Aerodynamic Parameters Research Articles

Buffeting performance of long-span bridges with different span affected by parametric typhoon wind

Currently, typhoon-related performance of long span bridges usually focus on a specific wind record such as wind speed and turbulence intensity during a full typhoon, however, the inter-correlation among wind characteristic parameters under typhoon wind climate is ignored. The existing investigation about structural responses during typhoon attacks are still limited at case-study analysis, and hardly provide a generalized framework to evaluate the structural performance especially for typhoon landing whole process. This study utilizes the measured wind speeds of the strong typhoon "Hagupit" to establish a unified typhoon parametric model, during which the correlation of typhoon wind parameters including angle of attack (AoA), turbulence intensity, integral length scale and mean wind speed were taken into consideration. The measured typhoon process charactered with center-through effect with M-type average wind speed curve. Furthermore, the structural performance of long-span bridges with different spans from 1500 m to 2500 m main span was systematically studied. The aerodynamic parameters of the bridge deck section, including the aerostatic coefficients, flutter derivatives at different AoAs, and aerodynamic admittance under different oncoming flow conditions were identified through wind tunnel tests. Finally, the wind-induced buffeting performance was calculated by the buffeting frequency domain algorithm, showing various structural wind effect characteristics during the typhoon landing whole process. The maximal buffeting response is not necessarily related with the wind speed, and other wind characteristics especially turbulence intensity and AoA, etc. also affect on the results.

Hypersonic Flow past LD-Haack Series, Parabolic Series, Power Series Nose Cone: A Comparative Study

This research paper presents a detailed aerodynamic analysis of three rocket nose cone designs—LD-Haack, Parabolic, and Power Series—under hypersonic conditions ranging from Mach 5 to Mach 12. Using advanced Computational Fluid Dynamics (CFD) simulations in ANSYS Fluent, the study focuses on key aerodynamic parameters, including drag force, drag coefficient, velocity, pressure, and temperature distributions. The results indicate that the Parabolic Nose Cone offers the most favorable aerodynamic performance, with the lowest drag force and drag coefficient across all Mach numbers. This superior performance can be attributed to its ability to streamline airflow and minimize boundary layer separation, effectively reducing pressure drag and limiting the onset of turbulent wake regions. In contrast, the LD-Haack Series Nose Cone, though designed to minimize wave drag at supersonic speeds, shows moderate drag at hypersonic velocities due to its less optimal control of boundary layer behavior. The Power Series Nose Cone, despite its highly tapered shape, experiences the highest drag. This is largely caused by increased flow separation and turbulent wake generation, which exacerbate pressure drag, particularly at higher Mach numbers. These findings highlight the critical influence of nose cone geometry on aerodynamic efficiency and emphasize the importance of optimizing designs for hypersonic applications. This study provides valuable insights for aerospace engineers seeking to reduce drag and improve performance in high-speed flight scenarios.

Quaternion-based non-singular nonlinear impact angle guidance for three-dimensional engagements

This paper proposes a three-dimensional impact angle-constrained nonlinear guidance strategy against different types of targets. To avoid the occurrence of singularities, in Euler angle-based approaches, the development of this guidance strategy is solely based on quaternion dynamics. An explicit relationship between the quaternions representing impact orientation and line-of-sight orientation at the time of collision is derived. Based on the obtained relation, a guidance law is derived using a sliding mode control technique to track the desired line-of-sight orientation for target interception. The performance of the proposed guidance strategy is evaluated for constant-speed and different time-varying-speed interceptor models accounting for the effect of varying aerodynamic parameters on interceptor speed. The numerical simulations performed show satisfactory results for all engagements, validating the efficacy and robustness of the proposed guidance law.

