The aviation industry faces the difficult task of maintaining and further increasing the population air mobility at the present stage of domestic air transport and country economy development. It is fixed in the Comprehensive Program for Russian Federation Aviation Industry Development until 2030 (as amended by Decree of Russian Federation Government No. 1102-r dated May 4, 2024). There is an urgent need to develop and introduce domestic production components into aircraft type design in the context of the cessation of interaction between Russian aviation enterprises and foreign suppliers of goods and services. These actions make it possible to ensure industrial technological sovereignty and further operation of aviation equipment with the required levels of reliability and safety. The article presents a flowchart of this process developed by the authors. The flowchart considers possible types of import substitution of components. The authors performed a comparative analysis of the forecast of fleet retirement and commissioning of newly developed aviation equipment based on the available statistical data on the operation of short-haul aircraft. The need for the development of sectoral corrective measures is shown based on its results. This fact confirms the relevance of the chosen research area. The process of integration of Russian-made components into the aircraft structure is considered from the point of view of program management in the publication. The authors describe the basic principles and methods of prioritizing projects using the example of 10 components. This considers the total budget of the program, as well as its resource intensity. The optimization task is formulated in the publication based on the results of the work performed. This publication is the main one for the further development of an algorithm that will allow solving priority tasks of continued airworthiness of both the fleet in operation and newly developed aircraft.

The paper presents the results of application of Seq2seq models based on neural networks for nowcasting-forecasting with a lead time of up to 2 hours – of thunderstorm activity in order to increase situational awareness of aircraft crews. Various recurrent and convolutional recurrent models were created and trained on the basis of radar meteorological observations of thunderstorm cells. The results showed that convolutional recurrent neural networks (ConvRNN, ConvLSTM, ConvGRU) outperform classical recurrent models and improve the thunderstorm forecast by 25–30% in terms of RMSE (root mean square error) metric compared to the baseline model, which always selects the most recent radar image available at the time of prediction. Nevertheless, despite the fact that the convolution recurrence models can accurately represent the general trend of thunderstorm cloud shape changes, the accuracy of predicting the intensity of thunderstorm cells is usually overestimated. Application of the proposed thunderstorm activity forecasting technology can enhance the situational awareness of the flight crew improving the projection of the current situation into the near future and optimizing the decision-making process for thunderstorm avoidance by providing crew members with predictive information about thunderstorm development on the navigation display screen. Future research is expected to further optimize the model architecture and integrate the predictive technology into flight crew decision support systems.

Currently, there is an urgent need to create a high-quality automated risk assessment tool for the use of (unmanned aircraft) UAVs. There is no universal approach to risk management in unmanned civil aviation, and the risk assessment of the operator is largely individual. At the moment, no tool has been developed for plotting optimal routes for UAV flights in airspace, which would avoid piloting in areas with unacceptable risk. The article suggests the use of fully functional geographic information systems (GIS) to assess the risks of performing a flight mission. For a qualitative assessment of the risks of a particular flight assignment, it is proposed to take into account the situational component in the relevant segment of airspace and the ground (surface) situation. The article systematizes the main groups of factors that are important for assessing the risks of using BV. UAV flights are exposed to environmental factors, while posing a danger to surrounding objects. A formula for analyzing the spatial and temporal distribution of risk values in the airspace is derived. The minimum size of the simulation cell is proposed. A universal approach to assessing the risks of a UAV flight by various operators is substantiated, and a methodology for spatiotemporal analysis of the distribution of risk values based on the use of GIS is given. The results of the analysis of spatial and temporal information in the GIS environment make it possible to zone the airspace according to the degree of flight acceptability and build the optimal route outside areas with an increased risk of an aviation incident or accident. The developed spatio-temporal risk-oriented model can be used to support management decision-making in terms of building optimal routes for the movement of UVs.

