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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 NTRS2016

Fluid Shifts: Otoacoustical Emission Changes in Response to Posture and Lower Body Negative Pressure

INTRODUCTION: The purpose of the NASA Fluid Shifts Study is to characterize fluid distribution and compartmentalization associated with long-duration spaceflight and to correlate these findings with vision changes and other elements of the visual impairment and intracranial pressure (VIIP) syndrome. VIIP signs and symptoms, as well as postflight lumbar puncture data, suggest that elevated intracranial pressure (ICP) may be associated with spaceflight-induced cephalad fluid shifts, but this hypothesis has not been tested. Due to the invasive nature of direct measures of ICP, a noninvasive technique of monitoring ICP is desired for use during spaceflight. The phase angle and amplitude of otoacoustic emissions (OAEs) have been shown to be sensitive to posture change and ICP (1, 2), therefore use of OAEs is an attractive option. OAEs are low-level sounds produced by the sensory cells of the cochlea in response to auditory stimulation. These sounds travel peripherally from the cochlea, through the oval window, to the ear canal where they can be recorded. OAE transmission is sensitive to changes in the stiffness of the oval window, occurring as a result of changes in cochlear pressure. Increased stiffness of the oval window largely affects the transmission of sound from the cochlea at frequencies between 800 Hz and 1600 Hz. OAEs can be self-recorded in the laboratory or on the ISS using a handheld device. Our primary objectives regarding OAE measures in this experiment were to 1) validate this method during preflight testing of each crewmember (while sitting, supine and in head-down tilt position), and 2) determine if OAE measures (and presumably ICP) are responsive to lower body negative pressure and to spaceflight. METHODS: Distortion-product otoacoustic emissions (DPOAEs) and transient evoked otoacoustic emissions (TEOAEs) were recorded preflight using the Otoport Advance OAE system (Otodynamics Ltd., Hatfield, UK). Data were collected in four conditions (seated, supine, 15 degrees head down tilt (HDT), and 15 degrees HDT with lower body negative pressure (LBNP)) to produce a range of ICP in each subject and test the susceptibility of OAEs to LBNP. LBNP was induced using the Russian Chibis suit to produce the same fit and pressures that would be experienced inflight during Chibis LBNP trials. Similar trials have occurred inflight on the ISS. A comparative analysis of preflight and inflight phase measurements and magnitudes was completed in both broad and narrow band frequency ranges. RESULTS: TEOAE data demonstrated notable phase shifts from 859-1640 Hz when the seated baseline condition is compared to supine, HDT, and HDT plus Chibis conditions. Changes were particularly pronounced at low frequencies and were consistent with the expected ICP changes. Preflight DPOAE magnitude data revealed changes consistent with increased ICP in two conditions at 1414 Hz, where a magnitude change (relative to the seated condition) was seen in the HDT position and in HDT plus Chibis. DISCUSSION: OAEs revealed systematic changes in phase and magnitude throughout all test conditions (including use of Chibis LBNP) that were consistent with ICP changes. Results indicate that OAEs may provide a rapid noninvasive means of monitoring ICP changes. The first two subjects are projected to complete inflight testing on the ISS in early 2016, with the full complement of 10 subjects scheduled to be complete in 2018.

Melgoza, R.↗
NASA NTRS1977

Observations of large transient magnetospheric electric fields

Transient electric field events were studied by means of the long double-probe instrumentation carried by the Imp 6 satellite, and nine clearly defined exceptionally large amplitude events are described. The events were observed in the midnight sector at geocentric distances of 3.5 to 5.5 earth radii at middle latitudes within a magnetic L shell range of 4.8 to 7.5; the duration is from one to several minutes with peak power spectra amplitudes occurring at a frequency of about 0.3 Hz. The events occur under magnetically disturbed conditions and are often associated with negative dH/dt excursions. The magnetospheric motions calculated for these electric fields indicate a quasi-stochastical diffusive process rather than the general inward magnetospheric collapsing motion expected during the expansive phases of auroral substorm activity. It is likely that the transient electric fields are responsible for the impulsive acceleration and injection of plasma to populate the outer radiation belt.

