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At least 19 records

Aerodynamic integration produces a vehicle shape with a negative drag coefficient

Negative drag coefficients are normally associated with a vessel outfitted with a sail to extract energy from the wind and propel the vehicle forward. Therefore, the notion of a heavy vehicle, that is, a semi truck, that generates negative aerodynamic drag without a sail or any external appendages may seem implausible, especially given the fact that these vehicles have some of the largest drag coefficients on the road today. However, using both wind tunnel measurements and computational fluid dynamics simulations, we demonstrate aerodynamically integrated vehicle shapes that generate negative body-axis drag in a crosswind as a result of large negative frontal pressures that effectively “pull” the vehicle forward against the wind, much like a sailboat. While negative body-axis drag exists only for wind yaw angles above a certain analytical threshold, the negative frontal pressures exist at smaller yaw angles and subsequently produce body-axis drag coefficients that are significantly less than those of modern heavy vehicles. The application of this aerodynamic phenomenon to the heavy vehicle industry would produce sizable reductions in petroleum use throughout the United States.

42 ENGINEERING↗

Profile-Drag Coefficients of Conventional and Low-Drag Airfoils as Obtained in Flight

Results of flight tests indicate that profile-drag coefficients which were obtained with the low-drag airfoils were lower than with the conventional types over the range of light coefficients tested. For comparable conditions of the lift coefficient and Reynolds Number, the low-drag airfoils have profile-drag coefficients which may be 27 percent lower than the profile drag of the conventional airfoils tested. Detailed results are presented graphically.

AIRFOILS - NAVY N-22 - CHARACTERISTICS↗

Effects of turbulence and number density on the drag coefficient of droplets

Droplet drag coefficients for polydispersed drops are determined via the behavior of drops decelerating on the stagnation streamline of a cylinder with an afterbody mounted in a wind tunnel test section. A variety of velocity, turbulence levels, and droplet number densities were studied. A force balance equation technique was used to determine drag coefficient. For the levels of number density, up to 700/cc, and turbulence, up to about 7 percent, no definite effects were seen. However, the smallest drops in the high turbulence case showed some evidence of drop-turbulence and/or drop-drop interactions. The drag results that were developed for this set of measurements agreed well with other empirical relations previously determined.

Rudoff, R. C.↗

An Investigation of the Effects of Volume Fraction on Drag Coefficient of Non-Spherical Particles Using PR-DNS

Prediction of the drag coefficient is required in gas-particle multiphase flow modeling and simulation. Experimental data and correlations on the fixed-bed system of spherical particles with high volume fractions for various possible arrangements are available in the literature. However, the effect of volume fraction on the drag coefficient of non-spherical particles is not well studied. In solving the momentum equation, the volume fraction plays a vital role in determining the flow resistances. In this paper, we study the impact of volume fraction in the range of 0.069 to 0.65 on the drag coefficient using the computational fluid dynamics (CFD) simulation of air for Reynold number in the range of 10 to 10000 using particle resolved direct numerical solution (PR-DNS). Regular non-spherical particles such as a cube, tetrahedron, and spheroids are used in this study since their single particle’s drag coefficient data are available in the literature for comparison. For this work, the simulations are carried out in the Ansys Fluent using polyhedral mesh, which consumes significantly less computational time and power. The study showed the sphericity and volume fraction have significant impact on the bed pressure drop and average drag coefficient of the particles in the bed especially in high Reynolds number regime. The bed of the spheroid experiences the lowest drag being the most streamlined particle, and the particles with the edges result in a large drag coefficient due to flow separation at the discontinuity. The vector plots verify this behavior where large wake regions are observed behind the tetrahedron particle.

