ABSTRACT. The present work numerically analyses the flow physics over SD7062 airfoil at low-to-moderate Reynolds numbers (Re=1.25×10⁵ and 4×10⁵). The transitional shear-stress transport (SST) γ-Reθ  is used to model the turbulence. Two-dimensional incompressible flow simulations are conducted at angles of attack between 0°≤α≤ 20° to characterize mean aerodynamic coefficients, laminar-to-turbulent transition locations, and wake structures. The results reveal smooth stall behavior, increasing stall angle (from α =14° to α =15°), lift performance and aerodynamic efficiency with higher Reynolds numbers. Transition onset is found to shift toward the leading edge as the angle of attack and Reynolds number enhance. Two distinct wake regimes, steady vortex sheet and unsteady alternating vortex shedding, are observed.

ABSTRACT. The design of fixed-wing vertical take-off and landing (FW-VTOL) unmanned air vehicles (UAVs) requires careful aerodynamic evaluation of both airfoils and wing geometries to balance lift, efficiency, and stability under varying flight conditions. This study presents a systematic evaluation of 35 airfoils using XFLR5 software, focusing on key aerodynamic parameters such as lift coefficient (Cl), drag coefficient (Cd), lift-to-drag ratio (Cl/Cd), moment coefficient, stall angle, and maximum lift values. Each airfoil is assessed under a range of Reynolds numbers (50,000 to 200,000), angles of attack (0° to 20°), freestream velocities (5-30 m/s), and varying chord lengths. The results revealed significant differences in performance; the S1223 airfoil exhibited the highest maximum lift coefficient, while the E374 showed the lowest. The lift-to-drag ratio is also highest for S1223, highlighting its suitability for low Reynolds number operations typical in small UAVs. Following airfoil selection, further analysis is performed on wing geometries using the NACA 0012 airfoil to explore the influence of taper ratio, aspect ratio, and leading-edge sweep angles on aerodynamic behaviour. Wings with taper ratios of 0.4 and higher demonstrated better stall characteristics and higher lift coefficients, while increasing sweep angles led to a reduction in lift and efficiency, especially at lower Reynolds numbers. The combination of these analyses provides a robust aerodynamic database and practical guidance for UAV designers seeking to optimize FW-VTOL platforms for specific mission profiles. This work contributes to the design methodology of FW-VTOL UAVs by identifying suitable airfoil and wing combinations for efficient performance across a broad range of flight conditions. The study serves as a foundational step toward integrated aerodynamic-propulsion design and will be extended in future work through high-fidelity CFD simulations and experimental validation of selected configurations.

ABSTRACT. This study investigates the aerodynamic performance of fixed-pitch propellers us-ing QBlade, an open-source simulation tool based on Blade Element Momentum (BEM) theory. Four commercial APC propellers—6×4, 6×5, 8×4, and 8×5—are analyzed across a range of advance ratios. The study aims to evaluate QBlade’s effectiveness in estimating performance parameters such as thrust coefficient, power coefficient, and propeller efficiency. Experimental data from the University of Illinois Urbana-Champaign (UIUC) propeller database are used for validation. Results show that QBlade can effectively predict performance trends, with rea-sonable agreement observed between numerical and experimental values. The ef-fect of propeller diameter and pitch on aerodynamic performance is discussed thoroughly.

ABSTRACT. This work presents the aerodynamic analysis of an unmanned aerial vehicle (UAV) model, which has been modified by incorporating a wingtip device, commonly referred to as a winglet. The integration of this feature aims to enhance the overall aerodynamic performance of the aircraft. In order to evaluate its effectiveness, simulations were conducted by ANSYS Fluent and the modified configuration was compared to the original baseline geometry. Through these simulations, key aerodynamic parameters such as lift and drag coefficients, pressure and velocity distributions, and vortex formation were analyzed. This comparison allows for a comprehensive assessment of the improvements achieved through the winglet implementation on the UAV's wing design.

