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This video highlights the Virtual Reality Laboratory. It shows off the different systems the lab supports for crew training including Charlotte Mass Handling, Robotics and hardware checkout and SAFER. It focuses on the SAFER (Simplified Aid for EVA Rescue) system and shows briefly how to perform a SAFER rescue in Virtual Reality.
The Neptune Odyssey mission concept is a Flagship-class orbiter and atmospheric probe to the Neptune–Triton system. This bold mission of exploration would orbit an ice-giant planet to study the planet, its rings, small satellites, space environment, and the planet-sized moon Triton. Triton is a captured dwarf planet from the Kuiper Belt, twin of Pluto, and likely ocean world. Odyssey addresses Neptune system-level science, with equal priorities placed on Neptune, its rings, moons, space environment, and Triton. Between Uranus and Neptune, the latter is unique in providing simultaneous access to both an ice giant and a Kuiper Belt dwarf planet. The spacecraft—in a class equivalent to the NASA/ESA/ASI Cassini spacecraft—would launch by 2031 on a Space Launch System or equivalent launch vehicle and utilize a Jupiter gravity assist for a 12 yr cruise to Neptune and a 4 yr prime orbital mission; alternatively a launch after 2031 would have a 16 yr direct-to-Neptune cruise phase. Our solution provides annual launch opportunities and allows for an easy upgrade to the shorter (12 yr) cruise. Odyssey would orbit Neptune retrograde (prograde with respect to Triton), using the moonʼs gravity to shape the orbital tour and allow coverage of Triton, Neptune, and the space environment. The atmospheric entry probe would descend in ∼37 minutes to the 10 bar pressure level in Neptune’s atmosphere just before Odysseyʼs orbit-insertion engine burn. Odysseyʼs mission would end by conducting a Cassini-like “Grand Finale,” passing inside the rings and ultimately taking a final great plunge into Neptuneʼs atmosphere.
Atmospheric methane (CH4) concentrations have shown a puzzling resumption of growth since 2007 following a period of stabilization from 2000 to 2006. Multiple hypotheses have been proposed to explain the temporal variations in CH4 growth, which attributes the rise of atmospheric CH4 either to increases in emissions from fossil fuel activities, agriculture, and natural wetlands or to a decrease in the atmospheric chemical sink. Here, we use a comprehensive ensemble of CH4 source estimates and isotopic δ13C-CH4 source signature data to show that the resumption of CH4 growth is most likely due to increased anthropogenic emissions. Our emission scenarios that have the fewest biases with respect to isotopic composition suggest that the agriculture, landfill, and waste sectors were responsible for 53 ± 13% of the renewed growth over the period 2007–2017 compared to 2000–2006; industrial fossil fuel sources explained an additional 34 ± 24%, and wetland sources contributed the least at 13 ± 9%. The hypothesis that a large increase in emissions from natural wetlands drove the decrease in atmospheric δ13C-CH4 values cannot be reconciled with current process-based wetland CH4 models. This finding suggests the need for increased wetland measurements to better constrain the contemporary and future role of wetlands in the rise of atmospheric methane and climate feedbacks. Our findings highlight the predominant role of anthropogenic activities in driving the growth of atmospheric CH4 concentrations.
An asymmetric, bifurcated normal shock train in a Mach 2 constant area, rectangular duct is investigated in the University of Michigan Direct Connect Isolator facility. High-speed schlieren imaging, wall static pressure measurements, surface oil flow visualization, and particle image velocimetry of a shock train are synthesized into a three-dimensional representation of shock train structure. This visualization is then used to inform the underlying flow physics of the distributed fluid dynamical processes along the structure. The detailed, three-dimensional morphology of the flow profile entering the shock train is shown to have a significant impact on the separated flow morphology of the shock train. This results in skewed supersonic core flow with alternating separation bubbles in the surrounding boundary layers. Finally, the efficacy of the prevailing pseudo-shock models in the literature is analyzed with the support of the available flow measurements. None are found to simultaneously model both the pressure and streamwise Mach number profile of the UMDCI pseudo-shock.
An asymmetric, normal bifurcated shock train in a Mach 2 constant area, rectangular duct is investigated in the University of Michigan Direct Connect Isolator facility. High-speed schlieren imaging, wall static pressure measurements, surface oil flow visualization, and particle image velocimetry of the shock train are synthesized into a three-dimensional representation. This visualization is then used to inform the underlying flow physics of the distributed fluid dynamical processes along the shock train. The detailed, three-dimensional morphology of the flow profile entering the shock train is shown to have a significant impact on the separated flow morphology of the shock train. This results in a skewed supersonic core flow with alternating separation bubbles in the surrounding boundary layers. Finally, the efficacy of the prevailing pseudo-shock models in the literature is analyzed with the support of the available flow measurements. None are found to model both the pressure and streamwise Mach number profile of the UMDCI pseudo-shock. Note: This presentation is accompanied by the video presentation that can be downloaded for viewing and is formatted as an mp4 with a runtime of 10 min 15 secs.