Mahyawansi, Pratik↗

Pre-Test Assessment of the Upper Bound of the Drag Coefficient Repeatability of a Wind Tunnel Model

A new method is presented that computes a pre{test estimate of the upper bound of the drag coefficient repeatability of a wind tunnel model. This upper bound is a conservative estimate of the precision error of the drag coefficient. For clarity, precision error contributions associated with the measurement of the dynamic pressure are analyzed separately from those that are associated with the measurement of the aerodynamic loads. The upper bound is computed by using information about the model, the tunnel conditions, and the balance in combination with an estimate of the expected output variations as input. The model information consists of the reference area and an assumed angle of attack. The tunnel conditions are described by the Mach number and the total pressure or unit Reynolds number. The balance inputs are the partial derivatives of the axial and normal force with respect to all balance outputs. Finally, an empirical output variation of 1.0 microV/V is used to relate both random instrumentation and angle measurement errors to the precision error of the drag coefficient. Results of the analysis are reported by plotting the upper bound of the precision error versus the tunnel conditions. The analysis shows that the influence of the dynamic pressure measurement error on the precision error of the drag coefficient is often small when compared with the influence of errors that are associated with the load measurements. Consequently, the sensitivities of the axial and normal force gages of the balance have a significant influence on the overall magnitude of the drag coefficient's precision error. Therefore, results of the error analysis can be used for balance selection purposes as the drag prediction characteristics of balances of similar size and capacities can objectively be compared. Data from two wind tunnel models and three balances are used to illustrate the assessment of the precision error of the drag coefficient.

drag coefficient measurement↗

Atmospheric Form Drag Coefficients Over Arctic Sea Ice Using Remotely Sensed Ice Topography Data, Spring 2009-2015

Sea ice topography significantly impacts turbulent energy/momentum exchange, e.g., atmospheric (wind) drag, over Arctic sea ice. Unfortunately, observational estimates of this contribution to atmospheric drag variability are spatially and temporally limited. Here we present new estimates of the neutral atmospheric form drag coefficient over Arctic sea ice in early spring, using high-resolution Airborne Topographic Mapper elevation data from NASA's Operation IceBridge mission. We utilize a new three-dimensional ice topography data set and combine this with an existing parameterization scheme linking surface feature height and spacing to form drag. To be consistent with previous studies investigating form drag, we compare these results with those produced using a new linear profiling topography data set. The form drag coefficient from surface feature variability shows lower values [less than 0.5-1 × 10(exp. −3)] in the Beaufort/Chukchi Seas, compared with higher values [greater than 0.5-1 ×10(exp. −3)] in the more deformed ice regimes of the Central Arctic (north of Greenland and the Canadian Archipelago), which increase with coastline proximity. The results show moderate interannual variability, including a strong increase in the form drag coefficient from 2013 to 2014/2015 north of the Canadian Archipelago. The form drag coefficient estimates are extrapolated across the Arctic with Advanced Scatterometer satellite radar backscatter data, further highlighting the regional/interannual drag coefficient variability. Finally, we combine the results with existing parameterizations of form drag from floe edges (a function of ice concentration) and skin drag to produce, to our knowledge, the first pan-Arctic estimates of the total neutral atmospheric drag coefficient (in early spring) from 2009 to 2015.

sea ice↗

Determination of the hypersonic-continuum/rarefied-flow drag coefficient of the Viking lander capsule 1 aeroshell from flight data

Results of an investigation to determine the full scale drag coefficient in the high speed, low density regime of the Viking lander capsule 1 entry vehicle are presented. The principal flight data used in the study were from onboard pressure, mass spectrometer, and accelerometer instrumentation. The hypersonic continuum flow drag coefficient was unambiguously obtained from pressure and accelerometer data; the free molecule flow drag coefficient was indirectly estimated from accelerometer and mass spectrometer data; the slip flow drag coefficient variation was obtained from an appropriate scaling of existing experimental sphere data. Comparison of the flight derived drag hypersonic continuum flow regime except for Reynolds numbers from 1000 to 100,000, for which an unaccountable difference between flight and ground test data of about 8% existed. The flight derived drag coefficients in the free molecule flow regime were considerably larger than those previously calculated with classical theory. The general character of the previously determined temperature profile was not changed appreciably by the results of this investigation; however, a slightly more symmetrical temperature variation at the highest altitudes was obtained.

