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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

ABSTRACT. Aircraft wings are traditionally designed for optimal performance within a narrow flight regime, resulting in aerodynamic inefficiencies under off-design conditions. Morphing wing technology offers a transformative approach by enabling dynamic shape adaptation during flight, thereby improving aerodynamic efficiency, fuel economy, and operational versatility. The increasing demand for enhanced aircraft performance and fuel efficiency has motivated the exploration of advanced morphing wing technologies. This paper reviews disruptive morphing wing topologies that offer significant deviations from conventional designs, enabling unprecedented aerodynamic performance. The review identifies a gap in the comprehensive analysis of novel morphing concepts, focusing on their potential for radical performance improvements. A systematic literature review was conducted, analyzing studies on unconventional morphing wing designs, actuation mechanisms, and control strategies. The main finding is that several disruptive topologies, such as continuous span morphing and 3D wing shape adaptation, demonstrate the potential for substantial aerodynamic benefits, including lift enhancement, drag reduction, and improved maneuverability. The principal conclusion is that these advanced morphing wing concepts hold promise for future aircraft designs, offering the potential to overcome the limitations of traditional fixed-wing configurations.

ABSTRACT. Accurate prediction of high-Reynolds-number wall-bounded turbulent flows is essential for the understanding and flow control of many engineering applications such as aircraft, turbomachinery, and marine vehicles. Additionally, most practical flows exhibit nonequilibrium effects such as pressure gradient, flow separation, and mean three-dimensionality. However, the direct numerical simulation (DNS) of high-Reynolds-number wall-bounded turbulent flows is not feasible owing to the prohibitive computational cost of resolving small-scale eddies near the wall. Wall-modeled large-eddy simulation (WMLES) presents an affordable predictive alternative to the DNS via the approximate modeling of flow physics near the wall (through a wall model) while resolving the outer scales directly on the computational grid. In this work, we focus on two aspects of wall models: (i) development and implementation of new/existing wall models, and (ii) application and comparison of different wall models in various nonequilibrium turbulent boundary layers. In the first part, we develop a novel spectral formulation for the ODE equilibrium wall model, showing its superior efficiency to the traditional approach. Furthermore, we extend the integral nonequilibrium wall model to an unstructured grid LES solver. In the second part, we explore three wall models with varying degrees of computational complexity and physical fidelity, to assess their performance in two controlled but reasonably realistic nonequilibrium flows over a flat plate. The first flow features a turbulent boundary layer undergoing a series of complex pressure gradient effects, while the second exhibits turbulent flow separation induced by suction and blowing. In the latter case, the more complex model clearly exhibits superior wall shear stress predictions. However, the same is not necessarily true in the former case, highlighting the need to adapt the existing wall models to different flow physics by modifying their underlying formulation or assumptions. Finally, a physic-based decomposition of skin friction, that shows separable contributions from various physical processes in the flow, is employed to explain the differing mechanisms of success/failure of wall models in different flows.

ABSTRACT. As global industries increasingly prioritize sustainability and performance, the development of advanced surface coatings plays a vital role in achieving greener and more efficient systems. This keynote introduces a novel approach through Liquid Additive Manufacturing (LAM) using hybrid materials derived from renewable resources. Specifically, the focus is on hybrid coatings composed of environmentally friendly silicon carbide (eSiC) extracted from rice husk waste, combined with graphene oxide (GO), applied onto titanium alloy material. This hybrid coating not only offers superior tribo-mechanical properties—such as high hardness, wear resistance, and reduced friction, but also addresses circular economy principles by recycling agricultural waste. The LAM approach, with its lower energy and equipment costs compared to conventional methods like CVD or PVD, provides a scalable, industry-friendly solution. This talk will highlight the promise of LAM, development of GO-eSiC hybrid coatings, material performance, and real-world applicability of this coating technology.

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

ABSTRACT. In 2022, the department introduced structured formative assessments into the Engineering Mathematics module to enhance student learning and exam readiness. Early implementation showed promising improvements in student engagement and performance. However, subsequent misuse of artificial intelligence (AI) platforms by students to complete these assessments raised concerns about authenticity and the actual learning achieved. This study explores the correlation between formative assessment scores and summative exam performance, focusing on the impact of AI use. Results reveal a growing discrepancy between formative success and summative outcomes, highlighting the urgent need to re-evaluate assessment strategies in technology-rich learning environments.

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

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

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

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

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

ABSTRACT. The Ahmed body, a widely used simplified vehicle model, forms the basis of this study, which systematically compares the aerodynamic performance of vertically mounted rigid and flexible rear flaps using computational fluid dynamics. The analysis examines drag reduction capability, flap deflection, wake suppression, and stress distribution on flexible flaps. Flap lengths of 0.1H, 0.2H, and 0.46H (H: frontal height of the Ahmed body) are investigated. For rigid flaps, the 0.46H configuration matches the experimental result. The flow control reduced drag by 3.8%, while the 0.1H flap, unique to this study, achieved a greater reduction of 9.9%. The 0.2H flap showed no benefit. In contrast, flexible flaps did not yield drag reduction, highlighting the significance of adding reinforcing cylinders to improve stiffness and performance.

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

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

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

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

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