4 research outputs found
Parachute Compartment Drop Test Vehicle for Testing the Crew Exploration Vehicle's Parachute Assembly System
Though getting astronauts safely into orbit and beyond has long been one of NASA?s chief goals, their safe return has always been equally as important. The Crew Exploration Vehicle?s (CEV) Parachute Assembly System (CPAS) is designed to safely return astronauts to Earth on the next-generation manned spacecraft Orion. As one means for validating this system?s requirements and testing its functionality, a test article known as the Parachute Compartment Drop Test Vehicle (PC-DTV) will carry a fully-loaded yet truncated CPAS Parachute Compartment (PC) in a series of drop tests. Two aerodynamic profiles for the PC-DTV currently exist, though both share the same interior structure, and both have an Orion-representative weight of 20,800 lbf. Two extraction methods have been developed as well. The first (Cradle Monorail System 2 - CMS2) uses a sliding rail technique to release the PC-DTV midair, and the second (Modified DTV Sled; MDS) features a much less constrained separation method though slightly more complex. The decision as to which aerodynamic profile and extraction method to use is still not finalized. Additional CFD and stress analysis must be undertaken in order to determine the more desirable options, though at present the "boat tail" profile and the CMS2 extraction method seem to be the favored options in their respective categories. Fabrication of the PC-DTV and the selected extraction sled is set to begin in early October 2010 with an anticipated first drop test in mid-March 2011
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Ephemeris and hazard assessment for near-Earth asteroid (101955) Bennu based on OSIRIS-REx data
Small bodies such as the near-Earth asteroid Bennu drift in their orbit due to thermal radiation forces (the Yarkovsky effect). Ground-based observations have indicated a nonzero probability of Bennu impacting Earth, depending on how its orbit evolves. Thus, among the goals of the OSIRIS-REx (Origins, Spectral Interpretation, Resource Identification, and Security-Regolith Explorer) mission to Bennu were to precisely measure the Yarkovsky effect and refine the impact hazard assessment for this body. Here we address these objectives. Using OSIRIS-REx spacecraft tracking data, we derive meter-level constraints on the distance between Earth and Bennu from January 2019 to October 2020. While these data greatly improve the knowledge of the trajectory of Bennu, they also require an unprecedented fidelity for the modeling of an asteroid’s trajectory. In particular, special care is needed to take into account the contribution of 343 small-body perturbers and the uncertainty in their masses. Radiation effects such as the Poynting–Robertson drag, so far only considered for interplanetary dust dynamics, now become a consideration for modeling the trajectory of a 500-m asteroid such as Bennu. By employing a thermophysical model based on OSIRIS-REx’s characterization of Bennu, we estimate a semimajor axis drift of−284.6 ± 0.2m/yr (signal-to-noise ratio∼1400) at epoch 2011 January 1 caused by the Yarkovsky effect. The largest source of modeling error is solar wind drag, which may lower the magnitude of the semimajor axis drift from the Yarkovsky effect by up to 0.16 m/yr. The Yarkovsky-related semimajor axis drift varies by roughly±1m/yr as the orbit of Bennu evolves due to planetary perturbations from 1900 to 2135. The Yarkovsky thermophysical model proves to be extremely accurate by predicting a bulk density estimate within 0.1% of that estimated through gravity science analysis. Compared to the information available before the OSIRIS-REx mission, the knowledge of the circumstances of the scattering Earth encounter that will occur in 2135 improves by a factor of 20, thus allowing us to rule out many previously possible impact trajectories. However, there remain some impact trajectories compatible with the data. Prior to the spacecraft encounter, the overall impact probability through 2200 was 3.7 × 10−4 (1 in 2700). As a result of our analysis, the cumulative impact probability through 2300 becomes 5.7 × 10−4 (1 in 1750) and the most significant individual impact solution is for September 2182, with an impact probability of 3.7 × 10−4 (1 in 2700). Both Bennu and (29075) 1950 DA have a Palermo scale value of −1.42 and share the distinction as the currently most hazardous object in the asteroid catalog
Anomaly Detection in Autonomous Deep-Space Navigation via Filter Bank Gating Networks
This study investigates methods for autonomous navigation of a deep-space spacecraft where one-way radiometric and on-board optical information are fused to create a fully informed state estimate. The specific focus is on using filter bank methods (i.e., Multiple Model Estimation [MME] and Mixture of Experts [MoE]) to detect when measurement and/or dynamical mis-modeling occurs. We develop a new χ2-based gating network for a filter bank that may be used to identify poorly performing filters (i.e., those with low weights), which may be used as a signal for mis-modeling in the system. In addition to defining and deriving this new weighting scheme, numerical simulations based on NASA’s InSight mission demonstrate this new algorithm’s performance with and without measurement and dynamical mis-modeling present
Anomaly Detection in Autonomous Deep-Space Navigation via Filter Bank Gating Networks
This study investigates methods for autonomous navigation of a deep-space spacecraft where one-way radiometric and on-board optical information are fused to create a fully informed state estimate. The specific focus is on using filter bank methods (i.e., Multiple Model Estimation [MME] and Mixture of Experts [MoE]) to detect when measurement and/or dynamical mis-modeling occurs. We develop a new χ2-based gating network for a filter bank that may be used to identify poorly performing filters (i.e., those with low weights), which may be used as a signal for mis-modeling in the system. In addition to defining and deriving this new weighting scheme, numerical simulations based on NASA’s InSight mission demonstrate this new algorithm’s performance with and without measurement and dynamical mis-modeling present