Blanchard, R. C.↗

Optimization-based calibration of hydrodynamic drag coefficients for a semisubmersible platform using experimental data of an irregular sea state

For the simulation of the coupled dynamic response of floating offshore wind turbines, it is crucial to calibrate the hydrodynamic damping with experimental data. The aim of this work is to find a set of hydrodynamic drag coefficients for the semisubmersible platform of the Offshore Code Comparison Collaboration, Continuation, with Correlation and unCertainity (OC6) project which provides suitable results for an irregular sea state. Due to the complex interaction of several degrees of freedom (DOF), it is common to calibrate drag coefficients with the time series of decay tests. However, applying these drag coefficients for the simulation of an irregular sea state results in misprediction of the motions. By using numerical optimization, it is possible to calibrate multiple drag coefficients simultaneously and effectively, while also considering several DOF. This work considers time series of structural displacements from wave tank tests of the OC6 project and from simulations of the same load cases in OpenFAST. Results are transferred into the frequency domain and the deviation between power spectral densities of surge, pitch and heave from experiment and numerical simulation is used as an objective function to obtain the best fitting drag coefficients. This novel numerical optimization approach enables finding one set of drag coefficients for different load cases, which is a major improvement compared to decay-test-tuned drag coefficients.

42 ENGINEERING↗

Development of a Deep Learning Model for Predicting the Drag Coefficients of Spherical and Non-Spherical Particles,

There is yet to be a well-established drag model for non-spherical particles required in a particle-laden flow that could cover a wide range of sphericities. This talk will explore the development of a general drag model for non-spherical particles by applying deep learning using available experimental data available in the literature. The integration of several raw experimental measurements from different sources and research directions allows the training of robust Artificial Intelligence and Machine Learning (ML) models. Neural networks are an ML approach inspired by the inner biological workings of the brain. This work aims to develop a Deep Neural Network (DNN) that predicts drag coefficient values with the ability to adapt appropriately to unseen data. Given the limited number of data points available and the variance found within the data collected from various sources, challenges may arise when looking to train the model. Our study tests and implements various model regularization techniques and assesses different loss and activation functions for the proposed DNN. The proposed model considers a broader range of features other than sphericity and Reynold number. These features include density ratio, solid volume fraction, lengthwise and crosswise sphericity, and more. Furthermore, we present the features that play a significant role in predicting different drag coefficients through feature importance. Within the investigated parameter ranges in this study, the following conclusions can be achieved and summarized below: • An improved drag coefficient model can be developed by considering more features such as, aspect ratio, lengthwise sphericity, crosswise sphericity, and density ratio. • DNN model can predict better results compared to traditional methods using MAE metric. • The proposed model addresses data challenges such as limited data and extreme data points through expanded feature-set and regularization. • Three major features that mostly affect the drag coefficient were identified from a feature importance analysis.

Presa-Reyes, Maria↗

Constraining the Drag Coefficients of Meteors in Dark Flight

Based on data in the aeronautics literature, we have derived functions for the drag coefficients of spheres and cubes as a function of Mach number. Experiments have shown that spheres and cubes exhibit an abrupt factor-of-two decrease in the drag coefficient as the object slows through the transonic regime. Irregularly shaped objects such as meteorites likely exhibit a similar trend. These functions are implemented in an otherwise simple projectile motion model, which is applicable to the non-ablative dark flight of meteors (speeds less than .+3 km/s). We demonstrate how these functions may be used as upper and lower limits on the drag coefficient of meteors whose shape is unknown. A Mach-dependent drag coefficient is potentially important in other planetary and astrophysical situations, for instance, in the core accretion scenario for giant planet formation.

