Drag Estimation Research Articles

Quantifying and reducing the cost of tagging: combining computational fluid dynamics and diving experiments to reduce impact from animal-borne tags.

Animal-borne instruments are essential research tools for ecologists and physiologists. An increasing number of studies have shown impacts of carrying a tag on behaviour and energetics, which can have implications for animal welfare and data validity. Such impacts are a result of the additional mass and/or drag loads, with the latter requiring empirical measurements or computational fluid dynamics (CFD) to estimate. To quantify and effectively minimize tag impacts from drag, a novel combined empirical and CFD approach is required. Here, we demonstrate such an approach using captive phocid seals and the widely used Sea Mammal Research Unit (SMRU) Instrumentation Group GPS/GSM tag. We (i) show a significant change in the behaviour of grey seals when carrying a tag (gen 1; associated with 16.4% additional drag); (ii) redesigned the tag (gen 2) resulting in a lower additional drag of 8.6%; (iii) show significant differences in behaviour when carrying a gen 2 compared to gen 1 tag, demonstrating that the redesign successfully reduced impact; and (iv) observed changes in the swim speed of seals that were consistent with predictions from CFD estimates of drag. The gen 2 instrument is now commercially available. This non-trivial case study should pave the way for similar studies in other taxa and species.

An Investigation of Internal Drag Correction Methodology for Wind Tunnel Test Data in a High-Speed Air-Breathing Vehicle Using Numerical Analysis

AbstractAccurate understanding of aerodynamic characteristics is critical for air vehicle design. This study applies the impulse-momentum theorem to estimate internal drag of an asymmetric air vehicle. Both computational fluid dynamics (CFD) and wind tunnel tests were employed. Numerical analysis using STAR-CCM + was conducted across various Mach numbers, while wind tunnel tests were conducted under only specific Mach number conditions. The measured data from wind tunnel tests, which is considered representative, were compared with CFD plane-averaged values, indicating fairly good agreement. However, discrepancies arose when comparing CFD cell-averaged values with the plane-averaged values. To address this, a correction function was developed to describe the differences. It was observed that the ratio of internal drag coefficient from the cell-averaged values to that of the plane-averaged values followed an exponential function of Mach number. This approach allows wind tunnel data to be transformed into a form akin to cell-averaged values, enhancing internal drag estimation accuracy. Future research will explore additional methodologies to further refine and validate the proposed approach.

Enhanced Drag Force Estimation in Automotive Design: A Surrogate Model Leveraging Limited Full-Order Model Drag Data and Comprehensive Physical Field Integration

In this paper, a novel surrogate model for shape-parametrized vehicle drag force prediction is proposed. It is assumed that only a limited dataset of high-fidelity CFD results is available, typically less than ten high-fidelity CFD solutions for different shape samples. The idea is to take advantage not only of the drag coefficients but also physical fields such as velocity, pressure, and kinetic energy evaluated on a cutting plane in the wake of the vehicle and perpendicular to the road. This additional “augmented” information provides a more accurate and robust prediction of the drag force compared to a standard surface response methodology. As a first step, an original reparametrization of the shape based on combination coefficients of shape principal components is proposed, leading to a low-dimensional representation of the shape space. The second step consists in determining principal components of the x-direction momentum flux through a cutting plane behind the car. The final step is to find the mapping between the reduced shape description and the momentum flux formula to achieve an accurate drag estimation. The resulting surrogate model is a space-parameter separated representation with shape principal component coefficients and spatial modes dedicated to drag-force evaluation. The algorithm can deal with shapes of variable mesh by using an optimal transport procedure that interpolates the fields on a shared reference mesh. The Machine Learning algorithm is challenged on a car concept with a three-dimensional shape design space. With only two well-chosen samples, the numerical algorithm is able to return a drag surrogate model with reasonable uniform error over the validation dataset. An incremental learning approach involving additional high-fidelity computations is also proposed. The leading algorithm is shown to improve the model accuracy. The study also shows the sensitivity of the results with respect to the initial experimental design. As feedback, we discuss and suggest what appear to be the correct choices of experimental designs for the best results.

