ABSTRACT. This study presents a numerical investigation of the aerodynamic perfor-mance of the NACA 64A-204 airfoil under subsonic (Mach 0.8) and super-sonic (Mach 1.5) conditions using two-dimensional CFD simulations in ANSYS Fluent. A steady-state RANS approach with the SST k–ω turbulence model and a validated C-type grid was employed to capture shock waves, boundary layer separation, and adverse pressure gradients with high accura-cy. Simulations were conducted over a wide angle-of-attack range (0° – 50°), covering both attached-flow and deep-stall conditions. Results reveal clear differences between regimes: while the airfoil sustains attached flow at mod-erate angles in subsonic conditions, supersonic flows generate strong oblique shocks, earlier separation, and reduced aerodynamic efficiency. The analysis highlights maximum lift and efficiency trends, Mach-dependent drag rise, and flow structure transitions. These findings provide not only detailed aero-dynamic insights into the NACA 64A-204 but also practical implications for high-speed aircraft design, offering a CFD-based reference for performance assessment, future experimental wind tunnel validation, and the develop-ment of drag-mitigation or flow-control strategies.

ABSTRACT. Titan, Saturn's largest moon, offers the unusual pairing of Earth-like nitrogen atmosphere, high 1.5-bar surface density, and low 0.14 g gravity – environments well-suited both to efficient, long-range flight but also to cryogenic, chemically complex operations. Preceding missions, such as Cassini-Huygens, have mapped Titan from orbit and via a single descent probe, yet comprehensive in-situ coverage has not been realized. The majority of aerial mission concepts proposed to date have concentrated on balloons or rotorcraft with comparatively little exploration of fixed-wing performance in Titan conditions. This paper presents a first-cut design of a fixed-wing platform – Titan Atmospheric Navigation and Investigation System (TITANIS) – to bridge this gap. TITANIS is designed for multi-mission, such as low-altitude terrain imaging, stratified atmospheric sampling, and micro-probe deployment along methane-lake shorelines. Using Raymer's sizing methods adapted to Titan's 5.4 kg m⁻³ air density, we define a small 1.14 m-span rectangular wing. Three low-Re airfoils (Eppler 387, Eppler 205, Selig 1223) are evaluated in 2-D CFD for –2° to 10° angles of attack; Eppler 387 has the best lift-to-drag ratio at the zero-incidence cruise point and is selected for the baseline. A 3-D CAD model depicts the high-wing, twin-boom H-tail configuration scaled to a stall speed near 7.8 m s⁻¹ in Titan air. An early 5 × 5 severity–likelihood risk matrix determines stall-margin uncertainty, low-temperature material brittleness, and battery capacity loss to be top design drivers, guiding early mitigation strategies. While it is a conceptual framework, the coupled aerodynamic and risk framework provides a quantitative foundation for guiding future power-plant trades, sub-scale testing, and final mission definition of fixed-wing exploration of Titan.

ABSTRACT. The Rotating Detonation Combustor (RDC) is an emerging technology in the field of propulsion that shows great promise in terms of potential for significant improvements in fuel efficiency and power density when compared to conventional combustion systems. The combustion process in RDCs involves both deflagration and detonation, as well as complex fluid dynamics, including oblique and reflected shock waves. Because of this complexity, the chemical mechanisms are crucial for developing accurate numerical models of RDCs. In this study, a two-dimensional RDC simulation was conducted utilizing three distinct chemical mechanisms. The objective of the study was to elucidate the disparities between the chemistry models. For this study, the following chemical mechanisms were selected for comparison: Burke, USCD, and one-step chemistry mechanisms. For comparison, a range of metrics was analyzed, including, but not limited to, parameters such as detonation height and peak values of static pressure and temperature. In addition, the mass fraction of some important species was analyzed to provide a comprehensive overview. The one-step chemistry mechanism serves as the baseline in this study. The results indicate that using the Burke chemical mechanism results in a lower detonation height, while higher values for pressure and temperature are observed. In simulations using the USCD chemical mechanism, the results are comparable to the baseline case, although they do not completely align. Additionally, OH chemiluminescence imaging has been identified as an effective method for recognizing the detonation wave in experimental studies. A significant limitation of the one-step chemistry mechanism is the absence of the OH radical, which is present in both the Burke and USCD mechanisms. Furthermore, numerical Schlieren images were obtained for each chemical mechanism and compared to enable a more detailed analysis of the wavefront.