Aggson, T. L.↗
NASA NTRSDate not supplied

A Machine Learning Approach to Improve Air Traffic Management Initiatives

Collaborating closely with commercial air carriers and related organizations, the Federal Aviation Administration(FAA) regulates air traffic and ensures the safety and efficiency of air operations. Air traffic controllers make strategic decisions, such as delaying, rerouting, or canceling flights, partly based on guidance provided by the FAA’s Air TrafficControl System Command Center (ATCSCC). The guidance includes, among other things, control measures known asTraffic Management Initiatives (TMIs) designed to enhance safety and improve operational efficiency. TMIs play a crucial role in managing the demand and capacity within the U.S. National Airspace System (NAS). Two major TMIs that are routinely used (primarily to mitigate the adverse effects of bad weather) are Ground Delay Programs (GDPs) andGround Stops (GSs). In a GDP, flights destined for airports facing thunderstorm activity experience delays at their origin airports. This proactive approach minimizes the risk of routing aircraft through hazardous weather conditions and also replaces (fuel burning) airborne delays with ground delays. In a GS, a temporary restriction is imposed on the departure or arrival of aircraft at a specific airport or within a designated airspace. Although other TMIs (e.g., miles-in-trail) are also implemented as part of (air) traffic flow management in the NAS, the focus of this work is on GDPs and GSs. Since TMIs, by design, lead to flight delays or cancellations, it is crucial to put in place the right set of parameters(e.g., scope and duration of the GDP). For example, when the end time of a GDP extends beyond what is necessary, it imposes unnecessary delays on departing flights. This situation could occur as a result of inaccurate prediction of the(required) duration of the GDP based on the weather forecast. On the other hand, if a GDP ends prematurely before the underlying capacity constraints are resolved at the destination airport, it may result in airborne holding. The delicate balance lies in matching the termination of the GDP precisely with the resolution of capacity constraints, avoiding both the imposition of unnecessary ground delays and the need for airborne holding due to premature program termination.Failing to specify the right parameters for TMIs also leads to flight delays, creating a significant obstacle in managing the increasing traffic volumes causing increased work load for the controllers. To address this issue, we propose the integration of Machine Learning (ML) models in the traffic flow management(TFM) pipeline. In current operations, decisions are made by human experts based on extensive training, historical patterns, available traffic and weather data. Since we have an abundance of data from past events that tell us the likely impact of various TMIs, by ingesting historical data, properly trained ML models can offer valuable insights and aid human decision-making. With the FAA increasingly exploring advanced analytics, ML emerges as a focal point for enhancing TFM within the National Airspace System (NAS). As a first step, this study aims to provide traffic controllers with decision-making support for the issuance and adjustment of TMIs. Data analytics and machine learning have been previously employed to address some of the challenges associated with TMIs. Numerous studies have concentrated on various facets of TMI issuance, exploring factors influencing TMI parameters, including arrival rate, airport capacity, and delay prediction. For example, using weather forecasts, several statistical methods were used to produce probabilistic capacity profiles which in conjunction with deterministic models provided insights into the GDP planning process [1–4]. The downside of using deterministic models is that they rely on fixed inputs and predetermined rules, which lack the ability to account for the inherent uncertainty and variability present in real-world scenarios. In a separate series of studies, researchers aimed to predict the occurrences of GDPs and GSs. The majority of these studies utilized various supervised learning methods, including Decision Trees, Naive Bayes, Support VectorMachines, and Random Forests to analyze the influence of weather conditions and arrival demand on TMI incidents[5–8]. However, these studies primarily focused on predicting the incidence of TMIs without explicitly addressing the scope of TMIs, including their duration and their geographical coverage. Furthermore, the emphasis of these studies was largely on GDPs, given their higher frequency and longer duration when compared to GSs. A limited number of studies focused on predicting the parameters of TMIs, specifically addressing their duration and extent. In one such study focusing on optimizing the TMI parameters at San Francisco International Airport (SFO),the authors utilized a probabilistic forecast of fog [9]. They simulated various capacity scenarios based on the (fog)burn-off forecasts, selecting GDP parameters that minimized airborne and overall ground delays. However, this approach exclusively emphasizes stratus (fog) burn-off as the primary determinant of GDP and GS, neglecting other influential factors like severe weather events, runway closures, lower capacity than traffic demand, and other important variables. Given the complexity of predicting the TMI and determining its scope, we seek a more holistic approach. We aim to consider all significant factors that could impact TMIs and their parameters. What sets this research apart is the fusion of all data