Erratum to: Use of the DBM Model to the Predict of Arrival of Coronal Mass Ejections to the Earth

Cosmic Research - An Erratum to this paper has been published: https://doi.org/10.1134/S0010952521120017     

Method of energy efficiency assessment for power supply of autonomous drive systems for perspective mobile objects

Based on an integrated approach, we solve the optimization problem for energy content and weight-dimensional characteristics of the electric servo drive by synthesis of structure and analysis of characteristics for different power supplies. The generalized power supply model, developed for different power supply of drive control systems, is given.     

Onboard system for measuring the parameters of wind vector during parking,starting and takeoff-landing modes for helicopter with aerometric and ion-beacon measuring channels

The problem and features of measuring the speed and the direction angle of the wind vector relative to the longitudinal helicopter axis during parking, starting and takeoff-landing modes by onboard means are considered. The construction principles, information processing algorithms and advantages of onboard system for measuring the wind vector parameters based on ion-beacon and aerometric measuring channels, are disclosed.     

On the stability of stationary motions of a system of coaxial bodies

We consider the stability of stationary motions of a model of a spacecraft as a system of coaxial bodies with small asymmetry caused by the shift of the axes of dynamic symmetry of bodies relative to the axis of rotation. We determine the stationary motions of the system; their stability is studied with respect to both the projections of angular velocity and the position of the axis of rotation. The sufficient conditions for the stability of these stationary motions are obtained by constructing a Lyapunov function, and the necessary conditions are obtained by analyzing the corresponding linearized equations of perturbed motion.     

Methodology of using artificial neural networks for imitating the loading of a single-rotor helicopter

A methodology of creating a loading imitation model of a single-rotor helicopter with artificial neural network algorithms is considered. Stages of creation, the structure, and an algorithm of searching for an optimal neural networks configuration of loading imitation model are presented.     

Study of thin-walled parts shaping process based on flanging and embossing

This paper presents the results of analyzing the shaping of thin-walled conical parts with the uniform thickness along generatrix.     

Influence of the interplanetary magnetic field on ULF oscillations of the ionospheric resonator

A weak but statistically reliable dependence of the diurnal activity of oscillations in the ionospheric Alfvén resonator on orientation of the interplanetary magnetic field ahead of the magnetospheric front has been detected based on observations of ULF oscillations at Sayan solar observatory Mondy of the Institute of Solar–Terrestrial Physics. The interpretation of the result has been proposed. The essence is that the electromagnetic fluctuations penetrate into the magnetosphere from the interplanetary environment and influence the ionospheric resonator. The formulation of the problem and the method of solving it are part of the broad program of the experimental and theoretical study of the influence of the interplanetary magnetic field on the oscillation regime of ULF oscillations of the magnetosphere.     

Ionosphere monitoring and inter-frequency bias determination using Galileo: First results and future prospects

We present first results of using the European Global Navigation Satellite System (GNSS) Galileo for determining the Total Electron Content (TEC). Furthermore, we describe a calibration technique which can be used to determine GNSS inter-frequency and inter-system biases along with calibrated TEC.     

An Artificial Neural Network based approach for estimation of rain intensity from spectral moments of a Doppler Weather Radar

By using a Doppler Weather Radar (DWR) at Shriharikota (13.66°N & 80.23°E), an Artificial Neural Network (ANN) based technique is proposed to improve the accuracy of rain intensity estimation. Three spectral moments of a Doppler spectra are utilized as an input data to an ANN. Rain intensity, as measured by the tipping bucket rain gauges around the DWR station, are considered as a target values for the given inputs. Rain intensity as estimated by the developed ANN model is validated by the rain gauges measurements. With the help of a developed technique, reasonable improvement in the estimation of rain intensity is observed. By using the developed technique, root mean square error and bias are reduced in the range of 34–18% and 17–3% respectively, compared to Z–R approach.