Search Results (80)

The Kuroshio Current’s flow velocity imposes exacting requirements on underwater vehicle propulsive systems. Ecological preservation necessitates low-noise propeller designs to mitigate operational disturbances. As technological evolution advances toward greater intelligence and system integration, intelligent unmanned systems are positioning themselves as a critical frontier in marine innovation. In recent years, the global research community has increased its efforts towards the development of high-maneuverability underwater vehicles. However, propeller design optimization ignores the key balance between acoustic performance and hydrodynamic efficiency, as well as the appropriate speed threshold for blade rotation. In order to solve this problem, the propeller design of the NACA 65A010 airfoil is optimized by using OpenProp v3.3.4 and XFlow 2022 software, aiming at innovating the propulsion system of shallow water agile submersibles. The study presents an integrated design framework combining lattice Boltzmann method (LBM) simulations synergized with fully Lagrangian-LES modeling, implementing rotational speed thresholds to detect cavitation inception, followed by advanced acoustic propagation analysis. Through rigorous comparative assessment of hydrodynamic metrics, we establish an optimization protocol for propeller selection tailored to littoral zone operational demands. Studies have shown that increasing the number of propeller blades can reduce the single-blade load and delay cavitation, but too many blades will aggravate the complexity of the flow field, resulting in reduced efficiency and noise rebound. It is concluded that the propeller with five blades, a diameter of 234 mm, and a speed of 500 RPM exhibits the best performance. Under these conditions, the water efficiency is 69.01%, and the noise is the lowest, which basically realizes the balance between hydrodynamic efficiency and acoustic performance. This paradigm-shifting research carries substantial implications for next-generation marine vehicles, particularly in optimizing operational stealth and energy efficiency through intelligent propulsion architecture. Full article

The aerodynamic optimization of airfoil shapes remains a critical research area for enhancing aircraft performance under various flight conditions. In this study, the RAE 2822 airfoil was selected as a benchmark case to investigate and compare the effectiveness of surrogate-based methods under an Efficient Global Optimization (EGO) framework and an adjoint-based approach in both single-point and multi-point optimization settings. Prior to optimization, the computational fluid dynamics (CFD) model was validated against experimental data to ensure accuracy. For the surrogate-based methods, Kriging (KRG), Kriging with Partial Least Squares (KPLS), Gradient-Enhanced Kriging (GEK), and Gradient-Enhanced Kriging with Partial Least Squares (GEKPLS) were employed. In the single-point optimization, the GEK method achieved the highest drag reduction, outperforming other approaches, while in the multi-point case, GEKPLS provided the best overall improvement. Detailed comparisons were made against existing literature results, with the proposed methods showing competitive and superior performance, particularly in viscous, transonic conditions. The results underline the importance of incorporating gradient information into surrogate models for achieving high-fidelity aerodynamic optimizations. The study demonstrates that surrogate-based methods, especially those enriched with gradient information, can effectively match or exceed the performance of gradient-based adjoint methods within reasonable computational costs. Full article

Reliable aerodynamic performance estimation is essential for both preliminary design and optimization in various aeronautical applications. In this study, a hybrid deep learning model is proposed, combining convolutional neural networks (CNNs) and operating directly on raw airfoil geometry, with parallel branches of fully connected deep neural networks (DNNs) that process operational parameters and engineered features. The model is trained on an extensive database of NACA four-digit airfoils, covering angles of attack ranging from −5° to 14° and ten Reynolds numbers increasing in steps of 500,000 from 500,000 up to 5,000,000. As a novel contribution, this work investigates the impact of random seed initialization on model accuracy and reproducibility and introduces a seed-based ensemble strategy to enhance generalization. The best-performing single-seed model tested (seed 0) achieves a mean absolute percentage error (MAPE) of 1.1% with an ${\mathrm{R}}^2$ of 0.9998 for the lift coefficient prediction and 0.57% with an ${\mathrm{R}}^2$ of 0.9954 for the drag coefficient prediction. In comparison, the best ensemble model tested (seeds 610, 987, and 75025) achieves a lift coefficient MAPE of 1.43%, corresponding to ${\mathrm{R}}^2$ 0.9999, and a drag coefficient MAPE of 1.19%, corresponding to ${\mathrm{R}}^2$ = 0.9968. All the tested seed dependencies in this paper (ten single seeds and five ensembles) demonstrate an overall ${\mathrm{R}}^2$ greater than 0.97, which reflects the model architecture’s strong foundation. The novelty of this study lies in the demonstration that the same machine learning model, trained on identical data and architecture, can exhibit up to 250% variation in prediction error solely due to differences in random seed selection. This finding highlights the often-overlooked impact of seed initialization on model performance and highlights the necessity of treating seed choice as an active design parameter in ML aerodynamic predictions. Full article

