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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Validation of Multisystem Countermeasures Protocol for Spaceflight during Antarctica Winter-over at Palmer Station (Palmer Countermeasures)

Stressors associated with spaceflight induce persistent immune compromise in astronauts which increase subclinical latent virus reactivation. In select crews, adverse clinical events have been documented. Antarctica winter-over (AWO) mission most closely reproduces these mission stressors: prolonged deployment, extreme environment, circadian misalignment, isolation, station lifestyle, and personal risk. The US maintains three primary stations in Antarctica: South Pole Station, McMurdo, and Palmer. Previous studies suggest that stations located near the interior of Antarctica (South Pole, McMurdo) have confounding effects on the immune system due to persistent hypobaric hypoxia. We hypothesized that winter-over at a coastal station (Palmer) would be more akin to spaceflight due to its normoxic but still extreme environment. Therefore, AWO at Palmer Station was selected, and validated in a pilot study [2], as the platform for testing and validating the effectiveness of an immune-restorative countermeasure protocol designed for deep space missions. Specifics include diet modifications, nutritional supplementation (vitamin D, probiotic, etc.), prescribed aerobic and resistive exercise, and a protocol of stress relieving virtual reality exercises. A multitude of biological sample types, including blood, saliva, and hair will be collected in tandem with the countermeasures in order to examine the combined effectiveness of the countermeasures. Samples and logs from subjects will be transported from Palmer Station to Johnson Space Center for further processing and distribution to co-investigators at the end of each winter-over. Extracted samples will be analyzed by appropriate testing platforms (Multiplex, qPCR, ELISA, etc.) to monitor alterations in leukocyte distribution, T cell and NK function, cytokine profiles, reactivation of latent herpesviruses, and nutritional factors. The data collected will be compared to a control year in which no countermeasures were deployed to evaluate the overall effectiveness of the analog and to validate the candidate immune countermeasure strategy. AWO 2023 concluded with the 4th in-mission timepoint conducted in September 2023. Samples for 16 subjects, including blood, saliva, hair, surveys, and PCR data, were all successfully returned from Antarctica to NASA/JSC mid-November 2023. Samples have since been distributed to co-investigators for further processing and analysis. With the completion of the first countermeasure year, preliminary data on the effectiveness of the deep-space protocol is being evaluated, however, no conclusions can be drawn yet until the completion of the second AWO countermeasure year, AWO 2024. AWO 2024 commenced in late-March 2024, with 13 subjects consenting and performing their baseline data collections (BDCs). Unique to the 2024 deployment, NSF lifted certain COVID restrictions and rallied the crewmembers in Punta Arenas, Chile. All NSF activities were transferred to this location and NASA was allowed, for the first time, to perform consent briefings, baseline samplings and training in person. This augment greatly increased the likelihood of success for the overwinter activities.

Cody L Gutierrez↗
NASA NTRSDate not supplied

Validation of Multisystem Countermeasures Protocol for Spaceflight during Antarctica Winter-over at Palmer Station (Palmer Countermeasures)

