Search Results (29)

Helopeltis cinchonae is an emerging pest of tea and causes severe damage to tea plantations in China. The female of H. cinchonae has been reported to produce a sex pheromone consisting of two components, hexyl (3R)-3-acetoxybutyrate and (5R)-1-acetoxy-5-butyroxyhexane, and lures containing the synthetic compounds have been shown to attract male H. cinchonae to traps in the field. This is the first time that components of the sex pheromone have been identified for a species of Helopeltis bug, but their field application has not been evaluated in detail. The present study shows that a blend of both compounds loaded into a polyethylene vial at 0.2 and 2 mg, respectively, caught significantly more male H. cinchonae bugs than the individual compounds and all the other tested blends. Sticky wing traps baited with the binary blend of compounds at the optimized ratio and dosage caught more bugs than bucket funnel or delta traps, and traps hung at a height of 10 cm above the tea shoots caught more bugs than those at other heights. The optimized traps and lures were used for monitoring the pest and two distinct population peaks of H. cinchonae were observed, the first one during mid-May to early June, and the other one in mid-September. Overall, the results of this study contribute to an environmentally-friendly approach to monitoring and managing H. cinchonae in the field. Full article

Numerical simulations of an 80-degree delta wing in free-to-roll motion are performed by applying the dynamic fluid–body interaction (DFBI) model and the overlap/chimera method using the URANS equations. The capabilities of modern computational fluid dynamics methods for predicting wing-rock phenomena over a wide range of angles of attack at low Mach numbers and strong wing–vortex interaction, including the vortex breakdown phenomenon, were investigated by comparing simulation results with wind tunnel test data. At low angles of attack, delays in the strength and position of the leading-edge vortices above the wing have a destabilizing effect on it, leading to the emergence of self-sustained limit-cycle oscillations. At high angles of attack, where vortex breakdown occurs, the available wind tunnel data show that there are two modes of wing self-oscillations in free-to-roll motion, namely, regular large-amplitude oscillations and irregular small-amplitude oscillations, where the excitation of the latter mode depends on the angle of attack and the initial roll angle of the wing motion. The performed numerical simulation also shows the existence of these two self-oscillatory modes in roll, qualitatively and quantitatively matching the experimental data. Full article

Wind estimation is crucial for studying the atmospheric boundary layer. Traditional methods such as weather balloons offer limited in situ capabilities; besides an Air Data System (ADS) combined with inertial measurements and satellite positioning is required to estimate the wind on fixed-wing drones. As pressure probes are an important constituent of an ADS, they are susceptible to malfunctioning or failure due to blockages, thus affecting the capability of wind sensing and possibly the safety of the drone. This paper presents a novel approach, using low-fidelity aerodynamic models of drones to estimate wind synthetically. In our work, the aerodynamic model parameters are derived from post-processed flight data, in contrast to existing approaches that use expensive wind tunnel calibration for identifying the same. In sum, our method integrates aerodynamic force and moment models into a Vehicle Dynamic Model (VDM)-based navigation filter to yield a synthetic wind estimate without relying on an airspeed sensor. We validate our approach using two geometrically distinct drones, each characterized by a unique aerodynamic model and different quality of inertial sensors, altogether tested across several flights. Experimental results demonstrate that the proposed cross-platform method provides a synthetic wind velocity estimate, thus offering a practical backup to traditional techniques. Full article

In recent years, leading-edge tubercles have gained significant attention as an innovative biomimetic flow control technique. This paper explores their impact on the aerodynamic performance and flow patterns of an airfoil through wind tunnel experiments, utilizing force measurements and tuft visualization at Reynolds numbers between 2.7 × 10⁵ and 6.3 × 10⁵. The baseline airfoil exhibits a hysteresis loop near the stall angle, with sharp changes in lift coefficient during variations in the angle of attack (AOA). In contrast, the airfoil with leading-edge tubercles demonstrates a smoother stall process and enhanced post-stall performance, though its pre-stall performance is slightly reduced. The study identifies four distinct flow regimes on the modified airfoil, corresponding to different segments of the lift coefficient curve. As the AOA increases, the flow transitions through stages of full attachment, trailing-edge separation, and local leading-edge separation across some or all valley sections. Additionally, the study suggests that normalizing aerodynamic performance based on the valley section chord length is more effective, supporting the idea that leading-edge tubercles function like a series of delta wings in front of a straight-leading-edge wing. These insights provide valuable guidance for the design of blades with leading-edge tubercles in applications such as wind and tidal turbines. Full article

