Aerodynamic Method Research Articles

Utilizing Artificial Neural Networks for Entry Vehicle Aerodynamic Characterization

Determining the dynamic stability of blunt body entry vehicles is a persistent engineering challenge, particularly in the low supersonic to subsonic flight regime where the behavior of the unsteady wake is a primary contributor. Dynamic stability quantities are determined by fitting measurements of a ballistic range campaign or a computational fluid dynamics (CFD) computational experiment to an assumed functional form in order to regress quasi-static stability coefficients. However, this data reduction process has many implicit assumptions that may not hold. This paper explores novel alternatives to the established methods for modeling blunt body aerodynamics. A six-degree-of-freedom CFD-in-the-loop flight model is used to run “virtual ballistic range tests,” fully capturing the relevant flow physics. Feed-forward and time-delay neural network models are fitted to the time-series trajectory and aerodynamic results, which can then be used to predict aerodynamic forces and moments. These models do not have a prescribed functional form and do not assume linearized aerodynamics. The models are evaluated for goodness-of-fit in their aerodynamic and trajectory prediction. The feed-forward neural network model resulted in a better prediction of the virtual ballistic range tests than a traditional database. The time-delay network had good open-loop performance but suffered from closed-loop instability.

Real-Time Ground Aeroservoelastic Test for Slender Vehicles Based on Condensed Aerodynamic Force Loading

Slender vehicles often encounter significant aeroservoelastic challenges due to their low elastic mode frequencies and wide servo control system bandwidths. Traditional analysis methods have limitations, including low modeling accuracy for real vehicles in numerical methods, scale errors in wind tunnel tests, and significant risks in flight tests. The ground aeroelastic stability test is an innovative experimental method designed to address these challenges. This novel method employs shakers to apply condensed unsteady aerodynamic forces in real-time to actual vehicles, serving for both the ground flutter test (GFT) and the ground aeroservoelastic test (GAT). While extensive research exists on the GFT, there is limited exploration of the GAT. For the GAT of a slender vehicle in this paper, the condensed aerodynamic forces are calculated using the quasi-steady aerodynamic derivative method. An improved, partially decoupled inverse model controller is designed for force control, guided by an assessment of coupling strength among different shakers. Ground experiments under various flight control laws and flight dynamic pressures produce accurate results. Numerical simulations and experimental results demonstrate high precision, with excitation force amplitude deviations within ±10% and phase deviations within ±5° within the frequency range relevant to aeroservoelastic stability.

Comparison of Unsteady Low- and Mid-Fidelity Propeller Aerodynamic Methods for Whirl Flutter Applications

Aircraft configurations with propellers have been drawing more attention in recent times, partly due to new propulsion concepts based on hydrogen fuel cells and electric motors. These configurations are prone to whirl flutter, which is an aeroelastic instability affecting airframes with elastically supported propellers. It commonly needs to be mitigated already during the design phase of such configurations, requiring, among other things, unsteady aerodynamic transfer functions for the propeller. However, no comprehensive assessment of unsteady propeller aerodynamics for aeroelastic analysis is available in the literature. This paper provides a detailed comparison of nine different low- to mid-fidelity aerodynamic methods, demonstrating their impact on linear, unsteady aerodynamics, as well as whirl flutter stability prediction. Quasi-steady and unsteady methods for blade lift with or without coupling to blade element momentum theory are evaluated and compared to mid-fidelity potential flow solvers (UPM and DUST) and classical, derivative-based methods. Time-domain identification of frequency-domain transfer functions for the unsteady propeller hub loads is used to compare the different methods. Predictions of the minimum required pylon stiffness for stability show good agreement among the mid-fidelity methods. The differences in the stability predictions for the low-fidelity methods are higher. Most methods studied yield a more unstable system than classical, derivative-based whirl flutter analysis, indicating that the use of more sophisticated aerodynamic modeling techniques might be required for accurate whirl flutter prediction.

