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NASA NTRS2018

Methodology and Application of HPC I/O Characterization with MPIProf and IOT

Combining the strengths of MPIProf and IOT, an efficient and systematic method is devised for I/O characterization at the per-job, per-rank, per-file and per-call levels of HPC programs running on the NASA Advanced Supercomputing Center. This method is applied to answer four I/O questions in this paper. A total of 13 MPI programs and 15 cases, ranging from 24 to 5968 ranks, are analyzed to establish the I/O landscape from answers to the four questions. Four of the 13 programs use MPI I/O and the behavior of their collective writes depends on the specific implementation of the MPI library used. The SGI MPT library, the prevailing MPI library for our systems, was found to gather small writes from a large number of ranks to perform larger writes by a small subset of collective buffering ranks. The number of collective buffering ranks invoked by MPT depends on the Lustre stripe count and the number of nodes used for the run. A demonstration of varying the stripe count to achieve double-digit speedup of one program's I/O was presented. Another program, which concurrently opens private files by all ranks and could potentially create a heavy load on the Lustre servers, was identified. The ability to systematically characterize I/O for a large number of programs running on a supercomputer, seek I/O optimization opportunity and identify programs that could cause a high load and instability on the filesystems is important for pursuing exascale in a real production environment.

Characterization↗
NASA NTRS2013

The Interplanetary Network Supplement to the Fermi Gbm Catalog of Cosmic Gamma-Ray Bursts

We present Interplanetary Network (IPN) data for the gamma-ray bursts in the first Fermi Gamma-Ray BurstMonitor (GBM) catalog. Of the 491 bursts in that catalog, covering 2008 July 12 to 2010 July 11, 427 wereobserved by at least one other instrument in the nine-spacecraft IPN. Of the 427, the localizations of 149 could beimproved by arrival time analysis (or triangulation). For any given burst observed by the GBM and one otherdistant spacecraft, triangulation gives an annulus of possible arrival directions whose half-width varies betweenabout 0. 4 and 32, depending on the intensity, time history, and arrival direction of the burst, as well as the distancebetween the spacecraft. We find that the IPN localizations intersect the 1 GBM error circles in only 52 of thecases, if no systematic uncertainty is assumed for the latter. If a 6 systematic uncertainty is assumed and added inquadrature, the two localization samples agree about 87 of the time, as would be expected. If we then multiply theresulting error radii by a factor of three, the two samples agree in slightly over 98 of the cases, providing a goodestimate of the GBM 3 error radius. The IPN 3 error boxes have areas between about 1 arcmin2 and 110 deg2,and are, on the average, a factor of 180 smaller than the corresponding GBM localizations. We identify two burstsin the IPNGBM sample that did not appear in the GBM catalog. In one case, the GBM triggered on a terrestrialgamma flash, and in the other, its origin was given as uncertain. We also discuss the sensitivity and calibration ofthe IPN.

INTERPLANET↗
NASA NTRS2015

Search for Sugars and Related Compounds in Residues Produced from the UV Irradiation of Astrophysical Ice Analogs

A large variety and number of organic compounds of prebiotic interest have been detected in meteorites. Among them, one sugar (dihydroxyacetone) as well as several sugar acids and sugar alcohols have been detected in Murchison and Murray [1]. Their presence in meteorites, along with amino acids, amphiphiles, and nucleobases [2-6], strongly suggests that molecules essential to life can form abiotically under astrophysical conditions. This hypothesis is supported by laboratory studies on the formation of complex organic molecules from the ultraviolet (UV) irradiation of astrophysical ice analogs (H2O, CO, CO2, CH3OH, CH4, NH3, etc.). These studies show that the organic residues recovered at room temperature after the UV irradiation of such ice mixtures contain amino acids [7-9], amphiphiles [4], nucleobases [10-13], and other organic complex organic compounds [14-16]. However, no systematic search for the presence of sugars, sugar acids, and sugar alcohols in laboratory residues have been reported to date, despite the fact that those compounds are involved in a large number of biological processes. Only a limited number of small (less than or equal to 3 carbon atoms) sugar derivatives such as glycerol and glyceric acid have been detected in residues [14-16]. In this work, we show results obtained from the systematic search for sugars and sugar-related compounds in organic residues produced from the UV irradiation of simple CH3OH and H2O+CH3OH ices, and more astrophysically relevant ice mixtures containing H2O, CH3OH, CO, and NH3. The results are compared with measurements of sugars and related compounds in primitive meteorites.

