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Chris L Ostrom

Publications and source records attributed to Chris L Ostrom.

5 records
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Pyrolysis Rate and Yield Strength Reduction in Carbon Fiber and Glass Fiber Composites under Reentry Heating Conditions

The behavior of composite materials, specifically carbon fiber-reinforced polymer (CFRP) and glass fiber-reinforced polymer (GFRP), under re-entry conditions poses a problem for orbital debris re-entry risk modeling. Since these materials pyrolyze rather than melt and their different components demise at different rates, modeling their destruction to determine ground impact risk is complex. Modern spacecraft are using these materials in ever-greater quantities owing to their superior strength-to -weight characteristics, and this has required that the orbital debris community improve its understanding of how these materials demise on re-entry.

Benton R Greene↗
NASA NTRSDate not supplied

Orbital Debris Mitigation and CubeSats

The 2019 Update to the United States Government Orbital Debris Mitigation Standard Practices (ODMSP) included CubeSats for the first time as a special class of space operations. This is the first governmental-level policy document that calls for CubeSats to follow quantitative recommendations for orbital debris mitigation. While CubeSats were never exempt from such recommendations, mission designers often under assess CubeSats due to their small size and historically low level of stored energy. Qualitative assessments of debris potential are less applicable as miniaturized energy systems (propulsive and electrical) become more available and as the “CubeSat” label is applied to larger payloads. Of particular interest to the long-term evolution of the debris environment is the likelihood of accidental explosion or collision; we must also consider the risk to the human population from reentering spacecraft. We discuss the on-orbit history of CubeSats and present guidance to assist in designing for future compliance with the new standard practices.

Chris L Ostrom↗
NASA NTRSDate not supplied

A New Statistical Estimate of the Radar Coverage of the Low Earth Orbit Debris Environment

For over three decades, the NASA Orbital Debris Program Office (ODPO) has used the Goldstone Orbital Debris Radar, Haystack Ultrawideband Satellite Imaging Radar (HUSIR), and Haystack Auxiliary (HAX) radar assets to collect data on the low Earth orbit (LEO) debris environment. Each radar, with its unique beamwidth, altitude and inclination coverage, and limiting size threshold, operates in a beam park mode to statistically sample the orbital debris population in LEO. Provided that these assets are shared with other users, the orbital debris data collection is not continuous; rather, intermittent data collects are acquired and sent to the NASA ODPO. To understand the sampling process conducted by each radar over time and any related observational biases, a Statistical Confirmation of Radar Uniformity or Bias (SCRUB) code has been implemented to model the coverage of these assets for informing future operations, as well as usage of the data collected from these ground-based sensors. For this analysis, Right Ascension of the Ascending Node (RAAN) is used as a metric to measure statistical coverage. A complete survey of the LEO environment is understood to be measurements that sufficiently sample all values of RAAN for each altitude-inclination pair visible from the radar asset. Regions of incompleteness or statistical bias can help inform future observation campaigns. The SCRUB tool evaluates the coverage of the LEO environment, not by examining individual objects that may pass through a sensor’s field of view (FOV), but by determining which orbit planes pass through the FOV. Once a pointing geometry for a radar site, observation time, and range extent are configured by the user, SCRUB computes the inclinations and altitudes that are visible by the sensor. For each inclination-altitude pair, there is a distinct pair of possible RAAN values, corresponding to the ascending and descending orbit passing through that point in the sensor cone. Repeating this process for all points in the beam, and for multiple time periods during an observation window, creates a matrix of all inclination-altitude-RAAN combinations that are visible during a sensor run. This process can then be repeated for all observations within a year (for an annual survey), propagating all the RAAN values to a common epoch, typically the start of a calendar year, and combining the observations to assemble a full estimate of the RAAN coverage of the LEO environment. This RAAN coverage can then be analyzed for uniformity of sampling, within a certain inclination-altitude pair, or between larger regions of the space environment. This paper provides a general overview of the radar assets utilized by ODPO, typical analysis data products assuming circular orbits, and a discussion of the algorithms that feed between modeling and measurement operations. Following the description of the algorithm, estimates of coverage using HUSIR radar data collected from multiple years are developed and compared.

Chris L Ostrom↗