Stressors associated with spaceflight induce persistent immune compromise in astronauts which increase subclinical latent virus reactivation. In select crews, adverse clinical events have been documented. Antarctica winter-over (AWO) mission most closely reproduces these mission stressors: prolonged deployment, extreme environment, circadian misalignment, isolation, station lifestyle, and personal risk. The US maintains three primary stations in Antarctica: South Pole Station, McMurdo, and Palmer. Previous studies suggest that stations located near the interior of Antarctica (South Pole, McMurdo) have confounding effects on the immune system due to persistent hypobaric hypoxia. We hypothesized that winter-over at a coastal station (Palmer) would be more akin to spaceflight due to its normoxic but still extreme environment. Therefore, AWO at Palmer Station was selected, and validated in a pilot study, as the platform for testing and validating the effectiveness of an immune-restorative countermeasure protocol designed for deep space missions. Specifics include diet modifications, nutritional supplementation (vitamin D, probiotic, etc.), prescribed aerobic and resistive exercise, and a protocol of stress relieving virtual reality exercises. A multitude of biological sample types, including blood, saliva, and hair will be collected in tandem with the countermeasures in order to examine the combined effectiveness of the countermeasures. Samples and logs from subjects will be transported from Palmer Station to Johnson Space Center for further processing and distribution to co-investigators at the end of each winter-over. Extracted samples will be analyzed by appropriate testing platforms (Multiplex, qPCR, ELISA, etc.) to monitor alterations in leukocyte distribution, T cell and NK function, cytokine profiles, reactivation of latent herpesviruses, and nutritional factors. The data collected will be compared to a control year in which no countermeasures were deployed to evaluate the overall effectiveness of the analog and to validate the candidate immune countermeasure strategy. AWO 2023 concluded with the 4th in-mission timepoint conducted in September 2023. Samples for 16 subjects, including blood, saliva, hair, surveys, and PCR data, were all successfully returned from Antarctica to NASA/JSC mid-November 2023. Samples have since been distributed to co-investigators for further processing and analysis. With the completion of the first countermeasure year, preliminary data on the effectiveness of the deep-space protocol is being evaluated, however, no conclusions can be drawn yet until the completion of the second AWO countermeasure year, AWO 2024. AWO 2024 commenced in late-March 2024, with 13 subjects consenting and performing their baseline data collections (BDCs). Unique to the 2024 deployment, NSF lifted certain COVID restrictions and rallied the crewmembers in Punta Arenas, Chile. All NSF activities were transferred to this location and NASA was allowed, for the first time, to perform consent briefings, baseline samplings and training in person. This augment greatly increased the likelihood of success for the overwinter activities.

Cody L Gutierrez↗
NASA NTRS1972

Apollo 15 time and motion study

A time and motion study of Apollo 15 lunar surface activity led to examination of four distinct areas of crewmen activity. These areas are: an analysis of lunar mobility, a comparative analysis of tasks performed in 1-g training and lunar EVA, an analysis of the metabolic cost of two activities that are performed in several EVAs, and a fall/near-fall analysis. An analysis of mobility showed that the crewmen used three basic mobility patterns (modified walk, hop, side step) while on the lunar surface. These mobility patterns were utilized as adaptive modes to compensate for the uneven terrain and varied soil conditions that the crewmen encountered. A comparison of the time required to perform tasks at the final 1-g lunar EVA training sessions and the time required to perform the same task on the lunar surface indicates that, in almost all cases, it took significantly more time (on the order of 40%) to perform tasks on the moon. This increased time was observed even after extraneous factors (e.g., hardware difficulties) were factored out.

Kubis, J. F.↗
NASA NTRS2019

Training, Retention, and Transfer of Data Entry Perceptual and Motor Processes Over Short and Long Retention Intervals

In 2 experiments, subjects trained in a standard data entry task, which involved typing numbers (e.g., 2147) using their right hands. At an initial test (20 min or 6 months after training), subjects completed the standard task, followed by a left-hand variant (typing with their left hands) that involved the same perceptual, but different motoric, processes as the standard task. At a second test (2 days or 8 months after training), subjects completed the standard task, followed by a code variant (translating letters into digits, then typing the digits with their right hands) that involved different perceptual, but the same motoric, processes as the standard task. At test, for each of the three tasks, half the trials were trained numbers (old) and half were new. Repetition priming (faster response times to old than new numbers) was found for each task, with extended delays only slightly decreasing the magnitude of the effect. Repetition priming for the standard task reflects retention of trained numbers, for the left-hand variant reflects transfer of perceptual processes, and for the code variant reflects transfer of motoric processes. There was, thus, evidence for both specificity and generalizability of training data entry perceptual and motoric processes even over very long retention intervals.

transfer↗
NASA NTRS1998

Neural Network and Regression Approximations in High Speed Civil Transport Aircraft Design Optimization