This paper presents the design, fabrication, simulation, and partial validation of a low-cost, fixed-wing unmanned glider equipped for temperature and image monitoring. Aerodynamic optimization was performed using XFLR5 and ANSYS Fluent 2023 R1, with spanwise variation between NACA 63(3)-618 and NACA 4415 to enhance performance. Wind tunnel tests of the selected airfoil showed good agreement with CFD predictions, with deviations within 5–10%. The airframe, fabricated using 3D-printed PLA with a cross-lattice structure, was integrated with an ESP32-CAM and temperature sensor. A reflective thermal coating was applied to mitigate the heat sensitivity of PLA. Propeller-induced flow was analyzed separately using the lattice Boltzmann method. Real-time flight behavior was simulated in a virtual environment via Simulink and FlightGear. While full in-flight testing is pending, the results demonstrate a scalable, open-source UAV platform for environmental monitoring and academic research. Full article

The computational complexity of airfoil optimization for aircraft wing designs typically involves high-dimensional parameter spaces defined by geometric variables, where each Computational Fluid Dynamics (CFD) simulation cycle may require significant processing resources. Therefore, performing variable selection to identify influential inputs becomes crucial for minimizing the number of necessary model evaluations, particularly when dealing with complex systems exhibiting nonlinear and poorly understood input–output relationships. As a result, it is desirable to use fewer samples to determine the influential inputs to achieve a simple, more efficient optimization process. This article provides a systematic, novel approach to solving aircraft optimization problems. Initially, a Kriging-based variable screening method (KRG-VSM) is proposed to determine the active inputs using a ikelihood-based screening method, and new stopping criteria for KRG-VSM are proposed and discussed. A genetic algorithm (GA) is employed to achieve the global optimum of the log-likelihood function. Subsequently, the airfoil optimization is conducted using the identified active design variables. According to the results, the Kriging-based variable screening method could select all the active inputs with a few samples. The Kriging-based variable screening method is then tested on the numerical benchmarks and applied to the airfoil aerodynamic optimization problem. Applying the variables screening technique can enhance the efficiency of the airfoil optimization process under acceptable accuracy. Full article

As a novel energy-saving and maneuvering device for ships, the gate rudder system (GRS) functions similarly to an accelerating duct. While providing additional thrust, its independently controllable rudder blades on either side of the propeller also enhance ship maneuverability. The GRS was first fully implemented on a container ship in Japan, demonstrating improved propulsion efficiency, fuel savings, and excellent performance in maneuvering, noise, and vibration reduction. In recent years, extensive research has been conducted on the hydrodynamic performance, acoustic characteristics, and energy-saving effects of the GRS. However, certain gaps remain in the research, such as a lack of systematic studies on optimal GRS design in the publicly available literature. Only Ahmet Yusuf Gurkan has investigated the sensitivity of propulsion performance to parameters such as rudder angle, rudder X-shift, rudder tip skewness, and blade tip chord ratio. Therefore, this study employs the JBC benchmark vessel and adopts a coupled CFD-CAESES approach to develop a matching optimization design for the GRS. The influence of geometric parameters—including GRS airfoil camber, maximum camber position, chord length, thickness, distance from the leading edge to the propeller plane, and the gap between the GRS and propeller blades—on ship propulsion performance is investigated. The sensitivity of these design variables to propulsion performance is analyzed, and the optimal GRS design is selected to predict and evaluate its energy-saving effects. This research establishes a rapid and comprehensive CFD-based optimization methodology for GRS matching design. The findings indicate that the gap between the GRS and propeller, the distance from the GRS to the stern, and the airfoil camber of the GRS significantly contribute to various performance responses. After GRS installation, the viscous pressure resistance of the JBC ship decreases, resulting in an 8.05% energy-saving effect at the designated speed. Full article

Kolmogorov–Arnold Networks (KANs) are a recent development in machine learning, offering strong functional representation capabilities, enhanced interpretability, and reduced parameter complexity. Leveraging these advantages, this paper proposes a KAN-based reduced-order model (ROM) for unsteady aerodynamics and aeroelasticity. To effectively capture temporal dependencies inherent in nonlinear unsteady flow phenomena, an architecture termed Kolmogorov–Arnold Gated Recurrent Network (KAGRN) is introduced. By incorporating a recurrent structure and a gating mechanism, the proposed model effectively captures time-delay effects and enables the selective control and preservation of long-term temporal dependencies. This architecture provides high predictive accuracy, good generalization capability, and fast prediction speed. The performance of the model is evaluated using simulations of the NACA (National Advisory Committee for Aeronautics) 64A010 airfoil undergoing harmonic motion and limit cycle oscillations in transonic flow conditions. Results demonstrate that the proposed model can not only accurately and efficiently predict unsteady aerodynamic coefficients, but also effectively capture nonlinear aeroelastic responses. Full article

