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At least 163 records · Page 9

Understanding Skill in EVA Mass Handling: Empirical Investigation - Volume 2

In this report we describe the details of our empirical protocol effort investigating skill in extravehicular mass handling using NASA's principal mass handling simulator, the precision air bearing floor. Contents of this report include a description of the necessary modifications to the mass handling simulator; choice of task, and the description of an operationally relevant protocol. Our independent variables are presented in the context of the specific operational issues they were designed to simulate. The explanation of our dependent variables focuses on the specific data processing procedures used to transform data from common laboratory instruments into measures that are relevant to a special class of nested control systems (discussed in Volume 1): manual interactions between an individual and the substantial environment. The data reduction is explained in the context of the theoretical foundation described in Volume 1. Finally as a preface to the presentation of the empirical data in Volume 3 of this report series, a set of detailed hypotheses is presented.

Riccio, Gary↗

Understanding Skill in EVA Mass Handling: Empirical Developments and Conclusions - Volume 3

Key attributes of skilled mass handling were identified through an examination of lessons learned by the extravehicular activity operational community. These qualities were translated into measurable quantities. The operational validity of the ground-based investigation was improved by building a device that increased the degrees of freedom of extravehicular mobility unit motion on the Precision Air-Bearing Floor. The results revealed subtle patterns of interaction between motions of an orbital replacement unit mockup and mass handler that should be important for effective performance on orbit. The investigation also demonstrated that such patterns can be measured with a variety of common instruments and under imperfect conditions of observation.

Riccio, Gary E.↗

Team Training and Retention of Skills Acquired Above Real Time Training on a Flight Simulator

Above Real-Time Training (ARTT) is the training acquired on a real time simulator when it is modified to present events at a faster pace than normal. The experiments related to training of pilots performed by NASA engineers (Kolf in 1973, Hoey in 1976) and others (Guckenberger, Crane and their associates in the nineties) have shown that in comparison with the real time training (RTT), ARTT provides the following benefits: increased rate of skill acquisition, reduced simulator and aircraft training time, and more effective training for emergency procedures. Two sets of experiments have been performed; they are reported in professional conferences and the respective papers are included in this report. The retention of effects of ARTT has been studied in the first set of experiments and the use of ARTT as top-off training has been examined in the second set of experiments. In ARTT, the pace of events was 1.5 times the pace in RTT. In both sets of experiments, university students were trained to perform an aerial gunnery task. The training unit was equipped with a joystick and a throttle. The student acted as a nose gunner in a hypothetical two place attack aircraft. The flight simulation software was installed on a Universal Distributed Interactive Simulator platform supplied by ECC International of Orlando, Florida. In the first set of experiments, two training programs RTT or ART7 were used. Students were then tested in real time on more demanding scenarios: either immediately after training or two days later. The effects of ARTT did not decrease over a two day retention interval and ARTT was more time efficient than real time training. Therefore, equal test performance could be achieved with less clock-time spent in the simulator. In the second set of experiments three training programs RTT or ARTT or RARTT, were used. In RTT, students received 36 minutes of real time training. In ARTT, students received 36 minutes of above real time training. In RARTT, students received 18 minutes of real time training and 18 minutes of above real time training as top-off training. Students were then tested in real time on more demanding scenarios. The use of ARTT as top-off training after RTT offered better training than RTT alone or ARTT alone. It is, however, suggested that a similar experiment be conducted on a relatively more complex task with a larger sample of participants. Within the proposed duration of the research effort, the setting up of experiments and trial runs on using ARTT for team training were also scheduled but they could not be accomplished due to extra ordinary challenges faced in developing the required software configuration. Team training is, however, scheduled in a future study sponsored by NASA at Tuskegee University.

