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At least 19 records

Acoustic and aerodynamic effects of rotor pitch angle for a variable-pitch, 6-foot diameter fan stage

An externally driven, 1.2 pressure ratio full-scale fan stage with an adjustable pitch rotor was tested in an outdoor facility at the Lewis Research Center. Rotor pitch angles resulting in minimum sideline perceived noise levels are defined as a function of stage thrust. Thrust-corrected fan noise variations are examined for operation at constant thrust, rotor tip speed, and stage work coefficient. At constant stage thrust, reducing the rotor pitch angle below design values increased the fan noise with the greatest change occurring in the blade passing tone level. At constant fan speed the minimum noise occurred at a particular rotor pitch angle, which was not the minimum thrust condition. With constant stage work coefficient, rear quadrant noise increased at above-design speed conditions.

Woodward, R. P.↗

Blunt Body Pitch Damping Measurements from Multiple Subsonic Free-to-Pitch Magnetic Suspension Trials

The yaw damping coefficients of two blunt entry vehicle models, measured from free-to-oscillate tests in the ODU/NASA subsonic magnetic suspension wind tunnel are presented. Multiple repeat trials were conducted for both models. Two separate data reduction methods were used to extract damping coefficients and yaw moment slope. Both methods identified similar damping and stability values, with differences being consistent with their known limitations.

magnetic suspension↗

Evolution of Pitch Angle Distributions of Relativistic Electrons During Geomagnetic Storms: Van Allen Probes Observations

We present a study analyzing relativistic and ultra relativistic electron energization and the evolution of pitch angle distributions using data from the Van Allen Probes. We study the connection between energization and isotropization to determine if there18is a coherence across storms and across energies. Pitch angle distributions are fit with a J(sub 0) sin(sup n)θ function, and the variable ’n’ is characterized as the pitch angle index and tracked over time. Our results show that, consistently across all storms with ultra relativistic electron energization, electron distributions are most anisotropic within around a day of Dst(sub min) and become more isotropic in the following week. Also, each consecutively higher energy channel is associated with higher anisotropy after storm main phase. Changes in the pitch angle index are reflected in each energy channel; when 1.8 MeV electron pitch angle distributions increase (or decrease) in pitch angle index, so do the other energy channels. We show that the peak anisotropies differ between CME- and CIR- driven storms and measure the relaxation rate as the anisotropy falls after the storm. The isotropization rate in pitch angle index for CME-driven storms is -0.15±0.02 day(sup −1) at 1.8 MeV, -0.30±0.01 day(sup −1) at 3.4 MeV, and -0.39±0.02 day(sup −1) at 5.2 MeV. For CIR-driven storms, the isotropization rates are -0.10±0.01 day(sup −1) for 1.8 MeV, -0.13±0.02 day(sup −1) for 3.4 MeV, and -0.11±0.0231 day(sup −1) for 5.2 MeV. This study shows that there is a global coherence across energies and that storm type may play a role in the evolution of electron pitch angle distributions. Plain Language Summary Using Van Allen Probes data, we measure pitch angle distributions of relativistic and ultra relativistic electrons. Anisotropic pitch angle distributions are sharply peaked around 90 degrees. More evenly distributed pitch angles are isotropic. Our results show that, consistently across all storms with ultra relativistic electron enhancements, electrons are most anistropic within around a day of storm onset and slowly isotropize in the following week. In addition, each consecutively higher energy channel is also associated with higher anisotropy after the main phase of geomagnetic storms, a characteristic which holds through the storm and recovery. Changes in the pitch angle index are reflected in each energy channel; when 1.8 MeV electrons increase (or decrease) in pitch angle index, so do all the other energy channels. In a superposed epoch study, we show that the peak anisotropies differ between different storm drivers (namely, coronal mass ejections and corotating interaction regions) and measure the isotropization rate as the anisotropy falls after the storm. This study shows that there is a global coherence across energies and that storm type may play a role in the evolution of electron pitch angle distributions.

pitch angle distributions↗

Comparison of Pre- and Post-Flight Estimations of Pitch Damping Coefficients for Unguided Entry Vehicles

