Search NASA⌕ Search

SEARCH · Search NASA

Results for “DRAG COEFFICIENT”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1944

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↗
NASA NTRS1991

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.↗
NASA NTRS2017

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↗
NASA NTRS2017

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↗
NASA NTRS1980

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.↗
NASA NTRS2011

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.↗
NASA NTRS1993

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↗
DOE OSTI2023

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↗
NASA NTRS1996

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.↗
NASA NTRS1983

The drag coefficient of cylindrical spacecraft in orbit at altitudes greater than 150 km

The spacecraft of the Geopotential Research Mission (GRM) are cylindrical in form and designed to fly with their longitudinal axes parallel to their direction of flight. The ratio of length to diameter of these spacecraft is roughly equal to 5.0. Other spacecraft previously flown had corresponding ratios roughly equal to 1.0, and therefore the drag produced by impacts on the lateral surfaces of those spacecraft was not as large as it will be on the GRM spacecraft. Since the drag coefficient is essentially the drag force divided by the frontal area in flight, lateral impacts, when taken into account make the GRM drag coefficient significantly larger than the coefficients used before for shorter spacecraft. A simple formula is derived for the drag coefficient of a cylindrical body flying with its long axis along the direction of flight, and it is used to estimate the drag for the GRM. The formula shows that the drag due to lateral surface impacts depends on the ratio of length-to-diameter and on a coefficient C sub LS (lateral surface impact coefficient) which can be determined from previous cylindrical spacecraft flown with the same attitude, or can be obtained from laboratory measurements of momentum accommodation coefficients.

Herrero, F. A.↗
NASA NTRS1961

The Drag Coefficient of Parabolic Bodies of Revolution Operating at Zero Cavitation Number and Zero Angle of Yaw

The form-drag coefficient of parabolic bodies of revolution with fineness ratios greater than 1 operating at zero angle of yaw and zero cavitation number is determined both theoretically and experimentally. Agreement between theory and experiment is very good, The theoretical form-drag coefficient of paraboloids is about half the form-drag coefficient of cones of comparable fineness ratio.

Johnson, Virgil E., Jr.↗
NASA NTRS1977

Comment on 'Drag coefficient of spheres in continuum and rarefied flows'

A paper by Henderson (1976) provides a method of predicting experimental sphere drag data. This approach uses two equations for the drag coefficient, one for relative Mach number less than one, one for relative Mach number greater than 1.75. For relative Mach numbers between these limits a linear interpolation procedure is followed. In a comment on this paper, it is claimed, on the basis of comparing predictions with experimental results, that a method proposed by Walsh (1975) gives better predictions of the drag coefficient for relative Mach numbers less than 1.75, provided that a modification of the procedure is made for relative Mach numbers less than 0.1. For values over 1.75, both methods are considered equally accurate. In a reply to this comment, it is agreed that the Walsh method is more accurate when Reynolds numbers are within a range between 20 and 200, and Mach numbers are between 0.5 and 1.25. Presumed errors and possible limitations in the Walsh procedure for predicting drag coefficients are discussed.

Walsh, M. J.↗
NASA NTRS1986

Variation of the drag coefficient and its dependence on sea state

Using a Gill propeller vane anemometer and resistance wave wires over a water column depth of 15 m, simultaneous measurements of the momentum flux and sea surface wave spectra were acquired from the Pisa mast, 28 km offshore in the German Bight during autumn and winter 1979. These data were analyzed to identify the relationship between wind stress and surface waves. It was found that wind stresses for wind speeds above 15 m/s were regularly higher than open ocean wind stresses as reported by Smith (1980) and by Large and Pond (1981) for the same mean wind speed. These results, when described in terms of the drag coefficient, compared closely with the results of Sheppard et al. (1972), who collected surface layer statistics over Lough Neagh, Northern Ireland. After modeling the surface waves of the North Sea as a function of wave saturation (or wave age), it became evident that variations in the magnitude of the drag coefficient could be explained by coincident variations in the surface wave energy spectrum. By applying the wave dependent roughness length model described by Kitaigorodskii (1973), the North Sea drag coefficient was predicted to be larger than drag coefficients reported from the open sea.

Geernaert, G. L.↗
NASA NTRS1988

The effect of sting interference at low speeds on the drag coefficient of an ellipsoidal body using a magnetic suspension and balance system

A Boltz body of revolution (fineness ratio 7.5:1) was tested in the Southampton University Magnetic Suspension and Balance System. The effects of sting interference on the drag coefficient of the model at zero angle of attack were noted as well as the effects on drag coefficient values at boundary layer trips. The drag coefficient values were compared with other sources and seemed to show agreement. The pressure distribution over the rear of the model with no sting interference was investigated including the use of boundary layer trips.

Newcomb, A. W.↗
DOE OSTI2024

Comparative Evaluation of Control-Oriented Heavy Duty Vehicle Air Drag Coefficient Models

Heavy-duty vehicles (HDVs) are a significant source of fuel consumption and greenhouse gas emissions, prompting solutions such as HDV platooning to mitigate these negative impacts through air drag reduction. The intervehicle distance in an HDV platoon needs to be carefully selected, such that the platoon-level energy efficiency and safety considerations can be well balanced. Underlying this problem lies in accurately modeling the relationship between HDV air drag coefficient and intervehicle distance. Through comprehensive evaluation and comparison, we analyze five control-oriented HDV air drag coefficient models, including the polynomial model, rational polynomial model, rational model, semi-quadratic model, and ridge model. Leveraging Scipy Curve-Fit toolbox and our previously compiled air drag coefficient datasets, we optimally identify the parameters inside each model. The calibrated models are then thoroughly evaluated via five complementary metrics. The comparison results reveal that the semi-quadratic model has the highest overall performance, while the widely adopted rational model only exhibits suboptimal performance.

Best, Micah↗