This article investigates the design of time-accurate input signals in the angle-of-attack and pitch rate space to identify the aerodynamic characteristics of a generic triple-delta wing configuration at subsonic speeds. Regression models were created from the time history of signal simulations in DoD HPCMP CREATE^TM-AV/Kestrel software. The input signals included chirp, Schroeder, pseudorandom binary sequence (PRBS), random, and sinusoidal signals. Although similar in structure, the coefficients of these regression models were estimated based on the specific input signals. The signals covered a wide range of angle-of-attack and pitch rate space, resulting in varying regression coefficients for each signal. After creating and validating the models, they were used to predict static aerodynamic data at a wide range of angles of attack but with zero pitch rate. Next, slope coefficients and dynamic derivatives in the pitch direction were estimated from each signal. These predictions were compared with each other as well as with the ONERA wind tunnel data and some CFD calculations from the DLR TAU code provided by the NATO Science and Technology Organization research task group AVT-351. Subsequently, the models were used to predict different pitch oscillations at various mean angles of attack with given amplitudes and frequencies. Again, the model predictions were compared with wind tunnel data. Final predictions involved responses to new signals from different models. A feed-forward neural network was then used to model pressure coefficients on the upper surface of the vehicle at different spanwise sections for each signal and the validated models were used to predict pressure data at different angles of attack. Overall, the models predict similar integrated forces and moments, with the main discrepancies appearing at higher angles of attack. All models failed to predict the stall behavior observed in the measurements and CFD data. Regarding the pressure data, the PRBS signal provided the best accuracy among all the models. Full article

Flight-by-feel (FBF) is an approach to flight control that uses dispersed sensors on the wings of aircraft to detect flight state. While biological FBF systems, such as the wings of insects, often contain hundreds of strain and flow sensors, artificial systems are highly constrained by size, weight, and power (SWaP) considerations, especially for small aircraft. An optimization approach is needed to determine how many sensors are required and where they should be placed on the wing. Airflow fields can be highly nonlinear, and many local minima exist for sensor placement, meaning conventional optimization techniques are unreliable for this application. The Sparse Sensor Placement Optimization for Prediction (SSPOP) algorithm extracts information from a dense array of flow data using singular value decomposition and linear discriminant analysis, thereby identifying the most information-rich sparse subset of sensor locations. In this research, the SSPOP algorithm is evaluated for the placement of artificial hair sensors on a 3D delta wing model with a 45$°$ sweep angle and a blunt leading edge. The sensor placement solution, or design point (DP), is shown to rank within the top one percent of all possible solutions by root mean square error in angle of attack prediction. This research is the first to evaluate SSPOP on a 3D model and the first to include variable length hairs for variable velocity sensitivity. A comparison of SSPOP against conventional greedy search and gradient-based optimization shows that SSPOP DP ranks nearest to optimal in over 90 percent of models and is far more robust to model variation. The successful application of SSPOP in complex 3D flows paves the way for experimental sensor placement optimization for artificial hair-cell airflow sensors and is a major step toward biomimetic flight-by-feel. Full article

This paper introduces innovative approaches to enhance and develop one-equation RANS models using gene-expression programming. Two distinct strategies are explored: overcoming the limitations of the Boussinesq hypothesis and formulating a novel one-equation turbulence model that can accurately predict a wide range of turbulent wall-bounded flows. A comparative analysis of these strategies highlights their potential for advancing RANS modeling capabilities. The study employs a single-case CFD-driven machine learning framework, demonstrating that machine-informed models significantly improve predictive accuracy, especially when baseline RANS predictions diverge from established benchmarks. Using existing training data, symbolic regression provides valuable insights into the underlying physics by eliminating ineffective strategies. This highlights the broader significance of machine learning beyond developing turbulence closures for specific cases. Full article

In order to improve the data productivity of a wind tunnel test, the model under investigation in the wind tunnel is moved continuously with a predetermined constant angular speed in the so-called pitch–traverse mode. Alternatively, the wind tunnel model can be moved in the so-called pitch–pause mode, in which it keeps its position for a certain (measurement) time at a fixed pitch position, after which it is moved to the next pitch position. The latter procedure is more time-consuming, so, for the same time interval, the number of measured data points taken in the pitch–pause mode is less than that for the pitch–traverse mode. Since wind tunnel test time can be quite expensive, in most wind tunnel tests where only conventional forces and pressures are recorded with conventional measuring systems, the wind tunnel model is moved in the pitch–traverse mode in order to obtain as much aerodynamic data as possible during the tunnel runtime. The application of the Pressure-Sensitive Paint (PSP) technique has been widely used in wind tunnel testing for the purpose of providing pressure data on wind tunnel models with high spatial resolution. The lifetime-based PSP method has several advantages over the intensity-based method since it often has higher accuracy. Up until now, the lifetime-based PSP technique has mainly been used for wind tunnel testing, where the test model has been moved to the pitch–pause mode. The traditional lifetime method using on-chip accumulation requires multiple (~1000) excitation light pulses to accumulate enough luminescence (fluorescence or phosphorescence) photons on the camera sensor to provide acceptable signal-to-noise ratios and, therefore, it may seem to be not compatible with a continuously moving wind tunnel model. Nevertheless, the present study verifies the application of lifetime-based PSP utilizing on-chip accumulation with a continuously moving wind tunnel model which would make the entire PSP data acquisition compatible with that of the conventional measurements (forces and pressures), as mentioned above. In this paper, the applicability of the lifetime-based PSP technique to a continuously moving wind tunnel model (in pitch–traverse mode) is investigated with the help of measurements in the transonic wind tunnel in Göttingen (TWG). For this investigation, PSP was applied on the delta-wing model DLR-F22, which is to be tested in TWG. The pressure distribution on the wind tunnel model was measured using the PSP lifetime method for both model movement modes (pitch–pause and pitch–traverse mode) so that the corresponding PSP results could be directly compared with each other. In addition, an error analysis of the PSP results was carried out and compared with the conventional pressure measurement results, hence providing an assessment of the accuracy of the PSP results; finally, a recommendation for future PSP measurements could be given. Full article

