Engineering topics

Campbell-Brown, M. D.

Publications and source records attributed to Campbell-Brown, M. D..

7 records

NASA NTRS2017

Recent Corrections to Meteoroid Environment Models

The dynamical and physical characteristics of a meteoroid affects its behavior in the atmosphere and the damage it does to spacecraft surfaces. Accurate environment models must therefore correctly describe the speed, size, density, and direction of meteoroids. However, the measurement of dynamical characteristics such as speed is subject to observational biases, and physical properties such as size and density cannot be directly measured. De-biasing techniques and proxies are needed to overcome these challenges. In this presentation, we discuss several recent improvements to the derivation of the meteoroid velocity, directionality, and bulk density distributions. We derive our speed distribution from observations made by the Canadian Meteor Orbit Radar. These observations are de-biased using modern descriptions of the ionization efficiency and sharpened to remove the effects of measurement uncertainty, and the result is a meteoroid speed distribution that is skewed slower than in previous analyses. We also adopt a higher fidelity density distribution than that used by many older models. In our distribution, meteoroids with T(sub J) less than 2 are assigned to a low-density population, while those with T(sub J) greater than 2 have higher densities. This division and the distributions themselves are derived from the densities reported by Kikwaya et al. (2009, 2011). These changes have implications for the environment. For instance, helion and antihelion meteors have lower speeds and higher densities than apex and toroidal meteors. A slower speed distribution therefore corresponds to a sporadic environment that is more completely dominated by the helion and antihelion sources than in previous models. Finally, assigning these meteors high densities further increases their significance from a spacecraft damage perspective.

Moorhead, A. V.↗

NASA NTRS2017

The Velocity and Density Distribution of Earth-Intersecting Meteoroids: Implications for Environment Models

No abstract available

Moorhead, A. V.↗

NASA NTRS2017

The Velocity and Density Distribution of Earth-Intersecting Meteoroids: Implications for Environment Models

Meteoroids are known to damage spacecraft: they can crater or puncture components, disturb a spacecraft's attitude, and potentially create secondary electrical effects. Because the damage done depends on the speed, size, density, and direction of the impactor, accurate environment models are critical for mitigating meteoroid-related risks. Yet because meteoroid properties are derived from indirect observations such as meteors and impact craters, many characteristics of the meteoroid environment are uncertain. In this work, we present recent improvements to the meteoroid speed and density distributions. Our speed distribution is derived from observations made by the Canadian Meteor Orbit Radar. These observations are de-biased using modern descriptions of the ionization efficiency. Our approach yields a slower meteoroid population than previous analyses (see Fig. 1 for an example) and we compute the uncertainties associated with our derived distribution. We adopt a higher fidelity density distribution than that used by many older models. In our distribution, meteoroids with TJ less than 2 are assigned to a low-density population, while those with TJ greater than 2 have higher densities (see Fig. 2). This division and the distributions themselves are derived from the densities reported by Kikwaya et al. These changes have implications for the environment: for instance, the helion/antihelion sporadic sources have lower speeds than the apex and toroidal sources and originate from high-T(sub J) parent bodies. Our on-average slower and denser distributions thus imply that the helion and antihelion sources dominate the meteoroid environment even more completely than previously thought. Finally, for a given near-Earth meteoroid cratering rate, a slower meteoroid population produces a comparatively higher rate of satellite attitude disturbances.

Moorhead, A. V.↗

NASA NTRS2016

Optical and Radar Measurements of the Meteor Speed Distribution

The observed meteor speed distribution provides information on the underlying orbital distribution of Earth-intersecting meteoroids. It also affects spacecraft risk assessments; faster meteors do greater damage to spacecraft surfaces. Although radar meteor networks have measured the meteor speed distribution numerous times, the shape of the de-biased speed distribution varies widely from study to study. Optical characterizations of the meteoroid speed distribution are fewer in number, and in some cases the original data is no longer available. Finally, the level of uncertainty in these speed distributions is rarely addressed. In this work, we present the optical meteor speed distribution extracted from the NASA and SOMN allsky networks [1, 2] and from the Canadian Automated Meteor Observatory (CAMO) [3]. We also revisit the radar meteor speed distribution observed by the Canadian Meteor Orbit Radar (CMOR) [4]. Together, these data span the range of meteoroid sizes that can pose a threat to spacecraft. In all cases, we present our bias corrections and incorporate the uncertainty in these corrections into uncertainties in our de-biased speed distribution. Finally, we compare the optical and radar meteor speed distributions and discuss the implications for meteoroid environment models.

