ABSTRACT. This paper presents a structured educational framework designed to enhance student comprehension of Guidance, Navigation, and Control (GNC) systems in the context of Low Earth Orbit (LEO) and Sun-Synchronous Orbit (SSO) missions. Given the interdisciplinary nature and growing complexity of space missions, the framework aims to bridge theoretical concepts with real-world applications. The GNC architecture is deconstructed into its primary subsystems—navigation sensors, guidance algorithms, and control actuators—while emphasizing their interactions and system-level integration.

The framework incorporates case studies from operational launch vehicles, including Falcon 9, PSLV, and Vega, to illustrate diverse implementations of GNC systems. Supplementary educational tools such as orbital mechanics visualizations, comparative GNC architecture analyses, and mission parameter calculators are integrated into the curriculum. Preliminary assessment with aerospace engineering students demonstrated a 37% increase in conceptual understanding compared to traditional instruction methods.

This work addresses the growing need for modernized educational resources in space systems engineering, particularly as the global space industry expands. The proposed approach contributes to cultivating the next generation of space engineers by making core GNC principles more accessible and practically grounded.

ABSTRACT. This proposal investigates whether complex behaviours in fluid and elastic systems, such as droplet splashes, elastic rebounds, vortex transitions, and soliton interactions, may reflect hidden geometric or topological constraints em-bedded in higher-dimensional configuration spaces. Traditional models like the Navier-Stokes and elasticity equations accurately describe many local dynamics, yet often fall short in explaining why specific morphologies emerge repeatedly or why certain transitions occur suddenly across parameter regimes. The study inte-grates ultra-high-speed imaging with a modular AI discovery system designed to infer governing laws and structural features directly from motion data. Four ca-nonical physical systems (droplet impacts, elastic rebounds, vortex rings, and shallow water solitons) are selected for their ability to exhibit repeatable, structured transitions under controlled conditions. The data is encoded into geometric and algebraic representations suitable for symbolic regression, manifold learning, and topological analysis. Mathematical tools, including fourth-order partial differential equations, Clifford algebra, and bifurcation models, are applied to interpret the inferred laws and classify their properties. Differential Galois Theory is used to assess solvability and symmetry of recovered equations. The aim is to determine whether consistent mathematical structure, if present, can offer a more compact or interpretable account of observed behaviours than traditional models. If successful, this approach may suggest that some forms of complexity in physical systems are shaped not by randomness alone, but by latent constraint structures that govern motion across both fluid and elastic regimes.

ABSTRACT. The fluid–structure interaction of a pivoting rigid wing connected to a spring and subjected to airflow is presented using a numerical approach. Fluid–structure interactions can, on the one hand, lead to undesirable aerodynamic behaviour or, in extreme cases, to structural failure. On the other hand, improved aerodynamic performance can be achieved if a controlled application within certain limitations is provided. Spring-mounted wings can be setup to decrease their incidence as flow speed increases, therefore decreasing its drag and lift when compared to a non-flexible wing.

The spring mounted wing concept has multiple applications. In the aerospace sector, the concept could be used on control surfaces to mitigate against the effects of gusts. The use of the concept will result in a lower lift and drag at a relatively higher flow speed found within a gust. The opposite effect occurs at a lower flow speed resulting in a more stable airframe overall. In the maritime sector, the concept can be applied to hydrofoils or propellers to mitigate against cavitation and hence improve performance and fatigue life. In the automotive sector, the concept can be used to reduce fuel consumption resulting in extended range or it can be used to achieve a higher top speed, whilst maintaining downforce and grip at lower speeds for cornering.

The general operation of the concept has previously been verified at low angles in the pre-stall region with that of a theoretical estimation using finite and infinite wings. This paper provides a numerical solution of the same problem, but reports the effect of using varying spring stiffness. The behaviour of a spring-mounted rigid symmetrical NACA0012 wing in a flow of air is studied. The wing is mounted ahead of the aerodynamic centre. Starting from a specified initial angle, the aerodynamic forces overcome a pre-set spring preload at incrementally increased freestream velocity. Stable results were found at all angles tested. An analysis is reported concerning how changing the spring torque settings effects performance. Finally, an evaluation of the systems’ effects was conducted with conclusions and future improvements.

ABSTRACT. Temperature variation affects the flow field characteristics and Reynolds Number (Re) of fluid, due to dependence of kinematic viscosity on temperature. This research uses the Osborne Reynolds apparatus to explore the impact of temperature variations on the flow characteristics of water flowing through a pipe at different velocities. The experiment systematically raises water temperature from 20°C to 40°C in increments of 5°C to varying sets of velocity. Ink dye injection visualizes flow regimes (laminar, transitional, turbulent) to validate the theoretical connection between Re and flow behavior. The primary objective is to demonstrate and calculate the interconnection between decreasing kinematic viscosity with increasing temperature which affects the Reynolds Number even at constant flow velocities. Additionally, the study aims to calculate the friction factor at various Reynolds Number values across varying temperature conditions. The analysis of these combined effects on Reynolds Number and friction factor will provide valuable insights into how temperature influences fluid flow characteristics and what changes are expected. The research concluded that temperature plays a pivotal role in determining the transition from laminar to turbulent flow, emphasizing the need to account for thermal effects in fluid system design. Further increased temperature reduced viscous effects which then led to greater kinetic energy within the fluid, which accelerated turbulence formation. Moreover, a trend of decreasing friction factor with increasing temperature was observed, indicating improved flow efficiency at elevated temperatures.

ABSTRACT. Human error continues to be a critical concern in military aviation maintenance, often leading to significant safety risks and operational setbacks. Despite its im-portance, the underlying factors that shape human error in this domain remain underexplored, particularly regarding the latent Performance Shaping Factors (PSFs) that influence personnel behavior. This research examines the influence of organizational, task-related, and environmental PSFs on human error through a quantitative method. Responses from 278 military maintenance technicians were gathered and subjected to Structural Equation Modeling (SEM) analysis for test-ing assumed relationships. Results show that all three domains of PSFs signifi-cantly influence human error, with task-related PSFs having the highest predic-tive ability (β = 0.30, p < 0.001), and then organizational (β = 0.28, p < 0.001) and environmental PSFs (β = 0.22, p < 0.001). Collectively, these latent factors explain 48% of the variation in human error, demonstrating their considerable combined effect. The findings highlight the multifaceted nature of human error causation and reinforce the necessity for focused organizational interventions that target multiple PSFs simultaneously to improve maintenance safety. This study expands the understanding of error dynamics in military aviation maintenance and offers a strong basis for developing proactive interventions to minimize human error. Subsequent research is invited to investigate these relationships in differing operational environments and over time to further enhance predictive models and inform adaptive safety management.

ABSTRACT. The exponential growth and the interconnected nature of digital technologies, the domains of human dimension and the cybersecurity plays a critical role in ensuring aviation safety. In cybersecurity, human factors such as user awareness, social engineering vulnerabilities, insider threats, and organizational security culture significantly influence the effectiveness of defense mechanisms. Similarly, in aviation safety, elements like situational awareness, crew resource management, fatigue, stress, and training impact operational performance and accident prevention. Particularly the factors of Cybersecurity Awareness (CSA), Negligence (N), Computer Literacy (CL), Emotional Stability (ES) would influence the Response Behavior which has found that a positive correlation with the Cybersecurity Index. This paper is developed from a positivist philosophy, treating the use of statistical, experimental and other numerical data, to describe the actions and phenomena observed, and the correlations and interactions between them. It is also used the deductive approach to test the theory and correlations of variables through a hypothesis. Target population of this study was stakeholders of the aviation industry and sample was scientifically drawn using proportionate stratified random sampling technique. Tool to measure variables was online questionnaire posted on Google Forms. Internal consistency reliability test was satisfied with fairly high value of Cronbach’s Alpha and sample adequacy was strengthen by KMO and Bartlett's Test with higher value of KMO. With the aviation industry’s growing reliance on interconnected systems, addressing the human element at the intersection of safety and cybersecurity is proven essential. Human errors, whether in digital behavior or operational judgment, can compromise both domains, highlighting the need for integrated, human-centric training and design. This paper has developed an index to support the implementation strategy to mitigate the vulnerabilities through cross-disciplinary approaches, continuous education, and culture development to build resilient systems that safeguard both digital and physical aspects of aviation operations.