ABSTRACT. Understanding shockwave formation and its interaction with different aerodynamic bodies is important not only for high-speed vehicle design but also for getting insight regarding complex aerodynamics / thermodynamics along with validation of commercially available flow solvers. This research investigated the shock structures around two basic geometries which are wedge (10°) and a shock cone (25° half-angle) using Schlieren imaging of supersonic wind tunnel of CAE. The research is backed with the analytical textbook classical formulations and steady Computational Fluid Dynamics (CFD) at Mach numbers of 1.5, 1.75, 2.0, and 2.25. The CFD simulations utilized the SST k–ω turbulence model with Sutherland's three-coefficient viscosity model for accurate boundary layer and shock resolution. Schlieren visualization captured the real-time shock angles, while the analytical θ-β-M relationships provided analytical benchmarks for comparison. The results reflected an excellent agreement of shockwave characteristics in between CFD and analytical calculations for attached shocks. The shock angle β and Mach number M correlation are analyzed for both the models. Shock to shock and shock to boundary layer interactions were also studied for double wedge using CFD simulations for enhanced understanding of shockwave phenomenon. This work provided a foundational validation for future high-speed aerodynamic studies and demonstrated the utility of combining experimental, analytical and numerical techniques for characterizing compressible flows.

ABSTRACT. Abstract This study investigates the development of an unmanned aerial vehicle (UAV) based fire extinguishing system tailored for aerodrome environments. In addition, the project aims to modify the drone to solve the challenges that traditional firefighting methods including delays in response time, limited visibility, and restricted access to fire sources. The project proposes a UAV system capable of remote and efficient fire intervention. The project is divided into two designs, each of which is equipped with different systems that are used to fight fires in different ways (vertically and horizontally). Furthermore, the designs are explained as follows: The first design used in horizontal firefighting includes a drone equipped with a carbon fiber cylinder, a nozzle, and an electrically controlled valve. The principle of this design is that when the drone approaches the fire, using the remote control of the drone, the valve releases compressed fire-extinguishing materials towards the flame through the nozzle. Moreover, the purpose of using a cylinder made of carbon fiber instead of Steel, is to contribute to weight reduction and increase strength, allowing high-pressure containment to increase the amount of fire extinguishing material and improve flight performance such as flight time. Finally, in this design, CO2 is the fire-extinguishing material chosen based on the common fire categories encountered in airport environments. The second design is used in vertical firefighting, which includes a UAV equipped with a release system separately controlled and fire-extinguishing balls. the principle of this design is when the drone reaches vertically above the fire zone, using a separate remote sends an order signal to the release system to drop the ball into the fire source, then the fire extinguisher ball explodes after a few seconds, leads to disperse its fire-material contents and firefighting. In addition, the size of the extinguisher ball correlates with the area it can effectively cover. Moreover, the fire extinguisher ball contains specific fire-extinguishing material that is capable of fighting all types of fire.

ABSTRACT. the frequent and disorganized shift changes in aviation workplaces, particularly in airbases, present significant challenges to operational efficiency, personnel accountability, and overall quality control. The lack of a structured handover process not only hampers productivity but also poses risks to safety and documentation accuracy, especially in high-security, fast-paced environments. Traditional attendance and monitoring systems, which rely heavily on manual inputs, are prone to errors and manipulation, making them insufficient for the demands of modern aviation operations. This paper proposes the integration of facial recognition technology into airbase sections as a transformative solution to personnel tracking and shift management. By deploying camera-based systems that detect and identify individuals in real time, the system captures essential data—such as personnel identity, section presence, and timestamp—automatically and relays it to the central quality management system. This not only streamlines the shift change process but also enhances traceability and accountability across aviation units. The proposed system utilizes machine learning algorithms to ensure high recognition accuracy and robust data protection, forming a digital infrastructure for transparent and efficient workforce monitoring. This innovative approach redefines quality assurance practices in aviation environments, offering a scalable and automated solution to a long-standing organizational issue.

ABSTRACT. In-flight pilots working in high-stress conditions in aviation markets need real- time health perception to minimize the chances of physiological disability in- flight. Nevertheless, the existing cockpit-integrated monitoring systems tend to be obstructive, lack coverage, or not available on older airplanes. The present paper would fill this gap by exploring the possibility of incorporating a consumer-grade wearable device (the Smart Ring) to provide continual, non- obstructive physiological monitoring of pilots in flight

ABSTRACT. In this Paper different advanced control methods will be presented and explained to find the optimum solution for the Benchmark control problem. Supporting this with mathematical evidence for the design control. There is always a gap between control theory and the implementation of that theory on an existing control application. Most of the control methods that were suggested or made by control engineers and researchers are not implemented in real control systems. Also, many existing industrial problems are not getting enough research and are not being studied in the academic field. Benchmark problems can help to reduce this gap and can suggest many solutions for the party involved in control theory and application roles. The target is to scan and provide different controls and modeling-related benchmark problems that can act as inspiration for future benchmark methods to provide optimization-suggested solutions. This research will understand different advanced control techniques and how efficiently can get better performance after comparing the results that come from those techniques. Check the requirements for the Benchmark problems and design a module to reach the possible optimum solution.