Nonlinear mathematical-programming-based design optimization can be an elegant method. However, the calculations required to generate the merit function, constraints, and their gradients, which are frequently required, can make the process computational intensive. The computational burden can be greatly reduced by using approximating analyzers derived from an original analyzer utilizing neural networks and linear regression methods. The experience gained from using both of these approximation methods in the design optimization of a high speed civil transport aircraft is the subject of this paper. The Langley Research Center's Flight Optimization System was selected for the aircraft analysis. This software was exercised to generate a set of training data with which a neural network and a regression method were trained, thereby producing the two approximating analyzers. The derived analyzers were coupled to the Lewis Research Center's CometBoards test bed to provide the optimization capability. With the combined software, both approximation methods were examined for use in aircraft design optimization, and both performed satisfactorily. The CPU time for solution of the problem, which had been measured in hours, was reduced to minutes with the neural network approximation and to seconds with the regression method. Instability encountered in the aircraft analysis software at certain design points was also eliminated. On the other hand, there were costs and difficulties associated with training the approximating analyzers. The CPU time required to generate the input-output pairs and to train the approximating analyzers was seven times that required for solution of the problem.

Patniak, Surya N.↗
NASA NTRS2021

Trend Detection of Atmospheric Time Series: Incorporating Appropriate Uncertainty Estimates and Handling Extreme Events

This paper is aimed at atmospheric scientists without formal training in statistical theory. Its goal is to, 1) provide a critical review of the rationale for trend analysis of the time series typically encountered in the field of atmospheric chemistry; 2) describe a range of trend-detection methods; and 3) demonstrate effective means of conveying the results to a general audience. Trend detections in atmospheric chemical composition data are often challenged by a variety of sources of uncertainty, which often behave differently to other environmental phenomena such as temperature, precipitation rate, or stream flow, and may require specific methods depending on the science questions to be addressed. Some sources of uncertainty can be explicitly included in the model specification, such as autocorrelation and seasonality, but some inherent uncertainties are difficult to quantify, such as data heterogeneity and measurement uncertainty due to the combined effect of short- and long-term natural variability, instrumental stability, and aggregation of data from sparse sampling frequency. Failure to account for these uncertainties might result in an inappropriate inference of the trends and their estimation errors. On the other hand, the variation in extreme events might be interesting for different scientific questions, for example, the frequency of extremely high surface ozone events and their relevance to human health. In this study we aim to, 1) review trend detection methods for addressing different levels of data complexity in different chemical species; 2) demonstrate that the incorporation of scientifically interpretable covariates can outperform pure numerical curve fitting techniques in terms of uncertainty reduction and improved predictability; 3) illustrate the study of trends based on extreme quantiles that can provide insight beyond standard mean or median based trend estimates; and 4) present an advanced method of quantifying regional trends based on the inter-site correlations of multi-site data. All demonstrations are based on time series of observed trace gases relevant to atmospheric chemistry, but the methods can be applied to other environmental data sets.

Trace gas↗
NASA NTRS1998

Real-Time Reconfigurable Adaptive Speech Recognition Command and Control Apparatus and Method

An adaptive speech recognition and control system and method for controlling various mechanisms and systems in response to spoken instructions and in which spoken commands are effective to direct the system into appropriate memory nodes, and to respective appropriate memory templates corresponding to the voiced command is discussed. Spoken commands from any of a group of operators for which the system is trained may be identified, and voice templates are updated as required in response to changes in pronunciation and voice characteristics over time of any of the operators for which the system is trained. Provisions are made for both near-real-time retraining of the system with respect to individual terms which are determined not be positively identified, and for an overall system training and updating process in which recognition of each command and vocabulary term is checked, and in which the memory templates are retrained if necessary for respective commands or vocabulary terms with respect to an operator currently using the system. In one embodiment, the system includes input circuitry connected to a microphone and including signal processing and control sections for sensing the level of vocabulary recognition over a given period and, if recognition performance falls below a given level, processing audio-derived signals for enhancing recognition performance of the system.