ABSTRACT. Hazardous material storage facilities are indispensable across various industrial sectors, including mining operations, defense manufacturing, research facilities, and construction. Ensuring safe storage of these materials is vital for accident prevention and public safety. However, storing these materials presents a complex optimization challenge, constrained by geometric and capacity limitations, hazard divisions, compatibility groups, regulatory safety standards, temperature, and stacking restrictions. Current practices predominantly rely on human judgment and historical trends, resulting in inefficiencies, delays, frequent adjustments, and elevated safety risks in high-consequence environments. This study aims to enhance the safety and efficiency of hazardous material storage by conceptualizing the problem as a multi-container loading problem, which is an NP-hard combinatorial challenge. The objective is to minimize the wasted space while satisfying a comprehensive array of explicit constraints. To achieve this, a Mixed-Integer Linear Programming (MILP) model is developed that employs preprocessing techniques to address stacking constraints, thereby streamlining the optimization process. The model is progressively refined by incorporating depot-specific limitations, operational needs, and practical storage requirements to enhance real-world applicability and is solved using exact solvers with a rolling horizon approach to boost computational efficiency. The MILP model is evaluated on specially designed synthetic instances that replicate real-world scenarios. Extensive computational experiments demonstrate that the model significantly improves storage efficiency and safety. Furthermore, these experiments elucidate the impact of individual constraints on the container occupancy, runtime, and packing configurations. The mathematically validated decision-support framework provides depot managers with actionable insights for handling high-consequence logistics, thereby enhancing safety compliance, minimizing delays, and optimizing space utilization.

ABSTRACT. Foreign Object Debris (FOD) presents a significant threat to aviation safety, impacting both civilian and military air operations worldwide. FOD refers to any object, whether natural or man-made, that poses a risk of damage to aircraft through ingestion, collision, or interference during ground operations or flight. This paper examines the critical impact of FOD on aircraft performance, operational costs, and passenger safety, highlighting notable incidents where FOD was a contributing factor to accidents and maintenance challenges. This study, while highlighting the current, well-established preventive measures such as regular runway inspections, advanced FOD detection systems, strict personnel protocols, and improved material management practices, are discussed as key strategies for mitigation, it emphasizes the need for novel approaches and improvements to them through emerging technologies to contribute to the evolving landscape of aviation safety. Furthermore, the importance of fostering a strong safety culture among airport authorities, ground crews, and airline operators, is reinforced as a critical element in minimizing FOD-related risks. One of the key contributions of this study is its exploration of identifying latent FOD hazards through cutting-edge technological innovations. For example, paved airfield surfaces dislodging and being ingested into engines and propellers are common risks. Additionally, bird repellents have not been effective in removing bird nests inside hangars, posing a persistent hazard. Has there been an effective method yet to prevent bird strikes, particularly during landing and takeoff? Adopting advanced technologies can significantly enhance the aviation industry's ability to prevent FOD events, ensuring safer skies and more efficient airport operations.

ABSTRACT. Introduction Airworthiness Safety Management Systems (SMS) are essential frameworks designed to enhance safety in aviation operations by systematically managing risks and ensuring continuous improvement. In military aviation, where operational demands are complex and high-stakes, integrating logistics into SMS is crucial for maintaining safety, efficiency, and mission readiness. This research explores the relationship between SMS and logistics in military aviation, emphasising how logistical processes—such as supply chain management, maintenance scheduling, and resource allocation—directly influence safety outcomes. Although logistics plays a crucial role, it often receives lesser priority. This research emphasises the connection between logistics elements and their significance to the SMS in military aviation.

Research Methods: This study initially employed a quantitative research approach, and the inferential statistics were analysed by establishing a null and an alternative hypothesis. The data that was gathered was analysed to find the regression based on a mediation model, which determined the strength and relationship among the variables. Thereafter, the findings were presented to a panel of experts through a Delphi method to arrive at the recommendations.

Findings: By analysing operational data from a case study of a selected military aviation entity, the study identifies key logistical factors that contribute to safety risks, including delays in parts delivery, inadequate maintenance practices, and insufficient personnel training. The research also highlights the role of advanced technologies, such as predictive analytics and real-time monitoring systems, in optimising logistics to support SMS objectives. Furthermore, the study examines the organisational and cultural challenges in aligning logistical operations with safety protocols, proposing strategies to foster collaboration between safety and logistics teams.

