SEARCH · Engineering Papers
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Human psychomotor performance measurements in rotating environments, using Langley complex coordinator and decision response time devices
Human capabilities such as dexterity, manipulability, and tactile perception are unique and render the hand as a very versatile, effective and a multipurpose tool. This is especially true for unknown environments such as the EVA environment. In the microgravity environment interfaces, procedures, and activities are too complex, diverse, and defy advance definition. Under these conditions the hand becomes the primary means of locomotion, restraint, and material handling. Facilitation of these activities, with simultaneous protection from the cruel EVA environment are the two, often conflicting, objectives of glove design. The objectives of this study was (1) to assess the effects of EVA gloves at different pressures on human hand capabilities, (2) to devise a protocol for evaluating EVA gloves, (3) to develop force time relations for a number of EVA glove pressure combinations, and (4) to evaluate two types of launch and entry suit gloves. The objectives were achieved through three experiments. The experiments for achieving objectives 1, 2, and 3 were performed in the glove box in building 34. In experiment 1 three types of EVA gloves were tested at five pressure differentials. A number of performance measures were recorded. In experiment 2 the same gloves as in experiment 1 were evaluated in a reduced number of pressure conditions. The performance measure was endurance time. Six subjects participated in both the experiments. In experiment 3 two types of launch and entry suit gloves were evaluated using a paradigm similar to experiment 1. Currently the data is being analyzed. However for this report some summary analyses have been performed. The results indicate that a) With EVA gloves strength is reduced by nearly 50 percent, b) performance decrements increase with increasing pressure differential, c) TMG effects are not consistent across the three gloves tested, d) some interesting gender glove interactions were observed, some of which may have been due to the extent (or lack of) fit of the glove to the hand, and e) differences in performance exist between partial pressure suit glove and full pressure suit glove, especially in the unpressurized condition.
The precision of the model of pattern motion analysis put forth by Adelson and Movshon (1982) who proposed that humans determine the direction of a moving plaid (the sum of two sinusoidal gratings of different orientations) in two steps is qualitatively examined. The volocities of the grating components are first estimated, then combined using the intersection of constraints to determine the velocity of the plaid as a whole. Under the additional assumption that the noise sources for the component velocities are independent, an approximate expression can be derived for the precision in plaid direction as a function of the precision in the speed and direction of the components. Monte Carlo simulations verify that the expression is valid to within 5 percent over the natural range of the parameters. The expression is then used to predict human performance based on available estimates of human precision in the judgment of single component speed. Human performance is predicted to deteriorate by a factor of 3 as half the angle between the wavefronts (theta) decreases from 60 to 30 deg, but actual performance does not. The mean direction discrimination for three human observers was 4.3 plus or minus 0.9 deg (SD) for theta = 60 deg and 5.9 plus or minus 1.2 for theta = 30 deg. This discrepancy can be resolved in two ways. If the noises in the internal representations of the component speeds are smaller than the available estimates or if these noises are not independent, then the psychophysical results are consistent with the Adelson-Movshon hypothesis.
Over the past decades, various technologies have been developed for electric grid operations to support clean energy, meet rising electricity demands, and address infrastructure concerns. However, the human factors aspect is often overlooked during rapid integration. Questions persist about how these technologies impact human performance. Simulators play a critical role in supporting investigation of human factors design concepts and conducting comprehensive usability testing to evaluate human performance and assess human reliability. This paper aims to address human factors research simulator requirements and conduct a comparative study of six different simulators. A detailed evaluation reveals that the evaluated simulators lack the ability to customize user interfaces. Additionally, their user interface designs do not fulfill the basic human factors design principles, potentially leading to increased response variability and reduced statistical power when conducting controlled experimental research. In the future, it is essential to develop scripting tools to integrate customizable user interfaces and simulation models, ensuring meeting research requirements.