sources relevant to the issuance and adjustment of TMIs and it represents the first comprehensive attempt to optimize TMIs in this manner. Since this comprehensive solution involves various aspects, we break down the problem into smaller components and input all parameters into a unified model called the “TMI Adjuster”. Figure 1 shows the overall framework and the list of datasets used in each model. The objective of the TMI Adjuster module is to deliver reliable, consistent and expedited recommendations for the progression, adjustment, and termination of TMIs. The ML solution entails developing a pipeline capable of predicting the necessity of a TMI (e.g., GS or GDP) along with its various parameters. For example, in the case of a GS, this includes the scope of the GS either in terms of distance from the destination airport or based on pre-defined airspace sectors. Here, scope refers to those regions and departing airports that are subject to the GS. In this paper, we concentrate on the issuance of GSs in the three major airports in the New York area — LaGuardia(LGA), John F. Kennedy International (JFK), and Newark Liberty International (EWR). We fuse traffic, weather and other relevant aviation data from years 2017 to 2019 to train and validate the ML models. In particular, we use the following datasets: •Terminal Aerodrome Forecast (TAF): meteorological forecasts specific to each airport, issued four times a day, covering predefined time periods. •TMI data: includes all GSs and GDPs along with their respective parameters. •Aviation System Performance Metrics (ASPM): includes traffic related data such as aircraft delays, arrival, and departure rates. •Notices to Airmen (NOTAMs): utilized to extract runway closure data and manage interdependencies between terminals in close proximity. •Flight cancellation data •Airspace Flow Programs (AFP): includes information on flight airborne holdings caused by TMIs. The data preprocessing entails transforming ASPM, TMI, AFP, NOTAMs, and weather data into an hourly format and consolidating all datasets by merging them based on date and time as the primary key. The TMI Adjuster framework comprises two parallel models: one dedicated to GS and a second model focused on GDP. As previously mentioned, our specific focus is on the GS model as a multi-classification problem. In this framework, each data point of the GS model input summarizes ten hours of data. Specifically, the data loader for the GS model generates the input and output of the model as follows: at a given time step, the input includes the actual traffic, weather, and TMI data from the two-hour window before the time step, alongside the weather forecast and scheduled traffic for the next 8 hours starting from the time step. Based on this information, the output of the GS model for each time interval consists of three dimensions. The first dimension represents a binary decision on whether there should be a GS in place for the next hour or not. The second dimension is related to the scope of the GS in the United States, and the third dimension is related to the scope of the GS in Canada (i.e., to determine if the GS impacts airports in Canada).One of the challenges with TMI modeling is the sparsity of TMI events, particularly regarding its scope. To address this challenge in the scope of the GS model output, we implement grouping. The GS scope for the US region is defined based on a list of centers that should be included when the GS is in place. With 20 centers in the US, we utilized historical data to group them into 4 categories. In particular, we summarized our historical data in a graph format where nodes represent centers, and link weights are defined based on the co-occurrence of centers in the scope parameter ofTMIs. By identified strongly connected components in this graph, we were able to partition the centers into four groups. We consider two model structures for the GS Model. Firstly, a hierarchical classification model [10], where the human decision-making for a GS is of hierarchical nature. The decision-maker first decides whether there is a need fora GS, and if the answer is yes, determines the scope. A hierarchical classification model organizes the problem into a class hierarchy, typically a tree or a Directed Acyclic Graph (DAG) structure, and considers the dependency of the decision in the previous step to the next component [10]. Here, we employ the local classifier per level approach, which involves training one multi-class classifier for each level of the class hierarchy. The second structure is the independent structure. In this setting, as the name suggests, we do not consider the dependency of the decisions in the different dimensions of the output of the model. Instead, for each dimension, we train a multi-class classifier independently. Table 1 summarizes GS model statistics for training, validation and testing. The table documents the effect of limiting data to the time steps when there was actually a TMI in place or when a TMI had just terminated. This resulted in a more balanced distribution of the GS class(GS positive class)versus “No GS”(GS negative class), which might help the training process. While JFK and LGA follow very similar distributions, with 40% and 42% GS positive class respectively, EWR has proportionally fewer GS incidents at 28%. Our subsequent phase involves evaluating the performance of both hierarchical structure and independent structure using different state-of-the-art multi-class classifier models such as Random Forest, Decision Trees, K-nearest Neighbors, and Logistic Regression and forecast the duration and scope of the GSs.