Salazar, George A.↗
NASA NTRS1986

Active controllers and the time duration to learn a task

An active controller was used to help train naive subjects involved in a compensatory tracking task. The controller is called active in this context because it moves the subject's hand in a direction to improve tracking. It is of interest here to question whether the active controller helps the subject to learn a task more rapidly than the passive controller. Six subjects, inexperienced to compensatory tracking, were run to asymptote root mean square error tracking levels with an active controller or a passive controller. The time required to learn the task was defined several different ways. The results of the different measures of learning were examined across pools of subjects and across controllers using statistical tests. The comparison between the active controller and the passive controller as to their ability to accelerate the learning process as well as reduce levels of asymptotic tracking error is reported here.

Repperger, D. W.↗
NASA NTRS1993

A computer-based training system combining virtual reality and multimedia

Training new users of complex machines is often an expensive and time-consuming process. This is particularly true for special purpose systems, such as those frequently encountered in DOE applications. This paper presents a computer-based training system intended as a partial solution to this problem. The system extends the basic virtual reality (VR) training paradigm by adding a multimedia component which may be accessed during interaction with the virtual environment. The 3D model used to create the virtual reality is also used as the primary navigation tool through the associated multimedia. This method exploits the natural mapping between a virtual world and the real world that it represents to provide a more intuitive way for the student to interact with all forms of information about the system.

Stansfield, Sharon A.↗
NASA NTRS2020

PPDIST, global 0.1° daily and 3-hourly precipitation probability distribution climatologies for 1979–2018

We introduce the Precipitation Probability DISTribution (PPDIST) dataset, a collection of global high-resolution (0.1°) observation-based climatologies (1979–2018) of the occurrence and peak intensity of precipitation (P) at daily and 3-hourly time-scales. The climatologies were produced using neural networks trained with daily P observations from 93,138 gauges and hourly P observations (resampled to 3-hourly) from 11,881 gauges worldwide. Mean validation coefficient of determination (R^(2)) values ranged from 0.76 to 0.80 for the daily P occurrence indices, and from 0.44 to 0.84 for the daily peak P intensity indices. The neural networks performed significantly better than current state-of-the-art reanalysis (ERA5) and satellite (IMERG) products for all P indices. Using a 0.1 mm 3 per h threshold, P was estimated to occur 12.2%, 7.4%, and 14.3% of the time, on average, over the global, land, and ocean domains, respectively. The highest P intensities were found over parts of Central America, India, and Southeast Asia, along the western equatorial coast of Africa, and in the intertropical convergence zone.

Hylke E. Beck↗
NASA NTRS1987

Cockpit resource management training

The 6th General Flight Crew Training Meeting held in Montreal in May, 1984 was for most IATA member airlines the first time they had been exposed to what was then a relatively new aspect of flight crew training-resource management training. In reviewing the results of this meeting the IATA Flight Crew Training SubCommittee (FCTSC), which had been responsible for the agenda and the meeting itself, concluded that because very few airlines had implemented a program or even appeared to understand the term resource management, a member airline survey should be conducted and the results analyzed. This presentation shows the results of that survey in a form which can be related to the topics of the workshop.

White, Lawson C.↗
NASA NTRS1994

Effect of resistance training on muscle use during exercise

This study examined the effect of resistance training on exercise-induced contrast shift in magnetic resonance (MR) images. It was hypothesized that a given load could be lifted after training with less muscle showing contrast shift, thereby suggesting less muscle was used to perform the exercise. Nine males trained the left quadriceps femoris (QF) muscle 2 days/wk for 9 wk using 3-6 sets of 12 knee extensions each day. The right QF served as a control. Exercise-induced contrast shifts in MR images evoked by each of three bouts of exercise (5 sets of 10 knee extensions with a load equal to 50, 75, and 100% of the maximum pretraining load that could be lifted for 5 sets of 10 repetitions) were quantified pre- and posttraining. MR image contrast shift was quantified by determining QF cross-sectional area (CSA) showing increased spin-spin relaxation time. One repetition maximum increased 14% in the left trained QF and 7% in the right untrained QF. Left QF CSA increased 5%, with no change in right QSF CSA. Left QF CSA showing contrast shift was less after each bout of the exercise test posttraining. This was also true, to a lesser extent, for the right QF at the higher two loads. The results suggest that short-term resistance training reduces MR image contrast shift evoked by a given effort, thereby reflecting the use of less muscle to lift the load. Because this response was evident in both trained and contralateral untrained muscle, neural factors are suggested to be responsible. The consequence of this adaptation could be to increase 'stress' per unit area of active muscle during the course of training and thereby evoke hypertrophy.