Parametrization Effects of the Non-Linear Unsteady Vortex Method with Vortex Particle Method for Small Rotor Aerodynamics

The aim of this article is to investigate the parameter sensitivity of the (Non-Linear) Unsteady Vortex Lattice Method-Vortex Particle Method [(NL-)UVLM-VPM] with Particle Strength Exchange-Large Eddy Simulations (PSE-LES) method on a lower Reynolds number rotor. The previous work detailed the method, but introduced parameters whose influence were not investigated. Most importantly, the Vreman model coefficient was chosen arbitrarily and was not suitable to ensure stability for this lower Reynolds number rotor simulation. In addition, the previous work presented a consistency study where geometry and time discretization were refined simultaneously. The present article starts with a comparative literature review of potential methods used to solve the aerodynamics of an isolated hovering rotor. This review highlights the differences in modeling, discretizations, sensitivity analysis, validation cases, and the results chosen by the different studies. Then, a transparent and thorough parametric study of the method is presented alongside discussions of the observed results and their physical interpretation regarding the flow. The sensitivity analysis is performed for the three free parameters of UVLM, namely Vatistas core size, the geometry and the temporal discretizations, and then for the three additional parameters introduced by UVLM-VPM, which are the Vreman model coefficient, the particle spacing, and the conversion time. The effect of different databases in the non-linear coupling is also shown. The method is shown to be consistent with both geometry and temporal refinements. It is also consistent with the expected behavior of the different parameters change, including the numerical stability that depends on the strength of the LES diffusion controlled by the Vreman model coefficient. The effect of discretization refinement presented here not only shows the integrated coefficients where different errors can cancel each other, but also looks at their convergence and where relevant, the distributed loads and tip singularity position. Finally, the aerodynamics results of the method are compared for different databases and with higher fidelity Unsteady Reynolds Averaged Navier–Stokes (URANS) 3D results on a lower Reynolds number rotor.

Mathematical Model of Impact Projectile Flight Dynamics as an Element of its Digital Twin

This paper gives the analysis of the structure and characteristics of the mathematical model of the impact projectile’s flight dynamics. The model is designed for being used as an element of the projectile’s digital twin. The model is based on differential motion equations of a gyro-stabilized solid with an axisymmetric mass distribution. Different types of angle variables were chosen for describing aerodynamics and formulating equations of motion. Non-linear (considering the nutation angle) dependences for aerodynamic coefficients are proposed. They are created by applying proven scientific concepts and research methods in aerodynamics of axisymmetric body and by comparing with known numerical and experimental results obtained in exterior ballistics of gyro-stabilized aviation and artillery projectiles. Special aspects of initial conditions for angles and angular velocity were also studied. Since the impact projectile is considered as an axially symmetric body, its self-rotation angle is not of practical inte rest. Using algebraic manipulations, the differential equation for this angle was eliminated from the set of equations. This has made it possible to significantly reduce stiff of the remaining system of differential equations. The Dormand-Prince method is recommended as a method of numerical integration. The method of the eight-order (with seventh-order uncertainty estimate) allows getting the high accurate solution of the differential equations set under relatively small computing costs. The model allows computing the projectile trajectory under various initial conditions, including the flight with high nutation angles up to 87°—89°. As a result, there is a possibility to determine the nature of the interaction between impact projectiles and typical targets (ricochet, surface effect, after-penetration effect) within a wide range of approach angles to the target’s surface (skin) unattainable during the full-scale tests. The possibility of solving similar problems allows to recommend the designed model as an element of the impact projectile’s digital twin intended for testing its exterior ballistics on the digital (virtual) test range. All testing calculations and final modeling were made by using the "GNU Octave" computational software package.