Farzan Masrour Shalmani↗
DOE OSTI2020

Improved Parametric Models for Explosion Pressure Signals Derived From Large Datasets

Accurate recording and characterization of explosion-induced pressure signals are key components of the forensic analysis of explosion events in the atmosphere. Parametric overpressure models based on several key waveform features (peak overpressure, positive pulse duration, and impulse) are widely used to estimate explosion energy in terms of trinitrotoluene equivalent yield. However, those models are often developed by a limited dataset, including only a few events or recordings at relatively short propagation distances. Here, we develop empirical waveform-parameter models based on a regression analysis of a large set of data curated from four chemical explosion experiments including 16 detonations. We measured peak overpressure and impulse for positive and negative phases from 1000 pressure signals recorded at local ranges (<20 km) with scaled distance up to 8000 m/kg 1/3 . Additionally, the measured waveform parameters showed large variation with respect to observing distances indicating the effects of atmospheric propagation. In this study, a second-order polynomial model was used in a least-squares regression to account for those propagation effects and to improve data fitting. In addition to model parameters for waveform features, we also determined range-dependent model uncertainties based on data variance. The model uncertainty represents the prediction error of our models and can be critical to evaluating the uncertainty of yield estimate.

58 GEOSCIENCES↗
NASA NTRS1987

Hysteresis in response to descending and ascending lower-body negative pressure

Changes in the indices of fluid redistribution and cardiovascular responses during graduated orthostatic stress were measured in 12 men subjected for 25 min to lower-body negative pressure (LBNP) test protocol that involved stepwise decreases (from the starting pressure of -8 to the final -50 mm Hg), followed by stepwise increases (back to -8 mm Hg) of LBNP. The values of many variables measured during the descending phase of LBNP were significantly different from the respective values measured during the ascending phase. These differences appear to be caused by a component of fluid translocation that occurs during LBNP and cannot be reversed within the duration of the procedure. It is hypothesized that this slowly-reversed component is the sequestration of fluid in the interstitial and the lymphatic compartments.

Tomaselli, Clare Marie↗
NASA NTRS1977

Observations of large transient magnetospheric electric fields

Transient electric field events were observed with the long, double probe instrumentation carried by the IMP-6 satellite. Nine, clearly defined, exceptionally large amplitude events are presented here. The events are observed in the midnight sector at geocentric distances 3.5 to .5.5 R sub e at middle latitudes within a magnetic L-shell range of 4.8 to 7.5. They usually have a total duration of one to several minutes, with peak power spectra amplitudes occurring at a frequency of about 0.3 Hz. The events occur under magnetically disturbed conditions, and in most cases they can be associated with negative dH/dt excursions at magnetic observatories located near the foot of the magnetic field line intersecting IMP-6. The magnetospheric motions calculated for these electric fields indicated a quasi-stochastical diffusive process rather than the general inward magnetospheric collapsing motion expected during the expansive phases of auroral substorm activity.

Aggson, T. L.↗
NASA NTRS1998

Magnetic Field Configuration of Active Region NOAA 6555 at the Time of a Long Duration Flare on 23 March 1991: An Exception to Standard Flare Reconnection Model

The high-resolution H(sub alpha) images observed during the decay phase of a long duration flare on 23 March 1991 are used to study the three-dimensional magnetic field configuration of the active region NOAA 6555. Whereas, all the large flares in NOAA 6555 occurred at the location of high magnetic shear and flux emergence, this long duration flare was observed in the region of low magnetic shear at the photosphere. The H(sub alpha) loop activity started soon after the maximum phase of the flare. There were few long loop at the initial phase of the activity. Some of these were sheared in the chromosphere at an angle of about 45 deg with the east-west axis. Gradually, increasing number of shorter loops, oriented along the east-west axis, started appearing. The chromospheric Dopplergrams show blue-shifts at the end points of the loops. By using different magnetic field models, we have extrapolated the photospheric magnetograms to the chromospheric heights. The magnetic field lines computed by using the potential field model correspond to most of the observed H(sub alpha) loops. The height of the H(sub alpha) loops were derived by comparing them with the computed field lines. From the temporal evolution of the H(sub alpha) loop activity, we derive the negative rate of appearance of H(sub alpha) features as a function of height. It is found that the field lines oriented along one of the neutral lines was sheared and low lying. The higher field lines were mostly potential. The paper also outlines a possible scenario for describing the post-flare stage of the observed long duration flare.

Choudhary, Debi Prasad↗
NASA NTRS2017

Understanding the International Space Station Crew Perspective following Long-Duration Missions through Data Analytics & Visualization of Crew Feedback

The International Space Station (ISS) first became a home and research laboratory for NASA and International Partner crewmembers over 16 years ago. Each ISS mission lasts approximately 6 months and consists of three to six crewmembers. After returning to Earth, most crewmembers participate in an extensive series of 30+ debriefs intended to further understand life onboard ISS and allow crews to reflect on their experiences. Examples of debrief data collected include ISS crew feedback about sleep, dining, payload science, scheduling and time planning, health & safety, and maintenance. The Flight Crew Integration (FCI) Operational Habitability (OpsHab) team, based at Johnson Space Center (JSC), is a small group of Human Factors engineers and one stenographer that has worked collaboratively with the NASA Astronaut office and ISS Program to collect, maintain, disseminate and analyze this data. The database provides an exceptional and unique resource for understanding the "crew perspective" on long duration space missions. Data is formatted and categorized to allow for ease of search, reporting, and ultimately trending, in order to understand lessons learned, recurring issues and efficiencies gained over time. Recently, the FCI OpsHab team began collaborating with the NASA JSC Knowledge Management team to provide analytical analysis and visualization of these over 75,000 crew comments in order to better ascertain the crew's perspective on long duration spaceflight and gain insight on changes over time. In this initial phase of study, a text mining framework was used to cluster similar comments and develop measures of similarity useful for identifying relevant topics affecting crew health or performance, locating similar comments when a particular issue or item of operational interest is identified, and providing search capabilities to identify information pertinent to future spaceflight systems and processes for things like procedure development and training. In addition, the comments were scored for sentiment using a polarity scoring algorithm to identify both positive and negative comments for particular groups and clusters, allowing the team to make analytically informed decisions regarding future hardware and operating procedures. The use of polarity scoring with time series analysis was used to provide insight into how crew health and habitability is changing throughout various spaceflight increments or the station lifecycle as a whole. Finally, a visualization framework was developed to address the needs of the end users to search for and analyze comments by user, category or mission. This paper will discuss how the use of an analytical framework in conjunction with the current human interface, improved the understanding of crew perspective and shortened the time for analysis allowing for more informed decisions and rapid development of improvements. These methods are significantly optimizing the way that this valuable data can be assessed and applied to current and future spaceflight design and development. This collaboration allows the FCI OpsHab team to effectively analyze and share data in a more automated and timely fashion. Trends are no longer derived manually and can be illustrated effectively and accurately with these evolving techniques to an ever growing group of human spaceflight end users.