Murchison and Murray↗
NASA NTRS2018

Biocene 2018 - Welcome to the Period of New Life

Biocene is the period of new life. When our descendants look back at this period in time, they will see evidence, in the geologic and electronic record, of anthropic climate change, growing population, and scarcity of resources. But they will also see the rebirth of human ingenuity as we overcame the challenges that faced us through nature-inspired exploration. The Periodic Table of Life (PeTaL) is a proposed tool and open source framework that uses artificial intelligence to aid in the systematic inquiry of biology for its application to human systems. This presentation defines the PeTaL concept and workflow. Biomimicry, biophysics, biomimetics, bionics and numerous other terms refer to the use of biology and biological principles to inform practices in other disciplines. For the most part, the domain of inquiry in these fields have been confined to extant biological models with the proponents of biomimicry often citing the evolutionary success of extant organisms relative to extinct ones. The primary objective of this paper is to expand the domain of inquiry for human processes that seek to model those that are, were or could be found in nature with examples that relate to the field of aerospace and to spur development of tools that can work together to accelerate the use of artificial intelligence in problem solving. Specifically specialized fields such as paleomimesis, anthropomimesis and physioteleology are proposed in conjunction with artificial evolution. Blockchain technology may be vital in allowing open source design tools such as PeTaL to democratize design and yet protect intellectual property. The overarching philosophy outlined here can be thought of as physiomimetics, a holistic and systematic way of learning from natural history. The backbone of PeTaL integrates an unstructured database with an ontological model consisting of function, morphology, environment, state of matter and ecosystem. Tools include text classification, thesaurus, data visualization, and analysis. Applications of PeTaL include guiding human space exploration, understanding human and geological history, and discovering new or extinct life.

Biocene↗
NASA NTRS2018

PYSAT: Python Satellite Data Analysis Toolkit

A common problem in space science data analysis is combining complementary data sources that are provided and analyzed in different formats and programming languages. The Python Satellite Data Analysis Toolkit (pysat) addresses this issue by providing an open source toolkit that implements the general process of space science data analysis, from beginning to end, in an instrumentindependent manner. This toolkit uses an Instrument object that enables systematic analysis of science data from a variety of platforms within a single interface. Basic functions such as downloading, loading, and cleaning are included for all supported instruments. Common analysis routines are also included, which are instrument and data source independent. A nanokernel is used to provide instrument independence, it is attached to the Instrument object and mediates the systematic and arbitrary modification of loaded data. Pysat uses the nanokernel to improve the rigor of time series analysis, support onthefly orbit determination, and cleanly span file breaks. Pysat's functions and higherlevel scientific analysis features are validated through the use of unit testing. Further adoption by the community provides a set of scientific results produced by a common core, constituting a distributed heritage that supports the validity of the underlying processing and scientific output. These features are used to demonstrate consistency between derived electron density profiles and measured ion drifts, particularly downward ion drifts in the afternoon hours during extreme solar minimum. Pysat builds upon open source Python software that is freely available and encourages communitydriven development.

Stoneback, R.A.↗
NASA NTRS2019

Planetary Entry Vehicle Prototyping Using Cubesats (or How to Progress on a Shoe-String Budget and Hope to Play with the Big Guys): The Micro Return Capsule (MIRCA)

Imagine standing on the surface of an alien planet or satellite. High in the sky, a soft breeze is interrupted by the whistling sound of a tiny probe sent from Earth to study the atmosphere, or to land on some high-value target on the surface. Now imagine that this probe is followed by a dozen others, all entering in distributed locations throughout the geographic landscape. These probes are systematically and methodically being released from an orbiting spacecraft, perhaps having arrived months in advance. Or maybe the probes themselves are released systematically months in advance by and approaching mother-ship. Although probes have been sent to celestial neighbors before, what is unique is that these new vehicles had their genesis on the highly popular Cubesat specification… My dream is to make spaceflight so mundane, we can actually routinely leave the bounds of our planet to explore en masse our solar system. For that, we must create systems that allow us to bring space exploration within the realm of our everyday lives. No longer exquisite systems but just good enough, where failure is an option … and a new opportunity.