A Cooperative Control Method for Wide-Range Maneuvering of Autonomous Aerial Refueling Controllable Drogue

In the realm of autonomous aerial refueling missions for unmanned aerial vehicles (UAVs), the controllable drogue represents a novel approach that significantly enhances both the safety and efficiency of aerial refueling operations. This paper delves into the issue of wide-range maneuverability control for the controllable drogue. Initially, a dynamic model for the variable-length hose–drogue system is presented. Based on this, a cooperative control framework that synergistically utilizes both the hose and the drogue is designed to achieve wide-range maneuverability of the drogue. To address the delay in hose retrieval and release, an open-loop control strategy based on neural networks is proposed. Furthermore, a closed-loop control method utilizing fuzzy approximation and adaptive error estimation is designed to tackle the challenges posed by modeling inaccuracies and uncertainties in aerodynamic parameters. Comparative simulation results show that the proposed control strategy can make the drogue maneuvering range reach more than 6 m. And it can accurately track the time-varying trajectory under the influence of model uncertainty and wind disturbance with an error of less than 0.1 m throughout. This method provides an effective means for achieving wide-range maneuverability control of the controllable drogue in autonomous aerial refueling missions.

Aerodynamic Performance Prediction for Wide-Incidence Turbines Using Graph Neural Network Models Driven by Small-Scale Experimental Data

Abstract To rapidly and accurately predict turbine rotor blade losses within a wide range of incidences (−50–30 deg), graph neural networks (GNNs) are utilized to predict the aerodynamic parameters of two-dimensional turbine blades based on a small-scale experimental dataset. By comparing the backpropagation neural network (BPnn) model and computational fluid dynamics (CFD) results, it is demonstrated that GNNs with appropriately designed graph structures can accurately and quickly predict high-fidelity aerodynamic parameters based on limited experimental data. Unlike traditional data-driven modeling approaches, two innovative methods for improving blade profiles into graph structures are proposed. Relatively few input features are used to comprehensively and effectively represent the turbine blade profile by applying blade profile features in the GNN. The research findings indicate that due to the graph structure, which divides the turbine blade profile into five nodes based on five key points, coupled with high-fidelity experimental data and the unique weight updating mechanism of the graph attention network (GAT) model, the GAT-5 model exhibits the best performance among the studied models. Additionally, when assessing unknown validation blade profiles, the GAT-5 model maintains an absolute error below 6% at an incidence angle of 30 deg compared to the experimental results.

ВИЗНАЧЕННЯ АЕРОДИНАМІЧНИХ ХАРАКТЕРИСТИК ЛІТАЛЬНОГО АПАРАТА З НАДЗВУКОВИМ ШВИДКОСТЯМИ ПОЛЬОТУ

The aircraft aerodynamic characteristics at supersonic flight modes can be determined with a high level of accuracy through testing the aircraft in wind tunnels or through time-consuming three-dimensional and analytical computational methods. However, in certain cases when the aircraft aerodynamic characteristics are already known within a given Mach number range for supersonic flight, it is possible to develop a relatively simple mathematical model for the aircraft aerodynamic characteristics at supersonic speeds using the aerodynamic properties of the supersonic wing leading edge for flight speeds Mf ≥ 1.2M. The object of the study is the aircraft aerodynamic characteristics at supersonic flight speeds. The subject of the study is the impact of the aircraft geometric features on the mathematical model, which is used to determine its aerodynamic characteristics in the supersonic flight speed range. The study hypothesizes that to determine the aerodynamic characteristics of an aircraft at Mf ≥ 1.2, it is sufficient to identify the values of the aircraft aerodynamic parameters at a flight speed of Mf =1.2 and then use aerodynamic analytical dependencies for the supersonic wing leading edge to determine these parameters at Mf ≥ 1.2. A mathematical model of the aircraft aerodynamic characteristics in the supersonic flight speed range was developed. Coefficients of drag polar and zero-lift drag for the reference mode Mf = 1.2 have been identified by the developed mathematical model. Then, the Mach number range for the aerodynamic characteristics of the NASA 1044 configuration has been extended to supersonic speeds of Mf = 1.8…4.0. The resultsof the aerodynamic calculations, obtained in the form of dependencies of the drag polar and zero-lift drag coefficients on Mach number, and the aircraft polar plot, have been compared with known NASA data for the 1044 configuration aircraft. The average modeling error of the aircraft aerodynamic characteristics in the supersonic speed range is less than 3%.