Bryant, Cody↗
NASA NTRS2012

Validation of Atmosphere/Ionosphere Signals Associated with Major Earthquakes by Multi-Instrument Space-Borne and Ground Observations

The latest catastrophic earthquake in Japan (March 2011) has renewed interest in the important question of the existence of pre-earthquake anomalous signals related to strong earthquakes. Recent studies have shown that there were precursory atmospheric/ionospheric signals observed in space associated with major earthquakes. The critical question, still widely debated in the scientific community, is whether such ionospheric/atmospheric signals systematically precede large earthquakes. To address this problem we have started to investigate anomalous ionospheric / atmospheric signals occurring prior to large earthquakes. We are studying the Earth's atmospheric electromagnetic environment by developing a multisensor model for monitoring the signals related to active tectonic faulting and earthquake processes. The integrated satellite and terrestrial framework (ISTF) is our method for validation and is based on a joint analysis of several physical and environmental parameters (thermal infrared radiation, electron concentration in the ionosphere, lineament analysis, radon/ion activities, air temperature and seismicity) that were found to be associated with earthquakes. A physical link between these parameters and earthquake processes has been provided by the recent version of Lithosphere-Atmosphere-Ionosphere Coupling (LAIC) model. Our experimental measurements have supported the new theoretical estimates of LAIC hypothesis for an increase in the surface latent heat flux, integrated variability of outgoing long wave radiation (OLR) and anomalous variations of the total electron content (TEC) registered over the epicenters. Some of the major earthquakes are accompanied by an intensification of gas migration to the surface, thermodynamic and hydrodynamic processes of transformation of latent heat into thermal energy and with vertical transport of charged aerosols in the lower atmosphere. These processes lead to the generation of external electric currents in specific regions of the atmosphere and the modifications, by dc electric fields, in the ionosphere-atmosphere electric circuit. We retrospectively analyzed temporal and spatial variations of four different physical parameters (gas/radon counting rate, lineaments change, long-wave radiation transitions and ionospheric electron density/plasma variations) characterizing the state of the lithosphere/atmosphere coupling several days before the onset of the earthquakes. Validation processes consist in two phases: A. Case studies for seven recent major earthquakes: Japan (M9.0, 2011), China (M7.9, 2008), Italy (M6.3, 2009), Samoa (M7, 2009), Haiti (M7.0, 2010) and, Chile (M8.8, 2010) and B. A continuous retrospective analysis was preformed over two different regions with high seismicity- Taiwan and Japan for 2003-2009. Satellite, ground surface, and troposphere data were obtained from Terra/ASTER, Aqua/AIRS, POES and ionospheric variations from DEMETER and COSMIC-I data. Radon and GPS/TEC were obtaining from monitoring sites in Taiwan, Japan and Italy and from global ionosphere maps (GIM) respectively. Our analysis of ground and satellite data during the occurrence of 7 global earthquakes has shown the presence of anomalies in the atmosphere. Our results for Tohoku M9.0 earthquake show that on March 7th, 2011 (4 days before the main shock and 1 day before the M7.2 foreshock of March 8, 2011) a rapid increase of emitted infrared radiation was observed by the satellite data and an anomaly was developed near the epicenter. The GPS/TEC data indicate an increase and variation in electron density reaching a maximum value on March 8. From March 3 to 11 a large increase in electron concentration was recorded at all four Japanese ground-based ionosondes, which returned to normal after the main earthquake. Similar approach for analyzing atmospheric and ionospheric parameters has been applied for China (M7.9, 2008), Italy (M6.3, 2009), Samoa (M7, 2009), Haiti (M7.0, 2010) and Chile (M8.8, 2010) eahquakes. Results have revealed the presence of related variations of these parameters implying their connection with the earthquake process. The second phase (B) of this validation included 102 major earthquakes (M>5.9) in Taiwan and Japan. We have found anomalous behavior before all of these events with no false negatives. False alarm ratio for false positives is less then 10% and has been calculated for the same month of the earthquake occurrence for the entire period of analysis (2003-2009). The commonalities for detecting atmospheric/ionospheric anomalies are: i.) Regularly appearance over regions of maximum stress (i.e., along plate boundaries); ii.) Anomaly existence over land and sea; and iii) association with M>5.9 earthquakes not deeper than 100km. Due to their long duration over the same region these anomalies are not consistent with a meteorological origin. Our initial results from the ISTF validation of multi-instrument space-borne and ground observations show a systematic appearance of atmospheric anomalies near the epicentral area, one to seven (average) days prior to the largest earthquakes, and suggest that it could be explained by a coupling process between the observed physical parameters and the pre-earthquake preparation processes.

