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This study used the Eulerian approach to investigate the effect of the type of gas on the depth of penetration and bubble distribution in a 2.5 × 0.3 × 5 m slag-fuming furnace without considering chemical reactions. The research compared the depth of penetration of air and hydrogen under similar injection conditions, specifically with a nozzle velocity (Vn) ranging from 10 to 110m/s and a temperature of 400 K, through a tuyere nozzle with a diameter (Dn) of 50 mm. The slag, a multicomponent liquid consisting of 12 components, is kept at a constant temperature (Ts) of 1,220 K. The gas-liquid interaction is simulated fortwo seconds using Star CCM+, employing the k -ϵ turbulence model and the S-Gamma model for the population model. Adaptive mesh refinement and adaptive time steps are utilised to accurately capture the liquid-gas interface and ensure convergence control. In the present study, while airflow carries coal particles, hydrogen flows as pure gas (without coal particles) through the nozzles (tuyere). Following thorough validation against experimental and numerical data, the study compared the Froude number for hydrogen and air in the specified range of Vn. The results indicate that the bubbles are concentrated within a range of 4.3 to 8.1 mm in front of the nozzle. Over time, the distribution of bubble sizes in the upward-moving zone expands. This expansion is likely due to the merging of bubbles, the increasing penetration depth, and the swelling velocity of the slag. 

Characterization of propeller blade vibrations is essential to ensure aerodynamic performance, minimize noise emissions, and maintain structural integrity in aerospace and unmanned aerial vehicle applications. Conventional high-fidelity finite-element and fluid-structure simulations yield precise modal predictions but incur prohibitive computational costs, limiting rapid design exploration. This paper introduces a data-driven surrogate modeling framework based on a feedforward neural network to predict natural vibration frequencies of propeller blades with high accuracy and a dramatically reduced runtime. A dataset of 1364 airfoil geometries was parameterized, meshed, and analyzed in ANSYS 2024 R2 across a range of rotational speeds and boundary conditions to generate modal responses. A TensorFlow/Keras model was trained and optimized via randomized search cross-validation over network depth, neuron counts, learning rate, batch size, and optimizer selection. The resulting surrogate achieves R-2>0.90 and NRMSE<0.08 for the second and higher-order modes, while reducing prediction time by several orders of magnitude compared to full finite-element workflows. The proposed approach seamlessly integrates with CAD/CAE pipelines and supports rapid, iterative optimization and real-time decision support in propeller design.

Aircraft electrification for propulsion is a promising way to alleviate the negative environmental impact of conventional carbon-powered aviation. Inclusion of the electrical powertrain aims to enhance design freedom, allowing for more efficient power systems and operational schemes. In this work, a design space exploration is performed, aiming to derive power management guidelines based on aircraft environmental performance. A 19-passenger commuter aircraft employing the series/parallel partial hybrid-electric architecture is examined. Two underwing-mounted turboprop engines are combined with a boundary layer ingestion fan mounted in the aft of the aircraft and powered by an electrical drive. The primary electrical energy source is a battery system. A multidisciplinary framework is utilized, comprising modeling approaches for multipoint thermal engine design, physics-based electrical component sizing and performance, aircraft sizing, mission design, and environmental assessment. The investigation revealed that the reference designed hybrid-electric configuration with entry-into-service (EIS) 2035 assumed technologies yields roughly 18% improvement in block consumption and emissions, but an 8% increase in maximum takeoff weight (MTOW), compared to its 2014 conventional counterpart. The design space exploration for an optimal power management scheme indicated a minimum average ratio of 1:1.35 between cruise and design point hybridization power. However, even the optimally operated hybrid aircraft showcases worse environmental performance compared to the conventional design of same entry-into-service date. The investigation has revealed that the complex powertrain and hybrid architecture selected may be more suitable for larger class aircraft, where aircraft requirements can be relaxed and higher degrees of electrification are not penalized or confined by set constraints.

