Drag Estimation Research Articles

Wind estimation by multirotor dynamic state measurement and machine learning models

We present multiple models for the problem of wind estimation by a multirotor drone in low altitude atmospheric turbulence. Data is collected by test flights with an instrumented drone in proximity to an anemometer for training, validation, and testing. Three machine-learning models are developed: a long–short-term-memory (LSTM) neural-network, an artificial neural-network, and a Gaussian-process-regression. These models are developed with variations in the inputs, considering the addition of drag estimations by known equations of motion and motor speeds, both of which improved performance. The LSTM model performed the best reaching 0.34 m/s root-mean-square-error in validation. The similarity between all model’s performance without optimization indicates that we may be approaching the limits of accuracy of the experimental “ground truth”- a single anemometer that cannot be exactly co-located with the drone. The performance demonstrated so far suggests that the method may be useful in pollutant plume characterization, preliminary wind surveys, and other applications.

On the multi-fidelity approach in surrogate-based multidisciplinary design optimisation of high-aspect-ratio wing aircraft

AbstractThe reduction of computational costs in the context of the Multidisciplinary Design Optimisation of a typical medium-range aircraft was investigated through an assessment of active constraints and the use of multi-fidelity models-based estimation of drag and structural stress. The results show that for this problem, from the set of considered constraints that includes flutter boundary, the active constraint is a 2.5g pull up Maximum Take Off Weight. Results show that the multi-fidelity approach reduced the required high-fidelity aerodynamic number of evaluations, for both drag assessment and stress assessment with sufficient level of accuracy for the former and conservatively for the latter. Further computational cost reduction can be achieved using a surrogate model based Multidisciplinary Design Optimisation. The best configuration attained shows an Aspect Ratio increase of 16%, a reduction of 4.5% in fuel consumption and wing structural weight increase of 2.7% relative to a predefined baseline configuration.

Estimation of Transport-Category Jet Airplane Maximum Range and Airspeed in the Presence of Transonic Wave Drag

One of the most difficult steps in estimating the cruise performance characteristics of high-subsonic transport-category turbofan-powered airplanes is the estimation of the transonic wave drag. Modern jet airplanes cruise most efficiently in the vicinity of the drag-divergence or drag-rise Mach numbers. In the initial design phase and later when the preliminary wind-tunnel and/or CFD computations and drag polars are known with increased accuracy, a method of estimating cruise performance is needed. In this study, a new semi-empirical transonic wave drag model using modified Lock’s equation was developed. For maximum range cruise estimations, an optimization criterion based on maximizing specific air range was used. The resulting nonlinear equations are of 12th- and 13th-order. Numerical Newton–Raphson nonlinear solvers were used to find real positive roots of such polynomials. The NR method was first tested for accuracy and convergence using known analytical solutions. A methodology for an initial guess was developed starting with the maximum-range cruise Mach without the wave-drag included. This guess resulted in fast quadratic convergence in all computations. Other novel features of this article include a new semi-empirical fuel-flow law, which was also extensively tested. Additionally, a semi-empirical turbofan thrust model usable for a wide range of bypass ratios and the entire flight envelope was developed. Such physics-based semi-empirical model can be used for a wide range of turbofans. The algorithm can be utilized to identify most beneficial input parameter values and combinations for the cruise flight phase. The model represents a powerful tool to estimate important cruise performance airspeeds located in the transonic regime. An intended application is in the conceptual development stages for early design optimizations of future airplanes. It is possible with additional effort to extend existing model capabilities to deal with supersonic transports optimal cruise parameters.

Novel methodology for performance characterization of vertical axis wind turbines (VAWT) prototypes through active driving mode