An approach for formation design and flight performance prediction based on aerodynamic formation unit: Energy-saving considerations

The performance improvement of swarm drones through aerodynamic shape optimization may be challenging due to folded size constraints imposed by the specific launch approach. However, fixed-wing aircraft swarms can benefit from formation flight in terms of energy consumption. This study introduces the concept of the “aerodynamic formation unit”, which consists of two or three aircraft that form an inseparable unit of the formation. Considering the Unmanned Aerial Vehicle (UAV) distribution and wingtip vortex interference in the formation, two typical aerodynamic formation units are optimized by the variable-fidelity aerodynamic optimization method based on space mapping. The aerodynamic characteristics of the formation UAVs that affect flight performance, such as lift-to-drag ratio (L/D ratio) and static stability are analyzed by Computational Fluid Dynamics (CFD) simulations. The L/D ratio (cruising condition) of the following aircraft can be increased by 22.8% and 57.5% in the optimal units that involve two and three aircraft respectively. Moreover, this study conducts several CFD simulations for multi-aircraft formations formed by the units, which show that the average L/D ratio of the formation can be improved by more than 19%. These results verify the feasibility and effectiveness of the “aerodynamic formation unit” concept and the optimization framework for formation parameters.

Comparison of Machine Learning and Classic Methods on Aerodynamic Modeling and Control Law Design for a Pitching Airfoil

Aerodynamic modeling and control law design methods are crucial foundational technologies that enable efficient maneuvering flight of aircraft. Hence, this study focuses on how to construct the aerodynamic model and design control law using machine learning, as well as their differences from classical methods. To conduct this, a modified NACA0012 airfoil with a tail functioning as an elevator is employed as the geometry model. Through the utilization of the rigid dynamic grid method and overlapping grid technology, the pitch of the airfoil and the deflection of the elevator are efficient to execute. Firstly, the pitching moment coefficient is sampled through both steady and unsteady computations. Then, multivariate nonlinear regression (MNR) models and artificial neural network (ANN) models are established based on steady and unsteady sampling data, respectively. Additionally, the obtained model is evaluated using open‐loop control laws. Based on the evaluation, the proportional‐integral‐derivative (PID) control algorithm is used to design the airfoil pitching control law using the MNR model. Meanwhile, deep reinforcement learning (DRL) is used to design the pitching control law using the ANN model. Finally, the PID and DRL controllers are implemented in a CFD environment for airfoil pitching control to verify their effectiveness in application scenarios. The results suggest that models based on both steady and unsteady data can reflect dynamic aerodynamic characteristics. However, using unsteady computation for data sampling significantly reduces time consumption compared to steady computation. Furthermore, the model constructed by ANN may have unexpected excellent characteristics. Both the PID and DRL control laws, designed based on the models, perfectly complete the control process in the CFD environment. This study provides valuable insights for the implementation of controllable maneuvering flight in aircraft.

Structure, spectroscopic properties and optical temperature sensing behavior of glass-ceramics containing polymorphic CaTa2O6: Er3+/Yb3+ nanocrystals

Novel glass-ceramics (GCs) containing polymorphic CaTa2O6: Er3+/Yb3+ nanocrystals are prepared by aerodynamic levitation method following with a heat-treatment of the precursor glasses (PG). Phase transition from cubic to orthorhombic crystal...

Rapid aerodynamic method for predicting the performance of interacting wing sails

Rapid performance prediction tools are required for the evaluation, optimization, and comparison of different wind propulsion systems (WPSs). These tools should capture viscous aerodynamic flow effects in 3D, particularly the maximum propulsion force, stall angles, and interaction effects between the lift-generating units. This paper presents a rapid aerodynamic calculation method for wing sails that combines a semi-empirical lifting line model with a potential flow-based interaction model to account for 3D interaction effects. The method was applied to a WPS that consisted of several wing sails with considerable interaction effects. The results were compared to CFD RANS simulations in 2D and in 3D. For the evaluated validation cases, the interaction model improved the prediction considerably compared to when the interaction was not accounted for. The method provided acceptable driving force, moments, and stall predictions, with negligible computational cost compared to 3D CFD simulations.

