RUDN University mathematician calculates the optimal trajectories to Mars and Mercury for a spacecraft with electric propulsion
Chemical rocket engines create a large thrust, which allows bringing tons of cargo in orbit for a few minutes. At the same time, a huge amount of fuel is consumed. Once the spacecraft is in outer space, a large thrust becomes unnecessary, especially for automatic interplanetary stations that can fly to their destination for years.
An electric propulsion system (EPS) is better suited for such missions. The propellantworking medium in an electric propulsion system is ionized gas, which is accelerated in a magnetic field. Due to the low consumption of the working mediumpropellant, the EPS is able to work for a very long time.
"Because of the low thrust levels of EPS, it can be used most effectively only at sufficiently large distances from the attracting objects (planets or massive satellitesmoons), i.e., in interplanetary flights", — the study's author, RUDN University mathematician Alexey Ivanyukhin explains.
According to him, in the case of the use of EPS in the vicinity of a massive body, the available jet acceleration can be extremely low in relation to the gravitational acceleration — at the level of 10−5-10−4. But on interplanetary trajectories, the level of jet acceleration of the EPS is not much inferior to the Sun’s gravity, and their ratio can be 10−2-10−1.
Alexey Ivanyukhin reminded that for the exploration of the Solar System at the turn of the century EPS have been used as sustainerprimary propulsion system. The first such spacecrafts were Deep Space 1 (passage of an asteroid and two comets fly-by), Smart-1 (enter lunar orbit insertion), Hayabusa (delivery of soil samples from the asteroid Itokawa), Dawn (consecutive flight to the asteroids Vesta and Ceres).
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Researchers from the Faculty of Artificial Intelligence at RUDN University conducted a large-scale study that revealed systemic errors in large language models (LLMs) when diagnosing depression based on text. This work, carried out in collaboration with colleagues from AIRI, Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences, Ivannikov Institute for System Programming of the Russian Academy of Sciences, Moscow Institute of Physics and Technology, and MBZUAI, not only identifies the problem but also lays the foundation for the creation of more reliable and secure tools for detecting depression and anxiety.
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Imagine a world where everyone has enough food, clean water, access to education, and decent work. A world where nature is protected and the future of our planet is cared for. These are the Sustainable Development Goals—to achieve a sustainable future for all! To this end, in 2015, the United Nations (UN) defined 17 Sustainable Development Goals (SDGs). The SDGs are a global plan that helps countries and people work together towards a better future. All 193 UN member states have joined the plan.
Researchers from the Faculty of Artificial Intelligence at RUDN University conducted a large-scale study that revealed systemic errors in large language models (LLMs) when diagnosing depression based on text. This work, carried out in collaboration with colleagues from AIRI, Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences, Ivannikov Institute for System Programming of the Russian Academy of Sciences, Moscow Institute of Physics and Technology, and MBZUAI, not only identifies the problem but also lays the foundation for the creation of more reliable and secure tools for detecting depression and anxiety.
Alexandra Sentyabreva, a junior researcher at the Laboratory of Cell Technologies and Tissue Engineering at RUDN Research Institute of Molecular and Cellular Medicine at the Russian University of People's Friendship, won the competition for young scientists at the All-Russian Scientific Conference “Topical Issues of Morphogenesis in Norm and Pathology.” She was awarded the Academician A.P. Avtsyn Prize.