Integration of deep learning and computational fluid dynamics for rapid aerodynamic force prediction of compressor blades

The distribution of flow fields around compressor blades is crucial for the performance and reliability of aircraft engines. To effectively obtain aerodynamic loads, this study combines deep learning with computational fluid dynamics (CFD) to develop an efficient aerodynamic prediction model. Initially, CFD is used to acquire detailed flow field data for the blade surface and its surrounding environment. Subsequently, a distance field parameterization method is applied to process the blade geometry, and deep learning models are used to capture the complex relationship between blade geometry and aerodynamic parameters with high precision. The results indicate that the proposed model can predict aerodynamic loads within seconds with a mean squared error of less than 2%. Compared to traditional parameterization methods and other deep learning approaches, this model exhibits higher accuracy. The findings highlight the effectiveness of integrating deep learning with CFD to enhance aerodynamic predictions and provide a promising approach for future aerodynamic modeling research.

Analysis of the efficacy of non-surgical treatment mainly focus on voice therapy and it's influencing factors in patients with unilateral vocal fold paralysis

Objective:Retrospective analysis of the efficacy and it's influencing factors of non-surgical treatment mainly focus on voice therapy for patients with unilateral vocal fold paralysis. Methods:The retrospective study includes 57 patients who were diagnosed with unilateral vocal fold paralysis and presented with hoarseness as their main complaint at the Department of Voice Medicine, Zhongshan Hospital of Xiamen University from August, 2021 to August, 2023. Judging the efficacy of non-surgical treatment mainly focus on voice therapy through changes in acoustic, aerodynamic, and laryngoscopic parameters; Analyze the relationship between patients' age, gender, duration of disease, cause of nerve injury, type of nerve injury, side of nerve injury and efficacy of non-surgical treatment. Results:After non-surgical treatment mainly focused on voice therapy, there were statistically significant differences（P<0.01） in the changes of vocal fold bow, glottal gap, glottal compression, loudness, Jitter, Shimmer, IC, and NC parameters. There is a statistically significant correlation between the duration of the disease and changes in glottal gap, Shimmer, and IC（P<0.05）, the side of nerve injury can affect changes of glottal gap and NC（P<0.05）. Conclusion:Non-surgical treatment mainly focused on voice therapy has a good efficacy on patients with unilateral vocal fold paralysis. The duration of the disease and the side of nerve injury may affect the efficacy.

Adaptive PSO-SO algorithm with Sobol sequence for aerodynamic physical parameter identification of projectiles

In the domain of aerodynamic physical parameter identification, conventional optimization algorithms are often limited by falling into local optima. To overcome this limitation, a novel adaptive PSO-SO algorithm based on Sobol sequences (SAPSO-SO) algorithm is proposed in this study. The algorithm integrates particle swarm optimization algorithms and snake optimization algorithms, utilizing Sobol sequences for initialization, which enhances the global search and local development ability of the algorithm by adaptively adjusting the inertia weights and learning factors. In addition, this study introduced a local optimal discriminant mechanism and a local search function to further enhance the optimization performance of the algorithms. In this study, the small interval constant method was used to subdivide the trajectory, relying on the three-degree-of-freedom ballistic model to identify the starting ballistic parameters and aerodynamic physical parameters of each small interval. The performances of the snake optimization algorithm, particle swarm optimization algorithm, C-K method, and SAPSO-SO algorithm in the identification of ballistic physical parameters were compared using the full ballistic simulation data of a high-speed rotating projectile as measurement data. The results show that the SAPSO-SO algorithm demonstrates excellent accuracy and effectiveness, especially in noisy simulation data, where its recognition accuracy is improved by 7.79% over the C-K method, highlighting its superior anti-noise performance and global optimization capability. It is comprehensively analyzed that the SAPSO-SO algorithm has strong global optimization potential in theory and shows a high degree of accuracy and stability in practical applications, independent of the selection of initial parameters.