Recommendations:  The findings underscore the importance of a holistic approach to SMS in military aviation, where logistics is not merely a support function but a core component of safety management. Recommendations include developing integrated frameworks that synchronise logistical and safety processes, enhancing training programs for personnel, and adopting data-driven tools to mitigate risks. This research contributes to the broader discourse on aviation safety by demonstrating how effective logistics management can enhance the resilience and reliability of military aviation operations, ultimately safeguarding lives and assets in high-risk environments.

ABSTRACT. Fatigue failure remains a critical concern in aerospace structural components. The combined effects of thermal treatment and mechanical processing in engineering components often result in the formation of residual stress fields. While tensile residual stresses can exacerbate existing flaws and reduce component lifespan, com-pressive residual stresses are beneficial as they inhibit crack propa-gation and enhance fatigue life. Shot peening is a widely used sur-face treatment technique aimed at inducing beneficial compressive stresses. This study investigates the effectiveness of shot peening in enhancing fatigue resistance by introducing compressive residual stresses in aerospace-grade 7449 aluminum alloys. Specimens were subjected to shot peening at three intensity levels, followed by residual stress measurements using X-ray diffraction. The experimental results were compared with numerical simulations conduct-ed through Finite Element Analysis (FEA), showing strong correlation. The study demonstrates that optimized shot peening parameters can significantly retard fatigue crack initiation and propagation, thereby offering an effective strategy for fatigue life extension in critical aerospace components.

ABSTRACT. This paper proposes a model where the Spiral Optimization Algorithm (SOA) would be used to optimize the system of minimized carbon emissions as well as energy costs of EV recharging stations. Four different charging modes are presented in the proposed framework: peak, off-peak, stochastic, and Electric Power Research Institute (EPRI) charging modes that represent a variety of different ways of consuming energy and different load patterns. The spiral inspired evolutionary algorithm SOA also provides a light weighted optimization mechanism whereby candidate solutions are repeatedly processed along the path of a spiral motion in an attempt to converge into the global optimum solution. Included in the approach is the smart scheduling techniques that could be used to distribute the load, minimize the load on a power grid and facilitate the functioning of a supply and demand balance, especially under the circumstances when the renewable energy sources are highly penetrated. The model was applied in MATLAB, Simulink, and the simulation study has been done testing it and comparing with those traditional optimization techniques.

ABSTRACT. In recent years, there has been an increasing focus on the integration of artificial intelligence (AI) to Unmanned Aerial Systems (UASs) for improved health monitoring and fault detection system. This paper presents a hybrid deep learning architecture based on Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) networks trained with synthetic sensor data including accelerometer readings, thermal behavior, voltage patterns, and communication anomalies for fault detection. This study aims to develop a modular framework for fault detection that can be simulated within the context of software-defined avionics so that it may become possible to implement and test. To simulate realistic subsystem anomalies, a number of fault injection events were incorporated into the simulation, including thermal spikes, voltage drops, and increased packet losses. A time-series windowed dataset was created, and the proposed CNN-LSTM model was trained and validated using a 70:30 train-test split, achieving a test accuracy of 98.5% with a corresponding area under the ROC curve (AUC) of 0.99, demonstrating high level of classification performance. A true positive rate of 96% for fault detection was found in the confusion matrix, suggesting the model's resilience in identifying unusual activity. This study offers a new insight into the use of interpretable artificial intelligence in avionics systems and suggesting that the simulation-based framework proposed could enhance both diagnostic accuracy and lead to more reliable and transparent modular avionics architectures.

ABSTRACT. The rapid development of Advanced Air Mobility (AAM) presents significant safety challenges in integrating Unmanned Aerial Systems (UAS) into shared airspace. Ensuring safe and efficient operations requires advanced navigation, communication, and collision avoidance technologies to support the coexistence of manned and unmanned aircraft. This study examines key safety challenges in AAM, including airspace management, real-time situational awareness, and regulatory compliance.