Ali, Syed Friasat↗

High Altitude Long Endurance (HALE) Unmanned Aircraft System (UAS): Pilot Knowledge, Skills and Abilities

This report summarizes the initial work accomplished by the ACCESS 5 Human System Integration (HSI) team to identify Unmanned Aircraft System (UAS) Pilot Knowledge, Skill and Ability (KSA), Training and Medical requirements. To derive this information the following tasks were accomplished: a) Mission and Function analyses were performed; b) Applicable FARs and FAA Advisory Circulars (ACs) were reviewed; c) Meetings were conducted with NASA and FAA Human Factors personnel; d) Surveys were completed by ACCESS 5 HSI Working group UA Pilots; e) Coordination meetings were conducted with the ACCESS 5 Policy IPT. The results of these efforts were used to develop a summary of the current qualifications. for an individual to function as a Pilot In Command (PIC) for UAs currently flown by UNITE companies, to develop preliminary Pilot KSAs for each phase of flight, and to delineate preliminary Pilot Training and Medical requirements. These results are to be provided to the Policy IPT to support their development of recommendations for UA Pilot Rating Criteria, training and medical qualifications. It is expected that the initially an instrument rated pilot will be required to serve as the PIC. However, as operational experience is gained, and automation is applied to accomplish various system functions, it is expected that pilot rating criteria could be lessened.

Source record↗

Improving Forecast Skill by Assimilation of Quality Controlled AIRS Version 5 Temperature Soundings

The AIRS Science Team Version 5 retrieval algorithm has been finalized and is now operational at the Goddard DAAC in the processing (and reprocessing) of all AIRS data. The AIRS Science Team Version 5 retrieval algorithm contains two significant improvements over Version 4: 1) Improved physics allows for use of AIRS observations in the entire 4.3 micron CO2 absorption band in the retrieval of temperature profile T(p) during both day and night. Tropospheric sounding 15 micron CO2 observations are now used primarily in the generation of cloud cleared radiances R(sub i). This approach allows for the generation of accurate values of R(sub i) and T(p) under most cloud conditions. 2) Another very significant improvement in Version 5 is the ability to generate accurate case-by-case, level-by-level error estimates for the atmospheric temperature profile, as well as for channel-by-channel error estimates for R(sub i). These error estimates are used for Quality Control of the retrieved products. We have conducted forecast impact experiments assimilating AIRS temperature profiles with different levels of Quality Control using the NASA GEOS-5 data assimilation system. Assimilation of Quality Controlled T(p) resulted in significantly improved forecast skill compared to that obtained from analyses obtained when all data used operationally by NCEP, except for AIRS data, is assimilated. We also conducted an experiment assimilating AIRS radiances uncontaminated by clouds, as done operationally by ECMWF and NCEP. Forecast resulting from assimilated AIRS radiances were of poorer quality than those obtained assimilating AIRS temperatures.

Susskind, Joel↗

Use of Quality Controlled AIRS Temperature Soundings to Improve Forecast Skill

AIRS was launched on EOS Aqua on May 4, 2002, together with AMSU-A and HSB, to form a next generation polar orbiting infrared and microwave atmospheric sounding system. The primary products of AIRS/AMSU-A are twice daily global fields of atmospheric temperature-humidity profiles, ozone profiles, sea/land surface skin temperature, and cloud related parameters including OLR. Also included are the clear column radiances used to derive these products which are representative of the radiances AIRS would have seen if there were no clouds in the field of view. All products also have error estimates. The sounding goals of AIRS are to produce 1 km tropospheric layer mean temperatures with an rms error of 1K, and layer precipitable water with an rms error of 20 percent, in cases with up to 90 percent effective cloud cover. The products are designed for data assimilation purposes for the improvement of numerical weather prediction, as well as for the study of climate and meteorological processes. With regard to data assimilation, one can use either the products themselves or the clear column radiances from which the products were derived. The AIRS Version 5 retrieval algorithm is now being used operationally at the Goddard DISC in the routine generation of geophysical parameters derived from AIRS/AMSU data. A major innovation in Version 5 is the ability to generate case-by-case level-by-level error estimates for retrieved quantities and clear column radiances, and the use of these error estimates for Quality Control. The temperature profile error estimates are used to determine a case-by-case characteristic pressure pbest, down to which the profile is considered acceptable for data assimilation purposes. The characteristic pressure p(sub best) is determined by comparing the case dependent error estimate (delta)T(p) to the threshold values (Delta)T(p). The AIRS Version 5 data set provides error estimates of T(p) at all levels, and also profile dependent values of pbest based on use of a Standard profile dependent threshold (Delta)T(p). These Standard thresholds were designed as a compromise between optimal use for data assimilation purposes, which requires highest accuracy (tighter Quality Control), and climate purposes, which requires more spatial coverage (looser Quality Control). Subsequent research using Version 5 sounding and error estimates showed that tighter Quality Control performs better for data assimilation proposes, while looser Quality Control better spatial coverage) performs better for climate purposes. We conducted a number of data assimilation experiments using the NASA GEOS-5 Data Assimilation System as a step toward finding an optimum balance of spatial coverage and sounding accuracy with regard to improving forecast skill. The model was run at a horizontal resolution of 0.5 degree latitude x 0.67 degree longitude with 72 vertical levels. These experiments were run during four different seasons, each using a different year. The AIRS temperature profiles were presented to the GEOS-5 analysis as rawinsonde profiles, and the profile error estimates (delta)T(p) were used as the uncertainty for each measurement in the data assimilation process.