ABSTRACT. In recent years, chaotic trajectory tracking has emerged as a novel approach to improve the evasiveness and unpredictability of guided projectiles. The integration of chaos-based guidance mechanisms—specifically, the Lorenz, Sprott-A, and Halvorsen systems—into a swarm projectile framework governed by PID controllers is the focus of this study. The major goal of this study was to find out how physically possible it is, how much control effort it takes, and how much energy it takes to follow realistic chaotic courses when there are external disturbances like wind. Three-dimensional projectile motion, wind perturbations, and actuator dynamics were integrated into a simulation-based methodology to resolve this issue. We employed gimbal angle calculations to find changes in pitch and yaw, as well as angular velocities and torque-based effort estimates. The results suggest that Sprott-A is the most suitable for energy-constrained systems, as it required the least angular and control effort, despite the fact that all chaotic systems exhibited trackable behaviour via PID regulation. On the other hand, Halvorsen demonstrated high torque demands and angular variability, suggesting a compromise between actuation burden and unpredictability. The total energy estimations, which included kinetic, potential, and rotational components, stayed within acceptable bounds for all systems. This showed that they could be used to model real-world projectile dynamics. This investigation facilitates the expansion of autonomous guidance systems' body of knowledge by quantifying the performance implications of chaotic reference tracking. These findings indicate that chaos-informed guidance can provide improved manoeuvrability without circumventing mechanical constraints when correctly calibrated, and it is appropriate for integration into swarm coordination and mission planning architectures.

ABSTRACT. General visual inspections are imperative for commercial and military aircraft to identify damage that may imperil flight safety. Currently, these inspections are predominantly carried out by skilled maintenance personnel who meticulously inspect the aircraft's surface to detect and document defects such as cracks, dents, corrosion, and broken fasteners. This manual process is time-intensive, prone to human error, and hazardous. Consequently, the implementation of computer vision and deep learning techniques for the automated detection of cracks, dents and corrosion in aircraft fuselage through advanced image processing techniques has gained traction across various fields. This advancement is facilitated by Unmanned aerial vehicles (UAVs) equipped with high-resolution cameras, where data is captured and processed utilizing sophisticated algorithms to enhance inspection accuracy and efficiency. The study utilized a dual-method approach, incorporating the Roboflow platform alongside EfficientNet-B7-based convolutional neural networks (CNNs) and Canny Edge Detection to facilitate highly precise crack pattern identification and analysis. By utilizing a dataset of more than 3,000 images, this sophisticated framework significantly enhances detection accuracy, even in structurally complex and challenging-to-access regions. This research demonstrates the effectiveness of integrating MATLAB-based image processing with deep learning techniques to establish a robust model for aircraft crack detection, offering valuable insights for aviation maintenance and safety.

ABSTRACT. Electronic Warfare (EW) involves utilizing the electromagnetic spectrum to gather intelligence on an adversary's activities while simultaneously disrupting their use of the spectrum. This is achieved without hindering the friendly forces' access to the electromagnetic spectrum. EW encompasses the entire electromagnetic spectrum and is employed across land, sea, air, and space. This module will specifically explore its application in airborne operations. EW targets all forms of hostile equipment that transmit or receive electromagnetic signals. This includes radar systems, various communication channels, weaponry guided by optical, infrared, or ultraviolet signals, and an array of devices that detect potential targets by analyzing emissions across these frequency bands. Electronic Warfare (EW) has emerged as a pivotal aspect of modern military operations, enabling strategic dominance through the manipulation of the electromagnetic spectrum. This paper explores the evolution, classifications, technological advancements, applications, and future trends of EW, highlighting its significance in contemporary and future combat scenarios. The study aims to provide an in-depth understanding of EW’s role in enhancing operational effectiveness while addressing the challenges faced in this dynamic domain.

ABSTRACT. Dissimilar welding of titanium alloys and stainless steels is a technologically challenging process primarily due to the formation of brittle intermetallic compounds (IMCs) at the interface, which severely degrades the mechanical properties of the weld. This study investigates the influence of two refractory interlayer materials thicknesses 0.1 mm and 0. 2mm Niobium (Nb on the weld quality of Ti-6Al-4V and SS-304 during automated Pulsed Gas Tungsten Arc Welding (P-GTAW). Both interlayers thicknesses were tested using identical welding parameters, and 0.1 mm thick copper filler wire. Tensile testing, Hardness profiling and optical microscopy were conducted to evaluate mechanical performance and microstructural evolution. The results clearly demonstrate that the use of thicker interlayer material significantly improved the ultimate tensile strength (UTS) and reduced the formation of brittle intermetallic compounds compared to 0.1 mm Nb. The thicker Nb interlayer (0.2 mm) was found to notably enhance joint strength and microstructural integrity compared to a thinner one, by providing better separation and diffusion control between the dissimilar metals. These findings highlight the crucial role of interlayer material selection in dissimilar metal welding and provides a way toward achieving stronger Ti-steel joints for aerospace and nuclear applications.

