Search Results (822)

The development of modern production systems involves numerous interdependent disciplines, heterogeneous data sources, and frequent design iterations, making the conceptual design phase particularly complex and error-prone. Model-Based Systems Engineering (MBSE) provides a promising approach to manage this complexity by enabling consistent and structured system representations. While domain-specific modeling languages (DSMLs) can tailor MBSE methods to specific domains, existing approaches often lack standardized semantics, user guidance, and tool support to ensure consistent model creation and verification. This paper introduces a DSML framework tailored for the conceptual design of production systems, integrating both methodological guidance and standard-based domain knowledge. The approach builds upon the Software Platform Embedded Systems (SPES) framework and extends Systems Modeling Language (SysML) through the Unified Modeling Language (UML) profile mechanism, providing clear modeling constructs, viewpoint-specific diagram types, and automated consistency checks. To enhance comprehensibility and domain alignment, the framework incorporates supplementary DSMLs that capture structures and semantics from established industrial standards. The proposed method is evaluated using an aircraft production case study, demonstrating improved applicability of MBSE for the conceptual design of complex production systems. Full article

Delays during turnaround operations are a significant source of operational inefficiency for airlines. They reduce airline profit margins by resulting in rescheduled flights and missed connections for passengers. This research paper presents the findings of an approach developed within the INTACT research project (subsequently called “the INTACT system”). The INTACT system aims to achieve reduced delays during turnaround operations and therefore increase their operational efficiency by introducing new technologies. A simulation study, including 350 simulated days, was conducted to assess the impact of three of INTACT’s abilities: (1) the localization of wheelchairs for passengers, (2) the assessment of what trolleys are onboard and how many trolley items are needed, and (3) visual observations of cabin failures and communication back to the destination airport. Results show that the implementation of these technologies leads to a statistically significant average delay reduction of 3 min per turnaround. Under the modeled schedule constraints in the discrete-event simulation, this reduction shifts the distribution of feasible daily flight counts, resulting in an average increase of 0.11 flights/day (38 additional completed flights over 350 simulated days) relative to the full-delay scenario. In addition, the cost–benefit analysis shows that the INTACT system saves an average of $966.95 in turnaround costs and gains $2714.29 in additional revenue per day and per aircraft. With estimated initial investment costs of around 2 million dollars, the payback period is only 1.5 years. During this study, gross additional revenue was reported as an upper-bound estimate; net operational benefit depends on airline-specific variable operating costs. The INTACT system can help to improve turnaround operation issues while providing positive economic performance for stakeholders in the industry. Full article

Edge cracking severely limits the rolling yield of magnesium alloy plates. A novel lattice severe deformation rolling (LSDR) process using corrugated rolls is proposed to suppress edge cracking. Numerical simulations, rolling experiments, and microstructural analyses were conducted, with results compared to conventional flat rolling (FR), to elucidate the suppression mechanism. LSDR induces a multi-peak stress distribution and restricts metal flow, thereby reducing additional stresses responsible for edge cracking. Deformation heat generated in local severe deformation zones compensates for thermal loss, alleviates the temperature gradient between the plate edge and center, and enhances overall plasticity. According to the Cockcroft–Latham fracture criterion, LSDR effectively limits damage growth and confines damage within a single lattice, suppressing crack propagation, whereas FR produces damage values far exceeding the critical value of 0.43. Furthermore, fine grains formed in severe deformation zones, together with dislocation entanglement induced by twinning, impede crack propagation. This work demonstrates the effectiveness of LSDR and provides a new approach for mitigating edge cracking in rolled metal plates. Full article