Introduction: Pre-flight predictions of pitch damping coefficient (𝐶!!+𝐶!"̇)curves are used in entry simulations to determine flight readiness and if any dynamic remediation strategies are required. Accurate characterization of these pitch damping coefficient curves is crucial for mission success. Historically, pre-flight estimations of these curves are derived experimentally either via ballistic range testing or with 1-degree-of-freedom (DOF) free-or forced-oscillation wind tunnel testing. Methodology:With post-flight best-estimated trajectories, a fitting procedure as described in Karlgaard, et. al. [1] is used to compare pre-and post-flight pitch damping coefficients. This technique relies on an assumed analytical form of the trajectory, a limited 3-DOF representation described in Schoenenbergerand Queen [2], which results in anEuler-Cauchy solution form.This solution assumes constant density,thus limited amplitude multi-peak windows of the trajectory are considered to populate the pitch damping-amplitudes pace. Fig. 1 shows preliminary estimations of the pitch damping coefficients estimated using the post-flight best estimated trajectoryfor MER B, using a3-amplitude-peak window. Important to note is that the Euler-Cauchy solution also assumes planar motion, thus coning or 𝛽contribution is not included. Further,the estimated post-flight pitch damping approximations and the pre-flight predictions shown are effective representations of pitch damping, or the integrated effect of the pitch damping coefficient over one pitch cycle at the corresponding cycle’s peak amplitude. Effective pitch damping coefficient curves provide more intuitive insights about where the vehicle is stable and permits readily processed comparisons between data-sets. It is important to note that most pitch damping curves, such as those reported in aerodatabases and utilized in flight mechanics trajectory simulations, are represented in instantaneous angle-of-attack space distinct from what is presented in Fig 1. The extracted post-flight pitch damping coefficient points show a wide range of values across a narrow band of amplitudes (Fig.1a), albeit centered on the published pre-flight approximation. This also applies to the prediction as a function of Mach in Fig1b, where the post-flight scatter points are centered around the pre-flight predictions, but the pre-flight predictions notably lack data aboveMach 5.Further tuning of the technique, such as changing the number of peaks considered in each stencil, resolving density in higher resolution, and employing more accurate fitting procedures (beyond scipy.curve_fit()), will be performed. PosterFocus:This study will apply this reconstruction method to the as-flown trajectories for the following unguided entry vehicles: MER A, MER B, IRVE3, Phoenix, Insight, Pathfinder, and SIAD. The pitch damping coefficient will be derived from these trajectories and compared with the pre-flight predictions. Comparing across different missions, entry environments, and vehicle geometries can inform where our pre-flight testing methodologies accurately capture the flight dynamics. Results will provide valuable insight into the accuracy of pre-flight predicted pitch damping curves. Beyond that, this method can shed light on how accurate these curves need to be, which can inform uncertainty ranges applied to pre-flight curves for other missions.

pitch damping coefficient↗

Why do pitched horizontal lines have such a small effect on visually perceived eye level?

In two experiments, visually perceived eye level (VPEL) was measured while subjects viewed two-dimensional displays that were either upright or pitched 20 degrees top-toward or 20 degrees top-away from them. In Experiment 1, it was demonstrated that binocular exposure to a pair of pitched vertical lines or to a pitched random dot pattern caused a substantial upward VPEL shift for the top-toward pitched array and a similarly large downward shift for the top-away array. On the other hand, the same pitches of a pair of horizontal lines (viewed binocularly or monocularly) produced much smaller VPEL shifts. Because the perceived pitch of the pitched horizontal line display was nearly the same as the perceived pitch of the pitched vertical line and dot array, the relatively small influence of pitched horizontal lines on VPEL cannot be attributed simply to an underestimation of their pitch. In Experiment 2, the effects of pitched vertical lines, dots, and horizontal lines on VPEL were again measured, together with their effects on resting gaze direction (in the vertical dimension). As in Experiment 1, vertical lines and dots caused much larger VPEL shifts than did horizontal lines. The effects of the displays on resting gaze direction were highly similar to their effects on VPEL. These results are consistent with the hypothesis that VPEL shifts caused by pitched visual arrays are due to the direct influence of these arrays on the oculomotor system and are not mediated by perceived pitch.