Ouzounov, Dimitar↗
NASA NTRS1987

Spacelab Life Sciences flight experiments: an integrated approach to the study of cardiovascular deconditioning and orthostatic hypotension

The microgravity environment of spaceflight produces rapid cardiovascular changes which are adaptive and appropriate in that setting, but are associated with significant deconditioning and orthostatic hypotension on return to Earth's gravity. The rapidity with which these space flight induced changes appear and disappear provides an ideal model for studying the underlying pathophysiological mechanisms of deconditioning and orthostatic hypotension, regardless of etiology. Since significant deconditioning is seen after flights of very short duration, muscle atrophy due to inactivity plays, at most, a small role. These changes in circulatory control associated with cephalad fluid shifts, rather than inactivity per se, are probably more important factors. In order to test this hypothesis in a systematic way, a multidisciplinary approach which defines and integrates inputs and responses from a wide variety of circulatory sub-systems is required. The cardiovascular experiments selected for Spacelab Life Sciences flights 1 and 2 provide such an approach. Both human and animal models will be utilized. Pre- and post-flight characterization of the payload crew includes determination of maximal exercise capacity (bicycle ergometry), orthostatic tolerance (lower body negative pressure), alpha and beta adrenergic sensitivity (isoproterenol and phenylephrine infusions), baroreflex sensitivity (ECG-gated, stepwise changes in carotid artery transmural pressure with a pneumatic neck collar), and responses to a 24 h period of 5 deg head-down tilt. Measurements of cardiac output (CO2 and C2H2 rebreathing), cardiac chamber dimensions (phased-array 2-dimensional echocardiography), direct central venous pressure, leg volume (Thornton sock), limb blood flow and venous compliance (occlusion plethysmography), blood and plasma volumes, renal plasma flow and glomerular filtration rates, and various hormonal levels including catecholamines and atrial natriuretic factor will also be obtained. The central venous catheter will be inserted immediately pre-launch and monitored with heart rate and blood pressure in-flight until cardiac output, respiratory gas exchange and quantitative 2D echocardiography measurements can be performed. In-flight hemodynamic measurements will be repeated at rest and during submaximal exercise daily and also during maximal exercise midway through the flight to document the timecourse and extent of cardiovascular changes in the payload crew. Parallel studies are planned for the animals. In addition to measurements of right atrial and aortic pressures and cardiac output, a dorsal micro-circulatory chamber will allow determinations of changes in capillary and venular architecture and function in six of the rats. The techniques and findings from many of the SLS-1 and 2 supporting studies have already yielded significant information about circulatory regulation in patients with both hypo- and hypertension. The flight experiments themselves will provide new data to test the validity of both animal and human models currently used for simulating the fluid shifts of a micro-gravity environment. The development of effective countermeasures, not only for short and long duration space travellers, but also for Earth-bound medical patients can then be physiologically based on experimental data rather than anecdote.

Non-NASA Center↗
DOE OSTI2022

Efficient generation of the 7th harmonic of Ti:sapphire (114.6 nm) vacuum ultraviolet pulses with 60 fs duration by non-collinear four-wave mixing in argon

The recent advances in femtosecond vacuum UV (VUV) pulse generation, pioneered by the work of Noack et al., has enabled new experiments in ultrafast time-resolved spectroscopy. Expanding on this work, we report the generation of 60 fs VUV pulses at the 7th harmonic of Ti:sapphire with more than 50 nJ of pulse energy at a repetition rate of 1 kHz. Additionally, the 114.6 nm pulses are produced using non-collinear four-wave difference-frequency mixing in argon. The non-collinear geometry increases the phase-matching pressure, and results in a conversion efficiency of ~10-3 from the 200 nm pump beam. The VUV pulses are pre-chirp-compensated for material dispersion with xenon, which has negative dispersion in this wavelength range, thus allowing almost transform-limited pulses to be delivered to the experimental chamber.

