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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Characterization of Plastic Degrading Bacteria from Environmental Samples by Genetic and Biochemical Analysis
Plastic is the major waste-product during NASA space missions, recycling this waste-stream to produce other beneficial materials would decrease upmass. Bacterial called plastisomes have been demonstrated to metabolize non-biodegradable plastics such as polyethylene and polystyrene. Characterization and engineering of these bacteria, and their eventual incorporation as life support systems would enable space flight beyond lower earth orbit. We will utilize molecular techniques to identify and isolate the most productive plastisome. Environmental samples obtained from locations known to be rich in plastic will be cultured in a laboratory defined-media supplemented with plastic as the sole carbon source. Cultures will be monitored for growth over time. Ribosomal DNA will be amplified from cultures that exhibit growth using PCR. These amplified fragments will be sequenced to determine the identity of the consortia in the cultures. We will then perform bioinformatics analysis on the data to identify the plastisomes and generate phylogenetic trees. Morphological and physiological profile of the plastisomes will also be conducted by microscopy and biochemical tests. Our results would reveal a bacterial strain that can break down plastics efficiently. The implication for this project would not only benefit space exploration but also make a major impact towards sustainability development on Earth.
Trends in optocoupler radiation degradation
This paper evaluates new optocoupler technologies and compares their radiation response with results for older devices.
Total dose degradation of MEMS optical mirrors
This paper discusses the effect of ionizing radiation on two types of deformable MEMS mirrors.
Relative degradation of near infrared avalanche photodiodes from proton irradiation
InGaAs and Ge avalanche photodiodes are compared for the effects of 63-MeV protons on dark current. Differences in displacement damage factors are discussed as they relate to structural differences between devices.
Estimation of coarse dead wood stocks in intact and degraded forests in the Brazilian Amazon using airborne lidar
Coarse dead wood is an important component of forest carbon stocks, but it is rarely measured in Amazon forests and is typically excluded from regional forest carbon budgets. Our study is based on line intercept sampling for fallen coarse dead wood conducted along 103 transects with a total length of 48 km matched with forest inventory plots where standing coarse dead wood was measured in the footprints of larger areas of airborne lidar acquisitions. We developed models to relate lidar metrics and Landsat time series variables to coarse dead wood stocks for intact, logged, burned, or logged and burned forests. Canopy characteristics such as gap area produced significant individual relations for logged forests. For total fallen plus standing coarse dead wood (hereafter defined as total coarse dead wood), the relative root mean square error for models with only lidar metrics ranged from 33 % in logged forest to up to 36 % in burned forests. The addition of historical information improved model performance slightly for intact forests (31 % against 35 % relative root mean square error), not justifying the use of a number of disturbance events from historical satellite images (Landsat) with airborne lidar data. Lidar-derived estimates of total coarse dead wood compared favorably with independent ground-based sampling for areas up to several hundred hectares. The relations found between total coarse dead wood and variables quantifying forest structure derived from airborne lidar highlight the opportunity to quantify this important but rarely measured component of forest carbon over large areas in tropical forests.
Aritifact detection and localization in perceptually-degraded subterranean environments
UNKNOWN
Thermochemical Degradation of HfSiO4 by Molten CMAS
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Photochemical and Microbial Degradation of Chromophoric Dissolved Organic Matter Exported from Tidal Marshes
Wetlands export chromophoric dissolved organic matter (CDOM) to estuaries, where CDOM is removed and transformed through biotic and abiotic process, subsequently impacting nutrient cycling, light availability, ecosystem metabolism, and phytoplankton activity. We examined the bioavailability and photoreactivity of CDOM exported from four Chesapeake Bay tidal marshes across three seasons and along an estuarine salinity gradient using three incubation treatments: 14-day microbial (MD), 7-day combined photochemical/microbial (PB+MD), and 7-day microbial incubation after photobleaching (MD after PB). CDOM absorption at 300 nm (aCDOM300) and dissolved organic carbon (DOC) concentrations showed strong seasonality, with minima in winter, but CDOM quality (absorption spectral slopes, fluorescence component ratios) was less variable seasonally. PB+MD over 7 days decreased aCDOM300 (–56.0%), humic-like fluorescence (–67.6%), and DOC (–17.8%), but increased the spectral slope ratio SR (=S275-295/S300-350) (+94.8%), suggesting a decrease in CDOM molecular weight. Photochemistry dominated the PB+MD treatment. Photoreactivity was greater during the winter and in marsh/watershed versus down-estuary sites, likely due to less previous light exposure. Prior photobleaching increased the bioavailability of marsh-exported CDOM, resulting in a greater loss of aCDOM300 and DOC, and a greater increase in humic-like fluorescence (–6.0%, –5.9%, and +18.4% change, respectively, over 7-day MD after PB incubations, versus –2.8%, –5.5%, and +2.6% change, respectively, over 14-day MD incubations). CDOM exported from a marsh downstream of a major wastewater treatment plant showed the greatest photoreactivity and bioavailability. This highlights the significance of human activity on estuarine CDOM quality and biogeochemical cycles.