Efficient ice protection systems are essential to ensure the operability and reliability of aircraft. In recent years, electromechanical resonant ice protection systems have emerged as a promising low-power alternative to current solutions. These systems can operate in two primary resonant modes: flexural and extensional. While extensional modes enable effective de-icing over large surface areas, their performance can be compromised by interference from flexural modes, particularly in thin, ice-covered substrates where natural mode coupling occurs. This study presents a strategy based on material selection for making the Young’s modulus-to-density ratio uniform. The final objective of this paper is to establish the design rules for a composite leading edge de-icing system. For this purpose, an incremental approach will be used on profiles with different radii of curvature: plate or beam (infinite radius), circular profile (constant radius), NACA profile (variable radius). For beam and plate structures, the paper shows that this coupling can be mitigated by selecting materials with a Young’s modulus-to-density ratio comparable to that of ice. For curved structures, the curvature-induced effect is another source of parasitic flexion, which cannot be controlled solely by material selection and requires careful thickness optimization. This study presents analytical and numerical approaches to investigate the origin of this effect and a design methodology to minimize parasitic flexion in curved structures. The methodology is applied to the design optimization of a glass fiber NACA 0024 airfoil leading edge, the performance of which is subsequently evaluated through icing wind tunnel testing. Full article

The Italian Aerospace Research Centre (CIRA) is developing an unmanned stratospheric platform for Earth observation and telecommunications, known as a High-Altitude Pseudo-Satellite (HAPS). This paper presents an aerodynamic and stability analysis of a new closed-wing HAPS configuration. The design uses a hybrid approach, combining aerodynamic and aerostatic forces to achieve weight balance, with the stability analysis accounting for the buoyancy force applied at the center of volume of the structure. Following the initial design phase, which aims for an altitude of 20 km, a speed of 16 m/s, and a payload capacity of 20 kg, a suitable configuration using a NACA 0018 airfoil is selected. The aircraft lift–drag curve is evaluated using a stationary, incompressible Reynolds-Averaged Navier–Stokes (RANS) analysis with a k-$\omega$ SST turbulence model in OpenFoam. A detailed longitudinal and lateral-directional stability analysis is also conducted using OpenFOam and AVL software. Full article

Hover-capable unmanned aerial vehicles (UAVs), including rotary-wing UAVs such as unmanned helicopters, multi-rotor drones, and tilt-rotor UAVs, are widely employed due to their hovering capabilities. In recent years, tilt-rotor aircraft, which offer both vertical takeoff and landing as well as rapid maneuverability, have increasingly become a research focus. This paper first proposes a design concept for a flying-wing configuration tilt-rotor tri-rotor UAV, detailing the selection of airfoils and the calculation of aerodynamic parameters. To address the specific operational requirements and flight characteristics of this UAV, a specialized tilting mechanism was developed, and a flight control system was designed and implemented using classical PID control methods. Finally, a prototype of the tilt-rotor tri-rotor UAV was fabricated and subjected to flight tests. The results from both simulations and flight tests confirmed that the UAV met the design performance criteria and that the control method was effective. Full article

This study evaluates the perfection of the crystal structure of single-crystal turbine blade castings made from the CMSX-4 nickel superalloy. The analysis included primary and secondary crystal orientation measurements using the Ω-scan method and the novel OD-EFG X-ray diffractometer. The selected microstructural parameters of the single crystals were also analyzed, including the assessment of stereological parameters and the degree of porosity. A creep test was performed according to standard procedures and under conditions simulating real operational environments. The model single-crystal turbine blades were manufactured using the Bridgman–Stockbarger method, with variable withdrawal rates of 1 and 3 mm/min. Heat treatment of the single-crystal castings involved solution treatment followed by double aging. The evaluation of structural perfection was carried out in three states: as-cast, after solution heat treatment, and after double aging. The crystallographic orientation of the blades was determined on both the airfoil and the root part. The study determined how crystallographic orientation and microstructural parameters influence the creep resistance of the castings. It was found that in the as-cast condition, the greatest influence on high creep strength has a small deviation of the primary and constant value of secondary crystal orientation along the height of the blade casting. After heat treatment, the highest creep resistance was obtained for the blade manufactured at a withdrawal rate at 1 mm/min. Full article