ABSTRACT. The integration of aviation Safety Management Systems (SMS) with Human Factors (HF) analysis remains insufficiently developed in maintenance environments despite their critical role in accident prevention. Current SMS frameworks often fail to adequately incorporate human factors methodologies, creating a significant gap between theoretical safety models and practical implementation in maintenance operations. This research investigates the efficacy of a novel integrated HF-SMS framework specifically designed for aviation maintenance organizations. The primary objective is to evaluate how systematic integration of human factors analysis techniques into established SMS protocols can reduce maintenance errors and enhance safety outcomes. Using a mixed-methods approach, this study collected data from 14 aviation maintenance organizations across military and civilian sectors. Quantitative analysis of 378 maintenance error reports was complemented by qualitative data from 42 semi-structured interviews with maintenance personnel and safety managers. The research deployed innovative assessment methodologies including digital task load monitoring (DTLM), cognitive process mapping, and physiological stress biomarkers to measure human performance factors objectively. The HFACS-ME (Human Factors Analysis and Classification System for Maintenance Extension) taxonomy was applied to classify reported errors, while SMS implementation was assessed using a validated maturity model augmented with real-time compliance monitoring analytics. Results demonstrate that organizations with higher levels of HF-SMS integration experienced a 37% reduction in maintenance errors compared to those with conventional SMS implementations. The research further identified three critical integration points in the maintenance process where human factors interventions proved most effective: task planning, documentation review, and post-maintenance verification. Predictive risk modeling using machine learning algorithms applied to the collected data enabled the development of an early warning system for maintenance error likelihood with 83% accuracy in validation testing. Additionally, organizations implementing the integrated approach reported significant improvements in safety reporting culture and error identification capabilities. These findings provide a foundation with constructive resources and checklists for a more coherent approach to aviation maintenance safety that acknowledges the centrality of human performance in complex technical systems. The proposed framework offers practical guidance for maintenance organizations seeking to enhance their safety management capabilities through systematic integration of human factors principles and advanced assessment techniques.

ABSTRACT. Wind Tunnel Testing (WTT) is an experimental way to find the aerodynamic forces and moments produced about the Centre of Gravity (CG) at wide ranges of Reynolds Number (Re). In this research, a scaled-down model of an aerial platform is tested in a CAE closed-circuit subsonic wind tunnel, emphasizing measuring aerodynamic forces and moments under different flight conditions. With a focus on wind tunnel sting balance calibration and wind tunnel corrections using a calibration matrix and corrective factors, the testing was carried out to examine the aircraft data and behavior at a range of free stream velocities and aerodynamic angles. Angle of attack varied from -13 to +18 degrees while angle of sideslip varied from -13 to +18 degree. For sideslip testing, the model was mounted on a sting balance with 90 degrees rotation and tested for angle of attack. The goal of the research is to shed light on the platform’s aerodynamic properties as a function of various con-figurations which are planned by varying different payload combinations. Reynolds number and velocity matching were used in the study to guarantee dynamic similarity between the scaled model and the actual platform, enabling a precise depiction of full-scale aerodynamic behavior. The results contribute to the understanding of aerodynamic forces such as lift, drag, side force and aerodynamic moments produced by these forces which are pitching, rolling, and yawing. Their dependencies upon flight conditions and aerodynamic angles are also investigated and commented upon. The results obtained are consistent with the aerodynamic principles and trends of such platform once matched with the data available in open literature. The methodology used in this work will serve as a foundation for further aerodynamic testing on configurations with payload combinations. The only deviation from conventional results is observed in the drag channel where the coefficient of drag was observed as zero at all negative angles of attack, depicting the non-functional state of the strain gauge associated with the drag channel of the sting balance. Results of other coefficients follow conventional trend.

ABSTRACT. This study presents the current and ongoing M.Sc. and Ph.D. studies about aircraft structural dynamics and aeroelasticity in the Department of Aerospace Engineering in the Middle East Technical University (METU) under the supervision of Prof. Yavuz Yaman.

The subjects presented are: Structural Dynamics of Smart Wraparound Fins, Ph.D. study. The advancements in modern air systems have led to an increasing demand for the long-range, slender guided rockets capable of conducting high-speed (supersonic or hypersonic), precise, and efficient operation. In order to meet the aerodynamic requirements while ensuring compact storage, these rockets necessitate improved wing/fin configurations. In the study wraparound fins (WAFs) are considered.

Computational Fluid Dynamics Based Fluid Structure Integrated Methods for Aeroelastic Effects on Flexible Wings in the Transonic Regime, M.Sc. study. Phenomena such as shock waves, shock-boundary layer interactions, and flow separations encountered in transonic speed regimes become challenging to explain using classical linear theories. In order to accurately model the aeroelastic instabilities such as buzz, flutter, buffeting, and limit cycle oscillation under these conditions, the time-dependent (unsteady) and highly accurate CFD methods are essential. Consequently, FSI methods that integrate computational fluid dynamics (CFD) with structural analysis solutions are going to be utilized.

Aeroelastic Analysis of a Generic Flying Wing UAV under Clean and Loaded Wing Configurations, M.Sc. study. In the study MSC/ NASTRAN® with FLDS® programs will be used to develop the structural model, and the dynamic analysis will detect the natural frequencies, mode shapes and coupled/decoupled behavior of bending and torsion modes of the UAV.

Structural Dynamics Modeling and Load Distribution Optimization of a Helicopter Rotor, M.Sc.study. The aim of this study is to optimize the design parameters—using an elastic beam model and the extensive analytical capabilities of CAMRAD II— in order to achieve the efficient load distribution in the rotor blades and subsystems.

ABSTRACT. This study explores the prediction of residual stress (RS) fields in a 3D-printed aircraft wing rib using finite element analysis (FEA), offering a transformative approach to improve structural performance in aerospace applications. The layered nature of additive manufacturing (AM) introduces significant residual stress due to thermal gradients, which can lead to part distortion and reduced fatigue life if not accurately managed. This project leverages advanced FEA simulations to model RS formation during both conventional and additive manufacturing processes, aiming to evaluate and compare the deformation behavior under operational loads. The 3D wing rib model, developed and analyzed using ABAQUS and ANSYS, incorporated validated material properties and layer-wise heat input simulation to replicate real-world AM conditions. Preliminary results indicate that optimized additive designs result in lower stress concentrations and improved distribution compared to traditionally manufactured counterparts. Validation of the simulation results is supported through the contour method and neutron diffraction references, ensuring realistic stress field estimations. The study supports sustainable engineering practices by minimizing material wastage and post-processing demands, aligning with the principles of environmental responsibility and manufacturing efficiency. Furthermore, the integration of design-for-AM strategies such as lattice infills provides added structural optimization. This research provides a foundation for future aerospace structural applications of AM, establishing a predictive and validated framework for residual stress management in critical load-bearing components.