Estimation of Passive Drag in Swimming via Experimental and Computational Means

Discussed is a comparison of computational and experimental evaluations of passive drag during human swimming. Experimentally, ten trials were conducted per athlete at five chosen velocities, using a commercial resistance trainer to record the tension force in a rope during a streamline position tow test. The resistive force recorded was assumed equal to the passive drag force and an average value of passive drag was found across each tow test. Mean passive drag values measured during the tow test were agreed well with existing experimental data across the range of velocities used, varying between 20 N at 1 ms−1 up to 100 N at 2 ms−1. Computationally, using the immersed boundary method in OpenFOAM, basic geometry validation cases and streamline passive drag cases were simulated. Validation cases were completed on 2D cylinders and 3D spheres with the drag coefficient found at low and high Reynolds numbers, using the simpleFoam solver within OpenFOAM. Results tended to be slightly over predictive when compared with existing simulation and experimental data in literature. The accuracy of results could potentially be improved using a finer mesh and better quality geometries. The passive drag was also computed using OpenFOAM over a range of velocities, similar to the experiments, varying from 30 N at 1 ms−1 to 120 N at 2 ms−1. Drag forces computed using simpleFoam were over predictive when compared to existing literature and the completed experiments, likely due to the inaccuracy of the geometry used in the simulations. When results were compared to existing literature for swimmers not in a perfect streamline position, more similar to the geometry used in this study, results were in better agreement. The accuracy of the results could be improved using a better quality geometry in the correct position.

CFD-Based Lift and Drag Estimations of a Novel Flight-Style AUV with Bow-Wings: Insights from Drag Polar Curves and Thrust Estimations

CFD-Based Lift and Drag Estimations of a Novel Flight-Style AUV with Bow-Wings: Insights from Drag Polar Curves and Thrust Estimations

The advancing wave front on a sloping channel covered by a rod canopy following an instantaneous dam break

The drag coefficient Cd for a rigid and uniformly distributed rod canopy covering a sloping channel following the instantaneous collapse of a dam was examined using flume experiments. The measurements included space x and time t high resolution images of the water surface h(x, t) for multiple channel bed slopes So and water depths behind the dam Ho along with drag estimates provided by sequential load cells. Using these data, an analysis of the Saint-Venant equation (SVE) for the front speed was conducted using the diffusive wave approximation. An inferred Cd=0.4 from the h(x, t) data near the advancing front region, also confirmed by load cell measurements, is much reduced relative to its independently measured steady-uniform flow case. This finding suggests that drag reduction mechanisms associated with transients and flow disturbances are more likely to play a dominant role when compared to conventional sheltering or blocking effects on Cd examined in uniform flow. The increased air volume entrained into the advancing wave front region as determined from an inflow–outflow volume balance partly explains the Cd reduction from unity.

Free fall drag estimation of small-scale multirotor unmanned aircraft systems using computational fluid dynamics and wind tunnel experiments

New European Union (EU) regulations for UAS operations require an operational risk analysis, which includes an estimation of the potential danger of the UAS crashing. A key parameter for the potential ground risk is the kinetic impact energy of the UAS. The kinetic energy depends on the impact velocity of the UAS and, therefore, on the aerodynamic drag and the weight during free fall. Hence, estimating the impact energy of a UAS requires an accurate drag estimation of the UAS in that state. The paper at hand presents the aerodynamic drag estimation of small-scale multirotor UAS. Multirotor UAS of various sizes and configurations were analysed with a fully unsteady Reynolds-averaged Navier–Stokes approach. These simulations included different velocities and various fuselage pitch angles of the UAS. The results were compared against force measurements performed in a subsonic wind tunnel and provided good consistency. Furthermore, the influence of the UAS`s fuselage pitch angle as well as the influence of fixed and free spinning propellers on the aerodynamic drag was analysed. Free spinning propellers may increase the drag by up to 110%, depending on the fuselage pitch angle. Increasing the fuselage pitch angle of the UAS lowers the drag by 40% up to 85%, depending on the UAS. The data presented in this paper allow for increased accuracy of ground risk assessments.

