Search Results (132)

Long-range rotating wrap-around-fin rockets may exhibit non-convergent conical motion at high Mach numbers, causing increased drag, reduced range, and potential flight instability. This study employs the implicit dual time-stepping method to solve the unsteady Reynolds-averaged Navier–Stokes (URANS) equations for simulating the flow field around a high aspect ratio wrap-around-fin rotating rocket at supersonic speeds. Validation of the numerical method in predicting aerodynamic characteristics at small angles of attack is achieved by comparing numerically obtained side force and yawing moment coefficients with experimental data. Analyzing the rocket’s angular motion process, along with angular motion equations, reveals the necessary conditions for the yawing moment to ensure stability during angular motion. Shape optimization is performed based on aerodynamic coefficient features and flow field structures at various angles of attack and Mach numbers, using the yawing moment stability condition as a guideline. Adjustments to parameters such as tail fin curvature radius, tail fin aspect ratio, and body aspect ratio diminish the impact of asymmetric flow induced by the wrap-around fin on the lateral moment, effectively resolving issues associated with near misses and off-target impacts resulting from dynamic instability at high Mach numbers. Full article

Aviation’s sustainability discourse often centres on flight emissions, but production and end-of-life phases also carry material, energy, and pollution impacts that are large enough to merit systematic intervention. With ~13,000 aircraft projected to retire over the next two decades—roughly 44% of the global fleet—the sector must scale responsible dismantling and material recovery to avoid lost opportunities for meeting future sustainability goals and to harness economic value from secondary parts and recycled feedstocks. Embedding major sustainability and circular economy principles into aircraft design, operations, and retirement can reduce waste, conserve critical materials, and lower lifecycle emissions while contributing directly to multiple SDGs. Furthermore, when considering particular aircraft types, thousands of narrow-body aircraft such as the Airbus A320 and Boeing 737 are due to reach their end of life over the next two decades. This research evaluates the economic and environmental feasibility of aluminium recycling from these aircraft, integrating material flow analysis, cost–benefit modelling, and a lifecycle emissions assessment. An economic assessment framework is developed and applied, with the results showing that approximately 24.7 tonnes of aluminium can be recovered per aircraft, leading to emissions savings of over 338,000 kg of CO₂e, a 95% reduction compared to primary aluminium production. However, scrap value alone cannot offset dismantling costs; the break-even scrap price is over USD 4200 per tonne. When additional revenue streams such as component resale and carbon credit incentives are incorporated, the model predicts a net profit of over USD 59,000 per aircraft. The scenario analysis confirms that aluminium recycling only becomes financially viable through multi-stream revenue models, supported by Extended Producer Responsibility (EPR) and carbon pricing. While barriers remain, aluminium recovery is a strategic opportunity to align aviation with circular economy and decarbonisation goals. Full article

This paper introduces a parallelized approach to reconstruct Koopman computational graphs from the perspective of parallel computing to address the computational efficiency bottleneck in approximating Koopman operators within high-dimensional spaces. We propose the KPA (Koopman Parallel Accelerator), a parallelized algorithm that restructures the Koopman computational workflow to transform sequential time-step computations into parallel tasks. KPA leverages GPU parallelism to improve execution efficiency without compromising model accuracy. To validate the algorithm’s effectiveness, we apply KPA to a flight trajectory prediction scenario based on the Koopman operator. Within the CUDA kernel implementation of KPA, several optimization techniques—such as shared memory, tiling, double buffering, and data prefetching—are employed. We compare our implementation against two baselines: the original Koopman neural operator for trajectory prediction implemented in TensorFlow (TF-baseline) and its XLA-compiled variant (TF-XLA). The experimental results demonstrate that KPA achieves a 2.47× speed up over TF-baseline and a 1.09× improvement over TF-XLA when predicting a 1422-dimensional flight trajectory. Additionally, an ablation study on block size and the number of streaming multiprocessors (SMs) reveals that the best performance is obtained with the block size of 16 × 16 and SM = 8. The results demonstrate that KPA can significantly accelerate Koopman operator computations, making it suitable for high-dimensional, large-scale, or real-time applications. Full article