ABSTRACT. Solar energy is a crucial component of renewable energy resources. The power output of solar energy primarily depends on irradiance and temperature, with the operating temperature of solar photovoltaic (SPV) panels significantly impacting their efficiency. While high irradiance enhances electrical output, it also raises panel temperatures, which negatively affects efficiency. This experiment aimed to cool solar PV panels to improve their efficiency. In this study, paraffin wax and soya wax were used as phase change materials (PCM) to regulate the panel tem-perature. The experiment was conducted at the University of Technology and Applied Sciences (UTAS)-Shinas during the winter season in the Sultanate of Oman. Performance comparisons were made between a conventional 30-watt SPV panel and a PCM-applied SPV panel. The experimental results demonstrat-ed a significant improvement in the open-circuit voltage (Voc), Voltage at maxi-mum load, Cell temperature and power output of the PCM-applied SPV panel compared to the conventional panel. The PCM-integrated panel achieved a 10% more output power than the standard SPV panel. These findings contribute to en-hancing sustainability in renewable energy projects by improving solar PV per-formance through effective thermal management.

ABSTRACT. A hybrid optimization algorithm consisting of the Moth Flame Optimizer and Dragonfly Algorithm is proposed in this work as an innovative control approach for grid-connected photovoltaic inverters. The newly developed hybrid MFO-DA algorithm tunes the proportional-integral controller gains to enhance the inverter’s dynamic performance and reduce harmonic distortion. The proposed technique was shown to outperform the conventional Particle Swarm Optimization method. The evaluation measures the impact on important parameters: source current, load current, converter injected current, wind energy system current and Total Harmonic Distortion. Simulations confirm that the hybrid MFO-DA algorithm delivers improved response speed and harmonic reduction, resulting in an all-round superior performance for the grid-connected PV system. This method performs better than the conventional PSO algorithm, suggesting its capability to improve the efficiency and power quality of PV grid-connected inverters.

ABSTRACT. Accurate prediction of the remaining useful life (RUL) of fuel cells is a critical enabler for ensuring reliable, safe, and sustainable operation of hydrogen-powered aviation systems. As the aviation sector moves toward decarbonization through hydrogen-electric propulsion, the ability to monitor and forecast fuel cell degradation becomes essential for predictive maintenance, system optimization, and mission-critical decision-making. However, conventional RUL prediction models often fail to effectively capture the complex spatial and temporal dependencies embedded in degradation signals, resulting in limited accuracy and robustness under dynamic operational conditions.

To address these limitations, this study introduces a novel hybrid deep learning framework WOA-CNN-MMHA that synergistically combines Convolutional Neural Networks (CNN), a Masked Multi-Head Attention (MMHA) mechanism, and the Whale Optimization Algorithm (WOA). The CNN module extracts localized spatial features from high-dimensional sensor data, while MMHA models long-range temporal dependencies and preserves critical sequential aging patterns. WOA is employed to optimize hyperparameters, enhancing convergence speed and reducing reliance on manual tuning. This integrated approach enables the model to simultaneously capture both fine-grained degradation characteristics and global deterioration trends, which are vital for accurate RUL estimation.

The framework is rigorously evaluated using real-world fuel cell degradation datasets representative of aviation environments. Experimental results demonstrate superior performance over state-of-the-art models such as GRU, CNN-GRU, and standard attention-based architectures, with significant improvements in RMSE, MAE, and MAPE metrics. Notably, the model exhibits strong robustness to incomplete or noisy data, underscoring its practical applicability in real-time aircraft monitoring systems.

This work highlights the importance of adopting a holistic modeling strategy that bridges multi-scale feature extraction with intelligent optimization, paving the way for enhanced prognostics in next-generation hydrogen-electric aircraft. By enabling proactive maintenance and improved energy management, the proposed framework contributes to the broader objective of integrating efficient and implementable hydrogen technologies into sustainable regional aviation.

ABSTRACT. Thermal management of electronic processing is a challenge due to increasing current density. Noble metal decorated GNP reinforced copper matrix composites have been developed and investigated for thermal management of smart electronic devices. Nanoparticles of noble metal were grafted on GNP with a limited amount of oxygen, and the decorated GNP was reinforced with copper and compacted at low pressure to create voids in the sintered samples to achieve convection and conduction characteristics in the samples. Decorated GNP was characterized by the Field Emission electron microscope, PS, and XRD. Sintered samples were tested for thermal conductivity and dispersion of decorated GNO in copper matrix. The results showed that nano particles of the noble metal were well attached to GNP, sintered, and thermal conductivity was improved. Tests performed on LED light showed 15 °C lower operation temperature and an increase in luminous.

ABSTRACT. Photovoltaic (PV) solar power is emerging as a major source of domestic energy provision globally. PV is also a feasible source of energy for small-scale applications in transportation, including light aircraft design, particularly unmanned aerial vehicles (UAVs). This paper will provide an overview of results recorded following installation of a hybrid photovoltaic (PV) solar system with combined battery storage, and installation on an electric-car smart-charger at a domestic property in Ireland, in 2023. The property, a modern energy-efficient domestic dwelling built in 2017, is a detached two-story house of area 265 m2. The attic provides additional usable floor space of 25 m2, which enabled placement of the PV inverter units. A PV installation company in the neighbouring townland of the dwelling, was engaged. The contract enabled i) installation of an integrated solar storage hybrid inverter and roof-mounted solar panel array, ii) installation of a Zappi e-car charger. The PV system incorporates an integrated 6.6kW inverter with 4.8kW battery storage, and a 16x420W solar panel array, placed on a front facing roof of orientation East/South-East, 30° incline. The Sofar hybrid inverter (HYD-6K-EP) is an energy storage inverter integrating grid-connected PV inverter and battery storage. DC power from the solar panels is directed to charge the batteries which hold their charge until required for use by the inverter control system. The inverter also incorporates maximum power point tracking (MPPT) which enables optimisation of the power output of the solar panels, achieved by dynamically controlling operating conditions to maximise on energy output with variation in sunlight intensity and temperature. PV energy is also used to charge the electric car.

The installation has resulted in significant PV generation with reduced energy billing over several months of the year, with revenue received by the property owner from the national utility for PV energy exported to the grid.

The paper will also discuss the potential benefits for domestic PV installation in warmer climate countries, such as the Sultanate of Oman.

ABSTRACT. Airports are air transportation facilities that rely heavily on the supply of electrical energy to support daily operations, from lighting to navigation systems. High energy consumption makes airports one of the contributors to carbon emissions in the aviation sector. This study aims to evaluate the potential application of Archimedes wind turbines as a small-scale energy plant at Ngloram Airport, Blora Regency, Central Java. Wind speed data was obtained from NASA's climate data-based RETScreen Expert software, which was then used to calculate turbine output power and energy through a technical simulation approach. An Archimedes turbine with a diameter of 1.5 meters and a sweep area of 1.77 m² was used as a study model, assuming a power coefficient (Cp) of 0.35 and an air density of 1.225 kg/m³. The simulation results indicate that an average annual wind speed of 2.7 m/s is only capable of producing electrical energy of approximately 170–200 kWh per year per turbine unit. When compared to the estimated annual energy needs of the airport, which is approximately 117,200 kWh, the contribution of one turbine unit is only around 0.15–0.17%. However, when analyzed for the Cashew Garden area (≈4,015 kWh/year), a single turbine can supply about 90–100 kWh annually, equivalent to 2.2–2.5% of the local energy demand. Although its direct contribution is still limited, the results of this study indicate that the Archimedes turbine has strategic potential as part of the airport's renewable energy system, particularly for supplying light loads in non-operational areas. These findings provide the basis for further exploration of integrating small-scale wind turbines into the airport environment to implement green airports.