Esper, Jaime↗
NASA NTRS2018

CALIPSO IIR Version 2 Level 1b Calibrated Radiances: Analysis and Reduction of Residual Biases in the Northern Hemisphere

Version 2 of the Level 1b calibrated radiances of the Imaging Infrared Radiometer (IIR) on board the Cloud-Aerosol Lidar and Infrared Satellite Observation (CALIPSO) satellite has been released recently. This new version incorporates corrections of small but systematic seasonal calibration biases previously revealed in Version 1 data products mostly north of 30° N. These biases – of different amplitudes in the three IIR channels 8.65 µm (IIR1), 10.6 µm (IIR2), and 12.05 µm (IIR3) – were made apparent by a striping effect in images of IIR inter-channel brightness temperature differences (BTDs) and through seasonal warm biases of nighttime IIR brightness temperatures in the 30–60° N latitude range. The latter were highlighted through observed and simulated comparisons with similar channels of the Moderate Resolution Imaging Spectroradiometer (MODIS) on board the Aqua spacecraft. To characterize the calibration biases affecting Version 1 data, a semi-empirical approach is developed, which is based on the in-depth analysis of the IIR internal calibration procedure in conjunction with observations such as statistical comparisons with similar MODIS/Aqua channels. Two types of calibration biases are revealed: an equalization bias affecting part of the individual IIR images and a global bias affecting the radiometric level of each image. These biases are observed only when the temperature of the instrument increases, and they are found to be functions of elapsed time since night-to-day transition, regardless of the season. Correction coefficients of Version 1 radiances could thus be defined and implemented in the Version 2 code. As a result, the striping effect seen in Version 1 is significantly attenuated in Version 2. Systematic discrepancies between nighttime and daytime IIR–MODIS BTDs in the 30–60° N latitude range in summer are reduced from 0.2 K in Version 1 to 0.1 K in Version 2 for IIR1–MODIS29. For IIR2–MODIS31 and IIR3–MODIS32, they are reduced from 0.4 K to close to zero, except for IIR3–MODIS32 in June, where the night-minus-day difference is around −0.1 K.

Garnier, Anne↗
NASA NTRS2019

Validation of Regional CO2 Concentrations in the ECMWF Real-Time Analysis and Carbon-Tracker Reanalysis with Airborne Observations from ACT-A Field Campaign

Through verifying against hundreds of hours of airborne in-situ measurements from the NASA-sponsored Atmospheric Carbon and Transport – America (ACT-A) field campaign, this study systematically examines the regional uncertainties and biases of the carbon dioxide (CO2) concentrations from two of the state-of-the-art global analysis products, namely the real-time analysis from the European Center (EC) for Medium Range Forecasting and NOAA’s near real-time Carbon Tracker (CT) reanalysis. It is found that both the EC and CT-NRT analyses agree reasonably well with the independent ACT-A flight-level CO2 measurements in the free troposphere but the uncertainties are considerably larger in the boundary layer during both the summer months of 2016 and the winter months of 2017. There are also strong variabilities in accuracy and bias between seasons, and across three different subregions in the United States (Mid-Atlantic, Midwest and South). Overall, the analysis uncertainties of the EC and CT-NRT analyses in terms of root-mean square deviations against airborne data are comparable to each other, both of which are between 1-2 ppm in the free troposphere but can be as large as 10 ppm near the surface, which are grossly consistent with the difference between the two analyses. The current study not only provides systematic uncertainty estimates for both analysis products over North America but also demonstrated that these two independent estimates can be used to approximate the overall regional CO2 analysis uncertainties. Both statistics are important in future studies in quantifying the uncertainties of regional carbon concentration and flux estimates, as well as in assessing the impact of regional transport through more refined regional modeling and analysis systems.

