Authors: Sagdiyev T.A.,Maturazov I.S.,Isakov N.A.

Abstract. The article investigates the causes, consequences, and prevention strategies related to aircraft engine failures. It provides a comprehensive classification of common engine malfunctions, examining mechanical wear, thermal stress, and operational factors that contribute to failures. A detailed analysis of statistical data on engine failure rates highlights critical trends and risk factors affecting engine performance and reliability. Furthermore, the study explores various diagnostic techniques designed to detect potential failures at early stages, reducing the likelihood of unexpected breakdowns. Modern aviation heavily relies on advanced maintenance strategies and cutting-edge technological solutions to enhance engine durability and efficiency. The article discusses preventive maintenance approaches, including predictive analytics, condition-based monitoring, and real-time diagnostics, which play a crucial role in minimizing failures. Additionally, the role of artificial intelligence and machine learning in fault detection and predictive maintenance is examined as a promising direction for improving aircraft engine reliability. The findings indicate that most engine malfunctions stem from mechanical degradation, excessive thermal loads, and human errors in operation and maintenance. Implementing regular inspections, utilizing advanced diagnostic tools, and integrating modern engineering solutions can significantly improve engine safety and longevity. The study underscores the necessity of continuous monitoring, timely preventive actions, and the adoption of innovative maintenance practices to enhance aviation safety and operational efficiency.

Keywords: aviation engines, fault analysis, aircraft maintenance, turbine inspection, non-destructive testing, thermal stress, mechanical wear, predictive maintenance, engine diagnostics.

Authors: Nagimov A.,Beketova G.

Abstract. In modern applications, Unmanned Aerial Vehicles (UAVs) are widely used in various industries such as logistics, agriculture, environmental monitoring, and emergency services. However, their operation is highly dependent on weather conditions, including wind speed, temperature, precipitation, and atmospheric pressure. The unpredictability of meteorological factors poses significant risks to the safety and efficiency of UAV flights.
This study proposes an intelligent weather prediction system for UAV flight planning, based on big data and machine learning technologies. The research examines modern methods of meteorological data processing, incorporating satellite imagery, IoT sensors, and historical records. To predict key weather parameters, advanced deep learning algorithms such as Long Short-Term Memory (LSTM) and Convolutional Neural Networks (CNN) are utilized. The developed system achieves a forecast accuracy of up to 92%, reducing flight planning time by 30% and enhancing overall operational safety. The integration of machine learning into UAV weather prediction systems ensures adaptability and enables rapid responses to changing climatic conditions. The obtained results highlight the significance of artificial intelligence and big data analytics in aviation. Additionally, this work suggests future research directions, including the consideration of additional environmental factors such as air quality and solar radiation, as well as the potential integration with autonomous flight management systems.

Keywords: big data, machine learning, weather forecasting, UAVs, flight planning, flight safety, predictive modeling.

Authors: Akhmet A.,Gusmanov A.,Akramkhanov A.,Akimbay Sh.