DEVELOPMENT OF ENERGY-EFFICIENT AIR DEDUSTING

Among the sources of internal pollution one can point to dust, breath products of passengers, various emissions from finishing materials of trains and metro stations, etc. This problem is usually solved in two ways: wet cleaning of tunnels and stations and using powerful tunnel vacuum cleaners. Both of these methods have common disadvantages. Firstly, dust removal can only be carried out at night, when there are no trains on the line. Secondly, the dust removal installations themselves are expensive and are effective only at low speeds of dust movement through the tunnel. All metros in the world have a problem with dust removal. Research methods include analytical and computational studies of air distribution in the metro ventilation network using mathematical modeling methods using graph theory and flow algorithms, as well as experimental studies of air flow parameters in natural conditions of the Almaty metro.This article proposes an innovative method for dust removal of tunnel air based on the use of piston action of trains and labyrinth filters installed in station ventilation joints. The parameters of the calculation model of the metro line are substantiated on the basis of a decomposition approach to the mathematical modeling of aerodynamic processes by moving from a linear model of the metro line to a periodic open-loop model. Computational aerodynamics methods were used to determine the patterns of changes in air speed through the ventilation vent and the available pressure drop depending on the speed and mode of trains passing through the station.

Computational aeroelastic analysis of wings based on the structural discontinuous Galerkin and aerodynamic vortex lattice methods

An original computational framework for the aeroelastic analysis of wings featuring general transverse section is developed. The framework is based on the coupling between a novel discontinuous Galerkin structural model and an aerodynamic vortex lattice method, which is implemented in both the planar and non-planar version. The structural model, which constitutes the novelty of the present work, allows generalized kinematics and is thus able to capture higher-order structural deformation modes. With respect to other more used structural representations, the discontinuous Galerkin approach is based on the use of discontinuous basis functions and suitably-defined boundary terms to enforce the inter-element continuity and boundary conditions. Such features naturally enable high-order accuracy, ease of parallelization and, specifically for this work, straightforward coupling with the vortex lattice method. The framework is validated through benchmark tests, providing favourable matching with reference literature data.

성대구증 환자의 공기역학적 검사 방법에 따른 치료 전과 후의 평균호기류율 비교*

성대구증 환자의 공기역학적 검사 방법에 따른 치료 전과 후의 평균호기류율 비교*

Development of a New Aerodynamic Method for the Mechanical Characterization of a Horizontal Axis Wind Turbine

Development of a New Aerodynamic Method for the Mechanical Characterization of a Horizontal Axis Wind Turbine

Aerodynamic shape optimization of the vortex-shock integrated waverider over a wide speed range

The vortex-shock integrated waverider over a wide speed range could significantly improve the aerodynamic performance of traditional waveriders by introducing the vortex effect at subsonic speeds. Therefore, it is promising to be widely used in the design of wide-speed-range aerospace vehicles. However, the design of the vortex-shock integrated waverider ignores the three-dimensional effect, the subsonic effect, and the viscous effect in the establishment of the reference flow field, which fails to obtain the expected ideal performance. Therefore, it is necessary to further improve the wide-speed-range performance of the vortex-shock integrated waverider by employing the aerodynamic shape optimization method. In this study, the wide-speed-range multipoint optimization of the vortex-shock integrated waverider is carried out using a gradient-based optimizer combined with adjoint gradient evaluations. The results show that the optimum configuration increases the subsonic lift and lift-to-drag ratio by 6.7 % and 7.1 %, while increasing the hypersonic lift-to-drag ratio by 1.4 %. The improvement of the aerodynamic performance at subsonic speeds is attributed to the enhancement of the leeward vortex effect. Also, the leeward surface near the leading edge is optimized to an inner concave region to further enhance the vortex lift, while guaranteeing against the volume decline. Furthermore, the Detached Eddy Simulation (DES) method and the Dynamic Mode Decomposition (DMD) method are used to analyze the vortex dynamic characteristics at subsonic speeds. By analyzing the first three modes, it is observed that the aerodynamic performance of the optimum configuration is improved mainly by the frequency reduction and the increase of the pressure difference between the windward and the leeward surface, which enhance the stability and strength of the vortex.