Vertical axis wind turbines (VAWT) are called to have an important role in the definitive penetration of renewable energies in the near future. Although still under development, they are considered good candidates for urban environments and offshore generation in deep waters. For its experimental characterization, wind tunnel testing of small-scaled VAWTs is usually employed. However, self-starting issues, reduced aerodynamic torques -for reliable measurement- and high rotational speeds -imposed by similarity- emerge as inherent operative problems. To overcome these issues, Active Driving Mode (ADM) is commonly used to drive the turbine under equivalent kinematic conditions introducing an external motor. Up to now, an accurate characterization of the turbine performance, in terms of retrievable aerodynamic power, is not available for this methodology in the open literature.This work presents the development and application of an innovative methodology for testing VAWT prototypes through ADM. Interesting advantages over the conventional determination of the turbine performance using Passive Driving Mode (PDM) are shown. It is demonstrated that a deep level of characterization and high-test control is achieved with a simple experimental set-up. In addition, the key aspects for the application of this methodology have been identified and studied in detail, like the isolation of the mechanical losses from the blade drag or the quantification of the parasitic drag of the turbine struts. Relevant conclusions have been revealed concerning the marginal effect of the induction factor on the parasitic drag, or the importance of a correct blade drag estimation for the computation of the mechanical losses. Finally, the methodology has been applied to a real wind tunnel set-up, for the characterization of a 3-bladed VAWT with a H-rotor based on the DU 06-W-200 profile. The performance results obtained experimentally have been accurately compared to CFD simulations.

Base drag estimation in suddenly expanded supersonic flows using backpropagation genetic and recurrent neural networks

In recent years, base pressure management has gained a lot of industrial importance due to its applications in missiles and projectiles. For certain aerodynamic vehicles, the base pressure becomes a critical factor in regulating the base drag. That prompted the current work to develop input–output relationships for a suddenly expanded flow process using experiments and neural network-based forward and reverse mapping. The objective of forward mapping (FM) is to predict the responses, namely base pressure (β), base pressure with cavity (βcav), and base pressure with rib (βrib), for a known combination of flow and geometric parameters, namely Mach number (M), nozzle pressure ratio (η), area ratio (α), and length to diameter ratio (ψ). On the other hand, an effort is made to decide the optimal set of flow and geometric parameters for achieving the desired base pressure by reverse mapping (RM). Neural network-controlled backpropagation and recurrent and genetic algorithms have been employed to carry out the forward and reverse mapping trials. A batch mode of training was employed to conduct a parametric study for adjusting and optimizing the neural network parameters. Due to the requirement of massive data for batch mode training, the data required for training was achieved using the response equations developed through response surface methodology. Further, the forecasting performances of the neural network algorithms are compared with the regression models (FM) and among themselves (RM) through random test cases. The findings indicate that all evolved neural network (NN) models could make accurate predictions in both forward and reverse mappings. The results obtained would help aerodynamic engineers control various parameters and their values that affect base drag.

Identification of particular hydrodynamic parameters for a modular type 4 DOF underwater vehicle by means of CFD method

PurposeThe development of robust control algorithms for the position, velocity and trajectory control of unmanned underwater vehicles (UUVs) depends on the accuracy of their mathematical models. Accuracy of the model is determined by precise estimation of the UUV hydrodynamic parameters. The purpose of this study is to determine the hydrodynamic forces and moments acting on an underwater vehicle with complex body geometry and moving at low speeds and to achieve the accurate coefficients associated with them.Design/methodology/approachA three-dimensional (3D) computer-aided design (CAD) model of UUV is designed with one-to-one dimensions. 3D fluid flow simulations are conducted using computational fluid dynamics (CFD) software programme in the solution of Navier Stokes equations for laminar and turbulent flow analysis. The coefficients depending on the hydrodynamic forces and moments are determined by the external flow analysis using the CFD programme. The Flow Simulation k-ε turbulence model is used for the transition from laminar flow to turbulent flow. Hydrodynamic properties such as lift and drag coefficients and roll and yaw moment coefficients are calculated. The parameters are compared with the coefficient values found by experimental methods.FindingsAlthough the modular type UUV has a complex body geometry, the comparative results of the experiments and simulations confirm that the defined model parameters are accurate and close to the actual experimental values. In the proposed k-ε method, the percentage error in the estimation of drag and lifting coefficients is decreased to 4.2% and 8.39%, respectively.Practical implicationsThe model coefficients determined in this study can be used in high-level control simulations which leads to the development of robust real-time controllers for complex-shaped modular UUVs.Originality/valueThe Lucky Fin UUV with 4 degrees of freedom is a specific design and its CAD model is first extracted. Verification of simulation results by experiments is generally less referenced in studies. However, it provides more precise parameter identification of the model. Proposed study offers a simple and low-cost experimental measurement method for verification of the hydrodynamic parameters. The extracted model and coefficients are worthwhile references for the analysis of modular type UUVs.

