Search Results (734)

Gusts have a significant impact on aircraft and need to be analyzed through flight simulations. The solution for time-domain gust aerodynamic forces stands as a pivotal stage in this process. With the increasing demand for flight simulations within gusty environments, traditional methods related to gust aerodynamics cannot fail to balance computational accuracy and efficiency. A method that can be used to quickly and accurately calculate the time-domain gust aerodynamic force is needed. This study proposes the fitting strip method, a gust aerodynamic force solution method that is suitable for real-time flight simulations. It only requires the current and previous gust information to calculate the aerodynamic force and is suitable for different configurations of aircraft and different kinds of gusts. Firstly, the fitting strip method requires the division of fitting strips and the calculation of the aerodynamic force under calibration conditions. In this study, the double-lattice method and computational fluid dynamics are used to calculate the aerodynamic force of the strips. Then, the amplitude coefficients and time-delay coefficients are obtained through a fitting calculation. Finally, the coefficients and gust information are put into the formula to calculate the gust aerodynamic force. An example of a swept wing is used for validation, demonstrating congruence between the computational results and experimental data across subsonic and transonic speeds, which proves the accuracy of the fitting strip method in both discrete gusts and continuous gusts. Compared with other methods, the fitting strip method uses the shortest time. Furthermore, the results of a calculation for normal-layout aircraft show that this method avoids the shortcomings of the rational function approximation method and is more accurate than the gust grouping method. Concurrently, gust aerodynamic force calculations were performed on aircraft with large aspect ratios and used in a real-time flight simulation. Full article

This study describes the use of artificial intelligence to predict the aerodynamic properties of wind turbine profiles. The goal was to determine the lift coefficient for an airfoil using its geometry as input. Calculations based on XFoil were taken as a target for the predictions. The lift coefficient for a single case scenario was set as a value to find by training an algorithm. Airfoil geometry data were collected from the UIUC Airfoil Data Site. Geometries in the coordinate format were converted to PARSEC parameters, which became a direct feature for the random forest regression algorithm. The training dataset included 60% of the base dataset records. The rest of the dataset was used to test the model. Five different datasets were tested. The results calculated for the test part of the base dataset were compared with the actual values of the lift coefficients. The developed prediction model obtained a coefficient of determination ranging from 0.83 to 0.87, which is a good prognosis for further research. Full article

This paper is the second in a two-part series presenting preliminary results on a passively controlled wind turbine rotor system using a flexible curved blade concept. Building on the initial findings, this segment explores the application of glass-fiber-reinforced polymer (GFRP) composites with strategically oriented layers to enhance blade flexibility and aerodynamic performance and ensure operational safety. Previously, we demonstrated that flexible blades fabricated from isotropic materials with an NACA4415 airfoil profile could self-regulate rotor RPM and power output in response to aerodynamic loads, offering a glimpse of controlled operational behavior, in contrast to straight blades of similar material geometry and aerodynamic characteristics. However, they did not fully meet the design objectives, particularly in achieving nominal power at the intended wind speeds and in safely halting operation at high wind speeds. The current study employs a GFRP blade with a simpler, flat geometry due to manufacturing constraints, diverging from traditional airfoil contours to focus on material behavior under aerodynamic loads. Despite these changes, the blade exhibited all desired operational characteristics: quick startup, stable power output across operational wind speeds, and effective shutdown mechanisms at high speeds. This success illustrates the potential of passively controlled blades designed with appropriately oriented composite layers. Challenges with load application methods—that were identified in the first installment—were addressed by adopting a generator connected to a rheostat, offering improved control over load variations compared to the mechanical brakes used previously. This advancement enabled more consistent data collection, particularly at lower Tip–Speed Ratio (TSR) values, although real-time control for maximum power point tracking was still out of reach. These findings not only confirm the effectiveness of the flexible blade concept but also highlight the need for further refinement in blade design and testing methodology to optimize performance and ease of manufacturing. Future work will continue to refine these designs and explore their scalability and economic viability for broader applications in wind energy technology and in particular to those of small Wind Energy Converter Systems (WECSs). Full article