NASA Center ARC↗

Progress on Inverse Estimation Technique of Non-Linear Pitch Damping Coefficient Curves Using Free-Flight CFD Generated Trajectories

Characterization of entry vehicle pitch damping coefficient curves is crucial to ensure appropriate re-entry and overall mission success. The pitch damping coefficient (C_(m_q )+C_(m_α ̇ )) is used to encapsulate the oscillatory growth or decay of a body during a trajectory. The inverse estimation technique utilizes an existing Free-Flight CFD (FF-CFD) dataset and wraps a reconstruction algorithm in an optimizer. The reconstruction integrates the planar equations of motion derived by Schoenenberger, Queen [1] using Python’s scipy.integrate.solve_ivp. The optimizer’s objective function is the normalized 𝐿2 residual of the angle of attack peaks between the reconstructed trajectory and the original data produced with FF-CFD. Inclusion of the peak times in this residual calculation allows for simultaneous optimization of the pitch moment coefficient, C_(m_α ). This residual equation is shown below in Eq. 1. The optimizer scipy.optimize.minimize was used with the gradient-based Powell method for the analysis presented, however the differential evolution method was investigated as means of comparison, and was found to produce marginally lower residual values with prohibitively longer run times. Further, the pitch damping curve is found by fitting a cubic interpolation function to a set of (α, (C_(m_q )+C_(m_α ̇ ))) control points, where the α points are held constant and the (C_(m_q )+C_(m_α ̇ )) values are the optimized parameters. The pitch moment curve uses a linear interpolation between the minimum and maximum α in the dataset. FF-CFD generated trajectories using the Dragonfly capsule geometry with the Genesis ballistic range model parameters were simulated and used for this analysis. These FF-CFD trajectories simulate planar motion, as restricted by the reconstructing the equations of motion, of three different cases: 1-DoF (free-to-pitch), 2-DoF (free-to-pitch and heave), and 3-DoF (free-to-pitch, heave, and decelerate). Pitch damping coefficient curves generated using this inverse estimation curve technique with FF-CFD 1-DoF Dragonfly data are found in Fig. 1. Preliminary results reconstructing ballistic range shots using these FF-CFD derived predictions of the pitch damping curve (Fig. 1) are shown in Fig. 2. It should be noted that the ballistic range shot used a Genesis model whereas the FF-CFD data used a Dragonfly geometry, however these geometries are similar.

entry↗

Comparison of Pre- and Post-Flight Estimations of Pitch Damping Coefficients for Unguided Entry Vehicles

Pre-flight predictions of pitch damping coefficient (C M q + C m ȧ ) curves are used in entry simulations to determine flight readiness and if any dynamic remediation strategies are required. Accurate characterization of these pitch damping coefficient curves is crucial for mission success. Historically, pre-flight estimations of these curves are derived experimentally either via ballistic range testing or with 1-degree-of-freedom (DOF) free-or forced-oscillation wind tunnel testing. With post-flight best-estimated trajectories, a fitting procedure as described in Karlgaard, et. al. is used to compare pre-and post-flight pitch damping coefficients. This technique relies on an assumed analytical form of the trajectory, a limited 3-DOF representation described in Schoenenberger and Queen, which results in an Euler-Cauchy solution form. This solution assumes constant density, thus limited amplitude multi-peak windows of the trajectory are considered to populate the pitch damping-amplitudes pace. The estimated post-flight pitch damping approximations and the pre-flight predictions shown are effective representations of pitch damping, or the integrated effect of the pitch damping coefficient over one pitch cycle at the corresponding cycle’s peak amplitude. Effective pitch damping coefficient curves provide more intuitive insights about where the vehicle is stable and permits readily processed comparisons between data-sets. It is important to note that most pitch damping curves, such as those reported in aero databases and utilized in flight mechanics trajectory simulations, are represented in instantaneous angle-of-attack space distinct from what is presented in the paper.

pitch damping coefficient↗

Static investigation of two STOL nozzle concepts with pitch thrust-vectoring capability

A static investigation of the internal performance of two short take-off and landing (STOL) nozzle concepts with pitch thrust-vectoring capability has been conducted. An axisymmetric nozzle concept and a nonaxisymmetric nozzle concept were tested at dry and afterburning power settings. The axisymmetric concept consisted of a circular approach duct with a convergent-divergent nozzle. Pitch thrust vectoring was accomplished by vectoring the approach duct without changing the nozzle geometry. The nonaxisymmetric concept consisted of a two dimensional convergent-divergent nozzle. Pitch thrust vectoring was implemented by blocking the nozzle exit and deflecting a door in the lower nozzle flap. The test nozzle pressure ratio was varied up to 10.0, depending on model geometry. Results indicate that both pitch vectoring concepts produced resultant pitch vector angles which were nearly equal to the geometric pitch deflection angles. The axisymmetric nozzle concept had only small thrust losses at the largest pitch deflection angle of 70 deg., but the two-dimensional convergent-divergent nozzle concept had large performance losses at both of the two pitch deflection angles tested, 60 deg. and 70 deg.