Drag Estimation in the Near Wake of the NREL's Airfoils Based on Hot-Wire Data

This paper presents the results of the drag coefficient estimations for different types of NREL airfoils based on the experimental data. Namely, it was S803, S807, S813, and S817 profiles with the same chord length. The investigations were conducted at three angles of attack α=0°, α=±5°, different chord-based Reynolds numbers 0.6×105, 1.3×105 and 2.6×105. While, measuring cross-sections were placed behind the trailing edge at x∙c−1≈0.2, 0.4 and 1.0. Experimental data were collected using a hot-wire split fiber probe 55R55, which allowed us to estimate the characteristics of turbulent flow in stream-wise and crosswise directions. According to the obtained results, the highest and lowest Cd values correspond to profiles S817 and S803, respectively. Moreover, the results show that more asymmetric profiles S803 and S807 have the lowest resistance at zero angles of attack. Research background: Application of Antonia and Rajagopalan methodology to drag assessment of various stream bodies. Purpose of the article: Comparative evaluation of the drag coefficients of the NREL airfoils based on instantaneous velocity distribution behind. Methods: Hot-wire anemometry with split fiber probe 55R55. Findings & Value added: The highest drag coefficient corresponds to the S817 profile. The asymmetry of the airfoil shape has a significant impact on its drag characteristics.

Transient evolution of basal drag during glacier slip

AbstractGlacier slip is usually described using steady-state sliding laws that relate drag, slip velocity and effective pressure, but where subglacial conditions vary rapidly transient effects may influence slip dynamics. Here we use results from a set of laboratory experiments to examine the transient response of glacier slip over a hard bed to velocity perturbations. The drag and cavity evolution from lab experiments are used to parameterize a rate-and-state drag model that is applied to observations of surface velocity and ice-bed separation from the Greenland ice sheet. The drag model successfully predicts observed lags between changes in ice-bed separation and sliding speed. These lags result from the time (or displacement) required for cavities to evolve from one steady-state condition to another. In comparing drag estimates resulting from applying rate-and-state and steady-state slip laws to transient data, we find the peaks in drag are out of phase. This suggests that in locations where subglacial conditions vary on timescales shorter than those needed for cavity adjustment transient slip processes control basal drag.

Improving the Flight Endurance of a Separate-Lift-and-Thrust Hybrid through Gaussian Process Optimization

A separate-lift-and-thrust hybrid is a modified fixed-wing drone which includes quadcopter rotors. This results in the combined capability of forwarding flight as well as vertical take-off and landing (VTOL), making it a low-cost method that can deliver substantial gains in utility. Though this is a strong point compared to other types of VTOL drones, the hybrid design may incur a significant trade-off because added weight and drag can severely reduce the drone's flight endurance. This study attempts to mitigate the impact by improving the configuration of the selection and positioning parameters. Since drag estimations are costly, a Gaussian process optimization method was performed, as it is economical with respect to the required number of iterations. A set of arbitrarily selected components was prepared for use with the optimization method, recording the relevant performance data and constructing the CAD models of the components for use in simulations. The optimization method was able to increase the estimated flight endurance to 27.99 minutes, a significant improvement compared to a set of random configurations, which only yielded 9.54 minutes at best. The respectable result was obtained even though difficulties were experienced regarding the infeasible regions that arise from the many constraints. Future implementation of this optimization approach can be further improved. It may be worthwhile to utilize a low-fidelity model from the base fixed-wing drone simulations, in contrast with using an initial zero mean for the prior of the Gaussian process.

The influence of the flow separation bubble and transition location on the profile drag of three 4-digit NACA aerofoil profiles

Modeling of the flow over aerofoil profiles at low Reynolds numbers is difficult due to the complex physics associated with the laminar flow separation mechanism. Two major problems arise in the estimation of profile drag: (1) the drag force at low Reynolds numbers is extremely small to be measured in a wind tunnel by force balance techniques, (2) the profile drag is usually calculated by pressure integration, hence the skin friction component of drag is excluded. In the present work, three different 4-digit NACA aerofoils are investigated. Measurements are conducted in an open-ended subsonic wind tunnel, while numerical work is performed by time Reynolds-averaged Navier Stokes (RANS) coupled with the laminar-kinetic-energy ( K-kl-w) turbulence model. The influence of the flow separation bubbles and transition locations on the profile drag is discussed and addressed. This paper gives important insights into importance of measurements at low Reynolds numbers for better aerodynamic loads predictions.

