by estimating the signal to noise ratio of APST and night sky test results. The maximum earth stray light angle is estimated to be 68°and a miniaturized baffle is designed with the exclusion angle of 27°.
The star tracker estimates pointing knowledge of a satellite in arcsecond accuracy in three axes without apriori knowledge. But star trackers are larger in size, heavier, power hungry and expensive for nanosatellite missions. The Arcsecond Pico Star Tracker (APST) is designed based on the limitations of nanosatellites and estimated to provide pointing knowledge in arcsecond. The APST is developed using fully COTS components because it's affordable, and less development time. A theoretical model is developed to estimate the performance of the COTS components (image sensor, lens, and baffle) used in the APST. Using this model, it's possible to validate if the components meet the requirements of the star tracker. But COTS component decreases the overall performance due to the errors in image sensor noise, lens distortion, and aberration etc. In APST, the lens distortion and inaccurate centroiding are the dominant error sources. The radial lens distortion causes an error in angular distance measurement, which leads misidentifying or identification of stars and high processing time. This leads to functional failure of APST. To overcome this, the relative star selection method is iv developed which selects the stars based on the angular distance information. Based on the fact that star pair with low angular distance has minimum measurement error, the relative star selection selects the four stars with low measurement error. It's compared with conventional bright star selection method, whereas stars are selected based on brightness. The relative selection algorithm is tested with 75-star constellation in star simulator and it has delivered 100% success rate and accuracy of 71 arcseconds in boresight. Whereas the conventional bright star selection delivered low success rate of 28% because the star pairs are not selected based on angular distance separation. Hence the relative star selection algorithm is efficient for APST.
Astronomical images captured by ground-based telescopes, including at University of Canterbury Mount John Observatory, are distorted due to atmospheric turbulence. The major constituents of atmospheric distortion are tip-tilt aberrations. The solution to achieve higher resolution is to develop and install a tip-tilt mirror control system on ground-based telescopes. A realtime tip-tilt mirror control system measures and corrects for tip-tilt aberrations in optical wavefronts. It effectively minimises the perturbation of the star image when observing with the aid of a telescope. To the best of our knowledge, this is the first tip-tilt mirror control system to be applied at a New Zealand astronomical observatory. This would extend the possibilities of correcting higher-order aberrations for 0.5 to 1.0 metre class, ground-based telescopes.
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.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.