Unlike typical fiber-reinforced polymers, aerospace composites consist of 90% carbon and 10% glass fabrics impregnated with thermosetting resin. Due to the strong bonding between fibers and the thermoset nature of the matrix, recycling these materials is particularly challenging. This study evaluates mechanical recycling of aircraft composite waste via industrial grinding and chemical recycling through a solvolysis process. Recovered fibrous fractions were integrated into an epoxy matrix at 50 wt% loading using hot-pressing and into polyamide 12 at 15 wt% via a twin-screw extrusion process. The mechanical results showed that chemically recycled fibers in epoxy reached a flexural modulus of 9.9 GPa and strength of 112 MPa, significantly outperforming mechanically recycled fillers (6.1 GPa and 98.0 MPa) compared to virgin carbon fibers (11.3 GPa and 132 MPa). In PA12, the addition of chemically recycled fibers yielded a 2.14 GPa modulus and a 67.7 MPa strength. Furthermore, life cycle assessment confirmed that both recycling routes drastically reduce global warming potential and aquatic ecotoxicity compared to landfilling. These findings indicate that while mechanical recycling is simpler, chemical solvolysis provides a superior pathway for the high-value circular reuse of complex aerospace waste in new thermoplastic and thermoset applications. Full article

In response to the complexity and uncertainty in assessing the safety and economic impacts of the Changed Product Rule (CPR) in civil aviation products’ airworthiness certification, this paper constructs a comprehensive evaluation model based on a cost–benefit analysis framework. In previous research, studies on aircraft modification costs have consistently been conducted from the perspective of design organizations, focusing on modeling and optimizing the one-time engineering costs of the modifications themselves or remaining confined to the level of safety performance without addressing the calculation of economic value. The model proposed in this paper considers the entire aircraft service lifecycle and uniformly quantifies potential impacts into monetary terms for comparison. The model encompasses safety improvements, cost estimation, and discounted cash flow analysis, aiming to provide decision-makers with quantitative tools for determining the applicability of the “impracticality exception” standard. This ensures that modifications to aviation products balance safety with economic viability. Through case studies involving fuel tank access panel design changes and Auxiliary Power Unit (APU) inlet duct fire protection requirements, the effectiveness and practicality of the model are validated, offering an empirical foundation for future policy formulation and industry regulation. Nevertheless, the parameters in the model depend on historical data, and appropriate parameters must be carefully selected. Although the model has taken into account the entire lifecycle of the aircraft, it is still based on static assumptions and fails to consider the impact of the rapid development of the aviation industry over time. Ongoing model refinement, international data collection, and integration of non-economic factors remain key directions for future research. Full article

This paper introduces an iceberg-based digital risk twin (DRT) framework for the health monitoring of complex engineering systems. The proposed model transforms multidimensional sensor and contextual data into a structured, interpretable three-dimensional geometry that captures both observable and latent risk components. Each monitored parameter is represented as a vertical geometric sheet whose height encodes a normalized risk level, producing an evolving iceberg structure in which the visible and submerged regions distinguish emergent anomalies from latent degradation. A formal mathematical formulation is developed, defining the mappings from the risk vector to geometric height functions, spatial layout, and surface composition. The resulting parametric representation provides both analytical tractability and intuitive visualization. A case study involving an aircraft fuel system demonstrates the capacity of the DRT to reveal dominant risk drivers, parameter asymmetries, and temporal trends not easily observable in traditional time-series analysis. The model is shown to integrate naturally into AI-enabled health management pipelines, providing an interpretable intermediary layer between raw data streams and advanced diagnostic or predictive algorithms. Owing to its modular structure and domain-agnostic formulation, the DRT approach is applicable beyond aviation, including power grids, rail systems, and industrial equipment monitoring. The results indicate that the iceberg representation offers a promising foundation for enhancing explainability, situational awareness, and decision support in the monitoring of complex engineering systems. Full article