This study proposes a computational fluid dynamics and computational structure dynamics (CFD/CSD) coupled method for calculating the buffet response of a variant tail wing. The large-scale separated flow in the buffet is simulated by the detached vortex approach, vibration deformation of the tail wing is solved by the dynamic mesh generation technique, and structural modeling is based on the mode method. The aerodynamic elastic coupling is calculated through the cyclic iteration of aerodynamics and the structural solution in the time domain. We verify the correctness of the proposed method through a typical delta wing calculation case, further simulate the buffet response of a variant tail wing in maneuver state, and finally realize buffet mitigation using an active excitation method. Overall, this study can provide an important reference for the design of variant-tailed aircraft. Full article

Eddy-viscosity-based turbulence models provide the most commonly used modeling approach for computational fluid dynamics simulations in the aerospace industry. These models are very accurate at a relatively low cost for many cases but lack accuracy in the case of highly rotational leading edge vortex flows for mid to low aspect-ratio wings. An enhanced adaptive turbulence model based on the one-equation Spalart–Allmaras turbulence model is fundamental to this work. This model employs several additional coefficients and source terms, specifically targeting vortex-dominated flow regions, where these coefficients can be calibrated by an optimization procedure based on experimental or high-fidelity numerical data. To extend the usability of the model from single or cluster-wise calibrated cases, this work presents a preconditioning approach of the turbulence model via a neural network. The neural network provides a case-unspecific calibration approach, enabling the use of the model for many known or unknown cases. This extension enables aircraft design teams to perform low-cost Reynolds-averaged Navier–Stokes simulations with increased accuracy instead of complex and costly high-fidelity simulations. Full article

In this work, the design features of delta wing vortex generators (DWVGs) on the thermo-hydraulic performance of heat exchangers are investigated using machine learning. Reynolds numbers, attack angle, length, wing-to-width ratio, and relative pitch ratio of DWVGs were used as descriptor variables, with Nusselt numbers, friction factors, and performance evaluation criterion (PEC) serving as target variables. Decision tree classification revealed the pathways leading to high or low values of the performance variables. Among many of those pathways, it was found that high Reynolds numbers (between 8160 and 9800) and high attack angles (greater than or equal to 47.5°) lead to high Nusselt numbers. On the other hand, an attack angle between 41° and 60°, a Reynolds number less than 8510, and a wing-to-width ratio greater than or equal to 0.4 causes a high friction factor. Finally, the PEC is likely to enhance when the Reynolds number is higher than or equal to 10,300 and the attack angle is between 47.5° and 60°. In addition to the decision tree analysis, SHapley Additive exPlanations (SHAP) analysis (a part of explainable machine learning) was also applied to reveal the importance of design features and their positive and negative effects on the target variables. For example, for a Nusselt number as the target variable, the Reynolds number was found to be the most influential variable, followed by the attack angle and the relative pitch ratio, all of which had a positive impact on the target. It was then concluded that machine learning methods could help provide strong insights into the configuration design features of heat exchangers in DWVGs to improve their efficiency and save energy. Full article