Chen, Hans W.↗
NASA NTRS2010

Kepler Instrument Performance: An In-Flight Update

The Kepler Mission is designed to detect the 80 parts per million (ppm) signal from an Earth-Sun equivalent transit. Such precision requires superb instrument stability on time scales up to 2 days and systematic error removal to better than 20 ppm. The sole scientic instrument is the Photometer, a 0.95 m aperture Schmidt telescope that feeds the 94.6 million pixel CCD detector array, which contains both Science and Fine Guidance Sensor (FGS) CCDs. Since Kepler's launch in March 2009, we have been using the commissioning and science operations data to characterize the instrument and monitor its performance. We find that the in-flight detector properties of the focal plane, including bias levels, read noise, gain, linearity, saturation, FGS to Science crosstalk,and video crosstalk between Science CCDs, are essentially unchanged from their pre-launch values. Kepler'sunprecedented sensitivity and stability in space have allowed us to measure both short- and long- term effects from cosmic rays, see interactions of previously known image artifacts with starlight, and uncover several unexpected systematics that affect photometric precision. Based on these results, we expect to attain Kepler's planned photometric precision over 90% of the field of view.

CCD↗
NASA NTRS2019

Hybrid RANS/LES Simulation of Jet Surface Interaction Noise

NASA’s Commercial Supersonic Technology (CST) project has formulated a technical challenge to design a quiet propulsion system for a low boom supersonic aircraft that meets Federal Aviation Authority’s airport noise regulations with sufficient margin. Several proposed configurations take advantage of shielding from the wing or other air-frame components. Development of carefully validated computational tools are necessary for critically evaluating installation concepts that are currently being proposed to meet the technical challenge. Semi-empirical models that predict the noise reduction potential of arbitrary shielding surfaces are yet to mature. Another key challenge is the systematic assessment of additional noise from the interaction between high speed jet turbulence and a surface in it’s vicinity. As a first step towards predicting noise reduction due to radical installation concepts from first principles, we simulate the noise generated by a high speed turbulent round jet near a simple planar surface. Detailed comparisons are made with a dedicated experiment conducted at NASA’s Glenn Research Center. Sensitivity of far-field noise predictions to grid resolution is systematically documented. A permeable Ffowcs Williams Hawkings (FWH) surface enclosing both the jet and the shielding surface is used to predict far-field noise from the simulated flowfield. Details of the structured overset grids, numerical discretization, and turbulence model are provided. Near-field comparisons to PIV data and far-field comparisons to microphone array measurements are discussed. Excellent agreement for an initial validation study on an isolated free round jet was obtained and the findings were utilized in the jet surface interaction study. The split between shielded and reflected side of the microphone array was captured with good agreement, as well as the peak in the noise spectra due to scattering of turbulent energy into sound by the trailing edge of the surface.

Stich, Gerrit-Daniel↗
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 NTRS2020

El Niño Related Tropical Land Surface Water and Energy Response in MERRA-2

Though El Niño events each have distinct evolutionary character they typically provide systematic large scale forcing for warming and increased drought frequency across the tropical continents. We assess this response in the MERRA-2 reanalysis and in a ten-member model AMIP ensemble. The lagged response (3-4 months) of mean tropical land temperature to El Niño warming in the Pacific Ocean is well represented. MERRA-2 reproduces the patterns of precipitation in the tropical regions, while the AMIP ensemble reproduces some regional responses better than others. Model skill is dependent on event forcing strength and temporal proximity to the peak of the sea surface warming. A composite approach centered on maximum Niño3.4 SSTs and lag relationships to energy fluxes and transports is used to identify mechanisms supporting tropical land warming. The composite necessarily moderates weather scale variability of the individual events, while retaining the systematic features across all events. We find that that reduced continental upward motions lead to reduced cloudiness and more shortwave radiation at the surface, as well as reduced precipitation. The increased shortwave heating at the land surface, along with reduced soil moisture leads to warmer surface temperature, more sensible heating and warming of the lower troposphere. While the composite provides a broad picture of the mechanisms governing the hydrologic response to El Niño forcing, the regional and temporal response in any given event can be quite variable. The 2015-16 El Niño, one of the strongest events, demonstrates some of the forced response noted in the composite, but with shifts in the evolution that depart from the composite, demonstrating the limitations of the composite and individuality of El Niño.