Mason, M. L.↗

Particle chaos and pitch angle scattering

Pitch angle scattering is a factor that helps determine the dawn-to-dusk current, controls particle energization, and it has also been used as a remote probe of the current sheet structure. Previous studies have interpreted their results under the exception that randomization will be greatest when the ratio of the two timescales of motion (gyration parallel to and perpendicular to the current sheet) is closet to one. Recently, the average expotential divergence rate (AEDR) has been calculated for particle motion in a hyperbolic current sheet (Chen, 1992). It is claimed that this AEDR measures the degree of chaos and therefore may be thought to measure the randomization. In contrast to previous expectations, the AEDR is not maximized when Kappa is approximately equal to 1 but instead increases with decreasing Kappa. Also contrary to previous expectations, the AEDR is dependent upon the parameter b(sub z). In response to the challenge to previous expectations that has been raised by this calculation of the AEDR, we have investigated the dependence of a measure of particle pitch angle scattering on both the parameters Kappa and b(sub z). We find that, as was previously expected, particle pitch angle scattering is maximized near Kappa = 1 provided that Kappa/b(sub z) greater than 1. In the opposite regime, Kappa/b(sub z) less than 1, we find that particle pitch angle scattering is still largest when the two timescales are equal, but the ratio of the timescales is proportional to b(sub z). In this second regime, particle pitch angle scattering is not due to randomization, but is instead due to a systematic pitch angle change. This result shows that particle pitch angle scattering need not be due to randomization and indicates how a measure of pitch angle scattering can exhibit a different behavior than a measure of chaos.

Burkhart, G. R.↗

Combined influences of gravitoinertial force level and visual field pitch on visually perceived eye level

Psychophysical measurements of the level at which observers set a small visual target so as to appear at eye level (VPEL) were made on 13 subjects in 1.0 g and 1.5 g environments in the Graybiel Laboratory rotating room while they viewed a pitched visual field or while in total darkness. The gravitoinertial force was parallel to the z-axis of the head and body during the measurements. The visual field consisted of two 58 degrees high, luminous, pitched-from-vertical, bilaterally symmetric, parallel lines, viewed in otherwise total darkness. The lines were horizontally separated by 53 degrees and presented at each of 7 angles of pitch ranging from 30 degrees with the top of the visual field turned away from the subject (top backward) to 30 degrees with the top turned toward the subject (top forward). At 1.5 g, VPEL changed linearly with the pitch of the 2-line stimulus and was depressed with top backward pitch and elevated with top forward pitch as had been reported previously at 1.0 g (1,2); however, the slopes of the VPEL-vs-pitch functions at 1.0 g and 1.5 g were indistinguishable. As reported previously also (3,4), the VPEL in darkness was considerably lower at 1.5 g than at 1.0 g; however, although the y-intercept of the VPEL-vs-pitch function in the presence of the 2-line visual field (visual field erect) was also lower at 1.5 g than at 1.0 g as it was in darkness, the G-related difference was significantly attenuated by the presence of the visual field. The quantitative characteristics of the results are consistent with a model in which VPEL is treated as a consequence of an algebraic weighted average or a vector sum of visual and nonvisual influences although the two combining rules lead to fits that are equally good.

Non-NASA Center↗

Acoustic and aerodynamic testing of a scale model variable pitch fan

A fully reversible pitch scale model fan with variable pitch rotor blades was tested to determine its aerodynamic and acoustic characteristics. The single-stage fan has a design tip speed of 1160 ft/sec (353.568 m/sec) at a bypass pressure ratio of 1.5. Three operating lines were investigated. Test results show that the blade pitch for minimum noise also resulted in the highest efficiency for all three operating lines at all thrust levels. The minimum perceived noise on a 200-ft (60.96 m) sideline was obtained with the nominal nozzle. At 44% of takeoff thrust, the PNL reduction between blade pitch and minimum noise blade pitch is 1.8 PNdB for the nominal nozzle and decreases with increasing thrust. The small nozzle (6% undersized) has the highest efficiency at all part thrust conditions for the minimum noise blade pitch setting; although, the noise is about 1.0 PNdB higher for the small nozzle at the minimum noise blade pitch position.

Jutras, R. R.↗