Research on compressor cascade flow field modeling method based on finite volume flux-informed neural network

For compressor cascade flow field modeling, there exists strong velocity shear in the leading edge separation flow, boundary layer, and wake, which leads to increased modeling errors. To improve the accuracy of the flow field modeling method, this paper introduces the concept of numerical flux from the finite volume method into the loss function to implement Euler equation physics-informed learning, and a finite volume flux-informed neural network (FVFI-net) is constructed. Selecting a high-load, large-turning-angle compressor cascade as the study object, a comparative analysis is conducted on the advantages and disadvantages of purely data-driven, weak physical constraint, and finite volume flux-informed methods in compressor cascade flow field modeling. The study found that compared to purely data-driven and weak physical constraint methods, FVFI-net can reduce the average error of aerodynamic parameters in the flow field by approximately 45.6% and 29.5%, respectively, at a 0° angle of attack. For the flow separation problem occurring at the suction side leading edge and the blade wake area caused by a 5° angle of attack, FVFI-net can effectively reduce modeling errors near the leading edge, in the wake region, and near the periodic boundaries, thus reducing the average error of the aerodynamic parameters of the flow field by about 49.2%and 31.3%, respectively, compared to pure data-driven and weak physical constraint methods.

Flow field reconstruction of compressor blade cascade based on deep learning methods

In the design process of compressors, calculating the S1 flow surface involves solving the Navier-Stokes equations, which results in slow convergence and makes determining cascade characteristics time-consuming. However, deep learning offers significant advantages in flow field reconstruction by not only automatically extracting complex flow features and reducing prediction time but also providing high accuracy in reconstruction. This paper implements the rapid reconstruction of the compressor S1 flow surface cascade flow field using two deep learning models: U-Net and 1D-CNN. Using a double-circular arc airfoil as an example, we selected four key design parameters that define the geometry and position of the airfoil, ultimately designing 5,292 sets of cascade geometries. By performing batch meshing and CFD simulations, we built a cascade flow field dataset. The U-Net neural network uses design parameters as input and outputs the aerodynamic distribution of the cascade flow field. After training, it can directly predict the flow field based on the design parameters. Since the U-Net model cannot directly obtain the aerodynamic parameter distribution and flow field aerodynamic coefficients on the airfoil surface, a 1D-CNN model is used as a complementary approach. The 1D-CNN model takes the design parameters as input and outputs the aerodynamic parameter distribution on the airfoil surface and the flow field aerodynamic coefficients. The prediction results show that the U-Net model achieves an average relative error of less than 1% in cascade flow field reconstruction, while the 1D-CNN model achieves an average relative error of less than 1% in predicting the pressure recovery coefficient and less than 2% in predicting the total pressure loss coefficient. This study presents a method for the rapid reconstruction of compressor blade cascade flow fields, which helps improve design efficiency and shorten the design cycle.

An enhanced Standardized Precipitation–Evapotranspiration Index (SPEI) drought-monitoring method integrating land surface characteristics

Abstract. Atmospheric evaporative demand is a key metric for monitoring agricultural drought. Existing ways of estimating evaporative demand in drought indices do not faithfully represent the constraints imposed by land surface characteristics and become less accurate over nonuniform land surfaces. This study proposes incorporating surface vegetation characteristics, such as vegetation dynamics data, aerodynamic parameters, and physiological parameters, into existing potential-evapotranspiration (PET) methods. This approach is implemented across the continental United States (CONUS) for the period from 1981–2017 and is tested using a recently developed drought index, the Standardized Precipitation–Evapotranspiration Index (SPEI). We show that activating realistic maximum surface conductance and aerodynamic conductance could improve the prediction of soil moisture dynamics and drought impacts by 29 %–41 % on average compared to more simple, widely used methods. We also demonstrate that this is especially effective in forests and humid regions, with improvements of 86 %–89 %. Our approach only requires a minimal amount of ancillary data while allowing for both historical reconstruction and real-time drought forecasting. This offers a physically meaningful yet easy-to-implement way to account for vegetation control in drought indices.