To address the limitations of traditional aircraft skin inspection, the aviation industry and academia have increasingly been exploring the integration of computer vision technologies into the defect detection process. These implementations of computer vision technologies rely on the performance of underlying neural network models, whose effectiveness is highly influenced by their hyperparameter configuration. To obtain optimum hyperparameters, an optimization procedure is often employed to optimize a certain combination of the model’s performance metrics. However, in the aircraft skin defect detection domain, studies to inspect the effect of different emphases in the performance metrics considered in this objective function are still not widely available. In this paper, we present our early observations regarding the influence of different performance metrics’ emphases during the hyperparameter tuning process on the overall performance of a computer vision model employed for aircraft skin defect detection. In this preliminary inspection, we consider the utilization of YOLOv12 and the Bayesian Optimization approach for the defect detection model and hyperparameter optimizer, respectively. We highlight the possible performance degradation of the model after a hyperparameter tuning procedure when the weight factor distribution of the performance metrics is not carefully considered. We note several weight factors of interest that could serve as initial possible “safe spots” for further exploration. Full article

During liquid drainage from intermediate vessels in various industrial processes such as continuous steel casting, aircraft fuel supply, and chemical separation, free-surface vortices commonly occur. The formation and evolution of these vortices not only entrain surface slag and gas, but also lead to deterioration of downstream product quality and abnormal equipment operation. The vortex evolution process exhibits notable three-dimensional unsteadiness, multi-scale turbulence, and dynamic gas–liquid interfacial changes, accompanied by strong coupling effects between temperature gradients and flow field structures. Traditional macroscopic numerical models show clear limitations in accurately capturing these complex physical mechanisms. To address these challenges, this study developed a mesoscopic numerical model for gas-liquid two-phase vortex flow based on the lattice Boltzmann method. The model systematically reveals the dynamic behavior during vortex evolution and the multi-field coupling mechanism with the temperature field while providing an in-depth analysis of how initial perturbation velocity regulates vortex intensity and stability. The results indicate that vortex evolution begins near the bottom drain outlet, with the tangential velocity distribution conforming to the theoretical Rankine vortex model. The vortex core velocity during the critical penetration stage is significantly higher than that during the initial depression stage. An increase in the initial perturbation velocity not only enhances vortex intensity and induces low-frequency oscillations of the vortex core but also markedly promotes the global convective heat transfer process. With regard to the temperature field, an increase in fluid temperature reduces the viscosity coefficient, thereby weakening viscous dissipation effects, which accelerates vortex development and prolongs drainage time. Meanwhile, the vortex structure—through the induction of Taylor vortices and a spiral pumping effect—drives shear mixing and radial thermal diffusion between fluid regions at different temperatures, leading to dynamic reconstruction and homogenization of the temperature field. The outcomes of this study not only provide a solid theoretical foundation for understanding the generation, evolution, and heat transfer mechanisms of vortices under industrial thermal conditions, but also offer clear engineering guidance for practical production-enabling optimized operational parameters to suppress vortices and enhance drainage efficiency. Full article

Most aircraft skin components are typical sheet metal components, and stretch forming serves as the primary forming process. The die face is the core foundation for both the finite element simulation and mold trial. Due to the intricate geometric characteristics of aircraft skin components and iterative revisions caused by stretch forming process adjustments and product design changes, the die face design of aircraft skin components is inherently time-intensive, highly complex, and prone to instability. To address these issues, a Hierarchical and Hybrid Association Method (HHAM) based on a robust updating mechanism and hybrid associations is proposed for the intelligent design system. HHAM can significantly enhance the stability and efficiency of die face design. Specifically, the hierarchical and automatic updating process of HHAM, incorporating robust error handling mechanisms, is the core methodology that guarantees the stability of complex and iterative die face design for aircraft skin. Moreover, the inter-module hybrid association, which integrates parametric modeling and automatic connection techniques, eliminates the instability in die face design updating caused by feature and topology variations. Additionally, robust geometric algorithms for wireframe modeling effectively improve the surface quality and generation success rate of the die face. The intelligent design system developed based on the CATIA platform has been successfully applied in two professional aircraft skin component manufacturing enterprises. Case studies and industrial application practices verify the effectiveness of the proposed system, achieving a 72.7% improvement in design efficiency and a 70.27% reduction in the risk of die face update errors. Full article