Hybrid electric aviation is a possible step toward sustainable flight. Several hybrid architectures and synergetic concepts have been investigated. However, environmental performance results seem to be inconsistent due to deviations in technology assumptions and a mismatch between the fidelity of methodologies used for simulation of different aircraft systems. A multidisciplinary framework is developed, consisting of detailed modeling approaches for thermal and turbomachinery components, electrical power system design, aircraft/mission, and environmental analysis. The framework is employed for the investigation of an entry-into-service 2035 30 passenger commuter aircraft with a design mission of 1000 nautical miles. The investigation of parallel hybrid electric, turbo-electric, and series/parallel partial architectures is performed through a systematic conceptual design approach. The analysis reveals a bare minimum battery technology of 0.75 kWh/kg and 0.8 kW/kg, needed to compete with the conventional aircraft's performance. High degrees of hybridization (>20%) trigger the snowball effect of aircraft mass and thrust requirement, counteracting specific fuel and performance benefits generated by electrification. The turbo-electric and series/parallel partial concepts are paired with an electrically driven boundary layer ingestion fan. For those concepts to result in any block fuel and emissions benefits compared to conventional counterparts, a drag reduction from wake ingestion of 7.5–10% is required, with power split ratios between the electrically driven fan and propellers being limited to 15% due to extensive mass increase.

Turboprops offer a promising pathway for sustainable aviation, as they can achieve high levels of propulsive efficiency and reduced installed drag compared to high bypass ratio turbofans. Turboprop engine cores, though, are rarely designed from scratch; instead, they remain geometrically similar and can be used across several engine variants, which is known as the concept of growth engines or core commonality. This paper investigates the impact of core commonality on the installed performance of the next generation small-core turboprops. First, a turboprop cycle design optimization is carried out based on a multipoint synthesis approach for 2035 entry into service assumptions. The propeller, nozzle, and engine core are individually designed and analyzed. Preliminary design studies of the core compressor are performed using a 2D streamline curvature algorithm, providing insights into the aerodynamic tradeoffs of highly loaded all-axial multistage compressors. The second part of this study examines the performance of growth engine variants by applying the common-core approach to the designed 2035 baseline turboprop engine. In this context, “growth” refers to increasing equivalent shaft power to meet the thrust demands of a derivative aircraft designed for higher passenger capacity and/or extended range. A common-core design methodology is developed and proposed, enabling power growth through zero-staging of the core compressor and power off-take from the free-power turbine to drive electric motors, which in turn power additional e-propellers in electrified turboprop variants. Three optimal growth engine designs are identified, achieving up to 34.8% power growth relative to the baseline turboprop while maintaining design constraints, including high-pressure spool overspeed limits, a fixed propeller design, and considerations for cooled or uncooled free-power turbines. Overall, this study systematically analyzes the common-core concept, reflecting the approach followed by engine manufacturers over the years. Copyright © 2026 by ASME.

Aviation plays a fundamental and valuable role in the modern world, yet it faces significant challenges, including high fuel costs and substantial environmental pollution. These issues have prompted the aviation industry to establish emission standards and develop less-polluting propulsion systems, such as those utilizing synthetic fuels, fuel cells, and electrification. Among these, electrification holds promise as a potential solution for reducing emissions in commuter aircraft, despite the mass limitations posed by batteries. In this study, a methodology was developed and implemented within in-house software to simulate the performance of a commuter aircraft with a hybrid-electric propulsion system. The analysis focused on key metrics like fuel economy and climb time to cruise altitude. The EMB-120 Brasilia was chosen as the base aircraft for this research. Its long-standing use by the Brazilian Air Force (FAB), the authors' extensive familiarity with its performance, and the availability of experimental data for lift and drag coefficients made it an ideal model for our simulations. To evaluate the performance of the hybrid propulsion system and compare it with the standard case, a gas turbine was utilized as the primary engine. Mathematical models were developed for the PW118 gas turbine, which powers the real aircraft that was considered the standard case, and for the PT6A-68C, which was suggested as a substitute for the hybrid system. To evaluate the aircraft's performance, a standard mission was simulated on a short-range route of 926 km (500 NM), flying at an altitude of 7,620 m (25,000 ft), a common mission that is used by Brazilian Air Force. For hybrid simulations, battery packs were tested with specific energies ranging from 0.125 kWh/kg to 0.750 kWh/kg, in multiples of the initial value. Batteries with 0.250 kWh/kg were considered the current state-of-the-art, while the 0.750 kWh/kg packs represent an extreme upper bound associated with far-future technological developments. The results demonstrated significant performance gains depending on the chosen battery technology and the power split, the hybrid system achieved fuel savings of up to 18% to 19% and reduced climb time by 17% to 25%. © 1965-2011 IEEE.