Rice (Oryza sativa) provides a major food resource worldwide, playing an important role in the global economy. Leptocorisa acuta (Hemiptera: Alydidae), commonly known as the rice seed bug, is a major pest of paddy crops in many rice-growing regions and it is considered a potential invasive pest in the United States. Here, we investigated the genetic structure and demographic history of 18 populations sampled from China and southeast Asia using double-digest restriction site-associated DNA sequencing (ddRAD-seq). Then, we performed niche modeling based on occurrence records under current and future climate scenarios. Our analyses suggested that the lack of genetic structure among populations of L. acuta is related to recent diversification, strong flight, and dispersal capability, leading to a high level of gene flow. The demographic history was not strongly affected by the last glacial maximum. Ecological niche modeling predicts that future suitable areas will expand in Asia and America, relative to the current conditions. The ecological niche results demonstrated that L. acuta is a potentially invasive pest to the United States (mainly Florida and nearby areas) under current and future scenarios. Moreover, the moderately and highly suitable areas will increase in America (primarily located in North America, namely Florida and nearby areas, and Mexico), Central American and Caribbean countries, and some regions of South America. Some South American countries have extensive rice crops and broadly suitable habitats that may indicate a higher invasion risk. Through population genetics, our study supports the strong dispersal capacity of this insect pest and calls for vigilance against its invasion in some countries in the Americas. Full article

During hypersonic flight, the air rudder shaft can undergo huge aerodynamic heating load, where it is necessary to design the thermal protection system of the air rudder shaft. Aiming to prevent the rudder shaft from thermal failure due to the heat endurance limit of materials, numerical investigations are conducted systemically to predict the active cooling performance of the rudder shaft with liquid water considering phase change. The validation of the numerical simulation method considering phase-change heat transfer is further investigated by experiments. The effect of coolant injection flow velocity on the active cooling performance is further analyzed for both the steady state and transient state. Finally, to achieve better cooling performance, an optimized design of the cooling channels is performed in this work. The results of the transient numerical simulation show that, employing the initial cooling structures, it may undergo the heat transfer deterioration phenomenon under the coolant injection velocity below 0.2 m/s. For the rudder shaft with an optimized structure, the heat transfer deterioration can be significantly reduced, which significantly reduces the risk of thermal failure. Moreover, the total pressure drop of the optimized rudder shaft under the same coolant injection condition can be reduced by about 19% compared with the initial structure. This study provides a valuable contribution to the thermal protection performance for the rudder shaft, as a key component of aircraft under the aero heating process. Full article

Mid-altitude sounding rockets are essential for atmospheric research and suborbital experimentation, where aerodynamic optimization and structural integrity are crucial for achieving targeted apogees. This study uses OpenRocket v23.09 for preliminary flight performance prediction and SolidWorks 2024 to integrate aerodynamic and structural analyses through Computational Fluid Dynamics (CFD) and Finite Element Analysis (FEA). SolidWorks Flow Simulation and SolidWorks Simulation are used to assess how nose cone and fin geometries, as well as thermal deformation, influence flight performance. Among nine tested configurations, the ogive nose cone with trapezoidal fins achieved the highest simulated apogee of 2639 m, with drag coefficients of 0.480 (OpenRocket) and 0.401 (SolidWorks Flow Simulation). Thermal–structural analysis revealed a maximum nose tip displacement of 0.7249 mm for the rocket with the ogive nose cone, leading to an increasing drag coefficient of 0.404. However, thermal deformation of the ellipsoid nose cone led to a reduction in the drag coefficient from 0.419 to 0.399, even though it exhibited a slightly higher maximum displacement of 0.7443 mm. Mesh independence was confirmed with outlet velocity deviations below 1% across refinements. These results highlight the importance of integrated CFD–FEA approaches, geometric optimization, and material resilience for enhancing the aerodynamic performance of subsonic sounding rockets. 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

This paper presents FWStab, a specialized video stabilization dataset tailored for flapping-wing platforms. The dataset encompasses five typical flight scenarios, featuring 48 video clips with intense dynamic jitter. The corresponding Inertial Measurement Unit (IMU) sensor data are synchronously collected, which jointly provide reliable support for multimodal modeling. Based on this, to address the issue of poor image acquisition quality due to severe vibrations in aerial vehicles, this paper proposes a multi-modal signal fusion video stabilization framework. This framework effectively integrates image features and inertial sensor features to predict smooth and stable camera poses. During the video stabilization process, the true camera motion originally estimated based on sensors is warped to the smooth trajectory predicted by the network, thereby optimizing the inter-frame stability. This approach maintains the global rigidity of scene motion, avoids visual artifacts caused by traditional dense optical flow-based spatiotemporal warping, and rectifies rolling shutter-induced distortions. Furthermore, the network is trained in an unsupervised manner by leveraging a joint loss function that integrates camera pose smoothness and optical flow residuals. When coupled with a multi-stage training strategy, this framework demonstrates remarkable stabilization adaptability across a wide range of scenarios. The entire framework employs Long Short-Term Memory (LSTM) to model the temporal characteristics of camera trajectories, enabling high-precision prediction of smooth trajectories. Full article