With the gradual increase in the maturity of wind energy technology, floating offshore wind turbines have progressively moved from small-capacity demonstrations to large-capacity commercial applications. As a direct component of wind turbines used to capture wind energy, an increase in the blade length directly leads to an increase in blade flexibility and a decrease in aerodynamic performance. Furthermore, if the floater has an additional six degrees of freedom, the movement and load of the blade under the combined action of wind and waves are more complicated. In this work, two types of semi-submersible wind turbines with different capacities are used as the research objects, and the load and motion characteristics of the blades of these floating offshore wind turbines are studied. Through the analysis of the simulation data, the following conclusions are drawn: with the increase in the capacity of the wind turbine, the flexible deformation of the blade increases, the movement range of the blade tip becomes larger, the blade root load increases, and the power fluctuation is more obvious. Compared with the bottom-fixed wind turbine, the flexible blade deformation of the floating offshore wind turbine is smaller; however, the blade root load is more dispersed, and the power output is more unstable and lower. Full article

This study proposes the use of light detection and ranging (LiDAR) remote sensing (RS) to support morphometric research for estimating the aerodynamic roughness length ($z_0$ ) of building placement on various scales. A LiDAR three-dimensional point cloud (3DPC) data processing graphical user interface (GUI) was developed to explore the $z_0$ and related urban canopy parameters (UCPs) in the Incheon metropolitan area in South Korea. The results show that multi-scale urban aerodynamic roughness exploration is viable and can address differences in urban building data at various spatial resolutions. Although validating morphological multi-scale UCPs using dense tall towers is challenging, emerging low-cost and efficient methods can serve as substitutes. However, further efforts are required to link the measured $z_0$ to building form regulations, such as floor area ratio, and expand RS research to obtain more quantitative and qualitative knowledge. Full article

This paper proposes a systematic approach for identifying the translational dynamics of a novel two-layer octocopter. Initially, we derive the non-linear theoretical dynamic model of the conventional octocopter using the Newton–Euler formulation, aimed at obtaining a simplified model suitable for tuning PID gains necessary for controller implementation. Following this, a controller is designed and tested in the Matlab/Simulink environment to ensure stable flight performance of the octocopter. Subsequently, the novel octocopter prototype is developed, fabricated, and assembled, followed by a series of outdoor flight tests conducted under various environmental conditions to collect data representing the flight characteristics of the two-layer vehicle in different scenarios. Based on the data recorded during flights, we identify the transfer functions of the translational dynamics of the modified vehicle using the prediction error method (PEM). The empirical model is then validated through different flight tests. The results presented in this study exhibit a high level of agreement and demonstrate the efficacy of the proposed approach to predict the octocopter’s position based only on motor inputs and initial states of the system. Despite the inherent non-linearity, significant aerodynamic interactions, and strongly coupled nature of the system, our findings highlight the robustness and reliability of the proposed approach, which can be used to identify the model of any type of multi-rotor or fixed-wing UAV, specifically when you have a challenging design. Full article

Large-eddy and direct numerical simulations generate vast data sets that are challenging to interpret, even for simple geometries at low Reynolds numbers. This has increased the importance of automatic methods for extracting significant features to understand physical phenomena. Traditional techniques like the proper orthogonal decomposition (POD) have been widely used for this purpose. However, recent advancements in computational power have allowed for the development of data-driven modal reduction approaches. This paper discusses four applications of deep neural networks for aerodynamic applications, including a convolutional neural network autoencoder, to analyze unsteady flow fields around a circular cylinder at Re = 100 and a supersonic boundary layer with Tollmien–Schlichting waves. The autoencoder results are comparable to those obtained with POD and spectral POD. Additionally, it is demonstrated that the autoencoder can compress steady hypersonic boundary-layer profiles into a low-dimensional vector space that is spanned by the pressure gradient and wall-temperature ratio. This paper also proposes a convolutional neural network model to estimate velocity and temperature profiles across different hypersonic flow conditions. Full article

