One of the most common non-stationary phenomena in the solar atmospheric plasma are coronal compression waves, observed ubiquitously in the extreme ultraviolet range. The importance of studying them is due to their possible involvement in plasma heating and solar wind acceleration. Numerous observations and spectral analysis of compression waves reveal features that differ significantly from those of conventional waves. We believe that they can be viewed as sequences of individual localized acoustic disturbances. Based on our refinement of the damping and dispersion properties of acoustic waves in a heat-conducting, high-temperature plasma with radiative losses, we are able to explain the main observed features of compression waves, including the formation of two dominant periods in the spectrum. We believe that their detailed study may also shed light on non-stationary processes in the lower atmosphere.

Special damping systems are used to reduce loading of cargos at a single impact. The work considers the damping options in a form of conical and cylindrical shells. Calculation and experimental study was conducted to determine the conceptual design and parameters of the damper capable of decreasing accelerations across the protected cargo at impact loading. The results of the first tests show that some dampers did not operate as designed. In particular, no deformation of conical dampers neither deceleration across the cargo was observed. Among other causes, the use of simplified material models resulted in deviation of the experimental results from the calculation. Upon validation of the calculation models the mechanical characteristics of the materials were refined and the most suitable material models were determined. The results of further experiments showed a satisfactory agreement between the calculation and experimental results. The conducted study was used to issue recommendations on selecting material models for dampers

This paper discusses modern tools and approaches to the design of ETL systems for the integration and preprocessing of raster, vector, and tabular geospatial data. These data can subsequently be used for analysis using machine learning methods. The proposed approach is based on a modular pipeline architecture adapted to the characteristics of GIS data formats. It supports integration with machine learning pipelines without requiring costly licenses or substantial modifications of existing platforms.

A specialized ETL pipeline based on the OpenNeurons platform and PostgreSQL/PostGIS database is presented. The system includes configurable modules for describing data sources and adapters implemented in Python using libraries such as geopandas, rasterio, and pyshp. The system also includes a driver for direct interaction with file storage and scheduled data updates. It further provides a web interface for task management, monitoring, and logging. The developed system was tested on real-world geospatial datasets. Firstly, a unified dataset containing 227 geological and geophysical attributes for the eastern sector of the Russian Arctic was created and prepared for machine learning analysis. Secondly, binary classification of 240 morphostructural nodes in the Caucasus region using Gradient Boosting and AutoKeras, an F1-score close to 1.0 was achieved on the test set. Comparison with the KORA-3 algorithm showed a 67% agreement in predictions, indicating the potential applicability of the proposed approach, although further validation on independent datasets is required. Compared to general-purpose ETL solutions, the proposed system offers low deployment costs, high extensibility through custom adapters, and tight integration with machine learning frameworks. The results demonstrate the applicability of the developed ETL pipeline for geospatial data processing tasks.

The Hirota method is applied to look for the soliton solutions of nonlinear higher order Schrӧdinger equations. The equations of the fourth and sixth orders of the Schrodinger hierarchy are studied in detail. Using the formulas for derivatives of the functions for the higher order equations are represented via the Hirota operator. The equations are presented as a system of two equations. One, two and three soliton solutions of the nonlinear Schrӧdinger hierarchy are obtained.

A mathematical model of a VVER-type reactor has been constructed in a point approximation, taking into account several temperature feedbacks. The qualitative transition of thermophysical equations to a point model is considered. Asymptotic equations in small deviations are obtained. Based on this model, the study formulates a linear regression problem in order to recover the temperature coefficients of reactivity from time series of fuel and coolant temperatures, and reactimeter. Initial estimates of the reactivity coefficients are obtained based on the statistical characteristics of the series. A high correlation between temperature variables leads to a degeneration of the covariance matrix. The determinant of the covariance matrix, located in the denominator, entails instability of the solution, which is the main obstacle to obtaining reliable identification results. To analyze the stochastic model and calculate covariances, the application of the Lyapunov equation for covariances to linearized equations is considered, and the values of derivative covariances are found. The conditions under which the Pearson correlation coefficient between differentiated temperature time series turns out to be less than the original time series are analytically determined. Combination of median filter and differentiating filter is proposed, along with regularization to restore the coefficients. The results obtained demonstrate the possibility of reducing multicollinarity, potentially increasing the stability of the obtained estimates of temperature reactivity coefficients in regression methods.

The article discusses approaches to ensuring the safety of the RBMK-1000 reactor during its decommissioning, including the complete removal of fuel from the reactor core. The article outlines the principles of safety based on regulatory requirements and the need to ensure critical safety functions for a permanently shut down reactor. The authors analyze the limits and conditions of safe operation, taking into account the specific characteristics of the reactor's operational state during its decommissioning. The expediency of automating the functions of analyzing the readings of neutron flux sensors, diagnosing the available reserves up to their sensitivity thresholds, and generating recommendations for repositioning the sensors within a separate system of information support for personnel at the stage of unloading nuclear fuel from the reactor core has been noted. The safety conditions for the RBMK-1000 reactor presented in the article, which involve the complete unloading of nuclear fuel from the core, can be used as a basis for developing a method for building an information support system for RBMK-1000 reactor units during their preparation for decommissioning.

After the accident at the Fukushima-1 nuclear power plant (Japan), the consequences were exacerbated by a steam-zirconium reaction with the formation of hydrogen, all the world's industrial companies that develop and produce nuclear fuel, got involved in active research on new combinations of nuclear fuel materials and fuel element shells, that is, in the development of new types of nuclear fuel that are resistant to accidents (the so-called tolerant fuel). This paper presents a comprehensive analytical methodology for assessing interconnections between the technological parameters of nuclear fuel cycle (NFC) for VVER/PWR/BWR reactors using tolerant fuel, and the impact of these parameters on the fuel component of the cost of nuclear power generation. Universal analytical relationships between burnout, enrichment, thermal tension of the fuel, the frequency of overloads and the number of heat-generating assemblies unloaded, consumption of fuel and natural uranium, as well as the cost indicators of key technological processes are shown. Grid diagrams have been constructed to determine the fuel component of the cost of nuclear power plant electricity in a wide range of technological parameters for tolerant fuel.

The article presents the methodological foundations for training operational and maintenance personnel of nuclear power plants using a physical-virtual training complex (PVTC). By analyzing the workflow, the most important components that should be implemented in the training system were identified. Based on the elements of the workflow, a model for developing trainees' skills during simulator sessions was developed. In order to improve the effectiveness of nuclear power plant staff training, professional skills required for servicing electric drive equipment have been formulated. Based on industry experience, it is clarified that in addition to competencies directly related to working with equipment, an absolutely essential skill is the ability to work with documentation, organize the workspace, and maintain stress resilience. As part of addressing this task, the components of the work process are described, including the objects and (interfering) factors that should be reproduced in the training simulator, as well as the actions of personnel with the objects under the influence of these factors. Considering the priority of safety in nuclear power plant operations, performing tasks on the simulator should train personnel to use error-prevention tools. Simulator tasks are formulated in such a way that during the training process, personnel learn to use error prevention tools (EPT). The dynamics of professional skill development during training on the simulator are shown, thereby demonstrating the connection between the simulator's functionality and the formation of necessary skills.