ABSTRACT. The Ahmed body, a broadly used simplified vehicle model, is the basis of our study. It replicates key aerodynamic characteristics such as flow separation, vortex generation, and wake formation. Understanding and controlling these aerodynamic features is essential for reducing drag and improving fuel efficiency in ground vehicles. In the literature, various passive flow control techniques, including elastic flaps, rigid flaps, vortex generators, and spoilers, have been explored to mitigate aerodynamic drag and reduce fuel consumption. These methods achieve drag reduction by delaying flow separation, minimizing the wake region, reducing recirculation zones, and suppressing large-scale vortex formation.

This study systematically compares the aerodynamic performance of flexible and rigid flaps in terms of their effectiveness in drag reduction by using computational fluid dynamics (CFD) analysis. During this analysis, the investigation focuses on their drag reduction efficacy, flap deflection characteristics, and the extent of wake suppression. Numerical approaches are employed to assess the dynamic behaviour of flexible flaps and their interaction with the flow field in contrast to rigid flaps. To evaluate their effects, this investigation will examine various flap lengths: specifically, 0.1H, 0.2H, 0.3H, and 0.4H (where H represents the height of the Ahmed body). Identifying the optimal lengths and proportions of the flaps is crucial for evaluating their effectiveness in minimizing the recirculation zone and for gaining insight into their relationship with oscillations. When analyzing these flap lengths, it is also vital to examine the amount of deflection, as this parameter significantly influences the lifespan of the flaps and the cost-effectiveness of the technique. This investigation will yield valuable insights into the advantages and limitations of each flap type, ultimately contributing to the development of efficient passive flow control strategies in automotive aerodynamics.

To sum up, determining the most effective flap type for drag reduction, whether flexible or rigid, is crucial. After selecting the flap type, evaluating the most suitable configuration is essential. Experimental analyses are more expensive and time-consuming than computational ones. Determining the type, configuration, and length ratio of the flap is vital to narrow down experimental variation.

ABSTRACT. This study presents the development of a practical framework for predicting the laminar-toturbulent transition in two-dimensional flows with an emphasis on industrial applications. The methodology is built upon widely used open-source computational fluid dynamics (CFD) tools, including OpenFOAM for simulation, blockMesh for mesh generation, and ParaView for visualization and post-processing. The research comprehensively addresses the fundamental governing equations of fluid flow, examines appropriate boundary conditions, and evaluates turbulence models with a particular focus on transition modeling techniques. Different solver configurations are employed based on flow compressibility: simpleFoam and pimpleFoam are used for incompressible flows, while rhoSimpleFoam is adopted for compressible flow regimes. The study systematically investigates numerical stability, solution convergence, and consistency by implementing various boundary condition types and discretization schemes. Grid independence tests are performed, and the results are validated through both experimental data and analytical benchmarks. Initial test cases include canonical flow problems, followed by more complex simulations involving airfoil geometries such as NACA0012. In addition to conventional CFD modeling, a supplementary analysis inspired by the LASTRAC (Langley Stability and Transition Analysis Code) approach is carried out. This allows for a comparative assessment of transition prediction accuracy between traditional CFD solvers and linear stability-based methods. The overall framework not only demonstrates the applicability of open-source tools in solving real-world engineering problems but also contributes to a deeper understanding of transitional flow phenomena in aerodynamic configurations.

ABSTRACT. This study investigates the critical interplay between civil aviation regulations and emerging technologies in development of sustainable domestic airline industry. Focusing on Personnel Licensing, Aircraft Operations, and Airworthiness, the research examines how aligning these regulatory domains with global standards can establish a robust foundation for growth. It underscores the importance of safety oversight, emphasizing awareness, user-friendly processes, and integrated systems to mitigate conflicting objectives and enhance sector sustainability. Drawing insights from the Gulf region, the paper highlights safety standards as a pivotal element in aviation development. The study further emphasizes the necessity of effective regulatory implementation, advocating for strong safety oversight and clear, accessible processes. It argues that successful implementation, rather than mere rule formation, is paramount for ensuring safety and operational efficiency. The significance of safety culture, attitude, and competency-based training is also explored, highlighting their role in the developmental process and the need for rigorous regulatory control and monitoring. Moreover, the paper delves into the transformative potential of integrating helicopter, propeller, and electric-propulsion aircraft into domestic and regional aviation. These technologies offer opportunities in tourism, remote access, and environmental sustainability. Recognizing the interconnectedness of the airline industry, the research proposes encouraging collaborations with sectors like logistics and infrastructure to broaden economic impact. Finally, the study recommends modernizing approval and control processes through digitization and enhanced stakeholder collaboration, ensuring a sustainable and globally competitive domestic aviation sector capable of maximizing economic and social benefits.

ABSTRACT. Standardizing safety frameworks for military aviation presents unique challenges due to operational complexities and diverse objectives. However, successful models demonstrate the feasibility of achieving high safety oversight while maintaining operational efficiency. This study explores the development of an enhanced military airworthiness regulatory framework, leveraging established global military standards and integrating relevant civil aviation regulations. A comparative analysis of an existing airworthiness system against leading nations identifies key areas for improvement and modernization. A central focus is the distinction between military aviation's decentralized responsibilities and civil aviation's centralized, structured approach. Military maintenance crews manage a broader scope of tasks, releasing aircraft through dispersed channels, contrasting with civil aviation's clear divisions and centralized oversight. This paper investigates the potential benefits of selectively integrating civil aviation's structured oversight into the military framework to enhance safety. The study underscores the necessity of modernizing military airworthiness regulatory compliance through digital tools, improving efficiency and oversight. Furthermore, it advocates for integrating civil aviation safety management practices to establish a robust continuing airworthiness process for military aviation. This integration aims to bolster safety without compromising operational effectiveness. A parallel-running project management approach is recommended to facilitate a seamless transition to the proposed framework. This strategy aims to minimize risks and ensure effective implementation, enabling the adoption of a modernized, globally aligned airworthiness regulatory framework tailored to the unique demands of military aviation.

ABSTRACT. Flight and maintenance planning (FMP) is fundamental to fleet sustainment, ensuring aircraft availability while minimizing operational disruptions which is essential component of military aviation. Traditional FMP methods rely on manual scheduling driven by historical trends and expert judgement resulting in suboptimal schedules, frequent adjustments, and inefficient resource utilization. This study aims to address these problems by developing an optimization framework that integrates Usage-Based Maintenance (UBM) and Calendar-Based Maintenance (CBM) into a unified Mixed-Integer Linear Programming (MILP) model enabling efficient and proactive scheduling. The proposed model maximizes aircraft availability while dynamically allocating flight hours, scheduling maintenance and optimizing resource utilization. The framework also includes two key mechanisms: Priority-Driven Scheduling, which ensures that high-priority aircraft receive timely maintenance to minimize downtime, and Adaptive Maintenance Integration, which embeds planned modifications and unplanned maintenance into existing schedules to ensure operational continuity. The MILP model is solved using exact solvers with rolling horizon approach, incorporating explicit constraints such as operational requirements, maintenance cycles, and resource availability. Preliminary validation with real-world data shows a 11% improvement in fleet availability and 7% improvement in resource utilization by merging/ streamlining maintenances, reducing inefficiencies compared to manual methods. This research contributes as a decision-support tool that enables maintenance planners to optimize schedules while balancing real world constraints. The framework addresses a key gap in existing FMP approaches by integrating UBM, CBM, and adaptive scheduling with priority-based resource assignment. Future work will incorporate stochastic disruptions and evaluate heuristic, metaheuristic, and machine learning-based optimization methods to enhance decision-making.