ABSTRACT. The increasing demand for lightweight and high-performance materials in structural applications has led to the development of metal matrix composites with enhanced mechanical properties. However, the fatigue behavior of such composites under cyclic loading remains a critical challenge, especially for applications involving dynamic stresses. This study aims to evaluate the fatigue life and fatigue limit of Al6061 alloy reinforced with silicon carbide (SiC) particles at varying weight fractions. The composite specimens were fabricated using the stir casting technique with SiC content of 3, 6, 9, and 12 wt%. A stress-life approach under constant amplitude loading was employed to assess the fatigue behavior of the composites. Experimental results indicate that the fatigue life significantly improves with increasing SiC content. Notably, the composite exhibits a fatigue life exceeding 10⁵ cycles when subjected to stress levels below 150 MPa. These findings demonstrate the potential of SiC-reinforced Al6061 composites for fatigue-resistant structural applications.

ABSTRACT. Integrating additive manufacturing (AM) with continuous carbon fiber-reinforced thermoset composites (CCFRTCs) offers significant potential for producing high-performance, near-net-shape composite structures with tailored mechanical properties. This study explores the development of additively manufactured hybrid fiber metal laminate (FML), combining the lightweight and high strength of brittle CCFRTC with the ductile aluminum metal. Additive deposition of reactive resin-infused fiber tow (ADRRIFT) process is employed to print a composite on a surface-treated metal substrate, with a strong interfacial bond for load transfer. This enables significant increases in design and manufacturing complexity, allowing for faster prototyping of efficient and multifunctional structures. The research investigates processing parameters, fiber-metal adhesion, and mechanical performance under impact loading. The results revealed that the mechanical properties are highly dependent on the fiber architecture, the metal and polymer composite interface, and the interlaminar strength of the polymer composite. FML impacted at 30 J exhibited up to 76% increase in peak load, 13% increase in absorbed specific energy, and 11% increase in density compared to the AM monolithic composite. Furthermore, this work lays the foundation for advancing hybrid metal composites through the ADRRIFT process, enabling the creation of complex geometries with freedom of material and fiber architecture not possible with conventional manufacturing processes.

ABSTRACT. As global demand for satellite deployment into Low Earth Orbit (LEO) and Sun-Synchronous Orbit (SSO) continues to accelerate, new geographic regions are exploring entry into the space launch sector. This study presents a strategic evaluation of Oman as a potential launch site for orbital missions, with a focus on LEO and SSO access. Leveraging Oman’s unique geographic position—situated near the equator with access to expansive coastal regions—the analysis examines key selection criteria, including latitude advantages, range safety, trajectory optimization, logistical infrastructure, and geopolitical stability.

Using a multi-criteria decision framework, we assess optimal launch azimuths for polar and sun-synchronous trajectories, highlight necessary downrange safety corridors over the Arabian Sea, and model orbital insertion efficiencies achievable from potential coastal sites such. Environmental impact assessments and regulatory frameworks are also considered to ensure sustainable development.

Preliminary findings indicate that Oman offers competitive benefits for mid-inclination and near-polar launches, especially for emerging commercial and government-led small satellite missions. The establishment of launch capabilities in Oman could serve regional demand while enhancing national technological leadership in aerospace sectors. This work aims to provide foundational guidance for policymakers, industry stakeholders, and academic researchers involved in developing Oman’s space infrastructure roadmap.

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.

ABSTRACT. Stop drill-hole has been used extensively in the past by researchers and engineers, particularly for aero-structures, to extend the fatigue life in those metallic specimens or structures that contain a crack. Indeed, drilling a hole in the tip of a sharp crack turns the crack into a round-tip notch resulting in a significant reduction in stresses around the initial crack. In this paper, an innovative method is introduced according to which instead of a single hole, two holes are drilled at the crack tip. The main purpose of using double stop-hole method is to reduce the stress singularity at the crack tip further and also to reduce the stress concentration in the vicinity of the stop holes in the cracked structural elements. The fatigue crack growth retardation is examined in this research both experimentally and numerically to explore the efficiency of the double-stop drill hole method. Different geometry parameters are considered in the finite element simulations to find the favorite positions of the two holes relative to the crack tip for better efficiency. Based on the finite element results, single edge-notch tension specimens made of an alloy steel are subjected to fatigue loading and the experimental results are compared for three different cases: plain specimens, specimens containing only a single hole and specimens possessing two holes. The numerical and experimental findings both reveal that the fatigue life enhancement resulted from the double stop-hole method is meaningfully larger than the that of the classical single-stop hole method. According to the finite element and experimental results obtained in the present research, one can suggest that the double stop-hole method can be considered as an efficient, inexpensive and simple technique for enhancing the fatigue life in cracked structures.