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The Origins Space Telescope ( Origins ) is one of four science and technology definition studies selected by National Aeronautics and Space Administration (NASA) in preparation of the 2020 Astronomy and Astrophysics Decadal survey in the US. Origins will trace the history of our origins from the time dust and heavy elements permanently altered the cosmic landscape to present-day life. It is designed to answer three major science questions: How do galaxies form stars, make metals, and grow their central supermassive black holes from reionization? How do the conditions for habitability develop during the process of planet formation? Do planets orbiting M-dwarf stars support life? Origins operates at mid- to far-infrared wavelengths from ~ 2.8 to 588 μm, is more than 1000 times more sensitive than prior far-IR missions due to its cold (~ 4.5 K) aperture and state-of-the-art instruments.
The Mars 2020/“Perseverance” rover carries a suite of space suit materials as part of the SHERLOC* calibration target [1]. The materials are periodically analyzed by SHERLOC as part of a regular calibration routine and are generating a rich data set regarding their degradation in the martian surface environment. The Maximization of Calibration Fabrics (Max-CF) project will effectively turn SHERLOC data into a measure of space suit material service lifetimes by exposing a second set of materials in a Mars chamber, replicating SHERLOC measurements using the analogous ACRONM** instrument at JSC, and then performing materials testing to include tensile testing. These data can be used to inform space suit design and/or materials development, improving crew safety for future Mars missions. This will partially address NASA’s Strategic Knowledge Gap 8 (Mars Surface Technology) which identifies a need to develop technologies to “sustain humans on the surface of Mars [and] enable human mobility and exploration” [2]. This abstract describes the overall Max-CF project and progress on the laboratory-based study to date.
The CALIPSO V2.00 Lidar Level 2 Polar Stratospheric Cloud data product is an updated version of an already order-able dat set. The changes were signed off by the CALIPSO Configuration Control Board, versioned, and the code uploaded to a code repository. There is no ITAR/SBU data or code associated with this product. Data will be publicly order-able at the NASA LaRC Atmospheric Sciences Data Center (ASDC). All documentation and web sites will be made public once the data product is released. The data is in HDF4 format and will be generated for majority of the mission (June 2006 - March 2021). The attached Data Products Catalog (v4.94) describes this new product in section 2.14, pp 115- 119.
Presented is a new quality assurance (QA) framework for Earth Observation missions that has been developed as a joint initiative between ESA and NASA. It aims ensure the rigorous assessment of all aspects of relevant aspects of mission quality, verifying claimed mission performance and, where applicable, reviewing the extent to which the mission follows community best practice in a manner that is “fit for purpose”. The QA framework has potential for more general use in both institutional and commercial Earth Observation – helping mission providers to understand the information their users' needs and empowering users to make informed decisions about which data is fit for their purpose.
Juvenile survival in birds is difficult to estimate but this vital rate can be an important consideration for management decisions. We estimated juvenile survival of cooperatively breeding Florida Scrub-Jays (Aphelocoma coerulescens) in a landscape degraded by fire suppression and fragmentation using data from marked (n = 325) and unmarked juveniles (n = 1,306) with an integrated hierarchical Bayesian model. To assess the combined analyses, we also analyzed these datasets separately, with a Cormack-Jolly-Seber (CJS) model (marked) and young model (unmarked). Our data consisted of monthly censuses of territorial family groups from Florida Scrub-Jay populations in East Central Florida collected over a 22-yr period. Juvenile survival was estimated from July when young Florida Scrub-Jays begin developing independence to March when they become first year individuals and grouped according to the habitat quality class of their natal territory that were based on shrub height (with intermediate shrub heights being optimal and short and tall shrub heights being suboptimal) and the presence of sandy openings (the preferred open having many sandy openings; closed not having enough). Parameter estimates in the combined analysis were intermediate to the separate analyses. Notable differences among the separate analyses were that suboptimal habitat survival was lower in the unmarked analysis, the unmarked analysis showed a linear effect of time not seen in the marked analysis, and there was an effect of male breeder death in the marked but not unmarked analysis. The combined data analysis provided more inference than did either data set analyzed separately including juveniles in optimal-closed territories unexpectedly had higher survival than those in optimal-open, survival increased through time, and male breeder death had a negative effect on survival. This study suggests that optimal-closed habitat may play an important role in juvenile Florida Scrub-Jay survival perhaps by providing better cover from predators and warrants further investigation for management implications.