Supervised Autonomy for Communication-Degraded Subterranean Exploration by a Robot Team
The importance of autonomy in robotics is magnified when the robots need to be deployed and operated in areas that are too dangerous or not accessible for humans, ranging from disaster areas (to assist in emergency situations) to Mars exploration (to uncover the mystery of our neighboring planet). The DARPA Subterranean (SubT) Challenge presents a great opportunity and a formidable robotics challenge to foster such technological advancement for operations in extreme and underground environments. Robot teams are expected to rapidly map, navigate, and search underground environments including natural cave networks, tunnel systems, and urban underground infrastructure. Subterranean environments pose significant challenges for manned and unmanned operations due to limited situational awareness. In the first phase of the DARPA Subterranean Challenge (held in August 2019; targeting underground tunnels and mines), Team CoSTAR, led by NASA JPL, placed second among 11 teams across the world, accurately mapping several kilometers of two mine systems and localizing 17 target objects in the course of four one-hour missions. While the main goal of Team CoSTAR at the end of this threeyear challenge (August 2021) is a fully autonomous robotic solution, this paper describes Team CoSTAR’s results in the first phase of the challenge (August 2019), focusing on supervised autonomy of a multi-robot team under severe communication constraints. This paper also presents the design and initial results obtained from field test campaigns conducted in various tunnel-like environments, leading to the competition.
How Does Forest Structure and Degradation Control Temperature and Water Fluxes in the Amazon?
UNKNOWN
Supervised Autonomy for Communication-Degraded Subterranean Exploration by a Robot Team
UNKNOWN
Object and Gas Source Detection with Robotic Platforms in Perceptually-Degraded Environments
In exploration-oriented robotic missions for disaster relief in unknown subterranean environments, it is of prime importance for a human supervisor to rapidly gain situational awareness of salient objects within the environment. In this paper we present an automated object detection pipeline that is adaptable to heterogeneous robots with arbitrary sensor configurations. It has been deployed in time-critical scenarios with multiple collaborative robots in a variety of demanding underground environments. For visually observable objects, detections are made in both the visible and thermal spectra using a state-of-the-art machine learning framework for object detection and classification. Our pipeline can be rapidly adapted to a specific task by using a small, structured dataset to fine-tune a pre-trained convolutional neural network (CNN). Relative localization is separated from the CNN for speed of operation. A robust architecture for localization is used with outlier rejection and a hierarchy of fall-back distance measurement methods. Point-source objects such as gas and WiFi hotspots can also be detected, by tracking signal strength over time and presenting an intuitive visualization on a map. Observations of each object types are presented to the operator in ranked confidence order for final evaluation.
Object and Gas Source Detection with Robotic Platforms in Perceptually Degraded Environments
No abstract provided
Spacecraft Materials Degradation Under Space-Simulated Low Earth Orbit (LEO) Environment
External spacecraft materials play an important role in satellite protection from the harsh space environment. Research has shown that the physical, chemical, and optical properties of matter change continuously as a result of exposure to solar radiation and aggressive chemical species produced in Earth’s upper atmosphere. Thorough knowledge of the material properties evolution throughout a planned mission lifetime helps to improve the reliability of spacecraft. Moreover, the establishment of correlation factors between true space exposure and accelerated space weather experiments at ground facilities enables accurate prediction of on-orbit material performance based on laboratory-based testing. The presented work aims to evaluate the radiation effects of low Earth orbit (LEO) environment, namely, exposure to the high-energy electrons, atomic oxygen (AO), and vacuum ultraviolet (VUV), of several modern spacecraft materials. The studied materials represent the “flight duplicates” of samples that are launched as a part of the 16th Materials International Space Station Experiment Flight Facility (MISSE-FF) mission in 2022.
Analysis of Handling Qualities and Power Consumption for Urban Air Mobility (UAM) eVTOL Quadrotors with Degraded Heave Disturbance Rejection and Control Response
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Spacecraft Materials Degradation Under Space-Simulated Low Earth Orbit (LEO) Environment
External spacecraft materials play an important role in satellite protection from the harsh space environment. Research has shown that the physical, chemical, and optical properties of matter change continuously as a result of exposure to solar radiation and aggressive chemical species produced in Earth’s upper atmosphere. Thorough knowledge of the material properties evolution throughout a planned mission lifetime helps to improve the reliability of spacecraft. Moreover, the establishment of correlation factors between true space exposure and accelerated space weather experiments at ground facilities enables accurate prediction of on-orbit material performance based on laboratory-based testing. The presented work aims to evaluate the radiation effects of low Earth orbit (LEO) environment, namely, exposure to the high-energy electrons, atomic oxygen (AO), and vacuum ultraviolet (VUV), of several modern spacecraft materials. The studied materials represent the “flight duplicates” of samples that are launched as a part of the 16th Materials International Space Station Experiment Flight Facility (MISSE-FF) mission in 2022.