The rapid emergence of Advanced Air Mobility (AAM) introduces critical safety challenges in integrating Unmanned Aerial Systems (UASs) into shared and in-creasingly congested airspace. Safe and efficient operations require robust solu-tions in navigation, communication, and collision avoidance to enable the coexist-ence of manned and unmanned aircraft. This paper investigates key safety con-cerns in AAM, including airspace management, real-time situational awareness, and regulatory compliance, with a particular focus on navigation safety. To ad-dress these challenges, we present a case study on the application of Visual Simul-taneous Localization and Mapping (Visual SLAM) for UAS navigation. Leverag-ing onboard cameras and AI-based feature tracking, Visual SLAM offers a resili-ent alternative to GPS, especially in GPS-denied or signal-degraded environments. Our evaluation across multiple operational scenarios demonstrates the effective-ness of this approach in improving navigation accuracy, obstacle detection and avoidance, and autonomous flight safety within AAM ecosystems. Furthermore, we explore the integration of Visual SLAM with Air Traffic Management (ATM) and UAS Traffic Management (UTM) systems, emphasizing interoperability and computational efficiency as critical enablers of large-scale deployment.

ABSTRACT. The project Real Time Tracking and Environment monitoring device for Outdoor Activities provides a comprehensive solution to enhance safety and connectivity for outdoor activities. It uses GPS technology for real-time sharing of location with teammates within the network. Location sharing with other members can be done using Radio Frequency technology. It enables users to share their location without relying on the cellular network and WIFI because remote areas face connectivity issues. Moreover, environment monitoring sensors are used to monitor temperature and atmospheric pressure which is used for local weather prediction. This system also features an Android Application, the Application has several tabs including the Track Location tab. This Tab displays the location of each user in the network on the map without Wi-Fi. Bluetooth low energy is used for data transmission between the device and android application. Weather Prediction is also displayed on the Android application. Moreover, the application also has an SOS Button which provides an extra layer of security for users and an SOS alert is displayed on the Application of each user by pressing the SOS button. It allows users to send SOS alerts in case of emergencies such as sudden storms. This device enhances safety and connectivity for outdoor Enthusiasts such as Hikers, Military operations in remote areas, and rescue operations

ABSTRACT. A blockchain is essentially a distributed database of records, or public ledger of all transactions or digital events that have been executed and shared among participating parties. Each transaction in the public ledger is verified by consensus of a majority of the participants in the system. Once entered, information can never be erased (Ølnes et al., 2017). The blockchain con-tains a certain and verifiable record of every single transaction ever made. Bitcoin, the decentralized peer-to-peer digital currency, is the most popular example that uses blockchain technology. The blockchain technology has worked flawlessly and found wide range of applications in both financial and non-financial world. The main hypothesis is that the blockchain establishes a system of creating a distributed consensus in the digital online world (Crosby et al., 2016a). This allows participating entities to know for certain that a digital event happened by creating an irrefutable record in a public ledger (Pournaras, 2020). It opens the door for developing a democratic open and scalable digital economy from a centralized one. There are tremendous opportunities in this disruptive technology, and the revolution in this space has just begun (Denis et al., 2020). This article aims to evaluate and critical-ly analyze the improvement in network delays in supply chain of Aviation Maintenance Organization operations. Moreover, this paper also evaluates and compares increase in efficiency in terms of exchange of data / infor-mation between nodes and clients (stakeholders) of an Aviation sector organ-ization.

ABSTRACT. Progress in power electronic-based converters is critical for developing high-power, cost-effective, and reliable charging solutions for electric vehicle (EV) batteries, particularly as the adoption of EVs continues to rise. This study introduces an innovative isolated hybrid three-port converter that integrates a single-phase full-wave bridge rectifier, a series resonant converter (SRC), and a dual active bridge (DAB) converter to achieve these objectives. The proposed three-port configuration reduces the number of components, leading to lower system costs and simplified design. Additionally, the inclusion of a multilevel rectifier (MLR) at the input stage enhances the input voltage waveform quality and reduces voltage stress on power switches. By incorporating fuzzy logic, the total harmonic distortion is significantly reduced to 0.19%. A simplified decoupled control strategy, utilizing pulse width modulation (PWM) and phase shift techniques, is implemented to manage power flow across all three ports simultaneously. The system is modelled and simulated in MATLAB/Simulink, with experimental validation conducted in a laboratory environment.