The thermodynamic turbulence structure of compressible aerodynamic flows is often characterised by the correlation coefficient of entropy with pressure or temperature. We study entropy fluctuations $s^{\prime }$ and their correlations with the fluctuations of the other thermodynamic variables in compressible turbulent plane channel flow using dns data. We investigate the influence of the hcb (Huang–Coleman–Bradshaw) friction Reynolds number ($100⪅R{e}_{{\tau }^{★}}⪅1000$) and of the centreline Mach number ($0.3⪅{\overline{M}}_{{\mathrm{CL}}_x}⪅2.5$) on the magnitude and location of the peak of the root-mean-square $s_{\mathrm{rms}}^{\prime }$. The complete series expansions of $s^{\prime }$ with respect to the fluctuations of the basic thermodynamic variables (pressure p, density $\rho$ and temperature T) are calculated for the general case of variable heat-capacity $c_p\left(T\right)$ thermodynamics. The correlation coefficients of $s^{\prime }$ with the fluctuations of the basic thermodynamic quantities ($c_{s^{\prime }{p}^{\prime }}$, $c_{s^{\prime }{\rho }^{\prime }}$, $c_{s^{\prime }{T}^{\prime }}$), for varying $(R{e}_{{\tau }^{★}},{\overline{M}}_{{\mathrm{CL}}_x})$, are studied. Insight on these correlations is provided by considering the probability density function (pdf) of s′ and its joint pdfs with the other thermodynamic variables. Full article

To overcome the time-consuming drawbacks of Computational Fluid Dynamics (CFD) numerical simulations, this paper proposes a hybrid model named PA-TLA (parallel architecture combining a TCN, LSTM, and an attention mechanism) based on the concept of intelligent aerodynamics and a parallel architecture. This model utilizes CFD data to drive efficient predictions of aircraft wake evolution at different initial altitudes during the approach phase. Initially, CFD simulations of continuous initial altitudes during the approach phase are used to generate aircraft wake evolution data, which are then validated against real-world LIDAR data to verify their reliability. The PA-TLA model is designed based on a parallel architecture, combining Long Short-Term Memory (LSTM) networks, Temporal Convolutional Networks (TCNs), and a tensor concatenation module based on the attention mechanism, which ensures computational efficiency while fully leveraging the advantages of each component in a parallel processing framework. The study results show that the PA-TLA model outperforms both the LSTM and TCN models in predicting the three characteristic parameters of aircraft wake: vorticity, circulation, and Q-criterion. Compared to the serially structured TCN-LSTM, PA-TLA achieves an average reduction in mean squared error (MSE) of 6.80%, in mean absolute error (MAE) of 7.70%, and in root mean square error (RMSE) of 4.47%, with an average increase in the coefficient of determination (R²) of 0.36% and a 35% improvement in prediction efficiency. Lastly, this study combines numerical simulations and the PA-TLA deep learning architecture to analyze the near-ground wake vortex evolution. The results indicate that the ground effect increases air resistance and turbulence as vortices approach the ground, thereby slowing the decay rate of the wake vortex strength at lower altitudes. The ground effect also accelerates the dissipation and movement of vortex centers, causing more pronounced changes in vortex spacing at lower altitudes. Additionally, the vortex center height at lower altitudes initially decreases and then increases, unlike the continuous decrease observed at higher altitudes. Full article

This study investigates the impact of wind shear on the flight dynamics of commercial aircraft where C* and C*U control laws are employed during the approach phase. Given the high incidence of flight accidents during takeoff and landing attributed to wind shear, this research aims to enhance aviation safety by analyzing control law behavior under varying wind shear conditions. A nonlinear flight simulation model was developed, utilizing aerodynamic and engine data from a B737, to explore the aircraft’s response to different wind shear intensities. The simulation analysis was used to compare the response of the aircraft with C* and C*U controllers, respectively, under different wind shear, and to evaluate the effectiveness of its stability enhancement in wind shear. It was found that in most cases, the controller can achieve a good stabilization effect, but in some cases of wind fields, the aircraft suffered more significant oscillation. Full article

Tautosyllabic segment sequences exhibit greater gestural overlap than heterosyllabic ones. In Spanish, it is presumed that word-final consonants followed by a word-initial vowel undergo resyllabification, and generative phonology assumes that canonical CV.CV# and derived CV.C#V onsets are structurally identical. However, recent studies have not found evidence of this structural similarity in the acoustics. The current goal is to investigate anticipatory and carryover vowel nasalization patterns in tautosyllabic, heterosyllabic, and resyllabified segment sequences in Spanish. Nine native speakers of Peninsular Spanish participated in a read-aloud task. Nasal airflow data were extracted using pressure transducers connected to a vented mask. Each participant produced forty target tokens with CV.CV# (control), CVN# (tautosyllabic), CV.NV# (heterosyllabic), and CV.N#V (resyllabification) structures. Forty timepoints were obtained from each vowel to observe airflow dynamics, resulting in a total of 25,200 datapoints analyzed. Regarding anticipatory vowel nasalization, the CVN# sequence shows an earlier onset of nasalization, while CV.NV# and CV.N#V sequences illustrate parallel patterns among them. Carryover vowel nasalization exhibited greater nasal spreading than anticipatory nasalization, and vowels in CV.NV# and CV.N#V structures showed symmetrical nasalization patterns. These results imply that syllable structure affects nasal gestural overlap and that aerodynamic characteristics of vowels are unaffected across word boundaries. Full article