Research on the aerodynamic characteristics of electrically controlled rotor under Parallel Blade Vortex Interaction using Lattice Boltzmann Method

An electrically controlled rotor (ECR), also known as a swashplateless rotor, employs a trailing edge flap (TEF) system for primary rotor control instead of a swashplate, demonstrating the significant potential in rotor vibration and noise reduction. To investigate the aerodynamic characteristics of the blade flap segment of the ECR under parallel blade vortex interaction, an aerodynamic analysis model based on the lattice Boltzmann method (LBM) is established using the D3Q27 lattice model. The model is validated against experimental data of both the airfoil with trailing edge flap and conventional airfoil under vortex interaction, showing that the LBM can effectively predict variations in aerodynamic loads under both conditions. Based on this model, the effects of different flap deflection angles and miss distances on the aerodynamic characteristics of the ECR under parallel BVI are analyzed. The results indicate that under strong vortex interaction, a region of flow separation forms due to the entrainment effect of the vortex and adverse pressure gradient. The small-scale vortex structure upstream of the flap can also be observed and is believed to contribute to the unsteady flow phenomena such as vortex structure splitting, development, and separation on the upper surface of the flap. The different flap deflection angles mainly affect the scale and type of vortex structures developed on the flap upper surface. As the miss distance increases, the interaction effect is significantly weakened compared to strong vortex interaction. However, as the vortex moves downstream along the airfoil lower surface, it entrains vorticity from the lower surface, ultimately forming a negative pressure region on the lower surface of the flap. The different flap deflection angles will influence the structural characteristics during the downstream motion of the vortex, which changes the size of the negative pressure region, causing differences in the magnitude of the variations in aerodynamic parameters.

Fatigue behavior of multi-row film cooling holes manufactured by lasers with different pulses under complex-temperature fields

This research investigates the fatigue behavior of multi-row film cooling holes produced by lasers with diverse pulse widths amid intricate thermal environments. Through laser drilling experiments, conjugate heat transfer simulations, and crystal plasticity finite element analyses, it explores the interplay of temperature and stress fields among multiple holes in these structures, and factors influencing fatigue damage and its severity. Additionally, it anticipates the fatigue fracture paths of multi-row film cooling hole structures. Findings reveal that while the drilling process and aerodynamic parameters significantly impact cooling effectiveness, their influence on cooling distribution is negligible. Fatigue damage distribution is shaped by structural imperfections from different processes, stress field interference among multiple holes, and material property alterations due to temperature changes. The extent of damage is primarily dictated by roundness errors resulting from the drilling process, with taper playing a minor role. Nonetheless, stress interference among multiple holes notably exacerbates stress concentration at the interference zone, leading to increased damage levels in film cooling holes crafted by picosecond lasers with minimal roundness errors. Moreover, in complex thermal environments, fatigue fracture paths of multi-row film cooling holes migrate and evolve contingent on temperature-induced shifts in material properties.

Energy harvesting from transverse galloping using a two-degree-of-freedom flow energy harvester

Abstract A two degree-of-freedom (2-DOF) galloping piezoelectric energy harvesting system where both oscillators are excited by the incoming flow is studied in this paper. A coupled lumped-parameter model is developed to simulate the electro-fluid-structural coupling behaviour assuming a quasi-steady aerodynamic flow field. The differential equations governing the dynamics of the lumped system are converted into nonlinear algebraic equations employing the harmonic balance method (HBM) and then solved using Newton’s method. The approximate analytical solutions are compared to the solutions obtained by numerical integration, and the results agree, both qualitatively and quantitatively. The solutions were subsequently used to investigate the effects of the bluff body dimension, mechanical, electrical, aerodynamic, and electromechanical parameters on the performance of the harvester and to illustrate how to optimise some of these parameters to reduce the cut-in wind speed and maximise the power output of the energy harvester. It will be shown that the energy harvesting performance could be significantly improved by introducing piezoelectric transducers on both oscillators and including both masses in the incoming flow. A comparative study between the proposed 2-DOF flow energy harvesting system, a single-degree-of-freedom (SDOF) galloping piezoelectric energy harvester (GPEH), and other configurations of 2-DOF GPEH shows that the present 2-DOF GPEH generates the largest power peak.