Susskind, Joel↗

Structured Transition of Wind Tunnel Operations Skills from Government-to Contractor-Managed

In 2004, NASA awarded the Research, Operations, Maintenance, and Engineering (ROME) contract at NASA Langley Research Center to a team led by Jacobs Technology, Inc. A key component of the contract was the transitioning of the five large wind tunnel facilities from NASA managed and NASA or NASA/contractor workforces to fully contractor operated. The contractor would manage daily operations while NASA would continue to develop long-term strategies, make decisions regarding commitment of funds and commitment of facilities, and provide oversight of the contractor's performance. A major challenge would be the transition of knowledge of facility operations and maintenance from the incumbent civil servant workforce to the contractor workforce. While the contract has since been modified multiple times, resulting in a blended NASA/ROME workforce across the facilities, the processes developed and implemented to capture and document facility knowledge from the incumbent subject matter experts, build training and certification programs, and grow individual skills across subject areas and across facilities, are worthy of documentation. This is the purpose of this paper.

Dunn, Steven C.↗

Improve Problem Solving Skills through Adapting Programming Tools

There are numerous ways for engineers and students to become better problem-solvers. The use of command line and visual programming tools can help to model a problem and formulate a solution through visualization. The analysis of problem attributes and constraints provide insight into the scope and complexity of the problem. The visualization aspect of the problem-solving approach tends to make students and engineers more systematic in their thought process and help them catch errors before proceeding too far in the wrong direction. The problem-solver identifies and defines important terms, variables, rules, and procedures required for solving a problem. Every step required to construct the problem solution can be defined in program commands that produce intermediate output. This paper advocates improved problem solving skills through using a programming tool. MatLab created by MathWorks, is an interactive numerical computing environment and programming language. It is a matrix-based system that easily lends itself to matrix manipulation, and plotting of functions and data. MatLab can be used as an interactive command line or a sequence of commands that can be saved in a file as a script or named functions. Prior programming experience is not required to use MatLab commands. The GNU Octave, part of the GNU project, a free computer program for performing numerical computations, is comparable to MatLab. MatLab visual and command programming are presented here.

Shaykhian, Linda H.↗

EVA Skills Training

Dr. Parazynski and a colleague from Extravehicular Activity (EVA), Robotics, & Crew Systems Operations (DX) worked closely to build the EVA Skills Training Program, and for the first time, defined the gold standards of EVA performance, allowing crewmembers to increase their performance significantly. As part of the program, individuals had the opportunity to learn at their own rate, taking additional water time as required, to achieve that level of performance. This focus on training to one's strengths and weaknesses to bolster them enabled the Crew Office and DX to field a much larger group of spacewalkers for the daunting "wall of EVA" required for the building and maintenance of the ISS. Parazynski also stressed the need for designers to understand the capabilities and the limitations of a human in a spacesuit, as well as opportunities to improve future generations of space. He shared lessons learned (how the Crew Office engaged in these endeavors) and illustrated the need to work as a team to develop these complex systems.

Parazynski, Scott↗

Global Gridded Crop Model Evaluation: Benchmarking, Skills, Deficiencies and Implications.