The United States' fleet of nuclear power plants (NPPs) have exceeded their original 40-year licenses and many are seeking license renewals to continue operations into the future. To support continued operation the Department of Energy's (DOE) Light Water Reactor Sustainability Program (LWRS) provides support for utilities to maintain and upgrade their power production capabilities. Control room modernization is one focus area, which aims to modernization the analog control rooms with digital controls and human-system interfaces (HSIs). The Turbine Control System (TCS) is a non-safety related system undergoing modernization efforts at multiple plants and utilities. Considerable human factors research efforts, comprised of expert reviews and operator in the loop studies were performed to develop human factors compliant and usable TCS. This report documents the final phase of the human factors engineering program used to design and validate the new digital TCS. According to the NUREG-0711 review guide, one of the last steps of human factors engineering program prior to implementation is human factors validation. This report details the method, results and conclusions from the human factors validation study of a collaborating utilities TCS slated to be implemented in one of their plants. One control room team consisting of two control room supervisors and two reactor operators participated in the validation. All team members had participated in the BNP TCS training program foregoing the TCS validation. Performance measures included task performance, situation awareness and workload, expert observation of any negative influences of human-system interface features on control room team performance, and interviews with the participating operators. Performance criteria were based on the performance scores and the topics identified by interviews and expert observations. The results showed that the crew using the new TCS clearly could achieve their overall objectives in the test scenarios with sufficient situation awareness. The new TCS compared to the old system provided clear improvements of the control room work regarding shell and chest warming and regarding valve and other system testing. However, a number of Human Engineering Discrepancies (HEDs) were identified. HEDs were prioritized (level 1, 2 or 3) according to potential safety, plant availability, operability or personnel performance consequences. Since no priority 1 HEDs were identified there is no HFE reason not to continue implementation of the TCS. The TCS upgrade is acceptable if the Priority 2 HEDs are resolved and dispositioned in a satisfactory way. Priority 3 HEDs should be noted and considered for future modifications.
Recent disasters have focused attention on performance problems due to the use of alcohol and controlled substances in the workplace. Environmental stressors such as thermal extremes, mixed gases, noise, motion, and vibration also have adverse effects on human performance and operator efficiency. However, the lack of a standardized, sensitive, human performance assessment battery has probably delayed the systematic study of the deleterious effects of various toxic chemicals and drugs at home and in the workplace. The collective goal of the research reported here is the development of a menu of tests embedded in a coherent package of hardware and software that may be useful in repeated-measures studies of a broad range of agents that can degrade human performance. A menu of 40 tests from the Automated Performance Test System (APTS) is described, and the series of interlocking studies supporting its development is reviewed. The APTS tests, which run on several versions of laptop portables and desktop personal computers, have been shown to be stable, reliable, and factorially rich, and to have predictive validities with holistic measures of intelligence and simulator performances. In addition, sensitivity studies have been conducted in which performance changes due to stressors, agents, and treatments were demonstrated. We believe that tests like those described here have prospective use as an adjunct to urine testing for the screening for performance loss of individuals who are granted access to workplaces and stations that impact public safety.
This report presents the results of the Work Domain Analysis for the Experimental Breeder Reactor (EBR-II). This is part of the phase of the research designed to incorporate Cognitive Work Analysis in the development of a framework for the formalization of an Operational Concept (OpsCon) for Advanced Small Modular Reactors (AdvSMRs). For a new AdvSMR design, information obtained through Cognitive Work Analysis, combined with human performance criteria, can and should be used in during the operational phase of a plant to assess the crew performance aspects associated with identified AdvSMR operational concepts. The main objective of this phase was to develop an analytical and descriptive framework that will help systems and human factors engineers to understand the design and operational requirements of the emerging generation of small, advanced, multi-modular reactors. Using EBR-II as a predecessor to emerging sodium-cooled reactor designs required the application of a method suitable to the structured and systematic analysis of the plant to assist in identifying key features of the work associated with it and to clarify the operational and other constraints. The analysis included the identification and description of operating scenarios that were considered characteristic of this type of nuclear power plant. This is an invaluable aspect of Operational Concept development since it typically reveals aspects of future plant configurations that will have an impact on operations. These include, for example, the effect of core design, different coolants, reactor-to-power conversion unit ratios, modular plant layout, modular versus central control rooms, plant siting, and many more. Multi-modular plants in particular are expected to have a significant impact on overall OpsCon in general, and human performance in particular. To support unconventional modes of operation, the modern control room of a multi-module plant would typically require advanced HSIs that would provide sophisticated operational information visualization, coupled with adaptive automation schemes and operator support systems to reduce complexity. These all have to be mapped at some point to human performance requirements. The EBR-II results will be used as a baseline that will be extrapolated in the extended Cognitive Work Analysis phase to the analysis of a selected advanced sodium-cooled SMR design as a way to establish non-conventional operational concepts. The Work Domain Analysis results achieved during this phase have not only established an organizing and analytical framework for describing existing sociotechnical systems, but have also indicated that the method is particularly suited to the analysis of prospective and immature designs. The results of the EBR-II Work Domain Analysis have indicated that the methodology is scientifically sound and generalizable to any operating environment.