ABSTRACT. Particle image velocimetry (PIV) has become a sophisticated technology utilised in both research and industry to measure flow properties in a non-intrusive manner. However, the cost remains prohibitive for students to implement this method in most undergraduate aerodynamics laboratories. Furthermore, the high-powered lasers typically employed in PIV systems can pose a safety hazard in the presence of large groups of students. This paper proposes a cost-effective PIV design and analysis system that can be readily implemented in aerodynamics laboratories. The system utilises a low-power, stationary laser light source to reduce expenses and enhance laboratory safety. An open-source analysis code is employed to further reduce costs. In laboratory exercises with this system, students will grasp the PIV data collection process, apply MATLAB to analyse the data, and describe the observed flow characteristics. The paper also provides detailed information on the system, with the aim of enabling others to construct similar systems for use in their own laboratories. Example applications for pumping liquid in a mini-pool and visualisation of the jet flow of a synthetic jet actuator are applied as applications of the PIV system at the end of the study.

ABSTRACT. In this study, artificial neural network (ANN) applications were used to pre-dict propulsive properties of small propellers utilizing experimental data and detailed geometry information of the propellers. Scaled conjugate gradient (SCG) algorithm was used in training of the ANN. The amount of geometry information of the propellers were varied as input to the algorithm and it was shown that more geometry information results in better prediction such that the mean relative error of efficiency prediction was reduced from 9.21% to 4.36%. Input layer has diameter, pitch, RPM, advance ratio (J), chord and twist distributions. Hidden layer has neurons number varying from 1 to 100. Output layer has thrust coefficient, power coefficient and efficiency. High coefficient of determination (R2) values were obtained around 0.99 and low percent errors obtained around 1.8% which suggests that ANN applications are useful tools in predicting propeller parameters and designing for propeller driven air vehicles.

ABSTRACT. Computational Fluid Dynamics (CFD) analysis traditionally depends on manual interpretation of complex flow patterns through methods which are both subjective and time-consuming and require extensive domain expertise. This research presents an innovative framework that synergizes synthetic physics-informed CFD data generation with explainable deep vision models to enable automated flow pattern classification. The study constructs a com-prehensive synthetic dataset using mathematical models that replicate realis-tic fluid flow behaviors across three regimes: laminar flows (Re: 2000) characterized by sinusoidal functions yielding smooth parallel streamlines, turbulent flows (Re: 2000) modeled with multi-scale chaotic and stochastic com-ponents, and separated flows exhibiting recirculation zones with exponential decay properties. Being aligned with established fluid mechanics principles, this physics-informed approach facilitates controlled parameter adjustments. The framework utilizes ResNet-50 as convolutional neural networks (CNN) attaining a test accuracy of 93.83%, and ViT-Base vision transformers achieving a test accuracy of 99.33%, to interpret velocity and vorticity field visualizations for flow pattern classification, enhanced by the Explainable Artificial Intelligence (XAI) technique Grad-CAM, which provides visual explanations to ensure model reliability. This approach can significantly benefit aerodynamics by improving the prediction of airflow behavior around air-craft. Furthermore, it offers potential for real-time aerodynamic analysis, supporting the development of more efficient and safer aviation technologies.

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. In the context of aviation industry, No Fault Found (NFF) is phenomena that develops from a pilot experiencing a fault but post-flight checks fail to reproduce the reported fault. Components declared as ‘NFF’ are evidence that a serviceable component was removed, and attempts to troubleshoot the root cause have been un-successful. The occurrence of NFF remains a significant operational challenge, contributing to unnecessary maintenance actions, increased operational costs, and resource wastages. Previously six paradigms (System Design, Fault Diagnosis, Reliability Engineering, Data Management, Human Factors & Economic Analysis) of NFF have been explored, but implications of NFF (lost man hours, maintenance cost, packaging / handling costs, machine down time and transportation cost) etc. have not been interlinked with lean / waste factors (defects, over production, waiting, non-utilized talent, transportation, inventory, motion & extra processing). This study proposes seventh paradigm of “Lean Framework” by undertaking a comprehensive industrial assessment of NFF phenomenon at Aviation Maintenance, Repair, and Overhaul (MRO) sector through a structured research process comprising a detailed literature review, an industrial survey for gap analysis, the development and dissemination of a targeted questionnaire, and subsequent quantitative data analysis. Based on responses from 50 aviation maintenance professionals, and with a survey reliability confirmed by a Cronbach’s Alpha value of 0.801, the study identifies the key eight lean wastes attributable to NFF events. High mean scores across all waste categories highlight resource wastages resulting from NFF events. In response to these findings, human centered six soft lean practices have been proposed as effective solutions: leadership commitment, supplier collaboration, team-based problem solving, continuous process improvement, technical personnel training, and stakeholder feedback system. Data analysis revealed strong endorsement of the proposed soft lean practices, emphasizing the urgent need for systematic intervention. The results highlight that addressing NFF requires not only technical diagnostic improvements but also strategic organizational and behavioral changes. The proposed lean framework offers a practical, scalable approach for Aviation MRO organizations aiming to reduce NFF wastes, optimize operational performance, and promote a culture of continuous operational excellence.