ABSTRACT. Aircraft hangars in arid regions such as Oman represent high energy demand facilities due to their large volume, high ventilation rates, and continuous cooling requirements. This paper presents a sustainable HVAC design strategy focused on energy efficiency and water conservation, aligned with Oman Vision 2040 and global decarbonization goals. The proposed approach integrates multiple techniques to optimize system performance and reduce environmental impact. High Seasonal Energy Efficiency Ratio (SEER) air-conditioning units are selected to reduce cooling energy consumption. Additionally, well-insulated building envelopes are employed to minimize external heat gain and source load. To ensure indoor air quality (IAQ) without increasing energy demands, an energy recovery ventilation system is implemented using a rotary energy recovery wheel. This system recovers both sensible and latent heat from the exhaust air stream to precondition incoming fresh air, reducing HVAC load. A novel feature of the design includes the collection and reuse of chilled water condensate, a byproduct of the cooling and dehumidification process. This water is repurposed for non-potable uses within the facility, contributing to water savings and sustainability. This paper investigates the potential of sustainable HVAC strategies to support building decarbonization by focusing on two key approaches: the optimal selection of high-efficiency air conditioning units and the effective recovery and reuse of condensate water. Typically, HVAC systems can generate approximately 1 to 2 liters of condensate water per hour per refrigeration ton, depending on indoor and ambient conditions. By adopting high-efficiency units, operational cost savings of up to 40% or more can be achieved based on the optimal selection of high-efficiency air conditioning units. Additionally, utilizing this freely available condensate water can significantly reduce freshwater consumption, and minimize related carbon emissions. The results provide a practical model that can be easily used and repeated for applying sustainable HVAC systems in aircraft hangars and other associated aeronautical large buildings that run in hot, dry climates.

ABSTRACT. The increasing threats posed by climate change, resource depletion, and environmental degradation have prompted a global reassessment of materials and manufacturing practices. This paper critically evaluates sustainability challenges in materials and manufacturing engineering, emphasizing interdisciplinary efforts to minimize environmental impacts while maintaining performance and economic viability. Key topics include sustainable material selection, energy and resource efficiency, environmentally conscious manufacturing, and the role of digital technologies. Also discussed as critical enablers of sustainability are the integration of circular economy principles, development of bio-based and recyclable materials, and deployment of smart manufacturing systems. Drawing on recent studies and international best practices, the paper outlines major obstacles and future research directions necessary to advance sustainable practices across the lifecycle of engineering products. Offering a novel, interdisciplinary synthesis of emerging strategies for advancing sustainability in materials and manufacturing engineering, this paper provides valuable guidance for researchers, engineers, and policy-makers seeking to reduce environmental impacts while maintaining industrial competitiveness

ABSTRACT. This report outlines the design and development of a 3D-printed lightweight VTOL drone aimed at enhancing aerial surveillance capabilities. The project initiates with a Work principle and background on VTOL UAVs, including. The NACA 4412 airfoil was chosen for its optimal balance between lift and drag, supported by Computational Fluid Dynamics (CFD) simulations that validate its moderate drag and manageable moment characteristics. Detailed calculations found the wing geometry, resulting in a high wing configuration with a tapered wing for structural efficiency and improved aerodynamic performance. Moreover, The UAV's airframe was designed using additive manufacturing (3D printing) with filaments such as LW-PLA-HT and PLA+, reinforced with carbon fiber tubes, to ensure it is lightweight, strong, and heat-resistant. Furthermore. This project demonstrates significant advancements in VTOL UAV design, providing a solid foundation for future developments by integrating modern technologies and innovative design practices.

ABSTRACT. This study investigates novel low-cost radar-absorbing materials (RAMs) designed to mitigate radar cross-section (RCS) in small unmanned aerial vehicles (UAVs), thereby advancing stealth capabilities through cost-effective synthesis methodologies. Experimental prototypes utilizing multifunctional composite coatings—comprising carbonaceous matrices doped with ferrite nanoparticles—demonstrated a radar signal attenuation of up to 75% across X-band frequencies (8–12 GHz), as validated through precision electromagnetic reflectivity analysis. The research aligns with Oman’s strategic objectives under Vision 2040, which prioritizes defense modernization and technological innovation as pillars of national security resilience. By developing domestically fabricated RAMs with competitive absorption performance at 40–60% lower production costs than commercial alternatives, this work bridges critical gaps in affordable stealth solutions while fostering indigenous technological capacity. The findings underscore the viability of scalable manufacturing protocols for next-generation metamaterials, emphasizing the interplay between nanoscale filler optimization and macroscopic electromagnetic dissipation. This innovation not only addresses immediate operational requirements for UAV stealth but also establishes a foundational framework for integrating adaptive radar evasion technologies into Oman’s defense infrastructure. Future efforts will focus on tunable frequency-selective coatings and machine learning-driven material design to enhance broadband absorption efficiency. The study contributes to global discourse on democratizing stealth technologies, offering a replicable model for resource-conscious militaries seeking to balance fiscal prudence with advancements in survivability and electronic warfare readiness.

ABSTRACT. Functionally Graded Materials (FGMs) produced via Fused Deposition Mod-eling (FDM) present new opportunities for tailored structural components in aerospace and engineering applications. However, a key limitation in poly-mer–polymer FGMs remains the variability of interlayer adhesion, which significantly impacts mechanical performance under loading. This study in-vestigates the influence of process parameters on the tensile behavior of du-al-material FDM-printed FGMs constructed using Acrylonitrile Butadiene Styrene (ABS) and Tough Polylactic Acid (PLA). Although the original de-sign targeted Polyether Ether Ketone (PEEK) for its superior thermal and mechanical properties, persistent processing constraints necessitated a material substitution with ABS—selected for its proven structural viability and compatibility with high-temperature FDM systems. A Taguchi Design of Experiments (DOE) framework was employed to evaluate the effects of nozzle temperature and raster angle on the ultimate tensile strength (UTS) of fabricated samples. Tensile testing was conducted in accordance with ASTM standards, and results were statistically analyzed to identify significant parameter interactions. Findings demonstrate that specific thermal and geometrical combinations yield notable improvements in tensile performance, underlining the critical role of process tuning in enhancing interfacial bonding. These insights contribute toward the development of mechanically reliable polymer-based FGMs and provide a basis for future optimization studies targeting functional grading in structural applications.

ABSTRACT. Engineering design involves selecting optimal materials to meet operational and managerial requirements. Advances in composites technology have led to light-weight, cost-effective materials with superior properties. Fiber Reinforced Additive Manufacturing (FRAM) enables production of composite parts with high mechanical performance, offering high strength-to-weight ratio, design flexibility, and rapid prototyping. Fused Filament Fabrication (FFF) is the most common AM technique, using fiber-reinforced polymer filaments. The properties of short fiber-reinforced composites in FFF are significantly influenced by process parameters. This research is an experimental investigation for the optimization of FFF process variables. Taguchi method (L9 array) for Design of Experiments (DOE) was used in the research to analyze the impact of process variables on volumetric accuracy and porosity of printed parts. Test samples as per ASTM D695 were manufactured using FFF type 3D printer (IEMAI Magic HT Pro). Short Carbon fiber-reinforced polyamide (CF-PA6) filament was used. Four printing parameters at three different levels were used, which are print temperature (260-280 0C), print speed (40-60 mm/s), layer height (0.25-0.35 mm) and raster angle (300-600). Porosity evaluation was carried out through optical micrography followed by image processing with ImageJ software. Volumetric expansion was observed in the range of 0.44 ml to 0.87 ml, whereas porosity ranged from 5.50% to 6.416%. Trade-off was observed between minimizing both objective parameters. The study provides valuable insights into optimized FFF printing parameters for achieving dimensional accuracy and porosity control of Fiber Reinforced Polymers (FRPs) produced through AM.