ABSTRACT. Strategic autonomy in space is a contemporary concept in the evolution of modern space powers. The notion of space being a cost-intensive endeavour has transformed into sustainable space through amalgamation of space-technology and space-economy into space ecosystems. Hence strategic autonomy in space now rests on four pillars, that of space-technology, -policy, -infrastructure and -collaborations. Nascent space powers are nations or entities that are pursuing indigenous development of space capabilities albeit they are posed with unique circumstances and must navigate through challenges that could be technological, economic, and geopolitical. This implies that nascent space powers including Pakistan need to work on developing space policy and regulatory frameworks that nurture the growth of indigenous space ecosystems for subsequent development of spacecraft and launch system, as well as space explorations while actively collaborating with international partners but without undue reliance on external entities. Thus, for Pakistan as well as nascent space powers in general, the question as to how strategic autonomy is attainable in space operations is becoming increasingly paramount. This research identifies the 4Ms strategy – Money, Mining, Military and Morphing as the key domains in which space technology readiness levels must be attained apriority. The strategy is implementable through a multi-sectoral regulatory framework. Moreover, implementing a bottom-up technology development approach vis top-down will be a more sustainable path for the development of autonomous space capabilities. Given the relentless nature of space contestation in the new space economy, the most plausible way by which nascent space powers including Pakistan can survive and thrive in this era, is by incubating a multi-sectoral space economy with adequate incentives and regulatory support for selectively entering into strategic collaboration with major space powers with the overall objective of enhancing the technology readiness levels for indigenously developing dual-use and ubiquitous space technologies and services.

ABSTRACT. Friction Stir Additive Manufacturing (FSAM) is a layer-by-layer solid-state AM process derived from friction stir lap welding. By joining metal plates below melting, FSAM produces fine equiaxed microstructures with superior mechanical properties and minimal melt-related defects (such as porosity or solidification cracks) compared to fusion-based AM. However, the process’s thermal–mechanical lap-weld character also introduces its own defect spectrum. Major defect classes reported in the literature include geometrical distortions (macroscopic misalignment or unbonded side edges), surface irregularities (e.g. flash, roughness, wormhole marks), internal flaws (e.g. interlayer voids, tunnels and “kissing” bond cavities), and metallurgical anomalies (e.g. incomplete bonding or oxide entrapment between layers). The review critically examines these FSAM defects – discussing their root causes and how they are detected or characterized. Defect detection in FSAM relies on both destructive techniques (cross-sectional microscopy and mechanical testing) and nondestructive methods (including ultrasonic scanning and X-ray computed tomography). Recent studies highlight several mitigation strategies aimed at minimizing defect formation. These strategies include optimizing tool geometry, fine-tuning process parameters, and applying enhanced axial force or post-weld forging to improve material consolidation and structural integrity.

ABSTRACT. This talk explores the multi-faceted engineering challenges and opportunities defining the next generation of aerospace technology. We begin by examining the development of Advanced Systems, specifically focusing on integrated, AI-driven architectures for flight control, propulsion, and structural health monitoring. The discussion will highlight the critical shift from federated systems to highly interconnected, cyber-physical aircraft capable of unprecedented levels of autonomy and efficiency. Concurrently, achieving this technological leap requires a transformation in the human element. The session will detail how Adaptive Organizations—characterized by agile development, cross-disciplinary collaboration, and digital thread implementation—are essential for rapid innovation and certification in complex, safety-critical environments. Finally, we will look toward the New Frontier of Flight, analyzing emerging domains like Urban Air Mobility (UAM), high-speed hyper sonics, and the critical need for sustainable aviation practices. This includes novel propulsion methods, such as hybrid-electric systems, and material science breakthroughs. Attendees will gain a comprehensive understanding of the holistic engineering approach required, spanning technology, process, and regulation, to safely and effectively usher in a new era of aerospace dominance.