Enhanced Unsteady Vortex Lattice Aerodynamics for Nonlinear Flexible Aircraft Dynamic Simulation

Several modeling extensions and numerical improvements to the unsteady vortex-lattice method are discussed for the simulation of very flexible aircraft dynamics. In particular, fuselage aerodynamics are included by means of linear source panels, polar corrections are incorporated on the aerodynamics under potentially large deformations, and a new wake discretization scheme is derived to accelerate the computations. The theory behind each approach is detailed and successfully verified on representative test cases. The resulting modeling environment is then exemplified in a study of the flight dynamics of a flexible aircraft demonstrator model. Results indicate that, for large wing deformations, a noticeable effect of fuselage aerodynamic interference appears on the wing aeroelastic behavior. The polar corrections improve the drag estimations and allow capturing lift decrements due to stall onset at high induced angles of attack, which then affects the gust loads. The wake discretization scheme enables a reduction of the computational time for dynamic simulations on a full aircraft model by about 20% while keeping the arising error negligibly small.

Path instabilities and drag in the settling of single spheres

The settling behavior of individual spheres in a quiescent fluid was studied experimentally. The dynamics of the spheres was analyzed in the parameter space of particle-to-fluid density ratio (Γ) and Galileo number (Ga), with Γ∈(1.1,7.9) and Ga∈(100,340). The experimental results showed for the first time that the mean trajectory angle with the vertical exhibits a complex behavior as Ga and Γ are varied. Numerically predicted regimes such as Vertical Periodic for low Γ values, and Planar Rotating for high Γ values were validated. In particular, for the denser spheres, a clear transition from planar to non-planar trajectories was observed, accompanied by the emergence of semi-helical trajectories corresponding to the Planar Rotating Regime. The spectra of trajectory oscillations were also quantified as a function of Ga, confirming the existence of oblique oscillating regimes at both low and high frequencies. The amplitudes of the perpendicular velocities in these regimes were also quantified and compared with numerical simulations in the literature. The terminal velocity and drag of the spheres were found to depend on the particle-to-fluid density ratio, and correlations between the drag coefficient and particle Reynolds number (Rep) as a function of Ga were established, allowing for the estimation of drag and settling velocity using Ga, a control parameter, rather than the response parameter Rep.

Assessment of drag prediction techniques based on radar data for supersonic vehicles

Flight testing is probably the most accurate approach for defining the aerodynamic characteristics of a flying vehicle. This is justified by the fact that compared to other approaches, either engineering or computational ones, flight testing is indeed the one that perfectly resembles the real flight environment. Flight data are either obtained by measuring the vehicle’s kinematics via onboard sensors or by tracking the vehicle’s flight via (commonly) radars. The advantages of the latter approach are evident in cases where modifying the vehicle design is not possible or in cases where rival/enemy vehicles are examined. The key issue for this approach is the quality and demands of the technique by which vehicle aerodynamic characteristics are reduced from flight-tracked data. In the open literature, different techniques are used to analyze radar data of vehicle position and utilize them to predict vehicle drag coefficient. Each technique has its strengths and pitfalls. In this paper, the three well-used techniques of drag estimation from radar data namely, Least Square (LS), Maximum Likelihood Estimation (MLE), and Stepwise regression (SR), are considered. The underlying principle, the output, and the range of validity for each technique are addressed with emphasis on what differentiates each of them. The viability and validity of the three techniques are addressed based on the own flight testing of a free-flight supersonic vehicle and using the point-mass flight model. Meteorological data are also recorded and flight conditions are used to enhance the resulting calculations. Based on experimental data available from the literature, a comparison is conducted for the techniques examined. Considering the lack of flight data utilized, and in conjunction with data from the literature, it has been concluded that the SR technique outperforms for a higher sample rate, however, the MLE is more feasible when there is a lack of data.

New estimates of pan-Arctic sea ice–atmosphere neutral drag coefficients from ICESat-2 elevation data