This study focuses on investigating students' learning effects and performance trends over a certain period using the Rancor Microworld Simulator. Specifically, it aims to determine the training required to collect HRA data from non-experts (i.e., students) using Rancor Microworld and the differences in human performance measures between students and professional operators. A longitudinal experiment is conducted with sixteen undergraduate students, using four Rancor Microworld scenarios in each of the four experiment trials. The study considers four human performance measurements workload, situation awareness, time, and error. Finally, the trend of students' performance is compared with operator data collected from the previous experiment. Overall, this research complements previous studies by providing insights into how much training is required to collect HRA data from non-experts and the differences in human performance measures between students and professional operators.
The unique characteristics of artificial gravity that affect human performance and physiology in an artificial gravity environment are reviewed. The rate at which these unique characteristics change decreases very rapidly with increasing radius of a rotating vehicle used to produce artificial gravity. Reducing their influence on human performance or physiology by increasing radius becomes a situation of very rapidly diminishing returns. A review of several elements of human performance has developed criteria relative to the sundry characteristics of artificial gravity. A compilation of these criteria indicates that the maximum acceptable rate of rotation, leg heaviness while walking, and material handling are the factors that define the minimum acceptable radius. The ratio of Coriolis force to artificial weight may also be significant. Based on current knowledge and assumptions for the various criteria, a minimum radius between 15.2 and 16.8 m seems desirable.
NASA and the FAA have initiated programs of research and development to provide flight crew, airline operations and air traffic managers with automation aids to increase capacity in en route and terminal area to support the goals of free flight for safe, flexible, predictable, and efficient operations. To support the development of those aiding systems human performance in automated aiding has been examined in empirical and computationally analytic studies. This paper presents a set of those studies in full mission simulation and the development of a predictive computational model of human performance. We have found that the combination of methodologies provide a powerful design-aiding process. We will describe three research programs in support of Free Flight Operations from the perspective of human performance requirements. We have examined procedures and communications in the use of voice and data-link operation at the transition between unconstrained (enroute) and constrained (terminal) airspace operations. We have examined the timing and form of Center TRACON Automation System (CTAS) advisories in descent. We have investigated the shape and dimensions of an 'alert zone' for air-based separation in unconstrained operations. Finally, we have examined the interaction of a ground-based conflict detection/resolution aiding system, as it interacts with a cockpit-based conflict alerting mechanism. Additional information is contained in the original extended abstract.
The purpose of this study was to compare flow constrained area (FCA) capacity setting methods for Collaborative Trajectory Options Program (CTOP) as they pertain to the Integrated Demand Management (IDM) concept. IDM uses flow balancing to manage air traffic across multiple FCAs with a common downstream constraint, as well as constraints at the respective FCA locations. FCA capacity rates can be set manually, but generating capacities for multiple, interdependent FCAs could potentially over-burden a user. A new enhancement to CTOP called the FCA Balance Algorithm (FBA) was developed at NASA Ames Research Center to improve the process of allocating capacity across multiple flow constrained segments in the airspace. The FBA evaluates the predicted demand and capacity across multiple FCAs and dynamically generates capacity settings for the FCAs that best meet capacity limits for all identified constraints. In a human-in-the-loop simulation study, both manual and automated capacity setting methods were evaluated in terms of their overall feasibility using measures of system performance, human performance, and qualitative feedback. Subject matter experts were asked to use three different methods to allocate capacity to three FCAs, either (1) by manually setting capacity for every 60-minute time window, (2) by manually setting capacity for every 15-minute time window, or (3) by using the FBA capability to automatically generate capacity settings. Results showed no significant differences in terms of overall system performance, indicated by similar ground delay and airport throughput numbers between methods. However, differences in individual strategies afforded by the manual methods allowed some participants to achieve system-wide delay that was much lower than the average. The FBA was the fastest method of capacity setting, and it received the lowest subjective rating scores on physical task load, mental task load, task difficulty and task complexity out of the three methods. Finally, participants explained through qualitative feedback that there were many benefits to using the FBA, such as ease of use, accuracy, and low risk of human input error. Participants did not experience the same limitations with the FBA that they did with the manual methods, such as reduced accuracy in the 60-minute manual condition, or high complexity in the 15-minute/manual condition. These results suggest that the FBA automation enhancement to CTOP maintains system performance while improving human performance. Therefore, the FBA could be introduced as a way to mitigate operator workload while planning a CTOP.