Michael G Bosilovich↗
NASA NTRS2020

Effects of Long-Duration Space Flight on Training Retention and Transfer

The space environment imposes on the astronaut crew significant physiological, psycho-social, and cognitive loads that can not be replicated on the ground. These loads likely impact crew performance. To date, no systematic data collection has taken place to understand the effects of such loads on crew members ability to retain trained knowledge and skills, and to transfer such knowledge and skills to novel situations. The research described here was originally requested by HRP management to be the first such study to systematically collect data on the effects of long duration space flight on training retention and transfer. Because current theories of retention and transfer are based on results obtained in university laboratories using undergraduate students as research participants, and because crew time in space is very expensive, this study was designed to compare the performance of 4 groups of subjects: crew members in space, crew members on the ground, crew-like subjects, and university undergraduate students. Results from the ground-phase of the study reported here demonstrate that crew members performance under cognitive load can not be predicted from the performance of university undergraduate students. It is still an open question the extent to which crew members cognitive performance in space can be predicted from the performance of crew members on the ground.

Barshi, Immanuel↗
NASA NTRS2012

Methods for Detection and Correction of Sudden Pixel Sensitivity Drops

PDC 8.0 includes implementation of a new algorithm to detect and correct step discontinuities appearing in roughly one of every twenty stellar light curves during a given quarter. An example of such a discontinuity in an actual light curve is shown in fig. 1. The majority of such discontinuities are believed to result from high-energy particles (either cosmic or solar in origin) striking the photometer and causing permanent local changes (typically -0.5% in summed apertures) in quantum efficiency, though a partial exponential recovery is often observed. Since these features, dubbed sudden pixel sensitivity dropouts (SPSDs), are uncorrelated across targets they cannot be properly accounted for by the current detrending algorithm. PDC de-trending is based on the assumption that features in flux time series are due either to intrinsic stellar phenomena or to systematic errors and that systematics will exhibit measurable correlations across targets. SPSD events violate these assumptions and their successful removal not only rectifies the flux values of affected targets, but demonstrably improves the overall performance of PDC de-trending.

Kolodziejczak, Jeffery↗
NASA NTRS2020

The GGCMI Phase 2 Experiment: Global Gridded Crop Model Simulations Under Uniform Changes in CO2, Temperature, Water, and Nitrogen Levels (Protocol Version 1.0)

Concerns about food security under climate change motivate efforts to better understand future changes in crop yields. Process-based crop models, which represent plant physiological and soil processes, are necessary tools for this purpose since they allow representing future climate and management conditions not sampled in the historical record and new locations to which cultivation may shift. However, process-based crop models differ in many critical details, and their responses to different interacting factors remain only poorly understood. The Global Gridded Crop Model Intercomparison (GGCMI) Phase 2 experiment, an activity of the Agricultural Model Intercomparison and Improvement Project (AgMIP), is designed to provide a systematic parameter sweep focused on climate change factors and their interaction with overall soil fertility, to allow both evaluating model behavior and emulating model responses in impact assessment tools. In this paper we describe the GGCMI Phase 2 experimental protocol and its simulation data archive. A total of 12 crop models simulate five crops with systematic uniform perturbations of historical climate, varying CO2, temperature, water supply, and applied nitrogen (“CTWN”) for rainfed and irrigated agriculture, and a second set of simulations represents a type of adaptation by allowing the adjustment of growing season length. We present some crop yield results to illustrate general characteristics of the simulations and potential uses of the GGCMI Phase 2 archive. For example, in cases without adaptation, modeled yields show robust decreases to warmer temperatures in almost all regions, with a nonlinear dependence that means yields in warmer baseline locations have greater temperature sensitivity. Inter-model uncertainty is qualitatively similar across all the four input dimensions but is largest in high-latitude regions where crops may be grown in the future.