Abstract. The effect that sea ice topography has on the momentum transfer between ice and atmosphere is not fully quantified due to the vast extent of the Arctic and limitations of current measurement techniques. Here we present a method to estimate pan-Arctic momentum transfer via a parameterization that links sea ice–atmosphere form drag coefficients with surface feature height and spacing. We measure these sea ice surface feature parameters using the Ice, Cloud and land Elevation Satellite-2 (ICESat-2). Though ICESat-2 is unable to resolve as well as airborne surveys, it has a higher along-track spatial resolution than other contemporary altimeter satellites. As some narrow obstacles are effectively smoothed out by the ICESat-2 ATL07 spatial resolution, we use near-coincident high-resolution Airborne Topographic Mapper (ATM) elevation data from NASA's Operation IceBridge (OIB) mission to scale up the regional ICESat-2 drag estimates. By also incorporating drag due to open water, floe edges and sea ice skin drag, we produced a time series of average total pan-Arctic neutral atmospheric drag coefficient estimates from November 2018 to May 2022. Here we have observed its temporal evolution to be unique and not directly tied to sea ice extent. By also mapping 3-month aggregates for the years 2019, 2020 and 2021 for better regional analysis, we found the thick multiyear ice area directly north of the Canadian Archipelago and Greenland to be consistently above 2.0×10-3, while most of the multiyear ice portion of the Arctic is typically around ∼1.5×10-3.

Sensitivity of Mountain Wave Drag Estimates on Separation Methods and Proposed Improvements

Abstract Internal gravity waves (GWs) are ubiquitous in the atmosphere, making significant contributions to the mesoscale motions. Since the majority of their spectrum is unresolved in global circulation models, their effects need to be parameterized. In recent decades GWs have been increasingly studied in high-resolution simulations, which, unlike direct observations, allow us to explore full spatiotemporal variations of the resolved wave field. In our study we analyze and refine a traditional method for GW analysis in a high-resolution simulation on a regional domain around the Drake Passage. We show that GW momentum drag estimates based on the Gaussian high-pass filter method applied to separate GW perturbations from the background are sensitive to the choice of a cutoff parameter. The impact of the cutoff parameter is higher for horizontal fluxes of horizontal momentum, which indicates higher sensitivity for horizontally propagating waves. Two modified methods, which choose the parameter value from spectral information, are proposed. The dynamically determined cutoff is mostly higher than the traditional cutoff values around 500 km, leading to larger GW fluxes and drag, and varies with time and altitude. The differences between the traditional and the modified methods are especially pronounced during events with significant drag contributions from horizontal momentum fluxes. Significance Statement In this study, we highlight that the analysis of gravity wave activity from high-resolution datasets is a complex task with a pronounced sensitivity to the methodology, and we propose modified versions of a classical statistical gravity wave detection method enhanced by the spectral information. Although no optimal methodology exists to date, we show that the modified methods improve the accuracy of the gravity wave activity estimates, especially when oblique propagation plays a role.

Exploiting High‐Density Zonal‐Sampling of HIRDLS Profiles Near 60°S to Investigate Missing Drag in Chemistry‐Climate Models

AbstractThis study exploits the high‐density zonal sampling at the turnaround latitude of the High Resolution Dynamics Limb Sounder (HIRDLS) in the Southern Hemisphere to investigate the missing drag in chemistry‐climate models near 60°S. Gravity wave (GW) properties including amplitude, zonal wavenumber, vertical wavelength, and momentum flux are estimated with a wave analysis method based on the S‐transform. Monthly means of GW properties compare well with estimates from previous studies. We further investigate the contribution to GW momentum flux above orographic and nonorographic regions and find that while fluxes are much larger locally over orographic regions, the contribution to the zonal mean is roughly 3 times smaller than the contribution over nonorographic regions. We also investigate the relationship with the zonal wind and find that GW momentum flux is highly correlated with the near surface winds over orographic regions. In addition to momentum flux, we also provide estimates of the zonal drag and use these estimates to evaluate the current GW parameterizations and resolved wave forcing in models participating in phase 1 of the Chemistry‐Climate Model Initiative (CCMI‐1). The HIRDLS zonal drag estimates suggest that the CCMI‐1 models have insufficient zonal drag, especially in June, July, and August, and that the majority of the missing drag is over nonorographic regions. Our discussion includes implications for the Brewer‐Dobson Circulation and ozone hole.

Numerical study of the main rotor hub and swashplate parasite drag estimation of a medium transport helicopter

This work is devoted to the determination of the parasite drag of the components of the main rotor hub and the swashplate of a medium transport helicopter Mi-8 type. As well as interference of components between themselves and the fuselage. The calculations were carried out using modern methods of computational fluid dynamics (CFD). The work was carried out taking into account the decision of The European Commission 7th Framework Programme "Clear Sky" Joint Technology Initiative (JTI).