Research into Remotely Piloted Aircraft Systems (RPASs) has expanded rapidly, yet the competencies, knowledge, skills, and other attributes (KSaOs) required of RPAS pilots remain comparatively underexamined. This review consolidates existing studies addressing human performance, subject matter expertise, training practices, and accident causation to provide a comprehensive account of the KSaOs underpinning safe civilian and commercial drone operations. Prior research demonstrates that early work drew heavily on military contexts, which may not generalize to contemporary civilian operations characterized by smaller platforms, single-pilot tasks, and diverse industry applications. Studies employing subject matter experts highlight cognitive demands in areas such as situational awareness, workload management, planning, fatigue recognition, perceptual acuity, and decision-making. Accident analyses, predominantly using the human factors accident classification system and related taxonomies, show that skill errors and preconditions for unsafe acts are the most frequent contributors to RPAS occurrences, with limited evidence of higher-level latent organizational factors in civilian contexts. Emerging research emphasizes that RPAS pilots increasingly perform data-collection tasks integral to professional workflows, requiring competencies beyond aircraft handling alone. The review identifies significant gaps in training specificity, selection processes, and taxonomy suitability, indicating opportunities for future research to refine RPAS competency frameworks and support improved operational safety. Full article

Cavitation in aircraft hydraulic systems continues to pose a serious problem for the aviation industry. This paper presents a new study on cavitation in aviation hydraulic fluid AMG-10 at its inception condition, corresponding to a relative pressure drop of Δp = 0.58, within a small-scale rectangular throttle channel of specified dimensions. Numerical simulations were performed in a quasi-steady-state framework using the realizable k–ε turbulence model combined with the Enhanced Wall Treatment approach, and the results were validated against time-integrated experimental data obtained via the shadowgraphy method. Cavitation was modeled using the Zwart–Gerber–Belamri model. The validated numerical model, which showed a pressure deviation of less than 10% from experimental data on the upper and lower walls, also demonstrated good agreement in the dimensions of the cavitation regions, confirming that the upper region is consistently larger than the lower one. Quantitative analysis demonstrated that regions with high vapor concentration are highly localized, representing only 0.048% of the channel volume at a 0.8 vapor fraction threshold. The analysis reveals that the cavitation regions spatially coincide with local pressure drops to values as low as 214 and 236 Pa near the upper and lower walls. These regions are also associated with wall jets, accelerated by the flow constriction to velocities up to 41.98 m/s. Furthermore, the cavitation region corresponds to a distinct peak in the mean turbulent kinetic energy field, reaching 164.5 m²/s², which decays downstream. Full article

Technological innovation in commercial Remotely Piloted Aircraft Systems (RPASs) is advancing rapidly. However, their operational efficiency remains limited by the need for on-site skilled human operators. Semi-autonomous drone-in-a-box (DIAB) systems are emerging as a practical solution, enabling automated, repeatable missions for applications such as construction site monitoring, security, and critical infrastructure inspection. Beyond industry, these systems hold significant promise for scientific research, particularly in long-term environmental monitoring where cost, accessibility, and safety are critical factors. In this technology demonstration, we detail the system implementation, discuss flight-planning challenges, and assess the overall feasibility of deploying a DJI Dock 2 DIAB system for remote monitoring of the Miles Ridge landslide in the Yukon Territory, Canada. The system was installed approximately 2.5 km from the landslide and operated remotely from across the country in Montreal, QC, about 4000 km away. A total of five datasets were acquired from July to September 2025, enabling three-dimensional reconstruction of the landslide surface from each acquisition. A comparison of extracted cross-sections demonstrated high reproducibility and accurate co-registration across acquisitions. This study highlights the potential of DIAB systems to support reliable, low-maintenance monitoring of remote landslides. Full article