Multidisciplinary design optimisation of a fully electric regional aircraft wing with active flow control technology

AbstractThe German research Cluster of Excellence SE2A (Sustainable and Energy Efficient Aviation) is investigating different technologies to be implemented in the following decades, to achieve more efficient air transportation. This paper studies the Hybrid Laminar Flow Control (HLFC) using boundary layer suction for drag reduction, combined with other technologies for load and structural weight reduction and a novel full-electric propulsion system. A multidisciplinary design optimisation framework is presented, enabling physics-based analysis and optimisation of a fully electric aircraft wing equipped with HLFC technologies and load alleviation, and new structures and materials. The main focus is on simulation and optimisation of the boundary layer suction and its influence on wing design and optimisation. A quasi three-dimensional aerodynamic analysis is used for drag estimation of the wing. The tool executes the aerofoil analysis using XFOILSUC, which provides accurate drag estimation through boundary layer suction. The optimisation is based on a genetic algorithm for maximum take-off weight (MTOW) minimisation. The optimisation results show that the active flow control applied on the optimised geometry results in more than 45% reduction in aircraft drag coefficient, compared to the same geometry without HLFC technology. The power absorbed for the HLFC suction system implies a battery mass variation lower than 2%, considering the designed range as top-level requirement (TLR).

Estimation of radial shaft seal, oil drag and windage loss in twin screw oil injected compressor

The objective of this paper is to study the mechanical power loss arising from radial shaft seal, oil drag, and windage within the twin-screw oil-injected screw compressor. The previous papers in the series presented the evaluation of power loss due to the gears and bearings where it was found that the calculated total power loss was underestimated when compared to the experimental results for different sizes of compressors and different operating conditions. This indicates that few additional contributing elements were missing and needed due consideration to enhance the prediction. Literature review of the basic fluid dynamics and transmission gears confirms that oil drag loss and windage loss can also contribute to the power loss considerably.This paper presents a review of a few methods for the prediction of the radial shaft seal, oil drag, and windage loss. Predictions with the use of these methods and their comparison with the experimental results are analysed in this paper. Experimental results of three different sizes of the compressors tested in laboratory conditions were taken as reference for the comparison at different operating speeds and pressure ratios. The analysis helps to understand the contribution of each element of the power loss which can help a designer to optimally design a screw compressor.

Convolutional neural networks for fluid flow analysis: toward effective metamodeling and low dimensionalization

We focus on a convolutional neural network (CNN), which has recently been utilized for fluid flow analyses, from the perspective on the influence of various operations inside it by considering some canonical regression problems with fluid flow data. We consider two types of CNN-based fluid flow analyses: (1) CNN metamodeling and (2) CNN autoencoder. For the first type of CNN with additional scalar inputs, which is one of the common forms of CNN for fluid flow analysis, we investigate the influence of input placements in the CNN training pipeline. As an example, estimation of drag and lift coefficients of an inclined flat plate and two side-by-side cylinders in laminar flows is considered. For the example of flat plate wake, we use the chord Reynolds number \(\hbox {Re}_\mathrm{c}\) and the angle of attack \(\alpha \) as the additional scalar inputs to provide the information on the complexity of wake. For the wake interaction problem comprising flows over two side-by-side cylinders, the gap ratio and the diameter ratio are utilized as the additional inputs. We find that care should be taken for the placement of additional scalar inputs depending on the problem setting and the complexity of flows that users handle. We then discuss the influence of various parameters and operations on the CNN performance, with the utilization of autoencoder (AE). A two-dimensional decaying homogeneous isotropic turbulence is considered for the demonstration of AE. The results obtained through the AE highly rely on the decaying nature. Investigation on the influence of padding operation at a convolutional layer is also performed. The zero padding shows reasonable ability compared to other methods which account for the boundary conditions assumed in the numerical data. Moreover, the effect of the dimensional reduction/extension methods inside CNN is also examined. The CNN model is robust against the difference in dimension reduction operations, while it is sensitive to the dimensional extension methods. The findings of this paper will help us better design a CNN architecture for practical fluid flow analysis.