In industrial machine learning, predictive performance alone is insufficient to ensure reliable deployment, as model behaviour may vary across different regions of the input space under limited data and evolving process conditions. This work investigates whether such variation can be systematically analysed through post-hoc methods. A model-agnostic framework is proposed in which interpretability metrics, including residuals and feature attributions, are embedded into a low-dimensional space and approximated using a continuous surrogate model. This representation enables the analysis of model behaviour as a structured landscape, rather than as isolated pointwise explanations. The approach is applied to ceramic heating element production, where two distinct regimes are identified. One corresponds to a stable region with consistent and accurate predictions, while the other reflects a transitional regime associated with increased ambiguity and sensitivity to feature interactions. These regimes are shown to align with known process conditions and temporal variation. The results demonstrate that model behaviour can be organised into coherent regions that are not observable through aggregate performance metrics alone. This provides a structured basis for post-hoc analysis, supporting targeted interpretation and further investigation of model reliability in industrial settings.

The flue gas associated with hydrogen fueled gas turbines has enhanced steam content and different thermophysical properties as compared to that of natural gas fuel case. The enhanced steam might lead to a rigorous corrosion degradation in the hot gas path components of the gas turbines such as turbine blades. In addition to this, high heat transfer rate can contribute to erosion, thermal fatigue, and creep damages. Hydrogen fueled gas turbines are also susceptible to some common routine faults such as fouling in the compressor section. Consequently, the health and performance of a hydrogen fueled gas turbines are degraded. Therefore, health monitoring in terms of remaining useful life (RUL) estimation of such turbines is of greater interest for the gas turbines OEMs and operators to ensure an enhanced availability and reliability in line with industry 4.0. The current study, therefore, develops a performance-based RUL estimation model for a 100-kW micro gas turbine that was recently retrofitted with hydrogen compliant FLOX burner. The validated performance model was further utilized for synthesizing run to failure data for fault diagnosis and RUL estimation. The study further incorporated linear and polynomial regression approaches and compared the end of life of gas turbines running on natural gas and hydrogen fuels. It became evident from the study that RUL of a gas turbine running on hydrogen fuel is approximately 6.47% lower than that of natural gas fueled gas turbines. These findings underline the necessity of using strong prediction models, as well as targeted maintenance actions, to limit the consequences of turbine corrosion in hydrogen powered micro gas turbines. The findings of the present study further provide new horizons for design modification and effective health monitoring of hydrogen fueled gas turbines.

In manufacturing, and particularly in manually driven processes, diagnostics and decision support tools that utilize data-driven methods are key factors for reliable production processes. The investment casting manufacturing process relies on quality assessment through microscope examinations of cross-sections (cutups) of produced pieces, traditionally depending on operator judgment to manually approve or reject parts, which may introduce bias. This work focuses on identifying and addressing the need for reliability and efficiency in the investment casting manufacturing process by proposing a decision support tool to assist the operator in defect detection and fault identification in a semi-automated way. Initially, we explore the machine learning classifier Random Forest and then propose the use of a convolutional neural network, a deep learning method, for improving binary classification accuracy when predicting the presence of a defect in a microscope-derived image. The model presents classification accuracy between faulty and non-faulty images at 98% as a key finding and also tested on new, never-before-seen images from the production process. The results demonstrate the transformative potential of introducing data-driven methods such as convolutional neural networks into manual manufacturing processes, paving the path for more reliable production methods in the investment casting manufacturing industry.

The aviation industry faces significant environmental challenges, prompting the implementation of regulations to mitigate the adverse effect of carbon-based energy and associated emissions. While electrified flight is a promising pathway, limitations in specific energy density of batteries narrow down the application space to commuter and regional classes. Towards that direction, this work investigates the design and operation of a series hybrid electric 30-passenger regional aircraft. A multi-disciplinary framework is utilized, comprising modelling approaches for multi-point thermal engine design, physics-based electrical component sizing and performance, aircraft sizing, mission design, and environmental assessment. Distributed propulsion with up to three propellers per wing is evaluated for aerodynamic benefits. With optimal wing redesign, drag reduction benefits only reach 1% for the selected aircraft class and flight velocities. Variable free power turbine speed operation is promising in reducing engine mass and improving performance of both thermal and electrical power systems. A combination of hybridization during take-off, climb and cruise defines the optimal design and operation guidelines for the hybrid concept. However, due to the increased mass of the battery and electrical power system, block fuel benefits only in the order of 5% are reported, compared to a turboelectric aircraft. When compared with a conventional configuration of same entry-into-service year, the series concept is outperformed in the examined range of battery assumed technologies.