ABSTRACT. The aviation industry's unwavering commitment to safety hinges on a robust maintenance culture. This article explores the multifaceted nature of maintenance culture within aviation, highlighting its critical role in ensuring airworthiness and preventing unwanted outcomes. A strong maintenance culture transcends mere adherence to regulations; it promotes a proactive, safety-conscious environment where every individual, from mechanics to management, prioritizes quality and vigilance. Central to this culture is a commitment to continuous improvement, driven by rigorous inspections, meticulous documentation, and comprehensive training. Effective communication and a transparent reporting system are essential, allowing for the rapid identification and resolution of potential issues. Furthermore, strengthening a "just culture" encourages the reporting of errors without fear of reprisal, enabling valuable lessons to be learned and systemic weaknesses to be addressed. The integration of advanced technologies, such as predictive maintenance and digital record-keeping, further enhances the efficiency and reliability of maintenance operations. These technologies facilitate data-driven decision-making, allowing for the early detection of anomalies and the optimization of maintenance schedules. However, the human element remains paramount. The cultivation of a positive safety climate, characterized by trust, respect, and shared responsibility, is crucial for maintaining high standards. This necessitates strong leadership, which champions safety as a core value and empowers employees to actively participate in safety initiatives. Ultimately, a thriving maintenance culture in aviation is a dynamic and evolving system, constantly adapting to new challenges and technologies, ensuring the continued safety and reliability of air travel.

ABSTRACT. An innovative and sustainable water treatment system that synergizes mechanical filtration through a vertically rotating disc with ultraviolet (UV) light disinfection is utilized, advancing traditional biological treatment methods. A rotating disc enhances particle removal while a UV chamber effectively disinfects the water, avoiding the implementation of any chemical product, thus promoting an eco-friendly solution with low operational costs. Computational Fluid Dynamics (CFD) simulations using ANSYS Fluent confirmed the significant impact of rotational speed on film thickness and filtration efficiency, validating the core design of the filtration system. The system has been significantly enhanced to integrate real-time chemical monitoring through pH sensors. If the treated water does not meet predefined safety standards, an intelligent feedback mechanism, powered by a motorized return system, redirects the water back for additional filtration and disinfection. This closed-loop feature minimizes waste, ensures consistently high-water quality, and reduces dependency on chemical treatments. Human intervention is minimized through implementation of AI-embedded monitoring technologies, optimizing the system autonomy. The innovative water treatment system demonstrates a practical application of smart technologies to support water security, a national priority under the Oman 2040 Vision’s environmental sustainability pillars. The design’s modularity, affordability, and environmental sensitivity make it a compelling solution for both local and global water treatment challenges. By offering a chemical-free, energy-efficient, and intelligent approach to water purification, this research sets a new benchmark for sustainable innovation in the water treatment sector.

ABSTRACT. The demand for higher efficiency and reduced weight in electric machines has driven designers to explore advanced materials and innovative assembly techniques. One such method is shrink-fitting, which offers advantages over traditional mechanical joints such as keyways, particularly in reducing overall weight and complexity whilst maintaining sufficient holding torque or axial resistance to load through friction. In electric machines, shrink-fitting can be applied between the motor housing and the stator to provide a structurally integral assembly. This method also enhances thermal conductivity and heat dissipation though the increased stressed on the stator can interduce higher iron losses. This paper investigates the mechanical effect of the shrink-fit process on stator materials, with a focus on understanding the frictional holding torque as first stage in the overall optimization of shrink-fit of stators in electric machine housing. Several physical parameters are experimentally examined, including material properties, surface topography, coefficient of friction at the interface under various pressure, and the effects of manufacturing processes such as wire EDM, grinding and punching

ABSTRACT. SkyScan is a UAV-based traffic monitoring and surveillance system designed to overcome the limitations of traditional methods, such as blind spots, limited scalability, and environmental constraints. This work enhances real-time object detection by proposing a modified YOLOv5n architecture, tailored for the VisDrone dataset. Key improvements include the addition of a fourth detection scale (P6/64), integration of a Convolutional Block Attention Module (CBAM), and deeper C3 layers to boost feature extraction and fusion. To further refine detection accuracy, especially for small and overlapping objects, SkyScan incorporates the Slicing Aided Hyper Inference (SAHI) technique in the post-processing stage. Optimization techniques such as quantization and resource-efficient inference are also employed. Comparative evaluation with YOLO variants (YOLOv5n, YOLO7n, YOLO12n) demonstrates that the enhanced model achieves a notable increase in mAP@0.5, reaching 0.35 compared to 0.30 from the baseline YOLOv5n. SkyScan ensures real-time object detection, tracking, and density estimation, offering a scalable and efficient solution for smart city surveillance with improved detection reliability