36 MATERIALS SCIENCE↗
NASA NTRS1995

Space Station Biological Research Project

NASA Ames Research Center is responsible for the development of the Space Station Biological Research Project (SSBRP) which will support non-human life sciences research on the International Space Station Alpha (ISSA). The SSBRP is designed to support both basic research to understand the effect of altered gravity fields on biological systems and applied research to investigate the effects of space flight on biological systems. The SSBRP will provide the necessary habitats to support avian and reptile eggs, cells and tissues, plants and rodents. In addition a habitat to support aquatic specimens will be provided by our international partners. Habitats will be mounted in ISSA compatible racks at u-g and will also be mounted on a 2.5 m diameter centrifuge except for the egg incubator which has an internal centrifuge. The 2.5 m centrifuge will provide artificial gravity levels over the range of 0.01 G to 2 G. The current schedule is to launch the first rack in 1999, the Life Sciences glovebox and a second rack early in 2001, a 4 habitat 2.5 in centrifuge later the same year in its own module, and to upgrade the centrifuge to 8 habitats in 2004. The rodent habitats will be derived from the Advanced Animal Habitat currently under development for the Shuttle program and will be capable of housing either rats or mice individually or in groups (6 rats/group and at least 12 mice/group). The egg incubator will be an upgraded Avian Development Facility also developed for the Shuttle program through a Small Business and Innovative Research grant. The Space Tissue Loss cell culture apparatus, developed by Walter Reed Army Institute of Research, is being considered for the cell and tissue culture habitat. The Life Sciences Glovebox is crucial to all life sciences experiments for specimen manipulation and performance of science procedures. It will provide two levels of containment between the work volume and the crew through the use of seals and negative pressure. The glovebox will accommodate use by two crew persons simultaneously and the capability for real time video down-link and data acquisition. In house testbeds and Phase B studies of the centrifuge validated the concepts of vibration isolation and autobalancing systems to meet the ISSA microgravity requirements. The vibration isolation system is effective above the centrifuge rotation frequency while the autobalancing system on the rotor removes vibration at and below the rotation rate. Torque of the Station, induced by spin-up/spindown of the centrifuge, can be minimized by controlling spin-up/spin-down rates. The SSBRP and ISSA will provide the opportunity to perform long-term, repeatable and high quality science. The long duration increments available on the Station will permit multigeneration studies of both plants and animals which have not previously been possible. The u-g habitat racks and the eight habitat centrifuge will accommodate sufficient number of specimens to permit statistically significant sampling of specimens to investigate the time course of adaptation to altered gravity environments. The centrifuge will, for the first time, permit investigators to use gravity itself as a tool to investigate fundamental processes, to investigate the intensity and duration of gravity to maintain normal structure and function, to separate the effects of u-g from other environmental factors and to examine artificial gravity as a potential countermeasure for the physical deconditioning observed during space flight.

Johnson, Catherine C.↗
DOE OSTI2022

Ionic Control over Ferroelectricity in 2D Layered van der Waals Capacitors

The van der Waals layered material CuInP 2 S 6 features interesting functional behavior, including the existence of four uniaxial polarization states, polarization reversal against the electric field through Cu ion migration, a negative-capacitance regime, and reversible extraction of Cu ions. At the heart of these characteristics lies the high mobility of Cu ions, which also determines the spontaneous polarization. Therefore, Cu migration across the lattice results in unusual ferroelectric behavior. Here, we demonstrate how the interplay of polar and ionic properties provides a path to ionically controlled ferroelectric behavior, achieved by applying selected DC voltage pulses and subsequently probing ferroelectric switching during fast triangular voltage sweeps. Using current measurements and theoretical calculations, we observe that increasing DC pulse duration results in higher ionic currents, the buildup of an internal electric field that shifts polarization loops, and an increase in total switchable polarization by ~50% due to the existence of a high polarization phase which is stabilized by the internal electric field. Apart from tuning ferroelectric behavior by selected square pulses, hysteretic polarization switching can even be entirely deactivated and reactivated, resulting in three-state systems where polarization switching is either inhibited or can be performed in two different directions.

36 MATERIALS SCIENCE↗
NASA NTRS2023

Global Assessment of Drought Characteristics in the Anthropocene

Contemporary understanding of the impacts of climate change on global drought characteristics (e.g., intensities, extents) is still limited and not well understood. This knowledge is critical because projected changes in climate are expected to impact on future water availability as well as influence decisions on how water resources are allocated. The main aim of this study is to improve understanding of drought characteristics (extents and duration) in the Anthropocene where rapid changes in the environment are caused by the composite influence of human activities and climate change. Multi-scale earth observation data (1980 - 2020) and the Coupled Model Intercomparison Project Phase 6 climate models, which incorporate the Shared Socioeconomic Pathways (2040 - 2070 and 2070 - 2100) are used to assess these characteristics as well as identify climatic hotspots where changes in drought characteristics could drive groundwater hydrology. Results show that towards the end of the 21st century, global land areas under drought will significantly decrease but their durations will not. Generally, there is evidence of significant decline in the proportion of areas that will experience various drought intensities (moderate, severe and extreme drought) in the future and for each category, drought affected areas will not reach 30% on average. Moreover, some regions are potential hotspots of climate–groundwater interactions where drought events could directly impact on groundwater. This is because of the varying degree of strong correlations (positive and negative) between climate and groundwater data in some areas (e.g., Australia, Europe, Southern Africa, Asia). The relatively strong negative correlations in some of these hotspots are indicative of the presence of considerable lags, that could be caused by aridity as well as human groundwater footprints.