Moorhead, A. V.↗

NASA NTRS2013

Automated Meteor Fluxes with a Wide-Field Meteor Camera Network

Within NASA, the Meteoroid Environment Office (MEO) is charged to monitor the meteoroid environment in near ]earth space for the protection of satellites and spacecraft. The MEO has recently established a two ]station system to calculate automated meteor fluxes in the millimeter ]size ]range. The cameras each consist of a 17 mm focal length Schneider lens on a Watec 902H2 Ultimate CCD video camera, producing a 21.7 x 16.3 degree field of view. This configuration has a red ]sensitive limiting meteor magnitude of about +5. The stations are located in the South Eastern USA, 31.8 kilometers apart, and are aimed at a location 90 km above a point 50 km equidistant from each station, which optimizes the common volume. Both single station and double station fluxes are found, each having benefits; more meteors will be detected in a single camera than will be seen in both cameras, producing a better determined flux, but double station detections allow for non ]ambiguous shower associations and permit speed/orbit determinations. Video from the cameras are fed into Linux computers running the ASGARD (All Sky and Guided Automatic Real ]time Detection) software, created by Rob Weryk of the University of Western Ontario Meteor Physics Group. ASGARD performs the meteor detection/photometry, and invokes the MILIG and MORB codes to determine the trajectory, speed, and orbit of the meteor. A subroutine in ASGARD allows for the approximate shower identification in single station meteors. The ASGARD output is used in routines to calculate the flux in units of #/sq km/hour. The flux algorithm employed here differs from others currently in use in that it does not assume a single height for all meteors observed in the common camera volume. In the MEO system, the volume is broken up into a set of height intervals, with the collecting areas determined by the radiant of active shower or sporadic source. The flux per height interval is summed to obtain the total meteor flux. As ASGARD also computes the meteor mass from the photometry, a mass flux can be also calculated. Weather conditions in the southeastern United States are seldom ideal, which introduces the difficulty of a variable sky background. First a weather algorithm indicates if sky conditions are clear enough to calculate fluxes, at which point a limiting magnitude algorithm is employed. The limiting magnitude algorithm performs a fit of stellar magnitudes vs camera intensities. The stellar limiting magnitude is derived from this and easily converted to a limiting meteor magnitude for the active shower or sporadic source.

Blaauw, R. C.↗

NASA NTRS2011

Video Meteor Fluxes

The flux of meteoroids, or number of meteoroids per unit area per unit time, is critical for calibrating models of meteoroid stream formation and for estimating the hazard to spacecraft from shower and sporadic meteors. Although observations of meteors in the millimetre to centimetre size range are common, flux measurements (particularly for sporadic meteors, which make up the majority of meteoroid flux) are less so. It is necessary to know the collecting area and collection time for a given set of observations, and to correct for observing biases and the sensitivity of the system. Previous measurements of sporadic fluxes are summarized in Figure 1; the values are given as a total number of meteoroids striking the earth in one year to a given limiting mass. The Gr n et al. (1985) flux model is included in the figure for reference. Fluxes for sporadic meteoroids impacting the Earth have been calculated for objects in the centimeter size range using Super-Schmidt observations (Hawkins & Upton, 1958); this study used about 300 meteors, and used only the physical area of overlap of the cameras at 90 km to calculate the flux, corrected for angular speed of meteors, since a large angular speed reduces the maximum brightness of the meteor on the film, and radiant elevation, which takes into account the geometric reduction in flux when the meteors are not perpendicular to the horizontal. They bring up corrections for both partial trails (which tends to increase the collecting area) and incomplete overlap at heights other than 90 km (which tends to decrease it) as effects that will affect the flux, but estimated that the two effects cancelled one another. Halliday et al. (1984) calculated the flux of meteorite-dropping fireballs with fragment masses greater than 50 g, over the physical area of sky accessible to the MORP fireball cameras, counting only observations in clear weather. In the micron size range, LDEF measurements of small craters on spacecraft have been used to estimate the flux (Love & Brownlee, 1993); here the physical area of the detector is well known, but the masses depend strongly on the unknown velocity distribution. In the same size range, Thomas & Netherway (1989) used the narrow-beam radar at Jindalee to calculate the flux of sporadics. In between these very large and very small sizes, a number of video and photographic observations were reduced by Ceplecha (2001). These fluxes were calculated (details are given in Ceplecha, 1988) taking the Halliday et al. (1984) MORP fireball fluxes, slightly corrected in mass, as a calibration, and adjusting the flux of small cameras to overlap with the number/mass relation from that work.

Campbell-Brown, M. D.↗

NASA NTRS2011

An Investigation of How a Meteor Light Curve is Modified by Meteor Shape and Atmospheric Density Perturbations

This is a preliminary investigation of how perturbations to meteoroid shape or atmospheric density affect a meteor light curve. A simple equation of motion and ablation are simultaneously solved numerically to give emitted light intensity as a function of height. It is found that changing the meteoroid shape, by changing the relationship between the cross-section area and the mass, changes the curvature and symmetry of the light curve, while making a periodic oscillation in atmospheric density gives a small periodic oscillation in the light curve.

Stokan, E.↗