General framework for unsteady aerodynamic prediction of airfoils based on deep transfer learning

Analyzing the unsteady aerodynamic performance of airfoils under dynamic stall using computational fluid dynamics (CFD) is computationally intensive. Although deep learning models can quickly predict aerodynamic parameters, their generalization capability on a small-scale dataset is often poor. This paper presents a novel deep transfer learning (TL) framework that combines model-based and instance-based transfer methods, termed synergistic instance-model TL. This framework facilitates rapid predictions of unsteady aerodynamic performance for various airfoils and pitch oscillations from the small-scale dataset. The framework integrates the accelerated training speed of model-based methods with the dynamic dataset expansion benefits of instance-based approaches. Initially, a pre-trained Wasserstein-deep convolutional generative adversarial network (W-DCGAN) is developed, combining a convolutional neural network with a generative adversarial network to predict aerodynamic hysteresis loops for the SC1095 airfoil in the source domain. The framework then fine-tunes the pre-trained model and incorporates weighted source domain dataset into the small-scale target domain dataset, producing the transferred model W-DCGAN-TL. This approach significantly reduces prediction inaccuracies compared to model-based and non-TL methods when applied to the small-scale dataset. The framework's flexibility allows the use of pre-trained models and datasets from related aerodynamic problems to address issues with insufficient data. Consequently, it is expected to reduce the dependency on extensive datasets, enhance design efficiency, and minimize resource requirements.

Temperament and Voice Quality in Patients With Vocal Fold Nodules

BackgroundVocal fold nodules are most common in women and patients with vocal fold nodules represent the largest group in voice clinics. The prevalence of vocal fold nodules is particularly high in professions where the voice is used on a regular basis. The quality of the voice is influenced by a number of factors, including temperament, stress, and emotional state. These factors can influence the physiological conditions of phonation.The objective of this study was to assess the acoustic parameters of voice in patients with vocal nodules in comparison to healthy controls, and to determine whether voice quality is influenced by emotional state and coping with stress. MethodsA total of 32 patients admitted to the ENT Department of the University Medical School with voice disorders between March and June 2007 constituted the study group. All patients were found to have a vocal nodules on physical and stroboscopic examination. The control group consisted of 30 healthy individuals who did not report any voice disorders. All subjects underwent voice recordings in the voice laboratory. Following the completion of the voice evaluation form, anaerodynamic assessment (a, s, s/z-time), an index of vocal impairment, the Rosenbaum Schedule of Learned Resourcefulness (RLRS) and the Temperament and Characteristics Inventory (TEMPS-A), all subjects underwent further assessment. Acoustic analysis was conducted using the CSL program in MDVP and the Vocal Assessment component of Dr. Speech. ResultsThe decrease in MPT in the study group was statistically significant. There were statistically significant differences in the parameters MFo, Jitt, RAP, PPQ, SHdB, Shim, APQ, NHR, SPI from the MDVP, Jitter, Shim% from the voice assessment, and the perceptual rating (H, R, B) from Dr. Speech’s voice assessment analysis. The differences in the dimensions of anxious temperament and the examination of stress problem-solving strategies were significant between the study group and the control subjects. Differences in aerodynamic and acoustic parameters were found between disordered and healthy groups, as well as between individuals with different personalities. Overall, those with nodules were less likely to manage stress well than those without nodules. ConclusionThe study group and the control subjects showed significant differences in anxious temperament dimensions and stress problem-solving strategies. There were also differences in aerodynamic and acoustic parameters between the disordered and healthy groups, as well as between the groups with and without personality temperament differences. Overall, those with nodules were less likely to manage stress well than those without nodules. This finding indicates that stress management options are not effectively utilized in patients with vocal fold nodules. So, it might be a good idea to look into some kind of therapeutic approach and patient education for stress management.

