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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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NASA NTRS2017

Development of an Integrated Sensorimotor Countermeasure Suite for Spaceflight Operations

Astronauts experience Postflight disturbances in postural and locomotor control due to sensorimotor adaptation to the unique environment of spaceflight. These alterations might have adverse consequences if a rapid egress were required following a Mars landing or on return to Earth after a water landing. Currently, no operational countermeasure is targeted to mitigate Postflight balance and locomotor dysfunction.

Bloomberg, J. J.↗

NASA NTRS2013

Capabilities, Performance, and Status of the SOFIA Science Instrument Suite

The Stratospheric Observatory for Infrared Astronomy (SOFIA) is an airborne observatory, carrying a 2.5 m telescope onboard a heavily modified Boeing 747SP aircraft. SOFIA is optimized for operation at infrared wavelengths, much of which is obscured for ground-based observatories by atmospheric water vapor. The SOFIA science instrument complement consists of seven instruments: FORCAST (Faint Object InfraRed CAmera for the SOFIA Telescope), GREAT (German Receiver for Astronomy at Terahertz Frequencies), HIPO (High-speed Imaging Photometer for Occultations), FLITECAM (First Light Infrared Test Experiment CAMera), FIFI-LS (Far-Infrared Field-Imaging Line Spectrometer), EXES (Echelon-Cross-Echelle Spectrograph), and HAWC (High-resolution Airborne Wideband Camera). FORCAST is a 540 m imager with grism spectroscopy, developed at Cornell University. GREAT is a heterodyne spectrometer providing high-resolution spectroscopy in several bands from 60240 m, developed at the Max Planck Institute for Radio Astronomy. HIPO is a 0.31.1 m imager, developed at Lowell Observatory. FLITECAM is a 15 m wide-field imager with grism spectroscopy, developed at UCLA. FIFI-LS is a 42210 m integral field imaging grating spectrometer, developed at the University of Stuttgart. EXES is a 528 m high-resolution spectrograph, developed at UC Davis and NASA ARC. HAWC is a 50240 m imager, developed at the University of Chicago, and undergoing an upgrade at JPL to add polarimetry capability and substantially larger GSFC detectors. We describe the capabilities, performance, and status of each instrument, highlighting science results obtained using FORCAST, GREAT, and HIPO during SOFIA Early Science observations conducted in 2011.

SOFIA↗

NASA NTRS2019

Soil Moisture Data Assimilation to Estimate Irrigation Water Use

Knowledge of irrigation is essential to support food security, manage depleting water resources, and comprehensively understand the global water and energy cycles. Despite the importance of understanding irrigation, little consistent information exists on the amount of water that is applied for irrigation. In this study, we develop and evaluate a new method to predict daily to seasonal irrigation magnitude using a particle batch smoother data assimilation approach, where land surface model soil moisture is applied in different configurations to understand how characteristics of remotely sensed soil moisture may impact the performance of the method. The study employs a suite of synthetic data assimilation experiments, allowing for systematic diagnosis of known error sources. Assimilation of daily synthetic soil moisture observations with zero noise produces irrigation estimates with a seasonal bias of 0.66% and a correlation of 0.95 relative to a known truth irrigation. When synthetic observations were subjected to an irregular overpass interval and random noise similar to the Soil Moisture Active Passive satellite (0.04 cm(exp 3) cm(exp -3)), irrigation estimates produced a median seasonal bias of <1% and a correlation of 0.69. When systematic biases commensurate with those between NLDAS‐2 land surface models and Soil Moisture Active Passive are imposed, irrigation estimates show larger biases. In this application, the particle batch smoother outperformed the particle filter. The presented framework has the potential to provide new information into irrigation magnitude over spatially continuous domains, yet its broad applicability is contingent upon identifying new method(s) of determining irrigation schedule and correcting biases between observed and simulated soil moisture, as these errors markedly degraded performance.

R Abolafia-Rosenzweig↗

NASA NTRSDate not supplied

Blue-enriched Light Improves Alertness and Mood Following Abrupt Awakening from Slow Wave Sleep