ABSTRACT. Aluminum alloys are the most usable material in industrial markets such as aerospace, marine, and automotive due to their excellent performance in resisting fatigue and corrosion. However, once it comes to the machining and particularly the drilling process, the quality of the drilled hole should be considerable to investigate the effect of cutting parameters, namely spindle speed and feed rate, on the inner surface of these holes, where they play a crucial role in many industrial areas. For instance, an aircraft’s wing requires namouras holes to be attached to the main structure by using rivets and bolts. The current paper examines the influence of cutting parameters (feed rates and spindle speed) on surface roughness in aluminum alloy Al5083 by using HSS drill bits. A CNC machine was utilized for the drilling process, where 48 holes were drilled without using any coolant and 48 holes under flooded cutting fluid. The experimental results revealed that both Ra and Rz increased by increasing the spindle speed and feed rate. However, the drilled holes with coolant have minimum Ra and Rz. The optimal parameters for better surface roughness were n= 1000 rpm and f= 100 mm/min in wet conditions. The results were supported by using the full factorial method and ANOVA (analysis of variance) to evaluate each input parameter’s contribution to the hole’s quality, which conclude that the optimal surface roughness is at lower levels of cutting parameters and in a wet environment which play a crucial role in reducing surface roughness with contributions 49% and 50% for both Ra and Rz, respectively, followed by feed rate and spindle speed with minimal contributions.

ABSTRACT. Various engineering system designs involve the utility of pipe flow in several forms. The wide domain of these applications includes hydraulic and pneumatic pipes utilized in aerospace, mechanical and civil engineering domains. For any engineering application involving sophisticated optimization, the relative/ absolute roughness of pipe and pipe friction factor must be known. Polypropylene Random Copolymer (PPRC) pipes are primarily used for plumbing systems because of their excellent thermal resistance, durability, and resistance to corrosion and scaling. These unique properties make them suitable for residential, commercial, and industrial applications. This study aims at the experimental determination of the frictional losses in PPRC pipes of various diameters at different Reynold’s numbers. The friction factor of pipes with two different radii was determined experimentally by measuring the pressure drop across a known pipe length. The trend of friction factor was plotted against variation of Reynold’s Number (Re) and superimposed on the Moody Chart, whereby the relative and the absolute roughness of PPRC pipe was calculated. These experimentally determined values are crucial for determining the suitability of the material in different conduits. It is concluded that the friction factor values decreased with an increase in Reynold’s number and the order of this decrease was found in agreement with the trend of the curves on the Moody chart which is the graphical representation of the Colebrook White equation. It is also concluded that relative roughness values of tested PPRC pipes ranged from 0.0001 to 0.0005. The research will serve as a foundation for selection of right diameter of PPRC pipes to be used in various industries like domestic water supply, industrial piping systems, irrigation systems, solar water heating systems, hot and cold water transport in commercial buildings and food and beverage industry.

ABSTRACT. This study presents an experimental, numerical and theoretical analysis regarding investigation of boundary layer characteristics over NACA-0015 airfoil under various operating conditions. Experimentally calculated boundary layer and velocity profiles proved to be instrumental in predicting aerodynamic forces and validation studies of numerical & turbulence models. This qualitative and quantitative research, followed by a theoretical and experimental validation scheme, contributes significantly to the field of aerodynamics with its applications in various engineering applications, particularly in the design and optimization of aerodynamic systems. Curve fitting technique was employed to develop an empirical relation for a velocity profile and integrated with momentum integral approach to eventually calculate the drag of an airfoil. Experimental, numerical and theoretical results were consistent with each other thereby validating the research methodology. Results were related with the classical Pohl Hausen and Von Karman boundary layer theories which served as the conventional guidelines to investigate the boundary layers characteristics of laminar and turbulent regimes. The efficacy of wind tunnel testing probe for investigating fluid flow dynamics inside a boundary layer along with key limitations encountered during the research has also been explored and commented upon. Physics of flow inside a boundary layer is discussed, analyzed and related with various aerodynamic parameters including Reynold’s number, angle of attack, velocity gradients and boundary layer thickness.

ABSTRACT. Fuel consumption and the reduction of emissions are of considerable importance in the design of aircrafts. Consequently, a substantial number of studies have been conducted in the extant literature to enhance the effectiveness of wings. In recent decades, boundary layer control methods have assumed a prominent role in achieving these objectives. The primary function of these methods is to delay the onset of flow separation, thereby reducing drag force and enhancing overall effectiveness. These methods can be categorised into two distinct groups: passive and active boundary layer control methods. Passive methods include riblets and vortex generators. Conversely, active methods encompass blowing, suction and zero net mass flux techniques. The present study employs a loudspeaker-driven synthetic jet actuator (SJA), a zero net mass flux method, to simulate the effects of geometrically optimised SJA at different working conditions (e.g. variable frequencies, amplitudes, etc.). The conditions under which these simulations are conducted are determined by Computational Fluid Dynamics (CFD). Unsteady Reynolds-averaged Navier-Stokes (URANS) simulations are conducted using the RNG k-ε turbulence model. Visual investigations of unsteady synthetic jets formed by the SJA are performed at frequencies ranging from 50 Hz to 130 Hz.

ABSTRACT. Boundary layer separation poses a critical challenge, significantly degrading aerodynamic performance, especially when an aircraft operates at high angles of attack (AoA). This phenomenon manifests as an abrupt detachment of the airflow from the airfoil surface, leading to a substantial increase in drag and a detrimental loss of lift, ultimately compromising flight efficiency and control. Traditional methods to mitigate this issue often involve complex active systems that add weight and require power, increasing operational costs and design complexity. This study introduces an innovative passive technique designed to effectively delay boundary layer separation. The core of this approach involves strategically injecting high-energy ram air from the lower, high-pressure surface of a subsonic airfoil to its upper, low-pressure surface. This transfer of momentum is achieved through a series of spanwise scoops integrated into the airfoil's structure. A key feature of this novel design lies in the ingenious mechanism controlling these scoops: they are covered with spring-loaded, flap-like regulators. These regulators are engineered to respond passively to changes in external pressure. As the AoA increases, the pressure on the upper surface of the airfoil decreases, causing the spring-loaded flaps to open automatically. This allows the higher-energy ram air to be injected into the boundary layer on the upper surface, re-energizing it and effectively delaying the flow separation. To rigorously validate the efficacy of this passive control method, extensive Computational Fluid Dynamics (CFD) simulations were conducted. These simulations modeled the airflow around the modified airfoil at various critical AoA: 5°, 12°, and 18°. The results consistently demonstrated a notable and significant delay in the onset of boundary layer separation across all tested AoAs. This delay directly translates into substantial aerodynamic benefits, including reduced drag and enhanced lift characteristics, particularly at higher angles of attack where separation is typically most problematic. This paper delves into the fundamental aerodynamic theory underpinning this passive separation control technique, details the practical design implementation of the spanwise scoops and their regulatory flaps, presents comprehensive flow visualization data from the CFD simulations, and discusses the profound implications of these findings for the future design of more efficient and controllable aircraft.