Ploutz, Lori L.↗
NASA NTRS1976

Joint aircraft loading/structure response statistics of time to service crack initiation

A reliability analysis for predicting the statistical distribution of time to fatigue crack initiation for aircraft structures in service is presented. The present analysis utilizes the statistical data of the specimen fatigue tests, the full-scale structure tests, and the statistical dispersion of aircraft service loads. The statistical distribution of the time to fatigue crack initiation of the full-scale structure under laboratory loading spectrum is assumed to be Weibull. The service loads for gust turbulences are modeled as Poisson processes for transport-type aircraft, while the maneuver loads are modeled as compound Poisson processes for fighter and training aircraft. It is found that the statistical distribution of time to fatigue crack initiation for aircraft structures in service is not Weibull and that the prediction on the basis of the Weibull distribution is unconservative, in particular in the early service time.

Yang, J.-N.↗
NASA NTRS1991

Predicting cloud-to-ground lightning with neural networks

A neural network is being trained to predict lightning at Cape Canaveral for periods up to two hours in advance. Inputs consist of ground based field mill data, meteorological tower data, lightning location data, and radiosonde data. High values of the field mill data and rapid changes in the field mill data, offset in time, provide the forecasts or desired output values used to train the neural network through backpropagation. Examples of input data are shown and an example of data compression using a hidden layer in the neural network is discussed.

Barnes, Arnold A., Jr.↗
NASA NTRS1978

Instructor and student pilots' subjective evaluation of a general aviation simulator with a terrain visual system

Ten student pilots were given a 1 hour training session in the NASA Langley Research Center's General Aviation Simulator by a certified flight instructor and a follow-up flight evaluation was performed by the student's own flight instructor, who has also flown the simulator. The students and instructors generally felt that the simulator session had a positive effect on the students. They recommended that a simulator with a visual scene and a motion base would be useful in performing such maneuvers as: landing approaches, level flight, climbs, dives, turns, instrument work, and radio navigation, recommending that the simulator would be an efficient means of introducing the student to new maneuvers before doing them in flight. The students and instructors estimated that about 8 hours of simulator time could be profitably devoted to the private pilot training.

Kiteley, G. W.↗
NASA NTRS2000

The Dynamical Evolution of A Tubular Leonid Persistent Train

The dynamical evolution of the persistent train of a bright Leonid meteor was examined for evidence of the source of the luminosity and the physical conditions in the meteor path. The train consisted of two parallel somewhat diffuse luminous tracks, interpreted as the walls of a tube. A general lack of wind shear along the trail allowed these structures to remain intact for nearly 200 s, from which it was possible to determine that the tubular structure expanded at a near constant 10.5 m/s, independent of altitude between 86 and 97 km. An initial fast decrease of train intensity below 90 km was followed by an increase in intensity and then a gradual decrease at longer times, whereas at high attitudes the integrated intensity was nearly constant with time. These results are compared to a model that describes the dynamical evolution of the train by diffusion, following an initial rapid expansion of the hot gaseous trail behind the meteoroid. The train luminosity is produced by O ((sup 1)S) emission at 557 nm, driven by elevated atomic O levels produced by the meteor impact, as well as chemiluminescent reactions of the ablated metals Na and Fe with O3. Ozone is rapidly removed within the train, both by thermal decomposition and catalytic destruction by the metallic species. Hence, the brightest emission occurs at the edge of the train between outwardly diffusing metallic species and inwardly diffusing O3. Although the model is able to account plausibly for a number of characteristic features of the train evolution, significant discrepancies remain that cannot easily be resolved.