Model compensation control of composite vertical take-off and landing UAV

Abstract The unmanned aerial vehicle (UAV) system for composite vertical take-off and landing (VTOL) is a complex, highly coupled, and nonlinear system which is sensitive to external disturbances and model uncertainties. The composite VTOL UAV system consists of a multi-rotor section and a fixed-wing section. To improve observation accuracy, the compensation function observer (CFO) uses a new structure that includes velocity information. The CFO is utilised to estimate the uncertainty and the external disturbances of the system model, which performs superior estimation accuracy compared to the extended state observer (ESO). In the modeling process of the VTOL UAV, the aerodynamic moment is calculated by means of the cross-product operation of force and force arm, which solves the problem of over-reliance on aerodynamic parameters in the traditional modeling approach. The controlled object is refined by CFO, and model compensation control (MCC) is used to realise the velocity and attitude control of the composite VTOL. The numerical simulation of MATLAB/Simulink and hardware-in-loop simulation (HIL) of Rflysim were implemented, and which were used to compare the MCC, active disturbance rejection control (ADRC), and proportion integration differentiation (PID). The simulation results confirm the superiority of MCC in controlling composite VTOL UAVs in terms of anti-disturbance and tracking speed.

Experimental and computational investigations of flexible membrane nano rotors in hover

With reduced size, the flight Reynolds number of the nano rotor decreases, leading to a sharp drop in the aerodynamic efficiency of the nano rotor. Therefore, improving the aerodynamic performance of the nano rotor at low Reynolds numbers through flow control methods becomes imperative. In this study, from the perspective of bionics, flexible materials are employed in nano rotor design. Seven different layouts of flexible membrane rotor blades are designed and fabricated. The influence of leading and trailing edge flexibility, as well as membrane occupancy ratio on rotor blade propulsion characteristics, is explored through propulsion performance tests in hover.Results show that among several layouts proposed in this study, the layout with both reinforced leading and trailing edges of the flexible membrane nano rotor blade exhibits excellent propulsive performance. However, the propulsion performance of the flexible membrane rotors doesn't vary linearly with the ratio of membrane area to the whole rotor area. The appropriate ratio or flexibility can increase the propulsive performance of the rotor, especially at medium and high collective angles. At 7000 RPM and a 20° collective angle, the Figure of Merit of the flexible membrane nano rotor increases up to 4.2% when comparing with the nano rotor without membrane. This improvement becomes more significant with higher collective angles. The structural natural vibration characteristics of each flexible membrane with different layouts are analyzed through modal tests, ensuring the accuracy of the finite element model for flexible membrane rotors. Numerical analysis of the fluid-structure coupling of a flexible membrane rotor with different layouts indicates that rotor structural vibrations is highly consistent with fluctuation of aerodynamic parameters. The deformation of the flexible membrane under aerodynamic forces enhances local blade camber, but reduces angles of attack. This, subsequently, minimizes the size of laminar separation bubbles and the intensity of the blade tip vortices at high collective angles. Consequently, rotor power coefficients decrease, and overall aerodynamic performance improves.

Acoustic, aerodynamic, and vibrational effects of ventricular folds adduction in an ex vivo experiment.

The excessive adduction of ventricular folds has been observed in patients with dysphonia and professional singers. Whether these changes in the ventricular folds are the cause or just a result of disease progression remains unclear, and their potential pathological and physiological implications are yet to be determined. This study aimed to examine the impact of different degrees of ventricular adduction on acoustics, aerodynamics, and vocal fold vibration. The excised models of mild and severe ventricular adduction were established. We recorded the vibration pattern of vocal folds and ventricular folds and measured acoustic metrics, including fundamental frequency (F0), Jitter, Shimmer, harmonic-to-noise ratio (HNR), and sound pressure level (SPL). Furthermore, we evaluated the aerodynamics index through phonation threshold pressure (PTP), phonation instability pressure (PIP), mean flow rate (MFR), phonation threshold flow (PTF), and phonation instability flow (PIF). Irregular vibrations of the ventricular fold were observed during ventricular adduction. Notably, mild and severe ventricular adduction conditions showed a significant increase in PTP, Shimmer, and Jitter, whereas MFR, PIF, and HNR decreased compared with the control condition. Ventricular adduction leads to the deterioration of acoustic and aerodynamic parameters. The aperiodic and irregular vibration of the ventricular folds may be responsible for this phenomenon, although further experiments are warranted. Understanding the functioning of ventricular folds can be beneficial in directing the treatment of muscle tension dysphonia and improving voice training techniques.Level of evidence: level 4.