For a special bilaterally symmetric airfoil (BSA), this paper designs an active flow control scheme based on the Co-Flow Jet (CFJ) and adaptive morphing technology, and establishes a numerical simulation method which is suitable for simulating aerodynamic characteristics. The accuracy and effectiveness of the numerical method has been verified through benchmark cases. This study investigates the effects of jet intensity, suction slot position and angle, and deflection angles of the leading and TE flap on the aerodynamic performance parameters and flow field structure of the bilaterally symmetric airfoil. The results show that the adaptive morphing technology can significantly improve the equivalent lift coefficient and equivalent lift-to-drag ratio of the bilaterally symmetric airfoil, without obviously increasing the CFJ power consumption coefficient. Selecting an appropriate CFJ intensity can achieve a relatively high equivalent lift-to-drag ratio with a low compressor power requirement. Moving the suction slot rearward can increase the lift coefficient, and placing it on the trailing edge (TE) flap can more efficiently delay flow separation, reduce power consumption, and increase the equivalent lift-to-drag ratio. The suction slot angle has little effect on the lift coefficient, but a larger suction slot angle can enhance the equivalent lift-to-drag ratio. Increasing the TE flap deflection angle enhances both the lift coefficient and drag coefficient, as well as the power consumption coefficient at high angles of attack. But it has little effect on the maximum equivalent lift-to-drag ratio. Increasing the leading edge flap deflection angle can improve the maximum equivalent lift-to-drag ratio while increasing the angle of attack corresponding to it. Overall, choosing a CFJ and adaptive morphing parameters by considering different factors can enhance the aerodynamic performance of the bilaterally symmetric airfoil. Full article

In this study, we determined an aerodynamic configuration to design structures applying composites for large-scale horizontal-axis wind turbine blades. A new aerodynamic and structural design method for large wind turbine blades is presented. The rated power of the wind turbine blade is 25 MW class. The tip speed ratio is 7. The diameter of the designed blade is 260 m. Therefore, thick airfoils were selected to design large-scale wind turbine blades considering structural stiffness and maximum lift coefficients. For the aerodynamic design method, it was designed with the optimal angle of attack having the maximum lift-to-drag ratio. The blade element theory and vortex theory were applied to aerodynamic design. For the aerodynamic design results, its validity was investigated via aerodynamic performance analysis. As a result of analyzing aerodynamic performance, it was confirmed that higher power was generated. At 12.5 m/s of rated wind speed, electrical power was 28.32 MW. The structural design considering the aerodynamic design results was carried out. The composite laminate theory was adopted. Structural safety was evaluated for the designed blades. Finally, the structural design results were analyzed as sufficiently valid. Full article

Many real-world expensive industrial and engineering multi-objective optimization problems (MOPs) are driven by historical, experimental, or simulation data. In such scenarios, due to the expensive cost and time required, we are only left with a small amount of labeled data to perform the optimization. These offline data-driven MOPs are usually solved by multi-objective evolutionary algorithms (MOEAs) with the help of surrogate models constructed from offline historical data. The key challenge in developing these data-driven MOEAs is that they have to replace multiple conflicting fitness functions by approximating these objective functions, which may produce cumulative approximation errors and misguide the search. In order to build a reliable surrogate model from a small amount of multi-output offline data and solve the DDMOPs, we have proposed an adaptive model selection method with a reliable individual-based model management-driven MOEA. The proposed algorithm dynamically selects between DNN and XGBoost by comparing their k-fold cross-validation MAE error, which can capture the true generalization ability of the surrogates on unseen data. Then, the selected surrogate is updated with a reliable individual selection strategy, where the individual who is closest, both in the decision and objective space, to the most preferred solution among labeled offline data is chosen. As a result, these two strategies guide the underlying MOEA to the Pareto optimal solutions. The empirical results of the ZDT and DTLZ benchmark test suite validate the use of the three state-of-the-art offline DDMOEAs, showing that our algorithm is able to achieve highly competitive results in terms of convergence and diversity for 2–3 objectives. Finally, our algorithm is applied to an offline data-driven multi-objective problem—transonic airfoil (RAE 2822) shape optimization—to validate its efficiency on real-world DDMOPs. Full article

This study explores the use of a passive control technique to mitigate aeroelastic effects on a wing operating near the ground. An aeroelastic model, based on a typical airfoil section, equipped with a nonlinear tuned vibration absorber (NLTVA), is established to study the interactions between the airfoil’s dynamics, aerodynamics, and the nonlinear energy dissipation mechanisms. Geometric nonlinearity is incorporated into the airfoil’s dynamics to account for possible large wing deflection and rotation. The flow is modeled based on the nonlinear unsteady discrete vortex method with the ground effect simulated using the mirror image method. Stability analyses are conducted to study the influence of NLTVA parameters on flutter mitigation and the bifurcation behavior of the airfoil near the ground. The numerical results demonstrate that the NLTVA effectively delays the onset of flutter and promotes a supercritical bifurcation in the presence of ground effect. Optimally tuning the NLTVA’s linear parameters significantly increases flutter speed, while selecting the optimal nonlinear parameter is key to preventing subcritical behavior near the ground and reducing the amplitude of post-flutter limit cycle oscillations. Overall, this study highlights the potential of the NLTVA in enhancing the aeroelastic stability of flying vehicles with highly flexible wings, especially under the influence of ground effects during takeoff and landing. Full article