Quantifying hydraulic roughness in a riparian forest using a drag force‐based method

AbstractFlow resistance through riparian forests due to drag on trees is often expressed in hydraulic models with an increase in a boundary resistance factor such as Manning's n. However, when Manning's n is used as a proxy for vegetation drag, this parameter is dependent on flow conditions and a single, uniform value may be inadequate for simulating a broad range of flood magnitudes. To investigate this issue, flow resistance, and the commensurate Manning's n values through a riparian forest were computed using measured drag forces and estimates of the forest structure and tree morphology. The computed Manning's n values were applied to a 2D hydraulic model (TUFLOW) to simulate an observed flood and a range of design floods. Modelled peak flood levels for the observed flood were 0.16 m lower on average than that recorded at debris marks. There was little difference in modelled flood levels when using the computed Manning's n compared to a traditional, uniform Manning's n. Reassuringly, the traditional method appears adequate when reliable calibration data is available. Otherwise, the method developed here provides a useful alternative in cases where calibration data is limited or for testing reforestation as a nature‐based solution in river or flood management.

Innovative modeling strategy of wind resistance for platoon vehicles based on real-time disturbance observation and parameter identification

Variable inter-vehicle distances influence significantly the wind resistance of platoon vehicles due to the sheltering of airflow. Accurate air drag estimation is extremely important for platoons in scenarios like energy-oriented driving and high-precision tracking. Most aerodynamic researchers have performed qualitative analysis of wind resistance for equally inter-spaced platoons, while the quantitative description of wind resistance variation with coupled inter-vehicle distances is rare. In addition, data measured through offline wind tunnel experiments, Computational Fluid Dynamics (CFD) simulations, or road tests via fuel consumption calibration for a period of time is unsynchronized, which may be unconvincing for real air drag estimation on road. Aiming at the quick and accurate approximation of platoon wind resistance, this paper proposes a novel and universal modeling strategy combining offline CFD simulation, online air drag observation, and real-time parameter identification. The variation characteristics of air drag with distance of a longitudinal platoon consisting of three homogeneous C-class Notchback cars are analyzed by CFD simulation. With appropriate data processing, a well-designed basis function is summarized. Then a novel wind resistance separation method combining Back-Propagation Neural Network (BPNN) and Extended State Observer (ESO) is proposed. Using the observed data stored in experience memory, the hybrid optimization method via particle swarm optimization (PSO) and gradient descent with momentum (GDM) is employed to identify the model parameters toward high accuracy and global optimality. Results of Hardware-In-the-Loop (HIL) experiment show that the proposed modeling strategy realizes effective real-time observation and accuracy description; the developed approximation model can describe the platoon wind resistance with continuous and coupled inter-vehicle distances, with the RMSE less than 11.4%.

LiDAR‐based semi‐automated mapping of drumlins and mega‐scale glacial lineations of the Green Bay Lobe, Wisconsin, USA: Ice sheet beds as glaciotribological systems

AbstractA machine learning methodology for processing and visualizing high‐resolution LiDAR digital data is used to map drumlins and mega‐scale glacial lineations (MSGLs) on the bed of the Late Wisconsin Green Bay Lobe in Wisconsin, USA, which exhibited surge‐like behaviour during deglaciation. Previous work has shown that streamlined bedforms are the product of erosional streamlining of pre‐existing sediment. Analysis of bedform height and elongation ratio using curvature‐based relief separation (CBRS) andK‐means clustering of 32,003 bedforms reveals a continuum of six morphotypes ranging from drumlins, through “channeled” more elongated multi‐crested drumlins, to MSGLs. Further statistical analysis shows that morphotypes cluster into six types of streamlined surfaces (S1–S6) recording progressive elimination of an antecedent overridden topography to produce a smoother bed. Initial, relatively high‐relief drumlinized surfaces (S1, S2) occur around the slower‐flowing lateral flanks of the lobe, where a pre‐existing hummocky morainal topography was only partially modified by subglacial erosion. More streamlined surfaces (S3, S4) dominated by multi‐crested more elongate drumlins of reduced relief amplitude are transitional to flow sets of MSGL‐dominated surfaces (S5, S6) indicative of much faster‐flowing ice streaming along the lobe's axis. Estimates of basal drag based on roughness calculations for each surface type identify a 61% reduction in frictional retardation from poorly streamlined surfaces S1 and S2 to MSGL‐dominated surfaces S5 and S6, with a step‐like reduction between drumlins and channeled drumlins (S3, S4) possibly recording the rapid onset of fast flow. Subglacial streamlining is argued to be accomplished by a thin (<1 m) “third layer” of deforming subglacial debris between ice and its bed which functioned as an erodent layer. A thin (<3 m) till cap, formed by aggradation of deforming debris, rests unconformably on heterogeneous core sediments. Streamlined subglacial surfaces are comparable to the “functional” surfaces resulting from erosion by a “third layer” of wear debris in engineering tribological systems, and also by gouge on faults. Pleistocene ice sheets expanded over pre‐existing landsystems, pointing to the broader relevance of the methodology and findings reported here.

