Forecasting non-scheduled air transportation demand is essential for effective resource allocation, operational planning, and decision-making. In this paper, the use of the ARIMA (Auto Regressive Integrated Moving Average) model for forecasting non-scheduled air transportation is explored. The ARIMA model is a widely employed time series forecasting technique which combines autoregressive (AR), differencing (I), and moving average (MA) components. It has been successfully applied to various fields and can be adapted to capture the patterns and trends in non-scheduled air transportation data. To forecast non-scheduled air transportation demand, historical data, including relevant variables are firstly collected. The data are processed by identifying and addressing any missing values, outliers, or trends that could affect the model's performance. Next, the ARIMA model is applied to the pre-processed data, utilising techniques such as model identification, parameter estimation, and model diagnostics. The ARIMA model captures the relationships between past observations and uses them to predict future demand for non-scheduled air transportation. The forecasting results from the ARIMA model provide insights into expected demand levels, peak periods, and potential fluctuations in non-scheduled air transportation. These forecasts enable decision-makers to optimise resource allocation, schedule aircraft availability, and enhance operational efficiency. However, it is important to note that the accuracy of ARIMA forecasts depends on various factors, including the quality and representativeness of the data, the appropriate selection of model parameters, and the stability of underlying patterns in the time series data. Regular model evaluation and refinement are crucial in maintaining forecasting accuracy.

This study presents a method for diagnosing the technical condition of aviation gas turbine engines (GTE) using recurrent neural networks (RNN) and long short-term memory networks (LSTM). The primary focus is on comparing the effectiveness of these models for forecasting key operating parameters of GTEs, such as vibrations, turbine-inlet temperatures, and rotor speeds of low and high pressure. The research involved thorough data cleaning and normalization, including handling missing values, normalization using Min-Max Scaling, outlier removal, data decorrelation, and time series smoothing. The RNN and LSTM models were trained using the backpropagation through time (BPTT) algorithm to accurately forecast GTE operating parameters. The results show that both models demonstrate high forecasting accuracy, but the RNN models perform better in most parameters. For vibration parameters (VIB_N1FNT1, VIB_N1FNT2, VIB_N2FNT1, and VIB_N2FNT2), RNN models achieved lower RMSE and MAE values, confirming their higher accuracy. For temperature parameters (EGT1 and EGT2), RNN models also showed higher accuracy rates. Meanwhile, LSTM models achieved better results for some rotor speed parameters (N21 and N22). The findings emphasize the necessity of choosing the appropriate model based on the nature of data and the specifics of the parameters to be forecast. Future research may focus on developing hybrid approaches that combine the advantages of both models to achieve optimal results in diagnosing the technical condition of GTEs.

In this paper the authors have created the integrated mathematical model of the transcribing system adapted to aviation conditions, taking into account many factors. The paper analyses the following main problems of transcribing Englishlanguage speech between pilots and air traffic controllers (ATC) (radio exchange), namely: the tendency to use abbreviations and specialized vocabulary, which can cause misunderstanding for one of the parties; speech illegibility due to noise in the cockpit or in the radio frequency zone; insufficient clarity and accuracy in expressing instructions by air traffic controllers can lead to errors in the understanding and execution of instructions by pilots; limitations in the availability of communication channels and their overloading; lack of training in the use of English-language terms and expressions in the air traffic control system. Inadequate training in English language terms and expressions can lead to difficulties in understanding instructions and messages between pilots and air traffic controllers; differences in accents and pronunciation of communicators can also cause difficulties in speech comprehension. Aviation communication errors are critical to aircraft safety. The ambiguity of certain phrases or expressions in English can lead to misinterpretation and misunderstanding of instructions by controllers; lack of context or lack of information about the current situation on board the aircraft can make it difficult to transcribe speech and lead to misunderstanding of messages; use of slang or informal expressions can make transcribing English-language speech more difficult and cause misunderstandings; lack of opportunity to ask clarifying questions or request a real-time repetition of a message can lead to misunderstandings; and the use of slang or informal expressions can lead to misunderstandings. Even the most minor errors can have disastrous consequences. The analysis revealed that in the overwhelming majority of cases it is linguistic factors that cause misunderstandings between participants in radio conversations, which is evidence of the need to develop and improve this model.