Abstract. Unmanned Aerial Vehicles (UAVs) have emerged as pivotal tools for addressing region-specific challenges in Kazakhstan, a nation characterized by vast geographic diversity, extreme climatic conditions, and infrastructural demands in remote areas. However, deploying UAVs in Kazakhstan’s unique operational environments—marked by temperature extremes (-40°C to +45°C), unpredictable wind gusts (15–20 m/s in the Almaty and Kostanay regions), and frequent GPS signal degradation in mountainous terrain—poses significant technical and logistical challenges. Physical testing of UAV control algorithms under these conditions is not only prohibitively expensive but also constrained by safety regulations, environmental unpredictability, and the sheer scale of operational zones. To address these barriers, this article proposes the development of a Kazakhstan-centric UAV simulation platform, designed to emulate the country’s environmental and operational realities with high fidelity.
Built on the Robot Operating System (ROS Noetic) and Gazebo 11, the platform integrates three novel components: (1) physics-based UAV dynamics calibrated using field data from Kazakh agricultural and disaster-response UAV deployments, including mass (1.5 kg), inertia tensor, and rotor thrust profiles; (2) synthetic sensor models (LiDAR, IMU, RGB cameras) with noise profiles tailored to regional conditions, such as dust-induced LiDAR range errors (±0.15 m) and temperature-dependent IMU drift (0.2°/hour at +40°C); and (3) environmental disturbance models derived from meteorological datasets provided by Kazhydromet, Kazakhstan’s national weather agency, including steppe wind dynamics (gusts up to 18 m/s) and probabilistic GPS signal loss (25–35% dropout rates in the Tian Shan mountains).
The platform’s modular architecture supports testing of adaptive control algorithms, including Model Predictive Control (MPC) for wind disturbance rejection, swarm coordination strategies for search-and-rescue missions, and reinforcement learning (RL)-based fault tolerance systems, under scenarios mirroring real-world Kazakh challenges. Case studies demonstrate its efficacy: in simulated high-wind scenarios (18 m/s gusts), a decentralized swarm coordination algorithm achieved 88% mission success in maintaining formation over the Tian Shan mountains, while an adaptive PID controller reduced trajectory tracking errors by 35% under +40°C sensor drift conditions. Cross-validation with field data from a DJI Matrice 300 UAV deployed in the Turkestan region confirmed a 94% correlation between simulated and real-world trajectory RMSE (0.12 m vs. 0.15 m), with energy consumption predictions deviating by less than 3% from observed values.

Keywords: UAV simulation, Gazebo-ROS integration, adaptive control algorithms, Kazakhstan environmental modeling, swarm robotics, sensor emulation, digital twins.

Authors: Abdulayev Kh.I., Allakhverdiyeva S.

Abstract. This article examines the application of non-destructive testing (NDT) methods for assessing the structural integrity of aircraft components made from polymer-based composite materials. Composite materials are widely used in aviation due to their high strength-to-weight ratio, corrosion resistance, and durability. However, these materials are subject to various defects caused by manufacturing processes, operational loads, and environmental factors such as temperature and humidity fluctuations. Traditional NDT methods, including ultrasonic, radiographic, optical-visual, capillary, and thermal testing, each have specific advantages and limitations. Ultrasonic testing, for example, does not provide comprehensive volumetric analysis, while radiographic methods require complex safety measures. Optical-visual techniques fail to detect internal defects, and capillary methods suffer from low productivity. To address these challenges, the study proposes improvements to existing diagnostic techniques, the development of new automated models, and the optimization of parametric indicators. The research also explores an integrated “human-machine-environment” system to enhance the reliability of defect detection and assessment. Advancements in NDT technologies will not only increase the accuracy and efficiency of aircraft inspections but also improve safety, extend service life, and reduce maintenance costs. The findings of this study contribute to the development of modern diagnostic complexes that ensure higher operational reliability of aircraft structures.

Key words: composite materials, defect, non-destructive testing method, loaded parts, diagnostic models, dynamic correlation.

Authors: Isgandarov I.A., Amirbayli S.

Abstract: In this article, analyzes the operational and technical characteristics of anti-icing systems used in modern civil aircraft, as a promising anti-icing system, a structural model of a system equipped with a microwave generator that can be installed on the wing of an aircraft, as well as on other aircraft surfaces that may be subject to icing, has been proposed. An application scheme for such a system for carbon-fiber and aluminum-based front edges has been developed, and the microwave generator to be used in the system will be used in the form of a block with low energy consumption and minimal traction on the icy parts of a particular type of aircraft.

Keywords: Anti-icing system, Leading edges ,Carbon fiber,De-icing, Anti-icing, Unmanned aerial vehicle,Composite,Dielectric ,Aerodynamic surface,Thermal anti-icing system, Pneumatic anti-icing system, Laminar flow, Turbulent flow, Microwave energy.

Authors: Suleimenova A.N., Karipbayev S.Zh.

Abstract. In the aviation industry, maintenance (MRO) is a critical process because it directly affects the safety, reliability, and cost-effectiveness of aircraft operations. Maintenance programs help to keep aircraft in serviceable condition, identify potential malfunctions before they occur, and optimize operating costs. This paper focuses on approaches to improve aircraft MRO performance, with emphasis on the maintenance program and reliability program, as well as opportunities to adapt procedures based on operator experience.