Crop models are increasingly used to simulate crop yields at the global scale, but so far there is no general framework on how to assess model performance. Here we evaluate the simulation results of 14 global gridded crop modeling groups that have contributed historic crop yield simulations for maize, wheat, rice and soybean to the Global Gridded Crop Model Intercomparison (GGCMI) of the Agricultural Model Intercomparison and Improvement Project (AgMIP). Simulation results are compared to reference data at global, national and grid cell scales and we evaluate model performance with respect to time series correlation, spatial correlation and mean bias. We find that global gridded crop models (GGCMs) show mixed skill in reproducing time series correlations or spatial patterns at the different spatial scales. Generally, maize, wheat and soybean simulations of many GGCMs are capable of reproducing larger parts of observed temporal variability (time series correlation coefficients (r) of up to 0.888 for maize, 0.673 for wheat and 0.643 for soybean at the global scale) but rice yield variability cannot be well reproduced by most models. Yield variability can be well reproduced for most major producing countries by many GGCMs and for all countries by at least some. A comparison with gridded yield data and a statistical analysis of the effects of weather variability on yield variability shows that the ensemble of GGCMs can explain more of the yield variability than an ensemble of regression models for maize and soybean, but not for wheat and rice. We identify future research needs in global gridded crop modeling and for all individual crop modeling groups. In the absence of a purely observation-based benchmark for model evaluation, we propose that the best performing crop model per crop and region establishes the benchmark for all others, and modelers are encouraged to investigate how crop model performance can be increased. We make our evaluation system accessible to all crop modelers so that other modeling groups can also test their model performance against the reference data and the GGCMI benchmark.

wheat↗

Assessing the Skill of Chlorophyll Forecasts: Latest Development and Challenges Ahead Using the Case of the Equatorial Pacific

Using a global ocean biogeochemical model combined with a forecast of physical oceanic and atmospheric variables from the NASA Global Modeling and Assimilation Office, we assess the skill of a chlorophyll concentrations forecast in the Equatorial Pacific for the period 2012-2015 with a focus on the forecast of the onset of the 2015 El Nino event. Using a series of retrospective 9-month hindcasts, we assess the uncertainties of the forecasted chlorophyll by comparing the monthly total chlorophyll concentration from the forecast with the corresponding monthly ocean chlorophyll data from the Suomi-National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite (S-NPP VIIRS) satellite. The forecast was able to reproduce the phasing of the variability in chlorophyll concentration in the Equatorial Pacific, including the beginning of the 2015-2016 El Nino. The anomaly correlation coefficient (ACC) was significant (p less than 0.05) for forecast at 1-month (R=0.33), 8-month (R=0.42) and 9-month (R=0.41) lead times. The root mean square error (RMSE) increased from 0.0399 microgram chl L(exp -1) for the 1-month lead forecast to a maximum of 0.0472 microgram chl L(exp -1) for the 9-month lead forecast indicating that the forecast of the amplitude of chlorophyll concentration variability was getting worse. Forecasts with a 3-month lead time were on average the closest to the S-NPP VIIRS data (23% or 0.033 microgram chl L(exp -1)) while the forecast with a 9-month lead time were the furthest (31% or 0.042 microgram chl L(exp -1)). These results indicate the potential for forecasting chlorophyll concentration in this region but also highlights various deficiencies and suggestions for improvements to the current biogeochemical forecasting system. This system provides an initial basis for future applications including the effects of El Nino events on fisheries and other ocean resources given improvements identified in the analysis of these results.

El Nin↗

Prediction Skill of U.S. Flash Droughts in Subseasonal Experiment (SubX) Model Hindcasts

Droughts that establish themselves over a short period of time (weeks to a few months), referred to as flash droughts, can have devastating impacts on agriculture, water resources, and ecosystems. The ability to predict such droughts in advance would greatly enhance our preparation for them and potentially reduce their impacts. The sub-seasonal time scale at which flash droughts occur emphasizes the importance of producing forecasts at weekly or finer intervals that extend beyond the numerical weather prediction time frame. Here we assess the ability of eight global forecast systems, each participating in the Sub-seasonal Experiment project (SubX), to predict key features associated with rapidly developing droughts over the United States during the last two decades. MERRA2 reanalysis is used as observations. Prediction skill for temperature and precipitation anomalies during these events is limited to the first 1-2 weeks after initialization for most hindcasts. However, there are some hindcasts in which large anomalies are well predicted 3-4 weeks or more in advance. The physical mechanisms that are key to the development of surface anomalies, including quasi-stationary atmospheric waves, were also evaluated. Most hindcasts were unable to capture the development or progression of such drought-inducing circulation features more than 1-2 weeks in advance.