The purpose of this paper is to assess the influence of a novel type of vortex creation device called the leading-edge vortex controller (LEVCON) on the aerodynamic characteristics of a fighter jet. LEVCON has become a trending term in modern military aircraft in recent years and is a continuation of an existing and widely used aerodynamic solution called the leading-edge root extension (LERX). LEVCON is designed to operate on the same principles as LERX, but its aim is to generate lift-augmenting vortices, i.e., vortex lift, at higher angles of attack than LERX. To demonstrate the methodology, a custom delta wing fighter aircraft is introduced, and details about its aerodynamic configuration are provided. The LEVCON geometry is designed and then incorporated into an existing three-dimensional (3D) model of the aircraft in question. The research is conducted using OpenFOAM 8, a high-fidelity computational fluid dynamics (CFD) open-source software. The computational cases are designed to simulate the aircraft’s flight at stall velocities within a high range of angles of attack. The results are assessed and discussed in terms of aerodynamic characteristics. A conclusion is drawn from the analysis regarding the perceived improvements in fighter jet aerodynamics. The analysis reveals that both lift and critical angle of attack can be manipulated positively. With the addition of LEVCON, the average lift gain in the high angle of attack (α) range is between 8.5% and 10%, while the peak gain reaches 19.4%. The critical angle of attack has also increased by 2°, and a flatter stall characteristic has been achieved. Full article

Understanding the characteristics of lead–zinc mine occurrences and mastering effective investigative techniques are paramount in modern ore prospecting. This research focuses on the forested region of Yichun city in China, with a specific emphasis on the strategic mineral resource of a lead–zinc mine. The study examines the distribution patterns of this mineral and employs advanced aeromagnetic exploration methods. Firstly, we analyzed the geological structure and features of the region by leveraging the latest high-precision aeromagnetic data collected using dynamic delta wing technology. This analysis was complemented by an assessment of the geological conditions of the research area, existing lead–zinc deposits, ground magnetic surveys, and verification studies. With the goal of establishing a meaningful correlation between aeromagnetic anomalies and lead–zinc deposits, we employed various potential field conversion techniques, including the reduction to the pole, vertical derivatives, upward continuation, and residual anomaly analysis techniques. Secondly, we investigated the metallogenic sites within this region and provided a comprehensive summary of the metallogenic circumstances and characteristics related to aeromagnetic prospecting. Thirdly, we employed human–computer interaction fitting inversion techniques to predict the potential for lead–zinc mine prospecting in areas exhibiting aeromagnetic anomalies. The study underscores the significance of high-amplitude and large-scale aeromagnetic anomalies in the study area. Furthermore, we examined the interplay between intrusive rocks, strata, and structural elements within the region to identify favorable conditions for lead–zinc mineralization. As a result of our analysis and discussions, a location was predicted where a lead–zinc mine may exist. The research methodology outlined in this article provides valuable insights for future lead–zinc mine exploration efforts in areas characterized by similar geological conditions. Full article

This paper introduces a generic model for the study of aerodynamic behaviour relevant to fifth-generation high-performance aircraft. The model design is presented, outlining simplifications made to retain the key features of modern high-performance vehicles while ensuring a manufacturable geometry. Subsonic wind tunnel tests were performed with force and moment balance measurements used to develop a database of experimental validation data for the platform at a freestream velocity of 20 m/s. Numerical simulations are also presented and validated by the experiments and further employed to ensure the vortex behaviour is consistent with contemporary high-performance platforms. A sensitivity study of the computational predictions from the turbulence modelling approach is also presented. This geometry is the first in a suite of representative aircraft geometries (the Sydney Standard Aerodynamic Models), in which all geometries, computational models, and experimental data are made openly available to the research community (accessible via this link: https://zenodo.org/communities/ssam_gen5/) to serve as validation test cases and promote best practices in aerodynamic modelling. Full article

The influences of V-shaped delta-wing baffles on the thermohydraulic performance characteristics in a round tube were experimentally tested. The V-shaped delta-wing baffles having a set number of wings (N = 4, 6, and 8) were comparatively tested. The V-shaped delta-wing baffles with various pitch ratios of P/D = 2.0, 2.5, and 3.0 were thoroughly fitted inside a tube. In the present work, the baffles were responsible for both the recirculation/reverse flow behind the solid baffle and the longitudinal vortex flow behind the V-shaped wing. The V-shaped winged baffles with N = 8 produced high heat transfer rates by promoting the development of reverse and vortex flows. These currents aid in fluid mixing between the two streams. Experimental results suggested that utilizing V-shaped delta-wing baffles having N = 4, 6, and 8 led to Nusselt number enhancement of up to 97–105.6%, 105.8–127.8% and 114.8–138.9%, respectively. When N was 8, the V-shaped wings baffles created additional multi vortex flows, which resulted in some fluid mixing between the vortex and the reverse flow. It was discovered that a greater turbulent intensity is imparted to the flow that was occurring between the V-shaped delta-wing baffles, which led to an increase in the rate of heat transfer when the pitch ratio was decreased. The increase in Nusselt number was up to 118.26–151.3% more than it was in a tube with the lowest pitch ratio (P/D = 2.0). It was also found that the baffles with N = 8 wings and P/D = 3.0 offered a maximum aerothermal performance factor (APF) of 1.01. Furthermore, the V-shaped delta-wing baffles have the potential for energy savings at low Re ≤ 6000, indicated by the APF beyond unity. Full article