ABSTRACT. Real-time 3D mapping and localization for Unmanned Aerial Vehicles (UAVs) performing in-flight inspections of civil aviation infrastructure is crucial for ensuring safety, reducing downtime, and enabling predictive maintenance. However, existing SLAM frameworks such as ORB-SLAM3 and NICE-SLAM struggle with the dynamic conditions encountered during UAV flight, including rapid viewpoint changes, moving obstacles, and non-rigid scene elements. We propose DMN-SLAM-UAV, a lightweight neural-implicit SLAM system tailored for UAV inspection tasks that integrates a real-time dynamic-object segmentation front end, a hierarchy of five compact MLP decoders for multi-scale geometry and appearance residuals, and an incremental octree (i-Octree) for efficient map storage. The i-Octree enables sparse, log-time updates, allowing onboard execution on an NVIDIA Jetson Orin with an average per-frame latency of 48 ms. We evaluate DMN-SLAM-UAV on a newly curated Dataset of Aerial Inspection Sequences (DAIS)—20 flight trajectories over runways and fuselage sections—and benchmark against ORB-SLAM3 and NICE-SLAM. Our approach reduces absolute trajectory error (ATE) by 37.6% and improves reconstruction completeness by 23.4% compared to ORB-SLAM3, while achieving 42% faster mapping updates than NICE-SLAM. Ablation studies confirm the contributions of dynamic masking and the multi-MLP architecture with statistical significance (p < 0.01). Furthermore, we release the DAIS dataset and our open-source implementation to foster future research. This work paves the way for robust, scalable UAV-based inspection solutions in civil aviation and beyond.

ABSTRACT. This paper introduces CMI4.1, an enhanced and data-driven smart maintenance maturity framework designed to advance the implementation of Condition-Based Maintenance (CBM) and improve the estimation of Remaining Useful Life (RUL) of mechanical components, specifically within the context of Pakistan’s aircraft manufacturing sector. The proposed model builds upon the previously published CMI4.0, which was developed by the same authors as a localized adaptation of the IMPULS Industry 4.0 readiness model by the German Mechanical Engineering Association (VDMA) and refined through expert consensus using the Delphi method. CMI4.1 expands the scope of its predecessor by incorporating additional enablers aligned with intelligent manufacturing environments, with a strong focus on digitalization, data integration, and AI readiness. The framework leverages machine learning and deep learning algorithms to analyze high-dimensional sensor data, enabling predictive maintenance, early anomaly detection, and real-time decision-making. Empirical validation within industrial settings confirms that CMI4.1 enhances CBM readiness assessments, minimizes unplanned downtime, improves operational reliability, and offers a scalable roadmap for smart maintenance transformation in emerging economies.

ABSTRACT. This article presents a comparison of two ultrasonic tightening control methods for evaluating the tightening state of preloaded bolted assemblies. The first method enables relative monitoring of clamping force evolution over time. The second method is based on coupling an Electromagnetic Acoustic Transducer (EMAT) with a piezoelectric sensor. This hybrid configuration combines the non-contact generation capability of the EMAT with the high sensitivity of the piezoelectric sensor. It relies on measuring the variation in ultrasonic wave propagation time to estimate bolt elongation and preload in an absolute manner. A major challenge addressed is the effect of temperature, which influences ultrasonic velocity. A compensation strategy is developed to correct these temperature-induced variations and ensure accurate tightening assessment. This approach enhances inspection flexibility and allows reliable monitoring without disassembling the joint.

ABSTRACT. Over the past decades, the investigation of wave transmission through peri-odic structures has gained interest among researchers, particularly in analyz-ing frequency band gaps, which have applications in vibration isolation, fre-quency filtering, etc. Tensegrity structure, a self-equilibrated network of pre-stressed tension and compression elements, enables geometry-driven dynam-ic control of wave transmission that overcomes previously manufactured-fixed structures and finds growing applications in civil engineering, robotics, space technology, etc. Motivated by this feature, the present study focuses on the numerical study of tunable wave transmission in periodic one-dimensional tensegrity architectures. First, a pre-stressed controlled two-dimensional planar tensegrity structure has been chosen for the analysis. Next, a stable equilibrium configuration was obtained using the minimiza-tion principle of its total potential energy by solving a nonlinear optimiza-tion solver. Nonlinear, followed by linearized equations of motion, were de-rived using the Lagrangian approach, and their responses are validated with the dispersion relations obtained by solving the Floquet-Bloch method under impulse load conditions. Two modes of wave transmission, i.e., symmetric and anti-symmetric modes, were identified and analyzed separately. The var-iation of band gaps over frequencies for each wave transmission mode has been analyzed in detail in a non-dimensional framework.

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. Drones, or Unmanned Aerial Vehicles (UAVs), have emerged as a revolutionary technology with diverse applications across industries due to their versatility in tasks deemed unsafe, inefficient, or impractical for humans. Rotary-Wing UAVs (RWUAVs), with their Vertical Take-Off and Landing (VTOL) capabilities, offer superior maneuverability in confined spaces compared to fixed-wing designs.