One of the key areas of development of the Russian Federation transport system and its regions is the improvement of infrastructure and route networks of passenger air transportation, including in hard-to-reach regions of the Russian Federation. Regional aviation is an important segment of the passenger air transportation network and the entire transport system of the country. In combination with local air transportation, regional aviation in most areas of the Far North and areas equated to them ensures their transport accessibility, aviation mobility of the population and in many cases is an alternative mode of transport. The state support measures for air carriers are being implemented to ensure the stable functioning of air transport and the development of transport accessibility in the regions of the Russian Federation. The article considers the main goals and measures of state subsidization of air transportation in the transport system of the country and its regions, as well as financial and non-financial measures of their state support, including in the context of external sanctions. A subsidy scheme has been proposed to consolidate the existing mechanisms thus ensuring the balanced risk minimization for the state and air carriers while expanding the route network of the country and regions. The processes of development of subsidy mechanisms and the corresponding regulatory and methodological framework, the effectiveness of their implementation, including taking into account the specifics of the northern and hard-to-reach regions, are analyzed.

During production of modern large transport aircraft, engine arrangement mounted on the elastic pylons under the wing is widely used. This arrangement of engines has certain advantages, however, there are also significant dynamic features due to the fact that the partial frequencies of vertical and horizontal (lateral) vibrations of elastic pylon-mounted engines are close to the wing bending and torsional natural frequencies of low modes. It is this frequency spectrum that determines the dynamic response of the aircraft as a whole to external disturbance input, and also significantly affects the dynamic stability of the aircraft. A number of technical solutions have been proposed to damp vibrations of the elastic pylon-mounted engines, including the implementation of the “freed engine” principle. To increase the dissipative parameters of the pylon-mounted engines vibrations, this paper proposes to use special devices – powered gyroscopes, which are the main part of the gyroscopic damping system. Numerous theoretical studies of the possibility of using powered gyroscopes have shown that the stability of a dynamic system can be increased by introducing additional gyroscopic, dissipative and potential forces into it. It is known that a method of direct gyroscopic stabilization is proposed to control aeroelastic oscillations of aircraft structural elements. The article proposes to use powered gyroscopes to damp lightly damped vibrations of pylon-mounted engines of a large aircraft. In order to assess the possibility of practical application of the gyroscopic damping system (GDS), experimental studies were conducted on a dynamically similar flutter model (DSFM) of a large aircraft type An-124 with four pylon-mounted engines under the wing. The studies included two stages: frequency and flutter tests. A gyroscopic device made according to the scheme of a rate gyroscope, which was installed inside the engine nacelle, was used as the GDS. The article presents the results of the experiments to assess the effect of the GDS on the dynamic characteristics of the DPFM. The analysis of the normalized amplitude-frequency characteristics of vertical and horizontal oscillations in the center of mass of the outboard engines shows a significant (by 1.5...5 times) decrease in the peak values of the oscillation amplitudes across the entire frequency range covered. The results of the experimental studies of the effect of the GDS on the flutter characteristics of the aircraft model showed a significant (7...15%) flutter speed enhancement at all levels of aircraft refueling. At the same time, with the gyroscopic damping system powered on, the self-oscillations are sluggish and incoherent, and the flutter modes change from one to another due to the gyroscopic coupling of the longitudinal and lateral motion.

Due to the increasing complexity of aircraft navigation equipment and the growing demands placed on them, there is a need to study and improve existing navigation and filtering algorithms by solving problems of developing full-scale research simulators. The article presents the results of work in the field of creating a full-scale simulator for research of navigation and filtering algorithms for a strapdown inertial navigation system (SINS) comprising: primary navigation data sensors made using microelectromechanical system technology (MEMS), servos and a navigation platform with two-degrees-of-freedom in roll and pitch. The article presents the features of the design, hardware and algorithmic implementation of the test rig taking into account the prospects for its development in terms of using the number of degrees of freedom of the platform (pitch, roll and yaw channels). The implemented principle of integrating the Simulink model of the control object is described. The control object consists of a controller based on the Arduino platform, a GPS sensor, a GY-91 sensor with an inertial measurement unit consisting of three orthogonally located: angular velocity meter, accelerometer and the single-channel barometer based on the MP280 MEMS. An algorithm for positional (manual) control of the navigation platform by pitch and roll angles using two servos, through a control stick and a virtual COM port is implemented. A diagram illustrating the logic of interaction of the structural elements of the simulator, a part of the software implementation of the complementary filter used, as well as the function of its calculation and simulation links of the Simulink model are presented. The information exchange between the PC and the Arduino microcontroller is considered. A conclusion was made about the feasibility of creating and using the developed simulator to justify the use of a particular navigation and filtering algorithm for a specific type of aircraft.