RUDN scientists have found out how to reduce the cost of flights to satellites
1200 spacecraft rotate in different orbits around the Earth. However, the period of their active existence is limited due to the short-lived on-board equipment, malfunctions and the inevitable fuel consumption. Classic maintenance schemes, when the service device is launched from the Ground, lead to huge costs. Such schemes are justified if the satellite is in orbit in a single copy and is of high value (for example, the Hubble telescope).
A team of RUDN scientists has found the best solution for servicing low-orbit groups that consist of dozens of satellites — it minimizes fuel consumption due to optimal maneuvering. Using the algorithm on board the service module will allow you to quickly and with high accuracy estimate the trajectory of the flight to the satellites for a limited time, taking into account the fuel supply on board the module.
"One of the primary tasks when creating promising space systems, along with technical implementation and solving legal issues, is the choice of the orbital construction of the system, the calculation of flight trajectories... We have created a number of high-speed algorithms and a software and mathematical apparatus for selecting the orbits of the space service system and analyzing its functioning according to various optimization criteria. Our algorithm is also applicable for assessing dangerous approaches to other satellites and space debris objects," Vladimir Razumny, Ph.D., Associate Professor of the Department of Mechanics and Mechatronics, Academy of Engineering, RUDN University.
RUDN summarized the results of the scientific competition "Project Start: work of the science club ". Students of the Faculty of Physics, Mathematics and Natural Sciences have created a project for a managed queuing system using a neural network to redistribute resources between 5G segments. How to increase flexibility, make the network fast and inexpensive and reach more users — tell Gebrial Ibram Esam Zekri ("Fundamental Computer Science and Information Technology", Master's degree, II course) and Ksenia Leontieva ("Applied Mathematics and Computer Science", Master's degree, I course).
The National Demographic Report, 2023 Demographic Well-Being of Russian Regions (hereinafter - the National Demographic Report) was prepared by the scientific team of the Institute of Demographic Studies of the Federal Research Center of the Russian Academy of Sciences, the Vologda Scientific Center of the Russian Academy of Sciences, Peoples' Friendship University of Russia, the Center for Family and Demography of the Academy of Sciences of the Republic of Tatarstan, as well as with the participation of leading scientists from the Republic of Bashkortostan, Stavropol Krai, Volgograd, Ivanovo, Kaliningrad, Nizhny Novgorod, Sverdlovsk Oblasts and Khanty-Mansi Autonomous Okrug–Yugra.
RUDN summarized the results of the scientific competition "Project Start: work of the science club ". Students of the Faculty of Physics, Mathematics and Natural Sciences have created a project for a managed queuing system using a neural network to redistribute resources between 5G segments. How to increase flexibility, make the network fast and inexpensive and reach more users — tell Gebrial Ibram Esam Zekri ("Fundamental Computer Science and Information Technology", Master's degree, II course) and Ksenia Leontieva ("Applied Mathematics and Computer Science", Master's degree, I course).
What is your first association with the word “laboratory”? Flasks and beakers? Microscopes and centrifuges? Yes, many of us would answer the same way.
The National Demographic Report, 2023 Demographic Well-Being of Russian Regions (hereinafter - the National Demographic Report) was prepared by the scientific team of the Institute of Demographic Studies of the Federal Research Center of the Russian Academy of Sciences, the Vologda Scientific Center of the Russian Academy of Sciences, Peoples' Friendship University of Russia, the Center for Family and Demography of the Academy of Sciences of the Republic of Tatarstan, as well as with the participation of leading scientists from the Republic of Bashkortostan, Stavropol Krai, Volgograd, Ivanovo, Kaliningrad, Nizhny Novgorod, Sverdlovsk Oblasts and Khanty-Mansi Autonomous Okrug–Yugra.