Drones are transforming military, civil, and commercial sectors. Military applications include Intelligence, Surveillance, and Reconnaissance (ISR) missions, enhancing battlefield awareness without risking human lives. In the civil sector, drones provide innovative solutions for monitoring, mapping, and inspection, improving productivity and safety. The integration of AI, autonomy, and improved battery and communication systems is expected to further expand drone applications. Projections indicate significant growth in commercial drone usage, including urban air mobility and express deliveries. The future of drones lies in their potential to reshape global interaction efficiently and sustainably.

However, the increasing use of drones necessitates assessing operational risks, particularly in adverse weather. Atmospheric/in-cloud icing poses a critical challenge in cold regions like the Arctic, where supercooled water droplets freeze on drone surfaces. This phenomenon significantly impacts performance, safety, and reliability. Drones are more susceptible to icing than manned aircraft due to lower operating speeds, higher humidity at low altitudes, and limited power. Therefore, the impact of ice accretion on drones requires specific examination.

Despite the broad applications of drones, research on ice accretion physics and its impact, especially on rotary-wing configurations, remains limited. This presentation will focus on the design and operation of drones in icing conditions and how icing affects their aerodynamic performance under various environmental and geometric factors.

ABSTRACT. This Keynote examines the technical and regulatory hurdles facing the next generation of electric vertical take-off and landing aircraft. The presentation highlights the aerodynamic, propulsion, energy, and software-assurance realities confronting eVTOL designers as prototypes transition toward certification and commercial operation. Topics include the implications of high disc loading, psychoacoustic noise impacts, battery containment and hybrid-energy trade-offs, and the certification of multi-propulsor DEP architectures. Beyond technology, the address explores operational safety, urban weather constraints, human factors, cybersecurity, and sustainability economics. Drawing parallels with past aviation milestones, it will be argued that transparent margins, verifiable safety cases, and realistic performance data—not marketing renderings—must define progress. The keynote concludes by urging the aerospace community to lead in establishing cross-domain standards, open data frameworks, and workforce development for a disciplined, evidence-based eVTOL future.

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. Aircraft line maintenance plays a critical role in ensuring flight safety, regulatory compliance, and operational efficiency, especially within the high-frequency, cost-sensitive environment of low-cost carriers (LCCs). As LCCs rely heavily on tight schedules and minimal ground times to maintain profitability, the effective scheduling and execution of line maintenance tasks during aircraft turnaround has emerged as a key area of research and operational innovation. This paper presents a comprehensive and systematic review of the hybrid optimization approaches developed and applied over the past two decades (2005–2025) to improve line maintenance scheduling with the explicit goal of minimizing aircraft turnaround time (TAT). The review encompasses over 100 academic and industrial sources, categorizing and analyzing contributions across three major theoretical domains: dynamic programming, heuristic/metaheuristic techniques, and machine learning–driven predictive analytics. It further investigates how hybrid models—combinations of algorithmic approaches—have evolved to address the inherent complexity, uncertainty, and real-time demands of line maintenance environments. In parallel, the review assesses the adoption of these models in industrial settings, highlighting successful applications, limitations, and scalability issues faced by major LCCs worldwide. A structured methodology was adopted to select, classify, and evaluate literature based on relevance, scientific rigor, and practical implications. Key performance indicators, such as reduction in TAT, resource utilization, task delay mitigation, and system robustness, are synthesized across studies using comparative tables and graphical summaries. This paper not only maps the chronological evolution and interdisciplinary convergence of hybrid optimization techniques in aviation maintenance but also identifies research gaps, including limited integration with real-time operational control systems, underuse of historical reliability data, and insufficient consideration of human factors in scheduling models. The review concludes with a set of forward-looking recommendations for academics and industry practitioners, advocating for the integration of predictive maintenance data, reinforcement learning, and digital twin environments in future line maintenance optimization research. Overall, this work contributes to the growing field of intelligent aviation operations by consolidating a fragmented body of knowledge and providing actionable insights for reducing TAT and enhancing maintenance decision-making in low-cost airline operations.

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. Machine learning (ML) is undeniably turning into a mainstream idea since its primary purpose is to enhance a system’s throughput by allowing a more intelligent usage of materials, processes and managing their resultant properties. In industrial applications, usage of ML not only decreases the lead time of the manufacturing process involved but also increases the quality and properties of the parts produced. Similarly, ML gives us an opportunity of creating completely or partially autonomous frameworks. Similar benefits are provided by additive manufacturing (AM) in the manufacturing regime as it too offers a unique combination of freedom of design, ultimate control over process parameters and eventual quality of a resultant product. AM involves the creation of parts in 3D by melting metallic powders in accordance with a 3D model. This talk discusses the utilization of machine learning techniques in various areas of additive manufacturing regime ranging from material selection and alloy development to parameter optimization, establishing process structure-property relationship and defect detection. Consecutive steps of the process i.e. data gathering, population establishment, model selection, training and application have been discussed. In the end, certain challenges associated with the long-term incorporation of machine learning in additive manufacturing and their probable solutions have been discussed.