Carter, R. T.↗

Review—Drag Coefficients of Non-Spherical and Irregularly Shaped Particles

Abstract The knowledge of simple and relatively accurate closure equations for the drag coefficients of nonspherical particles is very important for Eulerian multiphase numerical codes that require such inputs for the solution of the momentum equation. However, the existing correlations for the drag coefficients are laden with high uncertainty, which propagates in the numerical results. This review paper examines critically the state of our knowledge of the drag coefficients of nonspherical particles starting with our understanding of the “size” and “shape” of particles. Lengthscales and other parameters that have been used to characterize sizes of nonspherical particles are presented. Shape factors and shape descriptors that have been used in past correlations are also presented together with an appraisal of their applicability. Several correlations that have been developed for the determination of the drag coefficients of nonspherical particles with regular and irregular shapes are also presented together with available information on their accuracy and applicability. Based on the review of the available correlations general recommendations are offered on the use of the correlations as closure equations and inputs in computatioal fluid dynamics (CFD) codes.

Engineering↗

Drag coefficients for winter Antarctic pack ice

Air-ice and ice-water drag coefficients referenced to 10-m-height winds for winter Antarctic pack ice based on measurements made from R/V Polarstern during the Winter Weddell Sea Project, 1986 (WWSP-86), and from R/V Akademik Fedorov during the Winter Weddell Gyre Study, 1989 (WWGS-89), are presented. The optimal values of the air-ice drag coefficients, made from turbulent flux measurements, are (1.79 +/- 0.06) x 10 exp -3 for WWSP-86 and (1.45 +/- 0.09) x 10 exp -3 for WWGS-89. A single ice-water drag coefficient for both WWSP-86 and WWGS-89, estimated from periods of ice drift throught to represent free-drift conditions, is (1.13 +/- 0.26) x 10 exp -3, and the ice-water turning angle is 18 +/- 18 deg. It is suggested that for a typical Antarctic winter pack ice cover, the ice cover reduces the momentum flux from the atmosphere to the ocean by about 33 percent.

Wamser, Christian↗

Impact of Limited Degree of Freedom Drag Coefficients on a Floating Offshore Wind Turbine Simulation

The worldwide effort to design and commission floating offshore wind turbines (FOWT) is motivating the need for reliable numerical models that adequately represent their physical behavior under realistic sea states. However, properly representing the hydrodynamic quadratic damping for FOWT remains uncertain, because of its dependency on the choice of drag coefficients (dimensionless or not). It is hypothesized that the limited degree of freedom (DoF) drag coefficient formulation that uses only translational drag coefficients causes mischaracterization of the rotational DoF drag, leading to underestimation of FOWT global loads, such as tower base fore-aft shear. To address these hydrodynamic modeling uncertainties, different quadratic drag models implemented in the open-source mid-fidelity simulation tool, OpenFAST, were investigated and compared with the experimental data from the Offshore Code Comparison Collaboration, Continued, with Correlation (OC5) project. The tower base fore-aft shear and up-wave mooring line tension were compared under an irregular wave loading condition to demonstrate the effects of the different damping models. Two types of hydrodynamic quadratic drag formulations were considered: (1) member-based dimensionless drag coefficients applied only at the translational DoF (namely limited-DoF drag model) and (2) quadratic drag matrix model (in dimensional form). Based on the results, the former consistently underestimated the 95th percentile peak loads and spectral responses when compared to the OC5 experimental data. In contrast, the drag matrix models reduced errors in estimates of the tower base shear peak load by 7–10% compared to the limited-DoF drag model. The underestimation in the tower base fore-aft shear was thus inferred be related to mischaracterization of the rotational pitch drag and the heave motion/drag by the limited-DoF model.

17 WIND ENERGY↗

The Sensitivity of Large-Eddy Simulation to Local and Nonlocal Drag Coefficients at the Lower Boundary

It was found that the homogeneity of the surface drag coefficient plays an important role in the large scale structure of turbulence in large-eddy simulation of the convective atmospheric boundary layer. Particularly when a ground surface temperature was specified, large horizontal anisotropies occurred when the drag coefficient depended upon local velocities and heat fluxes. This was due to the formation of streamwise roll structures in the boundary layer. In reality, these structures have been found to form when shear is approximately balanced by buoyancy. The present cases, however, were highly convective. The formation was caused by particularly low values of the drag coefficient at the entrance to thermal plume structures.

Schowalter, D. G.↗