ABSTRACT. This research utilized subsonic Wind Tunnel Testing (WTT) for proposing Flight Dynamic Model (FDM) of a High-Speed Projectile (HSP). The reference platform is taken as HSP which is a medium range Surface to Air Missile (SAM). The research started with a collection of Point Cloud Data (PCD) through surface scanning and then developing a computational aided design (CAD) using CATIA®. 1/3rd scale down aluminum-based metal model was fabricated using lathe, milling and CNC milling machines. The aluminum model was tested inside wind tunnel at 6 different configurations among which 2 are without side rail while other 4 configurations have side rail installed over the body. The WTT were conducted for -15°≤α≤+15° at free stream velocities of 50mph, 100mph and 150mph with an objective to obtain necessary aerodynamic coefficients and stability derivatives. The validation of stability derivatives was carried out with CFD work which utilized ICEM CFD ® as meshing software and Fluent® as solver. Statistical software MISDAT®, was used to obtain dynamic stability derivatives. The static and dynamic stability derivatives were used to propose 4-DOF Flight Dynamic Model of the HSP. FDM so obtained was then used to predict the projectile’s behavior across different flight conditions ensuring optimal stability and control throughout its trajectory.

ABSTRACT. Abstract. Reproducing metallic components of an aircraft engine is a com-plex and resource intensive task, particularly when original CAD models and material specifications are unavailable. Reverse Engineering (RE) addresses these challenges by reconstructing the geometry and material properties of existing components, enabling independent reproduction and reducing reli-ance on Original Equipment Manufacturer (OEMs). This research developed and validated a parametric framework for RE by analyzing two metallic air-craft engine components. These are fuel pump impeller and a star washer—of varying geometric complexity. Point Cloud Data (PCD) captured using a GOM Core 5.0 3D scanner is processed in Geomagic Design X to generate parametric 3D models. The reconstructed CAD models are assessed for ac-curacy, with a deviation of ±308 microns, which falls within industry-accepted tolerances for such components. Material characterization is con-ducted using a combination of destructive and nondestructive techniques to assess the microstructure, phase composition and elemental distribution. X-ray fluorescence (XRF), Laser-Induced Breakdown Spectroscopy (LIBS) and X-ray diffraction (XRD) analyze the chemical and structural properties. Ma-terial analysis confirmed that the impeller is composed of Titanium Grade V alloy (Ti-6Al-4V), while the star washer is stainless steel 304 (SS304). Hard-ness testing measured values of 325.5 HV / 32.5 HRC / 304 HRB for the im-peller, and 207 HV for the star washer. X-ray diffraction (XRD) analysis fur-ther revealed a face-centered cubic (FCC) crystal structure for the star wash-er, reinforcing its identification as SS-304 and HCP for Ti 6-4. This research identifies viable manufacturing pathways, including subtractive and hybrid approaches, to ensure precise reproduction of the components. The struc-tured framework developed in this research addressed the spare part shortag-es by enabling indigenous manufacturing, reducing reliance on OEMs, and enhancing maintenance efficiency in the aerospace industry, particularly in developing nations.

ABSTRACT. Aeroelasticity is essential for evaluating the flexibility of lifting surfaces, as the resulting vertical air velocities can greatly affect an aircraft’s structural integrity. This study investigates the influence of material properties on the aeroelastic twist of a wing. The torsional and bending mode natural frequencies are first identified to determine the flutter speed analytically, using the P–K method and arbitrary motion dynamics via Wagner’s function. In addition to estimating the flutter speed, both pre- and post-flutter behaviors are analyzed. For a rectangular wing, the differential equation of the twist angle—derived by applying strip theory to slender beam theory—is solved to obtain the spanwise aeroelastic twist distribution. Because the wing box considered in this study incorporates spars and stringers, making it extremely stiff, aeroelastic flutter does not occur within the UAV’s flight envelope due to its high effective torsional rigidity. Consequently, numerical flutter analysis, including Fast Fourier Transform (FFT) of the time response, is not performed for this wing configuration. Since the effective torsional rigidity is very high, the twist angles along the half-span are expected to remain small. The findings provide valuable insights into the dynamic aeroelastic behavior and aerodynamic efficiency of a UAV wing.

ABSTRACT. Rocket Assisted Takeoff (RATO) for Unmanned Aerial Vehicles (UAVs) is gaining traction due to its ability to power flight vehicles to be launched without the requirement of paved runways. RATO operation also enhances flight performance especially during lift-off under high-payload or restricted terrain conditions. In RATO-UAVs the use of small rockets of 2 to 12 kN are best suited for sustaining high tempo operations. These Rockets can be powered with composite or chemically reacted solid propellants. These rockets are peculiar in terms of their small size, high chamber pressure, and ability to generate rapid thrust. This paper investigates the performance feasibility of using Di-Lead SQ-2 extruded double-base propellant vis-a-vis the Ammonium Perchlorate combined with conventional Hydroxyl-Terminated Polybutadiene i.e. AP-HTPB composite propellant. The comparison focuses on the variation of performance parameters including but not limited to specific impulse variations of both energetic materials with respect to altitude, high chamber pressure, and adiabatic flame temperatures. Results show that SQ-2 stores greater amount of energy as compared to HTPB – a fact established from thermochemical tests that are conducted using various design tools, including RPA®, ProPEP®, and SRM code. The Di-Lead SQ-2 propellant outperforms AP-HTPB in the specific altitude range of 0–50 km. It demonstrates superior performance with or without lead oxide additive due to the NC-NG matrix. A significant amount of energy is released from this matrix, making SQ-2 more energetic and reactive compared to the AP-HTPB formulation. It achieves a specific impulse of approximately 270s, regardless of the presence of lead oxide. The superior performance of SQ-2 propellant, especially in high-thrust scenarios, makes it an ideal choice for RATO UAV application. The high specific impulse of SQ-2 also results with reliable and efficient thrust, that helps in supporting tactical rocket missions and including then needed for rapid medical and supply-drop operations. This evaluation therefore establishes the SQ-2's suitability for near-vertical takeoff roles, offering a reliable and high-performance alternative to conventional composite propellants.

ABSTRACT. The accurate detection and tracking of objects in drone imagery is still an open problem because of the frequent rotation of the drone during the flight. These rotations affect greatly the orientation of the captured images of the drone. Traditional object detection systems like YOLOv5 produce bounding boxes that are not aligned with the rotated objects, therefore, suboptimal thumbnail generation results which affect the subsequent analysis tasks. This paper presents the Sha Rotation Thumbnail (SRT) algorithm, a new postprocessing technique, which, by evaluating from various perspectives, step-wise agrees with the most suitable object representation. The new method first implements different rotations (0°, 90°, 180°, and 270°) of the detected objects and then selects the thumbnail configuration that is most consistent with the object’s geometrical characteristics. A dataset of 7,425 drone captured images has been used to check the performance of the proposed system compared to a basic YOLOv5, resulting to SRT improved system giving a 9.5% increase in F1score (0.896 vs 0.818) and substantial gains in both precision (0.919 vs 0.844) and recall (0.875 vs 0.793). Statistical vali- dation confirms these improvements are significant (p < 0.001) across all performance metrics. The algorithm’s efficient implementation main- tains real-time processing capabilities while resolving a critical limitation in current aerial object detection systems.