GGCMI↗
NASA NTRS2020

Solar Contamination in Extreme-precision Radial-velocity Measurements: Deleterious Effects and Prospects for Mitigation

Solar contamination, due to moonlight and atmospheric scattering of sunlight, can cause systematic errors in stellar radial velocity (RV) measurements that significantly detract from the ~10 cm/s sensitivity required for the detection and characterization of terrestrial exoplanets in or near habitable zones of Sun-like stars. The addition of low-level spectral contamination at variable effective velocity offsets introduces systematic noise when measuring velocities using classical mask-based or template-based cross-correlation techniques. Here we present simulations estimating the range of RV measurement error induced by uncorrected scattered sunlight contamination. We explore potential correction techniques, using both simultaneous spectrometer sky fibers and broadband imaging via coherent fiber imaging bundles, that could reliably reduce this source of error to below the photon-noise limit of typical stellar observations. We discuss the limitations of these simulations, the underlying assumptions, and mitigation mechanisms. We also present and discuss the components designed and built into the NEID (NN-EXPLORE Exoplanet Investigations with Doppler spectroscopy) precision RV instrument for the WIYN 3.5m telescope, to serve as an ongoing resource for the community to explore and evaluate correction techniques. We emphasize that while “bright time” has been traditionally adequate for RV science, the goal of 10 cm/s precision on the most interesting exoplanetary systems may necessitate access to darker skies for these next generation instruments.

Arpita Roy↗
NASA NTRSDate not supplied

A Flexible Multibody Approach to Space Launch System Liftoff Pad Separation with Umbilical Disconnect

A flexible multibody dynamic framework is applied to the Space Launch System (SLS) liftoff Coupled Loads Analysis (CLA), enabling computational efficiencies and systematic inclusion of components and various nonlinearities. The objective of this work is to simulate the SLS liftoff transient pad separation event inclusive of umbilical disconnects. The vehicle stacking preloads and cryogenically induced preloads, due to the fueling of the Core Stage (CS), are integrated via specialized deformed coupling procedure to ensure full capture of the liftoff transient event. The Vehicle Stabilizer System (VSS) hydraulic struts are nonlinear and provide amplitude dependent damping, significantly contributing to the liftoff transient event. Ground Extensible Columns (EC) provide additional stiffness and preloads on the Mobile Launcher (ML), also significantly contributing to the liftoff transient. An advanced Henkel-Mar algorithm, with separation and re-contact, thus tracking the potential post separation re-contact between the booster aft skirt and ML, the umbilicals and vehicle, and ground EC separation. For this system level nonlinear dynamic simulation, the flexible multibody framework provides a systematic approach for the addition of component specific algorithms to enforce nonlinearities. This multibody framework is similar to an object-oriented programming language integrating classes of associated subroutines. As such, the complexities associated with the nonlinear CLA are greatly reduced, facilitating simplified bookkeeping as well as accelerating the execution of the nonlinear time-domain simulations.

Joel W Sills Jr.↗
NASA NTRS2020

Effects of Long-Duration Space Flight on Training Retention and Transfer

The space environment imposes on the astronaut crew significant physiological, psycho-social, and cognitive loads that can not be replicated on the ground. These loads likely impact crew performance. To date, no systematic data collection has taken place to understand the effects of such loads on crew members’ ability to retain trained knowledge and skills, and to transfer such knowledge and skills to novel situations. The research described here was originally requested by HRP management to be the first such study to systematically collect data on the effects of long duration space flight on training retention and transfer. Because current theories of retention and transfer are based on results obtained in university laboratories using undergraduate students as research participants, and because crew time in space is very expensive, this study was designed to compare the performance of 4 groups of subjects: crew members in space, crew members on the ground, crew-like subjects, and university undergraduate students. Results from the ground-phase of the study reported here demonstrate that crew members’ performance under cognitive load can not be predicted from the performance of university undergraduate students. It is still an open question the extent to which crew members’ cognitive performance in space can be predicted from the performance of crew members on the ground.

training↗