A fluid-dynamic reconstruction algorithm is presented that generates a least-squares best-fit, two-dimensional density field from a prespecified two-dimensional velocity field. This method recasts the mass-conservation equation as a modified Sylvester equation employing high-order operators derived from modified Bernstein polynomial expansions. To demonstrate its practical utility, this analytic methodology is applied to two canonical cases and a Particle Image Velocimetry dataset obtained from a Mach-2, mechanically back-pressured, isolator experiment. This methodology is envisioned to be used in conjunction with hypersonic-diagnostic techniques to aid in the quantification of isolator flow fields. However, also note that this reconstruction technique is well suited to other applications relevant to fluid dynamics, such as obtaining three-dimensional flow field reconstructions.
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A highly confined shock train is investigated in a direct-connect isolator facility with a Mach 2 inflow and a constant-area low-aspect-ratio rectangular test section. High-speed schlieren imaging, wall static pressure measurements, surface oil-flow visualization, and particle image velocimetry from this isolator are synthesized into a three-dimensional schematic of the shock train structure. Against this, the prevailing pseudoshock models in the literature are assessed to evaluate the validity of their underlying assumptions. None of the prevailing pseudoshock models are found to simultaneously model the pressure and Mach number profiles, indicating a gap in the model formation and underlying assumptions when applied to the experimental isolator of interest. The presence of distortion in the isolator flowfield, such as a wall-bounded vortex, is found to skew the structure of the shock train, altering the strength and distribution of the compressive pressure gradient. It is further observed that the separated flow morphology surrounding the shock train is not monolithic, as is typically assumed, adjusting the balance of compressive forces within the shock cells. These findings lead to the conclusion that existing flux-conserved modeling approaches require modification to be effective in distorted and highly confined cases, including closure models that capture the three-dimensional distorted structure of the approach flow and its evolution along the shock train.
The imprecise nature of three-dimensional (3D) printing limits the technology’s use beyond prototyping. For production of end-use parts, such as those for aerospace applications, improvements are needed to enhance quality and repeatability. Much of the difficulty in obtaining high quality printed parts lies in finding optimum printing parameters. Currently, this requires trial and error performed by an expert. Finding the optimum printing parameters is also obfuscated by the variation in optimum parameters throughout the part due to part geometry and printer effects. To allow for locally optimized printing parameters, one can envision a machine learning algorithm that could take in an object, predict the best printing parameters, and communicate these parameters to a printer. With this scenario in mind, we developed a tool that can predict and implement locally optimized printing parameters in 3D printing. This tool consists of elements designed to detect errors in a printed part, predict the probability of local flaws occurring at each point in the part, and select the optimal local parameters for the highest quality part given hardware limitations. The results of this work were highlighted in Advanced Materials Technologies. In this paper, we will discuss in greater depth the workflow and algorithms involved with this tool that were not detailed in the journal publication.
NASA’s Artemis campaign is making heavy use of simulation to help return humans to the lunar surface by the end of the decade. There are several aspects of the lunar surface and its environment which must be accurately modeled before these simulations can be relied upon to influence decisions being made under these programs. Digital Lunar Exploration Sites, a paper submitted to the 2022 IEEE Aerospace Conference, outlined the process used to generate the lunar surface in a digital environment. This paper will expand upon this topic and delve into the steps being taken by the NASA Exploration Systems Simulations (NExSyS) team at NASA’s Johnson Space Center (JSC) to properly verify and validate these simulations, with a focus on the visual aspects of the environment. Natural lighting validation relies in part on the wealth of data generated during the Apollo program. Many images taken by Apollo astronauts on the lunar surface have been replicated in the simulated environments to gain confidence in the accuracy of terrain and lighting models. However, because the environment the Artemis astronauts will experience at the Lunar South Pole (LSP) is dissimilar from the near-equatorial Apollo sites, other validation techniques must be applied. At the LSP, the sun crests only about three degrees above the horizon and when combined with the lack of a lunar atmosphere, lighting in this region is often very different than what a human would experience on Earth. Solar illumination, earthshine, human eye response, solar blooming, lunar regolith optical properties, and shadows cast by rocks and crater walls will play a significant role in an astronaut’s ability to safely conduct an Extra-Vehicular Activity (EVA) or perform a traverse with a lunar rover. Approaches for validation of these aspects of the rendered LSP environment are considered in this paper. In addition to natural lighting, approaches for the validation of artificial lighting models at the LSP are discussed. The JSC Lighting Lab has been studying the illumination profile of the Exploration Infomatics Subsystem (xINFO) lighting on the Exploration EVA Mobility Unit (xEMU). How these lights interact with the solar illumination and the shadows being cast on the lunar surface is of particular interest, so the validity of models representing these lights in a human-in-the-loop virtual reality environment becomes very important. This paper also touches on some of the simulation performance considerations when a Human in the Loop (HITL) is present, which drives the need for real time rendering of the environment. Natural and artificial lighting will play a crucial role to decisions being made when planning and executing missions at the Lunar South Pole (LSP) and it is vitally important to understand the LSP environment before we return.
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