https://jeelm.vgtu.lt/index.php/Aviation/issue/feedAviation2024-10-30T18:28:40+02:00Prof. Gintautas Bureikagintautas.bureika@vilniustech.ltOpen Journal Systems<p>Aviation publishes original research, reports and reviews about aviation. <a href="https://journals.vilniustech.lt/index.php/Aviation/about">More information ...</a></p>https://jeelm.vgtu.lt/index.php/Aviation/article/view/22143Wireless-based information model of the common operation of the elements of the aviation gas turbine engine2024-09-20T18:27:59+03:00Serhii Tovkachss.tovkach@gmail.com<p>The paper is focused on ensuring an automatic reliable operation of aviation engine in a wide range of modes using wireless data transmission. This also helps to reduce the weight of it’s control system, the mass and dimensions of the modular construction of the engine. It is possible only on the basis of complex study of the transition processes of the aviation engine with the mutual influence of the course, from the theoretical point of view. Firstly, it is necessary to define method for start up as the process of engine transition from a state of rest in ground conditions or autorotation mode in flight to minimum stable operation mode. Then, in process start up for the initial spin up of the engine rotor, fuel supply and ignition a special starting system based on the Wireless Distributed Automatic Control System must be used in the combustion chamber. In practical application, this study can be used to create the new generation of aviation gas turbine engines and their control systems for subsonic and supersonic aircraft, identification their models based on the diagnosing the state of the engine according to dynamic ones parameters.</p>2024-09-20T09:30:46+03:00Copyright (c) 2024 The Author(s). Published by Vilnius Gediminas Technical University.https://jeelm.vgtu.lt/index.php/Aviation/article/view/22146Improvement of fatigue management methodology related to flight crew2024-09-20T18:27:58+03:00Iyad Alomaralomar.i@tsi.lvSofija Alomarmetalsophia1@yahoo.comInna Stecenkostecenko.i@tsi.lv<p>This research focuses on flight crew fatigue and the improvement of a fatigue management methodology that helps in reducing fatigue for flight crew members, aiming to improve their well-being and overall aviation safety of flights. A thorough literature review established a foundation for understating fatigue and the available methodologies for fatigue management for flight crew members. To make the picture clearer, an empirical study was conducted, and it included surveys and interviews with flight crew members. The gathered data underwent detailed statistical and thematic analysis to identify key factors influencing fatigue among flight crew members. Findings revealed multiple contributors to the flight crew member fatigue. Using these insights, a fatigue management methodology is proposed, integrating real-world experiences with evidence-based strategies. The proposed methodology and the recommendations that were formed are relevant for a company management which is facing flight crew fatigue management issues.</p>2024-09-20T10:02:33+03:00Copyright (c) 2024 The Author(s). Published by Vilnius Gediminas Technical University.https://jeelm.vgtu.lt/index.php/Aviation/article/view/22194Analytical calculation approach for rocket nose cone structure with orthotropic material2024-10-11T18:28:23+03:00Arief Budi Sanjayaarie043@brin.go.idHaryadi Abrizalarie043@brin.go.idMuhammad Dito Saputraarie043@brin.go.idRahmat Alfi Duhriarie043@brin.go.idMuhamad Hananuputra Setiantoarie043@brin.go.idAhmedi Asrafarie043@brin.go.idHendra Gantinaarie043@brin.go.id<p>The Authors of this research developed an analytical calculation method to estimate the strength of nose cone structures made of orthotropic materials, which were crucial components in aircraft and spacecraft. Strength analysis of nose cones had been comprehensively addressed for isotropic materials; however, the lack of efficient approaches for orthotropic materials presented a challenge. In this research, a new analytical method was proposed, combining membrane stress theory for isotropic materials with classical laminate theory for orthotropic materials. This approach enabled the determination of stresses on the nose cone shell structure in both meridional and circumferential directions in an efficient and straightforward manner. The analysis results indicated that the developed analytical method exhibited stress distribution trends similar to those obtained using the Finite Element Method. Stresses in the +45° and –45° direction, as well as in-plane shear stress and Tsai-Wu failure indices, showed trend similarity between the two methods. Despite specific numerical differences in the calculation results, these consistent trends suggested that the analytical method could serve as a tool for the preliminary design of a nose cone structure with a similar configuration analyzed in this study.</p>2024-10-11T10:17:26+03:00Copyright (c) 2024 The Author(s). Published by Vilnius Gediminas Technical University.https://jeelm.vgtu.lt/index.php/Aviation/article/view/22173Deep learning-based proactive fault detection method for enhanced quadrotor safety2024-10-11T18:28:22+03:00Mehmet Ozcanmehmet_ozcan@eskisehir.edu.trCahit Perkgozcahitperkgoz@eskisehir.edu.tr<p>The early detection of faults in advanced technological systems is imperative for ensuring operational reliability and safety. While there is a growing interest in using artificial intelligence for fault detection, current methodologies often exhibit limitations in utilizing comprehensive system information and sensor data. Hidden faults within collected data further highlight the need for advanced analysis techniques. This study introduces a novel deep learning-based framework designed to predict faults and extract insights from complex system datasets. The model, consisting of LSTM-autoencoder and BiLSTM classification components, effectively reduces feature dimensions, thereby enhancing fault detection accuracy. The autoencoder’s latent layer identifies prominent features across various dimensions, while BiLSTM classification conducts bidirectional analysis using these features from both healthy and faulty states, facilitating early fault detection. Experimental results demonstrate the model’s efficacy, achieving an accuracy of 79.48% in predicting incipient faults 30 seconds before a serious malfunction occurs. This underscores the significant potential of the proposed framework in enhancing operational safety and reliability in complex systems. Moreover, the study emphasizes the importance of leveraging comprehensive data and advanced analysis techniques for early fault detection.</p>2024-10-11T10:43:49+03:00Copyright (c) 2024 The Author(s). Published by Vilnius Gediminas Technical University.https://jeelm.vgtu.lt/index.php/Aviation/article/view/22154A comparative analysis of the aerodynamic performance of supersonic missiles with conical and ogive nose shapes2024-10-30T18:28:40+02:00Mahdi Goucemmahdi.goucem@univ-usto.dzRaouf Khirik.raouf@campus.fct.unl.pt<p>This paper presents a numerical study conducted to analyze the aerodynamic performance of supersonic missiles consisting of a cylindrical body and four flat-plate rear fins arranged uniformly, equipped with conical and ogive heads. Computational Fluid Dynamics (CFD) simulations were performed using the ANSYS Fluent 17.1 solver, along with the Gambit grid generation software. The objective was to compare the aerodynamic characteristics of these two head designs in terms of drag, lift, and stability at supersonic speeds. Various flow parameters, including Mach number and angle of attack, were investigated to comprehensively assess the performance of the missile configurations. The results indicate clear differences in the aerodynamic behavior of conical and ogive heads. Specifically, there was a 2–11 percent increase in the lift coefficient of the conical heads compared to the ogive heads, and an increase in the drag coefficient of both conical and ogive heads.</p>2024-10-30T09:25:18+02:00Copyright (c) 2024 The Author(s). Published by Vilnius Gediminas Technical University.