This study investigates the environmental and economic dynamics of sustainable aviation through the perspectives of senior executives in Türkiye’s civil aviation sector. As global aviation continues to face increasing pressure to decarbonize, understanding how industry leaders perceive and respond to carbon emission challenges is critical. The research employs a qualitative methodology based on semi-structured interviews with ten executives across airlines, airports, and aviation authorities. Using Python-based data mining techniques and thematic analysis, three core themes emerged: (1) sustainable aviation experience and economic dimensions; (2) carbon emissions reduction and efficient aviation systems; (3) sustainable energy and alternative fuel technologies. Findings reveal that while environmental sustainability is a growing concern, operational costs, technological constraints, and regulatory uncertainties significantly influence implementation. Stakeholders emphasized the importance of coordinated action among governments, industry, and international organizations, especially in scaling Sustainable Aviation Fuels (SAFs) and enhancing infrastructure for electric and hydrogen-powered aircraft. The study concludes that achieving net-zero aviation by 2050 requires an integrated approach that balances technological innovation, policy incentives, and stakeholder engagement. This multidimensional insight contributes to the ongoing discourse on low-carbon transition strategies in aviation, offering policy-relevant implications for developing countries. Full article

Worldwide, carbon fiber (CF) demand has been rising over the last decade, which contrasts with the fact that up to 30–50% of composite materials in aircraft production are scrapped. This situation highlights the increasing need for recycling methods to reduce fabrication costs and global warming potential. Emerging technologies focus on recovering long CFs, as they represent the most valuable form but are also the most difficult to reclaim using conventional recycling methods. Hydrothermal treatments offer a promising alternative to valorize this waste by decomposing the polymer matrix under subcritical and supercritical conditions without significantly damaging the fibers. Water, isopropanol, and mixtures of water/isopropanol or water/acetone were tested as solvents, with and without the addition of zinc chloride (ZnCl₂) as a homogeneous catalyst. The influence of temperature, pressure, and solvent composition on resin degradation was evaluated. In this work, degradation rates of up to 92% were achieved at 415 °C, 233 bar, 120 min, 5 wt.% IPA, and ZnCl₂ 0.1 M. It should be noted that ZnCl₂ caused reactor corrosion. Furthermore, the recovered fibers retained their morphology, including the sizing layer, and showed mechanical properties similar to the original material, while a small H₂-rich gaseous fraction was generated as a byproduct of the hydrothermal degradation. Using water–isopropanol solutions resulted in the reactor being significantly cleaner than when using water alone, which can be advantageous for future scale-up and for reducing maintenance requirements. These results confirm the potential of hydrothermal processing as an efficient and selective method for the recycling and valorization of carbon-fiber-reinforced composites from the aeronautical industry. Full article

Frequency-modulated continuous-wave (FMCW) light detection and ranging (LiDAR) is a high-precision ranging and imaging system that has been widely used in various areas, such as self-driving vehicles and industrial inspection. However, during detection, the system is susceptible to noise interference. This interference results in a decrease in the signal-to-noise ratio (SNR) of mixed signals, which affects the ranging accuracy. In this study, a MATLAB r2021b simulation is used to generate LiDAR transmitted and echo signals, and Gaussian noise is introduced. After mixing, empirical mode decomposition (EMD) and wavelet transform (WT) are used to denoise mixed signals, and the denoising effects of different wavelet basis functions under different SNRs are analysed. Furthermore, an experimental FMCW LiDAR system is set up to collect practical target echo signals, and the simulation results are validated through experiments under various illumination conditions. The results also show that the noise in FMCW LiDAR signals is dominated by Gaussian noise and that the influence of environmental noise is minimal. The combined EMD-WT denoising algorithm and its wavelet basis optimisation strategy proposed in this study can be directly applied to practical scenarios with strict requirements for FMCW LiDAR signal quality, such as autonomous driving, aircraft navigation, and precision industrial measurement, providing theoretical basis and experimental support for wavelet basis selection and denoising strategies in different noise environments. Full article