Solar system

Abstract:

Astrobotic's Peregrine Mission-1 spacecraft experienced a propulsion system anomaly that prevented the lander from reaching the Moon. During the mission, several instruments operated successfully in cis-lunar space. Among them, the Peregrine Ion Trap Mass Spectrometer (PITMS) measured both the presence of outgassing water and nitrogen oxides traceable to the MON-25 oxidizer. We performed Direct Simulation Monte Carlo (DSMC) studies of the oxidizer leak on Peregrine to characterize the gas diffusion from the leak to the instrument, mediated by inter-species collisions and gas–surface interaction. We conclude that the latter process was prevalent and that diffusion paths through Peregrine are necessary to explain the PITMS detections. Our DSMC study and estimation of Peregrine's outgassing rate suggest that, at the early stage of the mission, the spacecraft released water at a rate comparable to the Space Shuttle and at a much larger rate than typical spacecraft during science operations. This provides useful information for planning future operations of science instruments on commercial missions.

Abstract:

Venus is home to thousands of volcanoes, with a wide range of volumes and sizes. Its surface is relatively young, with a temperature of approximately 735 K and an atmosphere of 92 bar. Past and possible ongoing volcanic outgassing is expected to provide a source to the sustenance of this massive atmosphere, dominated by CO2 and SO2. The lower atmosphere can be investigated in the near-infrared transparency windows on the nightside, such as the 2.3μm thermal emission window, which provides a chance of detection of species with volcanic origin, such as water vapor. The Planetary Spectrum Generator was used to simulate the nightside 2.3μm thermal emission window of Venus. We simulated the effect of a volcanic gas plume rising to a ceiling altitude, for species such as H2O, CO, OCS, HF and SO2. The sensitivity of the radiance spectrum at different wavelengths was explored as an attempt to qualitatively access detection for future measurements of both ground-based and space-instrumentation. We conclude from our qualitative analysis that for the H2O, CO and OCS plumes simulated there is potential to achieve a detection in the future, given a minimum required signal-to-noise ratio of 50. For SO2 and HF plumes, a higher signal-to-noise ratio would be needed.

Abstract:

The return home of the OSIRIS-REx spacecraft in September 2023 marked only the fifth time that anartificial object entered the Earth’s atmosphere at interplanetary velocities. Although rare, such events serve as valuable analogs for natural meteoroid re-entries; enabling study of hypersonic dynamics, shock wavegeneration, andacoustic-to-seismic coupling. Here, wereportonthesignaturesrecordedbyadense(100mscale)11-station array located almost directly underneath the capsule’s point of peak atmospheric heat ing in northern Nevada. Seismic data are presented, which allow inferences to be made about the shape of the shock wave’s footprint on the surface, the capsule’s trajectory, and its flight parameters.

Abstract:

This exploratory study investigates whether seismic signals can be used to infer fragmentation during a fireball event. Re-entry objects, particularly sample return capsules (SRCs) such as the one from the Hayabusa2 mission, behave similarly to slow meteors during atmospheric entry and provide valuable insights into natural fireball events. In this study, we initially analyze seismic signals from the Hayabusa2 SRC re-entry, which took place on 5 December 2020, over South Australia. The SRC’s signature was captured by a dense network of seismic stations (Eakin, 2018; O’Donnell et al., 2020), offering a unique opportunity to investigate the signals’ characteristics and verify their connection to the re-entry event. The ballistic trajectory was confirmed as the source shock mechanism for this event. We isolate this signal and use it as a reference for a ballistic shock signature and compare it to three other fireball case studies, including a subor-bital re-entry and two natural meteoroids. Although factors such as local geology and atmospheric conditions were not considered in this preliminary study, our results show promise with high correlations for events with purely ballistic trajectories and lower correlations for those involving fragmentation or airbursts. This implies that seismic data may be able to disambiguate whether any particular fireball event underwent significant fragmentation or airburst, key phenomena for assessing body strengths.

Abstract:

We present a new method, based on a joint application of a principal component analysis (PCA) and Gaussian mixture models (GMM), to automatically find similar groups of spectra in a collection. We applied the method (condensed in the public code chopper.py ) to archival Jupiter spectral data in the 2–5 µm range collected by NASA Juno/JIRAM in its first perijove passage (August 2016) and to mosaics of the great red spot (GRS) acquired by JWST/NIRSpec (July 2022). Using JIRAM data analyzed in previous work, we show that using a PCA+GMM clustering can increase the efficiency of the retrieval stage without any loss of accuracy in terms of the retrieved parameters. We show that a PCA+GMM approach is able to automatically identify spectra of known regions of interest (e.g., belts, zones, GRS) belonging to different clusters. The application of the method to the NIRSpec data leads to detection of substructures inside the GRS, which appears to be composed of an outer halo characterized by low reflectivity and an inner brighter main oval. By applying these techniques to JIRAM data, we were able to identify the same substructure. We remark that these new structures have not been seen before at visible wavelengths. In both cases, the spectra belonging to the inner oval have solar and thermal signals comparable to those belonging to the halo, but they present broadened 2.73 µm solar-reflected peaks. Performing forward simulations with the NEMESIS radiative transfer suite, we propose that the broadening may be caused by differences in the vertical extension of the main cloud layer. This finding is consistent with recent 3D fluid dynamics simulations.