Keywords: aircraft maintenance program, reliability program, efficiency improvement, optimization, statistical methods in maintenance.

Authors: İsgandarov İ.A., Abdullayeva S.S.

Abstract. The article provides an overview of the analysis of early spacecraft. The results of reliability studies are considered and the causes of failures are identified. As a result, some studies examined cause-and-effect hypotheses for reducing the failure rate of spacecraft, and some considered design or implementation deficiencies. Failure classes are listed in order of increasing severity of failures and they are in turn divided into categories. The article concludes with a division of failures into hazard categories, shown in a tabular form, and summary data are presented.

Keywords: spacecraft, reliability, infant mortality, systematic malfunctions, launch vehicle, software.

Authors: Abdulayev Kh.I.,Vazirova T.N.

Abstract. In recent years, the increasing threat of plastic explosives has posed significant challenges to aviation security agencies, emphasizing the critical need for their timely detection and neutralization. Simultaneously, interest in the terahertz region of the electromagnetic spectrum has grown considerably. This study investigates the potential of terahertz time-domain spectroscopy (THz-TDS) for detecting the spectral signatures of concealed plastic explosives and their compounds. Additionally, the article presents the conceptual design of a terahertz spectrometer specifically developed for identifying concealed hazardous substances.

Кey words: aviation security, terahertz spectrometer, femtosecond laser, GaSe, InSe crystals, plastic explosives, HMX, RDX, TNT

Authors: Tuleushova R.Zh., Zhіrnova O.V.

Abstract. The article examines the application of digital technologies in pilot training, with a focus on the use of simulators for unmanned aerial vehicles (UAVs). The aim of the research is to evaluate the effectiveness of simulators in the training of UAV operators and to identify their role in developing key professional skills. The study analyzes existing simulators and their application methods, as well as conducts a comparative analysis of their effectiveness compared to traditional training methods. The results show that simulators contribute to the accelerated acquisition of practical skills and reduce the risk of errors in real flights. The conclusion provides recommendations for improving training programs through the use of simulators and outlines directions for future research on the application of digital technologies in aviation education.

Key words: digital technologies, simulators, unmanned aerial vehicles, pilot training, aviation education, UAV operator training.

Authors: Donenko L.N., Dorenko I.L.,Donenko S.L.

Abstract. This article discusses an innovative approach to analyzing the condition of runways affected by various factors using fractal cluster analysis and unmanned aerial vehicles (UAVs). The main element is the use of fractal analysis and modern artificial intelligence technologies to identify and evaluate corrosion and other defects.

Keywords: fractal, UAV, aviation, concrete, bifurcation, airfield.

Authors: Maturazo I.S., Odamboev S.Q.

Abstract. This article analyzes the uniqueness of Boeing and Airbus aircraft, their structural structure, technological innovations, and manufacturing processes. It is analyzed how these companies differ from each other due to their different approaches to aerodynamics, automated processes, quality of passenger service and production efficiency. The main points that distinguish Boeing and Airbus from each other are analyzed, and the article provides detailed information about their contributions to the aviation industry.

Keywords: Boeing, Airbus, aircraft construction, technological innovation, production processes, market strategies.

Authors: Rysbekova A.A.,Abdimatova T.D.,Keribaeva T.B.,Suranchieva N.R.

Abstract. Aircraft hydraulic systems, especially on the Boeing 737 and Boeing 757 aircraft, are an integral part of their structure and operation. They play a key role in ensuring flight safety, cornering control, raising and lowering flaps, landing gear, and other important aspects of flight. The word” hydraulics “comes from the Greek word” water ” and originally meant the study of the physical behavior of water at rest and movement. Aircraft hydraulic systems ensure the operation of aircraft components. The operation of the chassis, rims, light steering and brakes is carried out mainly with the help of hydraulic power systems. In more detail, the comparative analysis of the Boeing 737 and Boeing 757 hydraulic systems is an important step in understanding and improving the technical characteristics and functionality of these models, which ultimately contributes to improving the quality and safety of aircraft transportation.

Key words: aircraft, design, hydraulic system, Pascal’s law, battery.