With the enhancement of thermodynamic cycle parameters and heat dissipation constraints in aero-engines, effective thermal management has become a critical challenge to ensure safe and stable engine operation. This study developed a transient temperature evaluation model applicable to the entire flight envelope, considering fluid–solid coupling heat transfer on both the main flow path and fuel systems. Firstly, the impact of heat transfer on the acceleration and deceleration performance of a low-bypass-ratio turbofan engine was analyzed. The results indicate that, compared to the conventional adiabatic model, the improved model predicts metal components absorb 4.5% of the total combustor energy during cold-state acceleration, leading to a maximum reduction of 1.42 kN in net thrust and an increase in specific fuel consumption by 1.18 g/(kN·s). Subsequently, a systematic evaluation of engine thermal management performance throughout the complete flight mission was conducted, revealing the limitations of the existing thermal management design and proposing targeted optimization strategies, including employing Cooled Cooling Air technology to improve high-pressure turbine blade cooling efficiency, dynamically adjusting low-pressure turbine bleed air to minimize unnecessary losses, optimizing fuel heat sink utilization for enhanced cooling performance, and replacing mechanical pumps with motor pumps for precise fuel supply control. Full article

In air traffic systems, aircraft trajectories between airports are monitored by the radar networking system forming dynamic air traffic flow. Accurate airport arrival flow prediction is significant in implementing large-scale intelligent air traffic flow management. Despite years of studies to improve prediction precision, most existing methods only focus on a single airport or simplify the traffic network as a static and simple graph. To mitigate this shortage, we propose a hybrid neural network method, called Dynamic Multi-graph Convolutional Spatial-Temporal Network (DMCSTN), to predict network-level airport arrival flow considering the multiple operation constraints and flight interactions among airport nodes. Specifically, in the spatial dimension, a novel dynamic multi-graph convolutional network is designed to adaptively model the heterogeneous and dynamic airport networks. It enables the proposed model to dynamically capture informative spatial correlations according to the input traffic features. In the temporal dimension, an enhanced self-attention mechanism is utilized to mine the arrival flow evolution patterns. Experiments on a real-world dataset from an ATFM system validate the effectiveness of DMCSTN for arrival flow forecasting tasks. Full article

This study investigates the aerodynamic performance of a fourth-generation normal shockwave inlet system, with a primary focus on minimizing pressure losses and ensuring uniform airflow distribution. A computational model was developed, incorporating a section of the fuselage along with the complete inlet duct. The model was discretized using a hybrid mesh approach to enhance numerical accuracy. The analysis was conducted at a flight altitude of 8000 m, encompassing 370 distinct cases defined by varying angles of attack and Mach numbers. This comprehensive parametric study yielded a dataset of 10,800 total pressure measurements across predefined sampling locations. Based on the obtained results, flow distortion coefficients in both circumferential (CDI) and radial directions (RDI) were systematically determined for each test case. The interdependencies between CDI, RDI, Mach number, and angle of attack (α) were analyzed and presented in a consolidated manner. In the second phase of the study, an artificial neural network (ANN) utilizing a Feed-Forward architecture was implemented to predict pressure distributions for intermediate flight conditions. The ANN was trained using the CFG algorithm, and the predictive accuracy was assessed through the determination coefficients computed by comparing ANN-based estimates with numerical simulation results. The findings demonstrate the efficacy of ANN-based modeling in enhancing the predictive capabilities of inlet flow dynamics, offering valuable insights for optimizing next-generation supersonic air intake systems. Full article