INTRODUCTION: All crew on the International Space Station (ISS) have a sleep opportunity at the same time. Emergencies arising during this time require all crew members to be abruptly awoken from sleep and to be alert, ready to work as a team, and to perform safety-critical tasks soon after waking. However, crew may experience sleep inertia after waking, which is associated with reduced alertness, poor mood, and impaired performance, especially if woken from deep sleep (slow wave sleep, SWS). Light has been shown to improve alertness during sleep deprivation and circadian misalignment. In this study, we assessed the efficacy of blue-enriched light to improve alertness and mood immediately after waking from SWS, i.e., during the sleep inertia period. METHODS: Twelve participants kept a sleep schedule of 8.5 h for 5 nights and 5 h for one night prior to the overnight laboratory visit (confirmed by actigraphy). Participants went to bed at their scheduled habitual bedtime in the laboratory and were monitored by standard polysomnography. After at least 5 min of SWS, participants were awoken and exposed to either red ambient light (control) or blue-enriched light (light) for 1 h. During this time, participants completed a subjective scale of alertness (Karolinska Sleepiness Scale, KSS) and visual analogue scales (VAS) of mood at 2 min, 17 min, 32 min, and 47 min after waking. Following this sleep inertia measurement period, all lights were turned off and participants were allowed to return to sleep. They were then awoken again from their subsequent SWS period and exposed to the opposite condition (control or light). A linear mixed-effects model with fixed effects of condition, time, and condition*time and a random effect of participant was used to determine the impact of light across the testing period. An average of baseline responses (pre-sleep) was included as a covariate. RESULTS: Compared to the control condition, participants exposed to blue-enriched light reported feeling more alert (KSS: F1,77=4.955, p=.029; VASalert: F1,77=8.226, p=.005), more cheerful (VAScheerful: F1,77=8.615, p=.004), less depressed (VASdepressed: F1,77=4.649, p=.034), and less lethargic (VASlethargic: F1,77=5.652, p=.020). DISCUSSION: Exposure to blue-enriched light immediately after waking from SWS may help to improve subjective alertness and mood. Future analyses will explore whether these findings extend to effects on cognitive performance. This countermeasure to sleep inertia may be suitable for implementation to alert crew members during mid-sleep emergencies but requires further testing in field settings.

alertness↗

NASA NTRS2022

An Overview of ARTMIP’s Tier 2 Reanalysis Intercomparison: Uncertainty in the Detection of Atmospheric Rivers and their Associated Precipitation

Atmospheric rivers, or long but narrow regions of enhanced water vapor transport, are an important component of the hydrologic cycle as they are responsible for much of the poleward transport of water vapor and result in precipitation, sometimes extreme in intensity. Despite their importance, much uncertainty remains in the detection of atmospheric rivers in large datasets such as reanalyses and century scale climate simulations. To understand this uncertainty, the Atmospheric River Tracking Method Intercomparison Project (ARTMIP) developed tiered experiments, including the Tier 2 Reanalysis Intercomparison that is presented here. Eleven detection algorithms submitted hourly tags--binary fields indicating the presence or absence of atmospheric rivers--of detected atmospheric rivers in the Modern Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) and European Centre for Medium-Range Weather Forecasts' Reanalysis Version 5 (ERA5) as well as six-hourly tags in the Japanese 55-year Reanalysis (JRA-55). Due to a higher climatological mean for integrated water vapor transport in MERRA-2, atmospheric rivers were detected more frequently relative to the other two reanalyses, particularly in algorithms that use a fixed threshold for water vapor transport. The finer horizontal resolution of ERA5 resulted in narrower atmospheric rivers and an ability to detect atmospheric rivers along resolved coastlines. The fraction of hemispheric area covered by ARs varies throughout the year in all three reanalyses, with different atmospheric river detection tools having different seasonal cycles.

ARTMIP↗

NASA NTRSDate not supplied

Changes in Alertness and Performance Over Time During Long-Haul Flying Across Multiple Time Zones

BACKGROUND: Long-haul pilots experience high levels of fatigue and circadian disruptions due to long work hours and flying over multiple time zones. The aim of this study was to describe changes in alertness and performance among flight crews during long-haul flights crossing multiple time zones. METHODS: All pilots flying long-haul operations from a single airline were eligible to participate. All participants collected data for ~2 weeks of their normal work schedule within airline operations, with at least two long-haul rotations, including rest days and layovers. Participants wore an Actiwach throughout the entire study period and completed a sleep diary (at bedtime, upon waking up and after each nap). Each participant completed a 5-min Psychomotor Vigilance Task (PVT) and a Karolinska Sleepiness Scale (KSS) pre-flight, on top-of-descent (TOD; inflight) and at the end of each flight (post-flight). Response speed (1/RT x 1000), lapses (RT > 500 ms), and alertness were assessed over time pre-flight, TOD, post-flight, using mixed-effects models with participant as a random factor. Linear models were assumed for response speed and alertness, while a negative binomial distribution was specified for lapses due to overdispersion. RESULTS: Forty-four long-haul pilots participated in the study (5 female; mean age 44.25 ± 10.06 yrs; mean flight hours 9834.3; ± 5334.1 hrs). Lapses increased post-flight relative to pre-flight (F(2, 665) = 3.67, p < 0.05). There was a main effect of response speed (F(2, 665) = 21.45, p < 0.001) with slower speed inflight and postflight compared to preflight (p < 0.001). The KSS increased over time from M = 4.02 (± 1.35) preflight to M = 5.15 (± 1.58) inflight, to M = 6.7 (± 1.51) postflight (F(2, 701) = 182.63, p < 0.001). DISCUSSION: Our preliminary analyses showed that both performance and subjective alertness worsened from the beginning to the end of a flight. Additional analyses will be conducted to investigate the changes in alertness and performance by direction of travel, sleep history, and flight timing and duration.

long-haul↗

NASA NTRSDate not supplied

Mapping Albedo Variations to Constrain the History of the Didymos System From Dart and Liciacube Observations