Research of a novel aerodynamic evaluation method for fixed-wing UAV

The aerodynamic parameters of unmanned aerial vehicles (UAVs) play an important role in the newly designed drone. For the purpose of the real-time measurement of the aerodynamic performance parameters of the UAV in flight status, based on the self-development connected-wing configuration airplane, a novel airborne aerodynamics test scheme is researched and verified in this work. The findings of this study indicate that the effectiveness of numerical calculations can be verified by comparison with both results of the numerical simulation and airborne flight test in the same conditions. The newly designed UAV equipped with this test system in the future, not only achieves quick and reliable results of aerodynamic performance and powered system efficiency but also can save the expense of wind tunnel experiments, which is of high potential to the UAV application.

New Insights into Flow for a Low-Bypass-Ratio Transonic Fan with Optimized Rotor

In this paper, a three-dimensional aerodynamics optimization system is built and applied to optimize a rotor blade to balance the conflicts between stall margin, total pressure ratio, adiabatic efficiency, and mass flow rate for the high-loading and transonic-flow fan. A novel flow diagnostic method based on vorticity dynamics theory is utilized to analyze the reasons for the improvement in aerodynamic performance in the optimized transonic fan. In the established aerodynamic optimization method, use the blade profile camber line curvature and its leading edge metal angle as the optimization variables, which are optimized by modifying the coordinates of their control points and introducing a genetic algorithm. Finally, the vorticity dynamics parameters, such as the boundary vorticity flux (BVF), azimuthal vorticity and skin-friction lines are used to diagnose the key flow features in the optimized and baseline fan passage. The results indicate that, by controlling skillfully the blade camber line curvature in the optimization improves the aerodynamic performance of the fan stage, increasing the total pressure ratio by 1.90% while increasing the mass flow rate and adiabatic efficiency by 5.82% and 4.45%, respectively. The formulas from the vorticity dynamics diagnosis method indicate a close link between the aerodynamic performance and vorticity dynamic parameters for the axial fan/compressor passage flow, and that both azimuthal vorticity and boundary vorticity flux have significant influence on fan stage performance. Moreover, the boundary layer separation flow on the rotor blade surface is accompanied by a spike of entropy and static pressure, and their derivative/gradient also suffer drastic changes under the effect of shock waves. Detailed flow information can be obtained about the on-wall with high accuracy based on the vorticity dynamics diagnosis method, which provides researchers with a novel method for the turbomachinery aerodynamic design and analysis in the aero-engine engineering development field.

Noise Reduction Design Method and Validation of Unequal-Pitch Blade Fan for Traction Motor

The traction motor of trains is an essential component that generates the traction force, but it has a significant influence on the indoor and outdoor acoustic environment during the running condition. To enhance passenger comfort and bolster the environmental performance of trains, regulatory standards and specifications governing train noise have imposed elevated criteria on both tonal noise and the overall A-weighted sound pressure level emanating from traction motors. This paper proposes an aerodynamic noise optimization design method based on aerodynamic interference. The objective function of the optimization is defined as the blade-passing frequency (BPF) noise and the A-weighted overall sound pressure level of the traction motor fan. The simulated annealing algorithm is used to optimize the circumferential distribution of the blades. The optimized unevenly spaced blade configuration of the fan effectively reduces the BPF sound pressure level amplitude by 4.6 dBA and the overall A-weighted sound pressure level by 1.2 dBA. The calculation results agree well with the experimental results. The study reveals that unevenly spaced blades contribute to better noise reduction at lower rotational speeds. However, the effect diminishes at higher speeds. The relationship between noise reduction and blade count is nonlinear, suggesting an optimal count for specific speeds.