Dynamic stability derivatives are critical parameters in the design of trajectories and attitude control systems for flight vehicles, as they directly affect the divergence behavior of vibrations in an aircraft’s open-loop system when subjected to disturbances. This study focuses on the estimation of dynamic stability derivatives using a computational fluid dynamics (CFD)-based force oscillation method. A transient Reynolds-averaged Navier–Stokes solver is utilized to compute the time history of aerodynamic moments for an aircraft model oscillating about its center of gravity. The NASA Common Research Model serves as the reference geometry for this investigation, which explores the impact of pitching, rolling, and yawing oscillations on aerodynamic performance. Periodic oscillatory motions are imposed while using a dynamic mesh technique for CFD analysis. Preliminary steady-state simulations are conducted to validate the computational approach, ensuring the reliability and accuracy of the applied CFD model for transonic flow. The primary goal of this research is to confirm the efficacy of CFD in accurately predicting stability derivative values, underscoring its advantages over traditional wind tunnel experiments at high angles of attack. The study highlights the accuracy of CFD predictions and provides detailed insights into how different oscillations affect aerodynamic performance. This approach showcases the potential for significant cost and time savings in the estimation of dynamic stability derivatives. Full article

Current trends in the aerospace and UAV sectors emphasize integrating Artificial Intelligence (AI) technologies into the design process. AI technologies necessitate extensive data to capture the non-linearities in fluid phenomena. To address these needs, this work focuses on automating the data aggregation process for fixed-wing platforms, ranging from Micro–Mini to HALE-Strike UAVs, as classified by NATO. Specifically, this paper presents a framework for automating the tedious tasks required for geometry generation, mesh generation, and solution setup in a commercial Computational Fluid Dynamics (CFD) solver, for any arbitrary wing within the aforementioned design space. By combining various well-established open-source suites and commercial software via Python scripting, the preprocessing steps up to the solution require only a few minutes on a typical laptop workspace. Despite the rapid geometry acquisition, mesh generation, and solution setup through the pipeline, the guidelines and common practices for subsonic external flow simulations are still strictly followed. This results in solutions with a deviation of merely sub 5% from those of an experienced designer, even for the extremes of the flight envelope. The proposed framework significantly reduces design iteration times, enabling more efficient and innovative UAV development. Additionally, the framework’s ability to accumulate high-quality data for machine learning enhances predictive modeling and optimization capabilities across UAV design practices. Full article

A computational fluid dynamics-based study of a corrugated wing section inspired by the dragonfly wing was performed for a low Reynolds number (10’000), focusing on gliding flight. The aerodynamic characteristics are compared to those of a typical technical aerofoil (NACA 0009). The objective of this study is to develop a simulation tool for the design and development of corrugated wings for aerospace applications and to gain a better understanding of the flow over corrugated wing sections. The simulation results were verified using a convergence study and validated by an angle of attack study and comparison with experimental results. The results demonstrated the simulations capability of predicting key flow features but there were some discrepancies from the experimental observations, mainly the prediction of the critical angle of attack. Overall, the simulation results demonstrated a comparable, if not better, aerodynamic performance compared to the technical aerofoil. Full article

Low-Reynolds-number propeller systems have been widely used in aeronautical applications, such as unmanned aerial vehicles (UAV) and electric propulsion systems. However, the aerodynamic sound of the propeller systems is often significant and can lead to aircraft noise problems. Therefore, effective predictions of propeller noise are important for designing aircraft, and the different phases in aircraft design require specific prediction approaches. This paper aimed to perform a comparison study on numerical methods at different fidelity levels for predicting the aerodynamic noise of low-Reynolds-number propellers. The Ffowcs-Williams and Hawkings (FWH), Hanson, and Gutin methods were assessed as, respectively, high-, medium-, and low-fidelity noise models. And a coarse-grid large eddy simulation was performed to model the propeller aerodynamics and to inform the three noise models. A popular propeller configuration, which has been used in previous experimental and numerical studies on propeller noise, was employed. This configuration consisted of a two-bladed propeller mounted on a cylindrical nacelle. The propeller had a diameter of $D=9^{″}$ and a pitch-to-diameter ratio of $P/D=1$, and was operated in a forward-flight condition with a chord-based Reynolds number of $Re=4.8\times {10}^4$, a tip Mach number of $M=0.231$, and an advance ratio of $J=0.485$. The results were validated against existing experimental measurements. The propeller flow was characterized by significant tip vortices, weak separation over the leading edges of the blade suction sides, and small-scale vortical structures from the blade trailing edges. The far-field noise was characterized by tonal noise, as well as broadband noise. The mechanism of the noise generation and propagation were clarified. The capacities of the three noise modeling methods for predicting such propeller noise were evaluated and compared. Full article