ABSTRACT. Abstract: The research focuses on the design, modelling, and fabrication of an Unmanned Aerial Vehicle (UAV) utilizing advanced 3D printing techniques. This study aims to address the challenges in UAV development by integrating innovative design approaches with additive manufacturing technologies to optimize performance and reduce production time. The UAV was conceptualized through comprehensive CAD modelling, followed by detailed simulations to ensure structural integrity and aerodynamic efficiency. Subsequently, the design was brought to life using 3D printing, which allowed for rapid prototyping and iterative improvements. The results demonstrated that the 3D-printed UAV met the desired specifications for lightweight, durability, and ease of assembly. This study highlights the potential of 3D printing as a viable method for UAV fabrication, offering significant advantages in terms of customization and cost-effectiveness. The findings suggest that this approach can be further explored for more complex UAV designs and applications, paving the way for future innovations in the field.

ABSTRACT. The escalating demand for robust and high-capacity wireless communication, especially in underserved rural and remote regions, necessitates exploring innovative alternatives to traditional terrestrial networks. Aerial platforms, encompassing High-Altitude Platforms (HAPs) and Unmanned Aerial Vehicles (UAVs), present a compelling solution for extending coverage, bolstering capacity, and enhancing network resilience. This study conducts a comprehensive review of the current state-of-the-art in aerial platform-based wireless communication, aiming to delineate recent advancements, identify persistent challenges, and chart future research directions for effective deployment and operation.

A systematic examination of diverse aspects of aerial platforms is undertaken, encompassing their classifications, operational frameworks, and the critical regulatory landscape governing their deployment. This review delves into key technical challenges, including intricate channel modeling, effective interference management, dynamic cell formation, and robust backhaul connectivity. Furthermore, it explores cutting-edge advancements in communication techniques specifically tailored for aerial platforms, such as sophisticated array antenna design, precise Radio Environment Maps (REMs), efficient Device-to-Device (D2D) communication, and intelligent resource management strategies.

The analysis reveals substantial progress in developing innovative technologies designed to leverage the unique capabilities of aerial platforms for wireless communication. However, it also underscores the critical importance of addressing economic viability and ensuring seamless coexistence between aerial networks and existing terrestrial and satellite infrastructure. These factors emerge as paramount areas for ongoing research and development. This review highlights the need for further investigation into optimized resource allocation, robust interference mitigation techniques, and the development of scalable and cost-effective deployment models to fully realize the potential of aerial platforms in bridging the digital divide and enhancing global connectivity.

ABSTRACT. The industrial and manufacturing aerospace sector is experiencing considerable digital transformation in which Artificial Intelligence (AI) plays a significant part in the maintenance revolution of aircraft. This paper investigates the combination of lifecycle management techniques and AI-driven predictive analytics to improve the efficiency of aircraft maintenance, decrease operational expenses, and enhance safety operations within the aeronautical sector. Nowadays, utilising predictive and condition-based maintenance the models are increasingly replacing conventional time-based maintenance programs and schedules. Different technologies of artificial intelligence (AI), like natural language processing, deep learning and machine learning are utilised to examine extensive amounts of operating data, allowing predictive models that predict the failures of the part before they happen, expanding the life of vital parts and reducing unscheduled downtime. Furthermore, using AI in managing the aircraft lifecycle enables the optimization and tracking of aircraft parts' health from innovation and design to decommissioning, providing sustainable fleet operations and cost-effective fleet processes or operations. Even though there are a lot of benefits that are provided when using AI for the aircraft maintenance system, there are different difficulties associated with the integration of the system, the quality of the data and regulatory observation remain. Overall, this paper presents an in-depth study of the recent use of AI in aircraft maintenance, actual-world case investigations of successful performances, and an understanding of how AI can enhance aircraft maintenance systems in the aeronautical field.

ABSTRACT. The use of highly efficient propulsion systems such as reusable scramjets and detonation engines is amongst the foremost methods for reduction in the cost of space operations. The concept of using detonation for high-performance propulsion has been explored for decades. Rotating detonation engines (RDEs) operate with continuous detonation waves, eliminating the inefficiencies of intermittent combustion and post-pulse purging. Detonation-based cycles operate on a pressure gain principle, which is fundamentally more thermodynamically beneficial than constant pressure combustion cycles like the Brayton cycle used in conventional gas turbines. Detonation allows more intense burning of fuels in smaller chambers with the size determined by the detonation-wave front scale. This study investigates the applicability of RDEs for sub-orbital and hypersonic cruise flight vehicles by analyzing the underlying detonation physics and thermodynamics governing their operation. Different thermodynamic cycle models, i.e. Humphrey, Fickett-Jacobs, and ZND have been analyzed for detonation engines. The Zel'dovich-von Neumann–Döring (ZND) model is considered the most appropriate for cycle analysis showing higher predicted work and efficiency compared to Humphrey and FJ cycles. The investigation is based on a fractional-factorial Design of Experiments (DoE) approach to study the influence of key input variables and propellant combinations including methane (CH4) and acetylene (C2H2) on performance metrics such as thrust and thermal stability, the DoE analysis identifies critical parameter of interactions that significantly affects engine behavior, offering a deeper understanding of optimizing RDE configurations for various operating conditions. Furthermore, the wave speeds in an RDE are found to be sensitive to the specific impulse, with different trends observed for varying nozzle geometries. The number of waves and wave speed depend on flow conditions and nozzle geometries. Additionally, a two-dimensional computational fluid dynamics (CFD) simulation is carried out using ANSYS Fluent to capture the flow field and validate the behavior of rotating detonation waves within the combustion chamber. Results from this integrated theoretical and computational approach demonstrate the feasibility of RDEs as compact, efficient propulsion solutions and highlight their potential application in sub-orbital flight vehicles including supersonic and hypersonic missiles, sustainer engines for low-cost launch systems, and other platforms.

ABSTRACT. The use of micro gas turbines is increasing across the application areas due to their high reliability, power density, and fuel flexibility. Hybrid aerial propulsion is a particularly rising area in addition to cogeneration, micro-grids, and grid support-stabilization applications. In this regard, there is a crucial need for compact and efficient combustors that can deliver high power in a lightweight and compact size. The combustor involves complex interactions between phenomena such as turbulent mixing, combustion, and heat transfer; therefore, a practical design requires simultaneous handling of various conflicting performance parameters, often requiring multiple design iterations and successive improvements. This study presents the design and multi-objective optimization of a micro gas turbine combustion chamber using a novel integrated approach to maximize the efficiency of the design process. The results indicate that using the approach significantly improves performance indicators compared to the baseline non-optimized design. The pressure loss is reduced by 4.4% of the total inlet pressure, and the pattern factor is enhanced by 47%, while simultaneously the volumetric dimensions are reduced by 62.27%.

ABSTRACT. This paper presents a methodology for validating MathWorks Simscape as a high-fidelity digital twin for aerospace control system development. A physics-based model of a reusable launch vehicle (RLV) is built with nonlinear effects such as variable mass, actuator limits, and environmental disturb-ances. Using a classical Proportional-Integral-Derivative (PID) controller as a transparent benchmark, the study focus-es on assessing physical fidelity rather than introducing new control methods. Validation compares simulated and expected dynamics, including disturbance rejection, mass-depletion ef-fects, and coupled six-degree-of-freedom responses. Results show Simscape matches the benchmark within 5–8% across the flight envelope, confirming its suitability for advanced Model-Based Design and potential Hardware-in-the-Loop (HIL) workflows. The PID-based framework provides a scal-able, cost-effective alternative to hardware-based verification.