Estimation of reserves of combustion process stability in gas turbine engine (GTE CC) based on artificial modeling of non-stationary process (NP) excitation in the combustion chambers in temperature-pressure parameters is an actual problem in engine engineering. An increasing number of aircraft require the use of engines with high gas dynamic stability (GDS) up to 30% and more, for example, when creating power plants for vertical and short take-off and landing aircrafts, ekranoplans (ground-effect vehicles) and etc. The use of computational fluid dynamics (CFD) tools for calculating combustion flows in the combustion chamber of a gas turbine engine is currently an integral part of the design process, since a numerical study, in contrast to a full-scale experiment, requires significantly fewer material resources providing the ability to model expensive and unsafe cases of aircraft flight operation that are difficult to implement at the stage of bench tests, such as: crossing a jet distrail or a shock wave front (e.g., when an ammunition detonates) in front of the air intake of an air-jet engine, critical crosswind during takeoff leading to flow separation on the air intake cowl, vertical gusts and atmospheric turbulence, flight at high angles of attack, aircraft evolution (slip, etc.). The results of numerical simulation are decisively determined by the limitations of the applied models and simplifying assumptions for the simulated flow. There are many sources of errors in any calculation using computational gas dynamics methods: accumulated calculation errors, sensitivity to grid size, discretisation, flow extrapolation in grid interfaces of the used solver (ANSYS.Fluent), errors of turbulence models, assumptions and simplifications applied to the design, etc. This paper considers the grid effect on the problem of proving the random nature of gas oscillations in the combustion chamber of a gas turbine engine, which is essential for determining the gas dynamic stability of the engine as a whole.

The task of improving the professional training of air traffic controllers is one of the most important in civil aviation (CA). This is due to the fact that the level of professional training largely determines the level of flight safety and the efficiency of airspace utilization. Updating and technical modernization of ATC systems and aids requires the development of new programs and methodologies for ATCO (ATC officers) training. The methodology of simulator training on the air traffic control simulator, which is a key component of practical training for ATCO in civil aviation educational institutions, also requires continuous improvement. This study analyzes and summarizes the experience of organizing and conducting training exercises on the air traffic control simulator at a university focusing on the phenomenon of exercises on the ATC simulator. The essential features of the exercise were considered: objective, task, aeronautical background, coherence with the training process, type, as well as properties: difficulty and complexity of the exercise. In studying the complexity of the exercise, the concepts of relative and absolute complexity were introduced. The relative complexity of the exercise reflects its external aspect in relation to its place in the structure of the academic discipline and within the system of all the skills being developed. The absolute complexity of the exercise reflects its internal structure as an interconnected set of skills required exclusively for the completion of that specific exercise. Analytical dependencies are proposed for calculating the relative and absolute complexity, taking into account the principle of one complexity. The concepts of practical, average, and individual difficulty of the exercises on the air traffic control simulator are introduced. An analytical dependence for their calculation is proposed. A classification of the exercise on the air traffic control simulator is proposed based on the following criteria: the objectives of the exercise, the form of the exercise, the task being solved in the exercise, the execution time, the degree of instructor involvement, and the form of the comeback from the instructor. Definitions of the concept of the exercise type and, in fact, the very concept of the exercise on the air traffic control simulator are proposed. The results obtained in this work are aimed at further development of theoretical principles in air traffic controllers training and can be used in organizing and conducting simulator practice on the air traffic controller simulator in educational institutions of civil aviation.

A methodology is proposed to obtain consistent and coherent estimates of greenhouse gas and precursor gas emissions from road transport and off-road vehicles and to quantify their accuracy and uncertainty. Accuracy increase of the estimates is achieved by detailing the initial data, reflecting the specific features of the national vehicle fleet structure and transport activity indicators, for which a wide range of statistical, probabilistic and expert methods are used. Using the methodology implemented in the “Transport Model” software product, it is possible to reconstruct time series of emissions for previous periods with an assessment of their accuracy and uncertainties, as well as to perform scenario modelling in order to forecast future emissions. The methodology was used to obtain quantitative estimates of three types of greenhouse gases emissions and three precursor gases from road transport and off-road vehicles for the period of 2010 to 2022, to compare the results with National Inventory data, to produce emission estimates for four categories of off-road vehicles for the first time, and to estimate fuel consumption and changes in the number of vehicles of all categories for the period of 1990 to 2022. An information array containing official statistical data on indirect indicators of transport activity by vehicle category for the period of 1990 to 2022 was compiled, the results of the emissions calculations were compared with the indirect indicators using multiple regression methods, and the accuracy and uncertainties of these results were quantitatively assessed. The estimated greenhouse gas emissions were considered as random values for which a confidence interval was calculated as an indicator of uncertainty and a median correction as an indicator of accuracy. The high quality of the results of the calculations based on the methodology considered was confirmed.