Development of Tail and Nose Cone for Underwater Vertical Profiler Using Fused Deposition Modelling Technology

Unmanned underwater vehicle (UUV) research is currently a prominent and quite well-known topic for researchers from various engineering disciplines. A wide number of applications for 3D printing technologies have been explored, including robotics, automotive components, food, healthcare, space, marine, etc. This paper introduces the implementation of additive manufacturing technology (3D printing) into marine applications. The use of various 3D printing processes to create complex, cost-effective profiles have recently gained popularity to test the durability of newly designed products. The subsequent sections will explain the development of 3D printed nose and tail cones for the Underwater vehicles which will be used for underwater exploration. The development process is divided into the design of nose and tail cones using Solidworks, a 3D design software, flow analysis for the estimation and reduction of drag, operational depth of 3D printed parts using FEA software ANSYS, and prototyping using fused deposition modelling technology. The developed tail and nose cone were implemented into the vertical profiler and tested at the NITK swimming pool and successfully profiled the vertical column of the pool.

Estimation of Drag Finishing Abrasive Effect for Cutting Edge Preparation in Broaching Tool.

In recent years, cutting edge preparation became a topic of high interest in the manufacturing industry because of the important role it plays in the performance of the cutting tool. This paper describes the use of the drag finishing DF cutting edge preparation process on the cutting tool for the broaching process. The main process parameters were manipulated and analyzed, as well as their influence on the cutting edge rounding, material remove rate MRR, and surface quality/roughness (Ra, Rz). In parallel, a repeatability and reproducibility R&R analysis and cutting edge radius re prediction were performed using machine learning by an artificial neural network ANN. The results achieved indicate that the influencing factors on re, MRR, and roughness, in order of importance, are drag depth, drag time, mixing percentage, and grain size, respectively. The reproducibility accuracy of re is reliable compared to traditional processes, such as brushing and blasting. The prediction accuracy of the re of preparation with ANN is observed in the low training and prediction errors 1.22% and 0.77%, respectively, evidencing the effectiveness of the algorithm. Finally, it is demonstrated that the DF has reliable feasibility in the application of edge preparation on broaching tools under controlled conditions.

A multiobjective surrogate-assisted optimisation and exploration of low-boom supersonic transport planforms

Optimal non-planar wing planform geometries for a Mach 2.2 45-seat supersonic transport are generated using Kriging-based Bayesian optimisation techniques on a 22-variable, 3-objective problem for two wing-loading conditions. Sonic boom loudness, drag, and root bending moment are simultaneously minimised at a fixed lift. A Python-based framework is developed for rapid evaluation of designs in a parallel computation environment, automating conceptual geometry generation, optimised mesh griding, Euler CFD evaluation, and thermoviscous atmospheric boom propagation. An empirical turbulent skin friction coefficient is used to correct the Euler drag and an estimate of wave drag is performed. Self-organising maps and polynomial chaos expansion Shapley effects are used to explore the design variables and their associated sensitivities with respect to the design objectives. A geometric centroid-based proxy for trim is used to filter the results; feasible extreme designs and a compromise design are compared and discussed. The results indicate a trade-off between each of the three objectives due to competing design requirements, however an improvement in two of the objective functions is possible by sacrificing the remaining objective. One possible compromise solution reduces the root bending moment coefficient by 25% and the sonic boom loudness by 24% at the cost of a 5% increase in drag.