Christopher E Ndehedehe↗
NASA NTRS2020

Neural Network Repair of Lossy Compression Artifacts in the Sept 2015 – March 2016 Duration of the MMS/FPI Dataset

During the Sept 2015 –March 2016 duration (sometimes referred to as Phase 1A) of the Magnetospheric Multiscale Mission (MMS), the Dual Electron Spectrometers (DES) were configured to generously utilize lossy compression. While this maximized the number of velocity distribution functions downlinked, it cameat the expense of lost information content for a fractionof the frames. Following this period of lossy compression, the DES was re-configured in a way that allowed for 95% of the framesto arrive to the ground without loss. Using this high-quality set offrameson-orbit observations, we compressed and decompressed the frameson the ground to create a side-by-side record of the compression effect. This record was used to drive an optimization method that (a) derived basis functions capable of approximating the lossless sample space and with non-negative coefficients and (b) fitted a function which maps the lossy framesto basis weights that recreate the framewithout compression artifacts. This methodis introduced and evaluated in this paper.Data users should expect a higher level of confidence in the absolute scale of density/temperature measurements andnotice less sinusoidal bias in the velocity X and Y components(GSE).

Magnetosphere, Neural Networks, Image Processing, ↗
NASA NTRS1997

Sleep and Rest Requirements: Physiological Considerations

Sleep is a vital physiological need which must be met to insure optimal functioning. A single night of significantly shortened sleep negatively impacts performance, alertness, and mood. Restricted sleep studies have shown that even a relatively small amount of sleep loss over several consecutive days can be additive and result in a cumulative sleep debt with similar detrimental effects. Compounding the problem of sleep loss in the operational environment is the poor correlation between subjective reports of sleepiness and objective measures of physiological sleep need. Some of the factors determining how sleepy an individual is at a given point in time are: (1) individual characteristics (e.g., amount of prior sleep and wakefulness, circadian phase, age), (2) environmental conditions (e.g., noise, temperature, amount of social interaction), and (3) task variables (e.g., signal rate, workload). Although sleep need can be masked with medications, the only way to reduce it is with sleep itself. The timing of the sleep period can affect sleep duration and quality and thus its restorative strength. The data are clear that increasing sleep time results in improved alertness. This paper will briefly review the scientific findings on sleep need, the effects of sleep loss, napping strategies, and the implications of incorporating physiologically sound sleep and rest strategies into the operational aviation environment.

Neri, David F.↗
DOE OSTI2025

The AGORA High-resolution Galaxy Simulations Comparison Project. VIII. Disk Formation and Evolution of Simulated Milky Way Mass Galaxy Progenitors at 1 < z < 5

We investigate how differences in the stellar feedback produce disks with different morphologies in Milky Way–like progenitors over 1 ≤ z ≤ 5, using eight state-of-the-art cosmological hydrodynamics simulation codes in the AGORA project. In three of the participating codes, a distinct, rotation-dominated inner core emerges with a formation timescale of ≲300 Myr, largely driven by a major merger event, while two other codes exhibit similar signs of wet compaction—gaseous shrinkage into a compact starburst phase—at earlier epochs. The remaining three codes show only weak evidence of wet compaction. Consequently, we divide the simulated galaxies into two groups: those with strong compaction signatures and those with weaker ones. Galaxies in these two groups differ in size, stellar age gradients, and disk-to-total mass ratios. Specifically, codes with strong wet compaction build their outer disks in an inside-out fashion, leading to negative age gradients, whereas codes with weaker compaction feature flat or positive age gradients caused primarily by outward stellar migration. Although the stellar half-mass radii of these two groups diverge at z ∼ 3, the inclusion of dust extinction brings their sizes and shapes in mock observations closer to each other and to observed galaxies. We attribute the observed morphological differences primarily to variations in the stellar feedback implementations—such as delayed cooling timescales, and feedback strengths—that regulate both the onset and duration of compaction. Overall, our results suggest that disk assembly at high redshifts is highly sensitive to the details of the stellar feedback prescriptions in simulations.

Jung, Minyong [Seoul National Univ. (Korea, Republ↗