Artificial Neural Network Application for Aerodynamics of an Airfoil Equipped with Plasma Actuators

Prediction of the aerodynamic forces acting on a NACA 2415 airfoil equipped with plasma actuators is carried out by using artificial neural network. The data sets for ANN model include the experiments which are plasma actuator positions for effective flow control, different Reynolds numbers and various attack angles. Mean absolute percentage and mean squared errors are calculated to assess the performance of the training and the testing stages of ANN model in prediction of drag and lift coefficients. The maximum error for lift and drag estimation are 12.84% and 23.705%, respectively. Also, as a part of the presented study, the process parameters affecting the performance of the plasma actuators in active flow control around a NACA 2415 airfoil is presented in detail. The well-matched results of the ANN based estimations of the ANN indicates that there is almost no need for dealing with complex experimental studies to determine the aerodynamic performance of the NACA2415 airfoil, hence providing the advantage of saving time and cost. Furthermore, the experimental results along with the ability of ANN to estimate aerodynamic performance parameters provide a good database in the active flow control related research field.

Full configuration drag estimation of short-to-medium range fixed-wing UAVs and its impact on initial sizing optimization

The paper presents the derivation of a new equivalent skin friction coefficient for estimating the parasitic drag of short-to-medium range fixed-wing unmanned aircraft. The new coefficient is derived from an aerodynamic analysis of ten different unmanned aircraft used for surveillance, reconnaissance, and search and rescue missions. The aircraft is simulated using a validated unsteady Reynolds-averaged Navier Stokes approach. The UAV’s parasitic drag is significantly influenced by the presence of miscellaneous components like fixed landing gears or electro-optical sensor turrets. These components are responsible for almost half of an unmanned aircraft’s total parasitic drag. The new equivalent skin friction coefficient accounts for these effects and is significantly higher compared to other aircraft categories. It is used to initially size an unmanned aircraft for a typical reconnaissance mission. The improved parasitic drag estimation yields a much heavier unmanned aircraft when compared to the sizing results using available drag data of manned aircraft.

Optimisation Studies for an Efficient Aerodynamic Configuration of a Blended Wing Unmanned Aerial Vehicle

There are various configurations and parameters that contribute to the Design of Unmanned Aerial Vehicles for specific applications. This paper deals with an innovative design of an unmanned aerial vehicle for a specified class of UAVs that require demands such as long endurance, minimized landing space with vertical take-off and landing (VTOL) capabilities. The focal point of this design is superimposing the high endurance blended wing design into tri-copter to address these parameters. The preliminary calculations are initially performed for the blended wing VTOL vehicle based on the required payload capacity and endurance. Superimposing the tri-copter will decrease the aerodynamic efficiency of the vehicle. Computational fluid dynamics (CFD) is a branch of fluid mechanics that uses numerical methods and algorithms to solve complex problems involving fluid flow which will effectively employed to reduce the cost and time during the conceptual and preliminary design stages. CFD analysis was carried out to estimate the major parameters like lift, drag, lift coefficient (CL) and drag coefficient (CD) for various Angle of Attack (AoA) for configurations of blended wing vehicle with and without tri-copter system in the cruise condition. Thus, the vehicle design and propulsion system is effectively optimized using this drag estimation.

Experimental and analytical investigation of fluid drag losses in rolling element bearings

A Four Bearing Test Rig was designed and developed to measure frictional torque of oil lubricated rolling element bearings under various operating conditions. Deep groove ball bearings and radial needle roller bearings were tested for a range of speeds and lubricants. In this investigation, the portion of frictional torque caused by fluid drag losses was determined by analyzing the difference between a fully flooded (submerged) and a minimally lubricated bearing. Ansys Fluent computational fluid dynamics software was used to corroborate and model the different bearing geometries and operating conditions evaluated in the test rig. Drag force of bearing components was calculated from the CFD simulations and compared to the experimental results. The results demonstrate that they are in good agreement. Frictional torque due to fluid drag was further compared to an empirical friction model available in open literature. The CFD model provides a physics-based estimate of fluid drag which corroborates well with the experimental results, while the open literature empirical model tends to over-predict frictional torque from fluid drag. Experimental and analytical results from this investigation suggest that bearing cage design has a small impact on overall fluid drag losses, while substantial improvements can be made by optimizing lubrication conditions and bearing type. The presented CFD model provides an efficient approach to asses fluid drag losses for various bearing geometries and operating conditions.