Vertical profile and flux measurements of ammonia in a deciduous forest in Japan towards improvement of bi-directional exchange model

Ammonia (NH3) is a major component of reduced nitrogen. A bi-directional exchange of NH3 takes place between the atmosphere and surface. Although the study of reduced nitrogen is gaining prominence in recent years, quantification of NH3 deposition is technically challenging due to its complex properties; consequently, this generates significant uncertainty regarding the estimation of total nitrogen deposition. Based on past studies, it has been reported that Asia has numerous high-risk nitrogen deposition sites; however, only a few studies have investigated the NH3 exchange in this region. To clarify the exchange process and achieve improved accuracy regarding the estimation of nitrogen deposition in Asia, we conducted measurements of vertical profile and flux of NH3 in a forest in Japan during summer (July 21–August 1, 2015), winter (February 23–February 29, 2016), and autumn (September 27–October 11, 2016). We measured daytime and nighttime NH3 concentrations at four or five heights of an observation tower in the forest by using filter-pack holders, and determined NH3 fluxes by using the aerodynamic gradient method. During daytime, NH3 showed emission above the canopy in summer, and near the forest floor in winter. There was no clear emission trend in autumn. During nighttime, NH3 showed deposition from the top of the canopy to the forest floor for all observed periods. NH3 exchange in the forest possibly had seasonal and diurnal variations. The flux measurements showed large NH3 emissions at daytime in summer and small depositions at nighttime in summer and autumn. Mean flux during the observation periods was 0.026 μg m−2 s−1. The daytime flux during leafy periods was found to have a strong correlation with solar radiation. At daytime in summer, flux also had strong correlations with relative humidity and horizontal wind speed. We also estimated NH3 fluxes in summer by employing a bi-directional exchange model to verify the applicability of the model at the study site. Inferred fluxes obtained via the model showed large emissions during daytime and agreed with the observation results; however, the model could not reproduce the nighttime deposition. This discrepancy was improved by applying more suitable cuticular resistances.

Time-Domain Identification Method Based on Data-Driven Intelligent Correction of Aerodynamic Parameters of Fixed-Wing UAV

In order to overcome the influence of complex environmental disturbance factors such as nonlinear time-varying characteristics on the dynamic control performance of small fixed-wing UAVs, the nonlinear expression relationship of neural networks (NNs) is combined with the recursive least squares (RLSs) identification algorithm. This paper proposes a hybrid aerodynamic parameter identification method based on NN-RLS offline network training and online learning correction. The simulation results show that compared with the real value of the identification value obtained by this algorithm, the residual error of the moment coefficient is reduced by 69%, and the residual error of the force coefficient is reduced by 89%. Under the same identification accuracy, the identification time is shortened from the original 0.1 s to 0.01 s. Compared with traditional identification algorithms, better estimation results can be obtained. By using this algorithm to continuously update the NN model and iterate repeatedly, iterative learning for complex dynamic models can be realized, providing support for the optimization of UAV control schemes.

Aircraft parameter estimation using a stacked long short-term memory network and Levenberg-Marquardt method

To effectively estimate the unknown aerodynamic parameters from the aircraft’s flight data, this paper proposes a novel aerodynamic parameter estimation method incorporating a stacked Long Short-Term Memory (LSTM) network model and the Levenberg-Marquardt (LM) method. The stacked LSTM network model was designed to realize the aircraft dynamics modeling by utilizing a frame of nonlinear functional mapping based entirely on the measured input–output data of the aircraft system without requiring explicit postulation of the dynamics. The LM method combines the already-trained LSTM network model to optimize the unknown aerodynamic parameters. The proposed method is applied by using the real flight data, generated by ATTAS aircraft and a bio-inspired morphing Unmanned Aerial Vehicle (UAV). The investigation reveals that for the two different flight data, the designed stacked LSTM network structure can maintain the efficacy of the network prediction capability only by appropriately adjusting the dropout rates of its hidden layers without changing other network parameters (i.e., the initial weights, initial biases, number of hidden cells, time-steps, learning rate, and number of training iterations). Besides, the proposed method’s effectiveness and potential are demonstrated by comparing the estimated results of the ATTAS aircraft or the bio-inspired morphing UAV with the corresponding reference values or wind-tunnel results.