The Double Asteroid Redirection Test (DART) relied on its high-resolution, broad-band camera DRACO to successfully execute its impact experiment on September 26, 2022. While targeting Dimorphos, the ~150 m diameter moon of the Didymos binary asteroid system, DART also imaged the ~760 m diameter primary. LICIACube, a ride-along CubeSat released from DART prior to impact, carried two cameras, LEIA and LUKE, pan and wide-angle RGB color cameras, respectively, to witness the impact and also image both bodies. In addition to critical data that enabled and observed the impact, these cameras provided the highest spatial resolution data of any binary asteroid system and the first for near-Earth asteroids. Mapping and comparing albedo units on both the primary and secondary and placing them in the context of other S-type asteroids will help constrain the physical relationships and prior interactions between the two bodies and thus reveal the formational and evolutionary history of the Didymos system.

J. M. Sunshine↗

NASA NTRSDate not supplied

Sex Differences in Perceptions of Sleep Inertia Following Nighttime Awakenings

Study Objectives: The influence of biological sex on sleep inertia symptoms is currently unknown. We investigated the role of sex differences in the subjective experience and objective cognitive manifestation of sleep inertia following nighttime awakenings. Methods: Thirty-two healthy adults (16 female, 25.91 ± 5.63 years) completed a one-week at-home study with one experimental night during which sleep was measured by polysomnography and participants were awakened during their habitual sleep time. Participants completed a psychomotor vigilance task (PVT), Karolinska Sleepiness Scale (KSS), visual analog mood scales, and a descending subtraction task (DST) prior to sleep (baseline) and at 2, 12, 22, and 32 minutes after awakening. A series of mixed-effects models with Bonferroni-corrected post-hoc tests were used to examine the main effects of test bout and sex, and their interaction, with a random effect of participant, and order of wake-up and sleep history as covariates. Results: All outcomes except for percent correct on the DST showed a significant main effect of test bout, with worse performance after waking compared to baseline (all ps < .003). Significant effects of sex (p = .002) and sex × test bout (p = .01; R2M = .49, R2C = .69) were observed for KSS, with females reporting a greater increase in sleepiness from baseline to after waking compared to males. Conclusions: These results suggest that while females reported feeling sleepier than males following nighttime awakenings, their cognitive performance was comparable. Future research is needed to determine whether perceptions of sleepiness influence decision-making during the transition from sleep to wakefulness.

sleep inertia↗

NASA NTRSDate not supplied

Changes in Oculomotor Behavior and PVT Reaction Time During One Night of Sleep Deprivation

INTRODUCTION: The Psychomotor Vigilance Test (PVT) is a widely used objective measure of sustained attention, alertness, and fatigue. Previous studies consistently show that prolonged wakefulness and disrupted sleep patterns lead to increased lapses of attention and slower reaction times. These findings have critical implications for various professions, including healthcare, aviation, transportation safety, and spaceflight. In this study, we employed linear mixed models (LMM) to investigate hourly-measured 5-minute PVT reaction times during one night of total sleep deprivation. Our goal was to characterize the contribution of homeostatic sleep pressure (time awake) and circadian phase (salivary melatonin levels) on the dynamics of PVT reaction time. MATERIALS & METHODS: Data from twelve human participants were used in the analysis. Participants were healthy non-smokers, aged 18 and 40, with normal sleep habits defined as Pittsburg Sleep Quality Index scores < 5, and Morningness – Eveningness Questionnaire scores > 42 and < 58, respectively. Participants followed a constant-routine protocol and arrived at the NASA sleep laboratory approximately 1 to 2 hours after their habitual waking time. Tympanic temperature was measured every 30 min to provide a real-time estimate of circadian phase. Participants were required to stay awake throughout the laboratory experiment, which continued until their tympanic temperature had returned to baseline levels. This approach ensured that we could capture each participant's circadian trough and recovery, typically occurring between 24 and 26 hours after waking. The PVT and saliva melatonin were measured every hour, starting approximately from 3 hours after awakening. More information about the measurement protocol can be found in the publication by Stone et al. We used PVT reaction times between 100 and 10000 ms to calculate Reciprocal Reaction Times (RRTs). LMM models were employed to assess the contribution of time awake and saliva melatonin levels on changes in RRTs. Two models were created: the first model treated time awake as a fixed effect and the second model considered both the salivary melatonin level and time awake as fixed effects. Participants were included as a random effect in both models. We compared the models using an Analysis of Variance (ANOVA). The models were computed using the 'lmer' function from the 'lme4' package in R, and LMM p-values were determined using Satterthwaite's method. RESULTS: We found that time awake had a statistically significant effect on PVT RRTs during one night of sleep deprivation [χ2 = 2132.4, df = 1, p < 0.001]. In addition, the model including both saliva melatonin levels and time awake was statistically significantly better than one that uses just time awake [χ2 = 17.4, df = 1, p < 0.001]. DISCUSSION & CONCLUSION: As expected, these preliminary results suggest that the time awake and circadian phase each contribute to performance reductions as measured by the PVT. Future analyses will explore the contributions of other factors to the model.

sleep deprivation↗