Tail Control Enhances Gliding in Arboreal Lizards: An Integrative Study Using a 3D Geometric Model and Numerical Simulation.

The ability to glide through an arboreal habitat has been acquired by several mammals, amphibians, snakes, lizards, and even invertebrates. Lizards of the genus Draco possess specialized morphological structures for gliding, including a patagium, throat lappets, and modified hindlimbs. Despite being among the most specialized reptilian gliders, it is currently unknown how Draco is able to maneuver effectively during flight. Here, we present a new computational method for characterizing the role of tail control on Draco glide distance and stability. We first modeled Draco flight dynamics as a function of gravitational, lift, and drag forces. Lift and drag estimates were derived from wind tunnel experiments of 3D printed models based on photos of Draco during gliding. Initial modeling leveraged the known mass and planar surface area of the Draco to estimate lift and drag coefficients. We developed a simplified, 3D simulation for Draco gliding, calculating longitudinal and lateral position and a pitch angle of the lizard with respect to a cartesian coordinate frame. We used PID control to model the lizards' tail adjustment to maintain an angle of attack. Our model suggests an active tail improves both glide distance and stability in Draco. These results provide insight toward the biomechanics of Draco; however, future in vivo studies are needed to provide a complete picture for gliding mechanics of this genus. Our approach enables the replication and modification of existing gliders to better understand their performance and mechanics. This can be applied to extinct species, but also as a way of exploring the biomimetic potential of different morphological features.

Velocity data-based determination of airfoil characteristics with circulation and fluid momentum change methods, including a control surface size independence test

An experimental method for determination of aerodynamic loads is presented. It is based on velocity vector field results obtained with Particle Image Velocimetry (PIV). As PIV is an optical measurement technique, the developed method for load determination can be defined as noninvasive. It is shown that the only information needed to estimate the lift and drag forces exerted on a body placed in the flow is a velocity distribution measured around the investigated object. Therefore, PIV results provide sufficient input experimental data to be used. Fundamental fluid mechanics theories were employed to develop algorithms for load estimation. Determination of the lift force is based on velocity circulation calculations. It is obtained by integrating the velocity field along a closed-loop encircling the body. An essential achievement made is the development of a procedure for finding an optimal size of the integration curve used for lift calculations. In the case of the drag force estimation, an analysis of fluid momentum changes has been used. The momentum deficit, within a given control volume containing the analysed aerofoil, is determined and related to the reaction drag force exerted on the body. Additionally, pressure field reconstruction based on velocity data, which enabled an application of small control surfaces and kept the drag estimation error at a satisfactorily low level, was introduced. The developed method was tested and verified with the reference computational fluid dynamics simulation results and applied further to the wind tunnel experimental data. A flow around the standard NACA0012 aerofoil at two flow regimes was investigated (Re=0.7times 10^5 and Re=1.4times 10^5). Lift and drag coefficient characteristics as a function of the angle of attack were obtained. An exceptional agreement between the experimental and reference numerical lift characteristics was attained (relative differences no larger than 5%). In the case of drag estimation, an acceptable level of similarity was observed (max. discrepancies below 20%).Graphic abstract

A simple method for drag estimation for wedge-like fairings in hypersonic flow

ABSTRACTThe addition of wedge-like fairings onto the side of missiles and space launch vehicles, to shield devices such as cameras and reaction jet nozzles, creates additional drag, particularly when in supersonic and hypersonic freestream flow. An experimental and computational study was performed to obtain aerodynamic data on simple representative configurations to test the accuracy of simple theories for the drag increment due to these types of fairings. A semi-empirical method to estimate drag on wedge-shaped projections is presented, which may be used by missile designers to provide predictions of the drag increment due to wedge-like fairings. The method is shown to be valid where the wedge width is much smaller than body diameter, and across the Mach number range 4–8.2 but is likely to be valid for higher Mach numbers. Drag coefficient is found to increase with increasing wedge angle and reducing wedge slenderness, although increasing slenderness tends to increase skin friction drag.