Most previously studies had considered that plant fungal disease spread widely and quickly by airborne fungi spore. However, little is known about the release dynamics, aerodynamic diameter, and pathogenicity threshold of fungi spore in air of the greenhouse environment. Grape gray mold is caused by Botrytis cinerea; the disease spreads in greenhouses by spores in the air and the spore attaches to the leaf and infects plant through the orifice. In this study, 120 μmol/L propidium monoazide (PMA) were suitable for treatment and quantitation viable spore by quantitative real-time PCR, with a limit detection of 8 spores/mL in spore suspension. In total, 93 strains of B. cinerea with high pathogenicity were isolated and identified from the air samples of grapevines greenhouses by a portable sampler. The particle size of B. cinerea aerosol ranged predominately from 0.65–3.3 μm, accounting for 71.77% of the total amount. The B. cinerea spore aerosols were infective to healthy grape plants, with the lowest concentration that could cause disease being 42 spores/m³. Botrytis cinerea spores collected form six greenhouse in Shandong Province were quantified by PMA-qPCR, with a higher concentration (1182.89 spores/m³) in May and June and a lower concentration in July and August (6.30 spores/m³). This study suggested that spore dispersal in aerosol is an important route for the epidemiology of plant fungal disease, and these data will contribute to the development of new strategies for the effective alleviation and control of plant diseases. Full article

In the frame of the H2020 MORE&LESS project co-funded by European Commission, a test campaign for a hypersonic vehicle demonstrator took place at the INCAS Trisonic Facility. CFD analysis was used to quantify the effects of the wind tunnel model support, the closed engine nacelle, and to perform the Reynolds number extrapolation. Three sets of simulations were used in order to generate the corrections. The wind tunnel configuration with sting, sting cavity, and closed nacelle was used as the baseline, with the aim of matching the experimental results as precisely as possible. A configuration with a flow-through nacelle and the shock cone in the appropriate position for each Mach number and no sting or cavity was used to determine the effect of the sting and the closed nacelle. For the Reynolds extrapolation, a 1:1 model was used, with the boundary conditions deriving from the theoretical trajectory of the vehicle. The CFD results for the wind tunnel configuration closely align with the experimental data. Significant differences between the three configurations can be observed just for the pitching moment, and those are caused by the presence of the sting and the open nacelle. The difference in Reynolds number does not seem to have a significant effect on the aerodynamic coefficients. 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

An experiment-supported simulation process chain is set up to perform numerical forced response analyses on a transonic high-pressure compressor front stage at varying operating conditions. A wake generator is used upstream of the rotor to excite a specific resonance within the operating range of the compressor. Thereby, extensive aerodynamic and structural dynamic experimental data, obtained from state-of-the-art rig testing at the Transonic Compressor Darmstadt test facility at the Technical University of Darmstadt, are used to validate numerical results and ensure realistic boundary conditions. In the course of this, five-hole-probe measurements at steady operating conditions close to the investigated resonance enable a validation of the steady aerodynamics. Subsequently, numerically obtained aeroelastic quantities, such as resonance frequency, and damping, as well as maximum alternating blade stresses and tip deflections, are compared to experimental blade tip timing data. Experimental trends in damping can be confirmed and better explained by considering numerical results regarding the aerodynamic wall work density and secondary flow phenomena. The influence of varying loading conditions on the resonance frequency is not observed as distinctly in numerical, as in experimental results. Generally, alternating blade stresses and deflections appear to be significantly lower than in the experiments. However, similar to the aerodynamic damping, numerical results contribute to a better understanding of experimental trends. The successive experimental validation shows the capabilities of the numerical forced response analysis setup and enables the highlighting of challenges and identification of potential further adaptations. Full article