Jenniskens, Peter↗
NASA NTRS1990

Project LOCOST: Laser or Chemical Hybrid Orbital Space Transport

A potential mission in the late 1990s is the servicing of spacecraft assets located in GEO. The Geosynchronous Operations Support Center (GeoShack) will be supported by a space transfer vehicle based at the Space Station (SS). The vehicle will transport cargo between the SS and the GeoShack. A proposed unmanned, laser or chemical hybrid orbital space transfer vehicle (LOCOST) can be used to efficiently transfer cargo between the two orbits. A preliminary design shows that an unmanned, laser/chemical hybrid vehicle results in the fuel savings needed while still providing fast trip times. The LOCOST vehicle receives a 12 MW laser beam from one Earth orbiting, solar pumped, iodide Laser Power Station (LPS). Two Energy Relay Units (ERU) provide laser beam support during periods of line-of-sight blockage by the Earth. The baseline mission specifies a 13 day round trip transfer time. The ship's configuration consist of an optical train, one hydrogen laser engine, two chemical engines, a 18 m by 29 m box truss, a mission-flexible payload module, and propellant tanks. Overall vehicle dry mass is 8,000 kg. Outbound cargo mass is 20,000 kg, and inbound cargo mass is 6,000 kg. The baseline mission needs 93,000 kg of propellants to complete the scenario. Fully fueled, outbound mission mass is 121,000 kg. A regeneratively cooled, single plasma, laser engine design producing a maximum of 768 N of thrust is utilized along with two traditional chemical engines. The payload module is designed to hold 40,000 kg of cargo, though the baseline mission specifies less. A proposed design of a laser/chemical hybrid vehicle provides a trip time and propellant efficient means to transport cargo from the SS to a GeoShack. Its unique, hybrid propulsion system provides safety through redundancy, allows baseline missions to be efficiently executed, while still allowing for the possibility of larger cargo transfers.

Dixon, Alan↗
NASA NTRS2014

Expansion of the Real-time Sport-land Information System for NOAA / National Weather Service Situational Awareness and Local Modeling Applications

The NASA Short-term Prediction Research and Transition (SPoRT) Center in Huntsville, AL (Jedlovec 2013; Ralph et al. 2013; Merceret et al. 2013) is running a real-time configuration of the Noah land surface model (LSM) within the NASA Land Information System (LIS) framework (hereafter referred to as the "SPoRT-LIS"). Output from the real-time SPoRT-LIS is used for (1) initializing land surface variables for local modeling applications, and (2) displaying in decision support systems for situational awareness and drought monitoring at select NOAA/National Weather Service (NWS) partner offices. The SPoRT-LIS is currently run over a domain covering the southeastern half of the Continental United States (CONUS), with an additional experimental real-time run over the entire CONUS and surrounding portions of southern Canada and northern Mexico. The experimental CONUS run incorporates hourly quantitative precipitation estimation (QPE) from the National Severe Storms Laboratory Multi- Radar Multi-Sensor (MRMS) product (Zhang et al. 2011, 2014), which will be transitioned into operations at the National Centers for Environmental Prediction (NCEP) in Fall 2014. This paper describes the current and experimental SPoRT-LIS configurations, and documents some of the limitations still remaining through the advent of MRMS precipitation analyses in the SPoRT-LIS land surface model (LSM) simulations. Section 2 gives background information on the NASA LIS and describes the realtime SPoRT-LIS configurations being compared. Section 3 presents recent work done to develop a training module on situational awareness applications of real-time SPoRT-LIS output. Comparisons between output from the two SPoRT-LIS runs are shown in Section 4, including a documentation of issues encountered in using the MRMS precipitation dataset. A summary and future work in given in Section 5, followed by acknowledgements and references.

Case, Jonathan L.↗