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June 5, 2026
Neural Network Maps as a Method for Constructing Mathematical Models
Scientists from HSE University–Nizhny Novgorod and the Institute of Physics Belgrade, Serbia, are jointly exploring the application of machine learning techniques and neural networks to the study of nonlinear dynamics. Natalya Stankevich, Leading Research Fellow at the Laboratory of Topological Methods in Dynamics of the Faculty of Informatics, Mathematics, and Computer Science at HSE University–Nizhny Novgorod, spoke to the HSE News Service about this international project.
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Comparison of Coulomb-2, NASCAP-2K, MUSCAT and SPIS codes for geosynchronous spacecraft charging

Advances in Space Research (includes Cospar Information Bulletin). 2016. Vol. 57. No. 2. P. 671–680.
Novikov L., Makletsov A. A., Sinolits V. V.

In the paper, we discuss numerical modeling of spacecraft charging in geosynchronous orbit which was done using Coulomb-2, NASCAP-2K and SPIS codes, and present data obtained using the MUSCAT code too. The main distinctive features of the codes above are specified, description of the Coulomb-2 code is given in more details. We compare the results of calculations obtained for similar models of spacecrafts with identical surface materials and parameters of the space plasma environment. The possible reasons of divergence of the modeling results are discussed

Research target: Physics Electronics and Electrical Engineering
Priority areas: engineering science
Language: English
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Keywords: mathematical modelingspacecraft chargingspace plasmamaterial properties
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