Deangelis, Anthony M.↗

Generalizable Skills and Knowledge for Exploration Missions

This report describes research conducted under Cooperative Agreement 80NSSC18K0042 for the Human Factors and Behavioral Performance Element, Human Research Program, located at the National Aeronautics and Space Administration’s (NASA) Johnson Space Center. The research addresses the Risk of Inadequate Mission, Process, and Task Design and the Risk of Performance Errors Due to Training Deficiencies during exploration-class space missions by identifying the tasks that will be conducted by human crew during an expedition to Mars and the abilities, skills, and knowledge that will be required of crew members. By focusing on an expedition to Mars, we have considered the extremes of what is possible for human space exploration during the first half of the 21st Century and accommodated the human requirements for missions to asteroids, Cis-Lunar orbit, and a return to the Moon.

Stuster, Jack↗

Generalizability of Manual Control Skills between Control Tasks of Varying Difficulty

This paper presents the results of an experiment that was performed at NASA Ames Research Center using 18 participants in two different groups who trained a task for ten days, with the goal of identifying how skill generalization would occur between two similar tasks of varying difficulty. A cybernetic approach was used. The first group was trained in a simple one-dimensional tracking task and transferred to a difficult two-dimensional tracking task. For the second group, this was reversed. Training with a simple task before transferring to the difficult task resulted in a slower convergence to final performance. However, it did allow participants to start with a better initial performance in the difficult task. Furthermore, after training with a simple task, participants controlled with a higher gain and generated lower lead time constants. However, possibly due to the number of participants, this experiment did not find any statistical evidence to support the conclusion that training with a simple task version helps in learning a more complex task.

Pieters, Marc A.↗

Impasse-Driven Tutoring for Reactive Skill Acquisition

We introduce a new approach to intelligent tutoring in performance-oriented training environments based on a method called situated plan attribution. The aim of this method is to provide contextualized tutoring for procedural tasks requiring reactive, goal-oriented skills. We use the term plan attribution instead of plan recognition because it does not assume that the problem solver is consciously executing plan. We avoid some of the pitfalls of other popularly used methods, i.e., model tracing and procedure net grammars, by selectively using an expert cognitive model to generate advice after detecting a problem solving impasse. The tutor attributes a set of plans to the student based on a task description. Each action is evaluated with respect to: the student's attributed plans, its actual effects on the training device, and the contextualized goals associated with the plans.

Johnson, W. Lewis↗

Assessing the Skills of a Seasonal Forecast of Chlorophyll in the Global Pelagic Oceans

While forecasts of atmospheric variables, and to a lesser degree ocean circulation, are relatively common, the forecast of biogeochemical conditions is still in its infancy. Using a dynamical ocean biogeochemical forecast forced by seasonal forecasts of atmospheric and physical ocean variables, we produce seasonal predictions of chlorophyll concentration at the global scale. Results show significant Anomaly Correlation Coefficients (ACCs) for the majority of regions (11 out of the 12 regions for the 1-month lead forecast). Root mean square errors are smaller (<0.05μg chlorophyll (chl) L−1) in the Equatorial regions compared to the higher latitudes(range from 0.05 up to 0.13 μg chl L−1). The forecast for all regions except three (North Atlantic, South Pacific and North Indian) are within the Semi-Interquartile Range of the satellite chlorophyll concentration (Suomi-National Polar-orbiting Partnership (NPP), 27.9%). This suggests the potential for skillful global biogeochemical forecasts on seasonal timescales of chlorophyll, primary production and harmful algal blooms that could support fisheries management and other applications.

ocean biogeochemistry↗

Starfleet Medical: Knowledge Skills and Abilities of Crew Medical Officers on Exploration Missions

Anticipating the medical skills necessary for deep space exploration missions is one of the greatest space medicine challenges. Spontaneous medical events unrelated to the space environment for which resourcing is severely limited. Novel medical events in the space environment for which are unknown unknowns. Exploration missions are remote, long duration, and low resource which increases the risk and consequences of medical events and require increased crew autonomy.

Levin, DR↗