The purpose of this study was to compare flow constrained area (FCA) capacity setting methods for Collaborative Trajectory Options Program (CTOP) as they pertain to the Integrated Demand Management (IDM) concept. IDM uses flow balancing to manage air traffic across multiple FCAs with a common downstream constraint, as well as constraints at the respective FCA locations. FCA capacity rates can be set manually, but generating capacities for multiple, interdependent FCAs could potentially over-burden a user. A new enhancement to CTOP called the FCA Balance Algorithm (FBA) was developed at NASA Ames Research Center to improve the process of allocating capacity across multiple flow constrained segments in the airspace. The FBA evaluates the predicted demand and capacity across multiple FCAs and dynamically generates capacity settings for the FCAs that best meet capacity limits for all identified constraints. In a human-in-the-loop simulation study, both manual and automated capacity setting methods were evaluated in terms of their overall feasibility using measures of system performance, human performance, and qualitative feedback. Subject matter experts were asked to use three different methods to allocate capacity to three FCAs, either (1) by manually setting capacity for every 60-minute time window, (2) by manually setting capacity for every 15-minute time window, or (3) by using the FBA capability to automatically generate capacity settings. Results showed no significant differences in terms of overall system performance, indicated by similar ground delay and airport throughput numbers between methods. However, differences in individual strategies afforded by the manual methods allowed some participants to achieve system-wide delay that was much lower than the average. The FBA was the fastest method of capacity setting, and it received the lowest subjective rating scores on physical task load, mental task load, task difficulty and task complexity out of the three methods. Finally, participants explained through qualitative feedback that there were many benefits to using the FBA, such as ease of use, accuracy, and low risk of human input error. Participants did not experience the same limitations with the FBA that they did with the manual methods, such as reduced accuracy in the 60-minute manual condition, or high complexity in the 15-minute/manual condition. These results suggest that the FBA automation enhancement to CTOP maintains system performance while improving human performance. Therefore, the FBA could be introduced as a way to mitigate operator workload while planning a CTOP.
Tests for measuring primary perceptual-motor performance for assessing space environment effects on human performance
A model of the various human factors issues and interactions that might affect crew safety is developed. The first step addressed systematically the central question: How is this space station different from all other spacecraft? A wide range of possible issue was identified and researched. Five major topics of human factors issues that interacted with crew safety resulted: Protocols, Critical Habitability, Work Related Issues, Crew Incapacitation and Personal Choice. Second, an interaction model was developed that would show some degree of cause and effect between objective environmental or operational conditions and the creation of potential safety hazards. The intermediary steps between these two extremes of causality were the effects on human performance and the results of degraded performance. The model contains three milestones: stressor, human performance (degraded) and safety hazard threshold. Between these milestones are two countermeasure intervention points. The first opportunity for intervention is the countermeasure against stress. If this countermeasure fails, performance degrades. The second opportunity for intervention is the countermeasure against error. If this second countermeasure fails, the threshold of a potential safety hazard may be crossed.
A model of the various human factors issues and interactions that might affect crew safety is developed. The first step addressed systematically the central question: How is this Space Station different from all other spacecraft? A wide range of possible issue was identified and researched. Five major topics of human factors issues that interacted with crew safety resulted: Protocols, Critical Habitability, Work Related Issues, Crew Incapacitation and Personal Choice. Second, an interaction model was developed that would show some degree of cause and effect between objective environmental or operational conditions and the creation of potential safety hazards. The intermediary steps between these two extremes of causality were the effects on human performance and the results of degraded performance. The model contains three milestones: stressor, human performance (degraded) and safety hazard threshold. Between these milestones are two countermeasure intervention points. The first opportunity for intervention is the countermeasure against stress. If this countermeasure fails, performance degrades. The second opportunity for intervention is the countermeasure against error. If this second countermeasure fails, the threshold of a potential safety hazard may be crossed.
Securing enough data has been a main challenge in human reliability analysis (HRA). Many researchers and institutes have made a lot of efforts for collecting HRA data to produce reasonable human error probabilities (HEPs) as well as reduce the uncertainty of HRA quantification. Representatively, U.S. Nuclear Regulatory Commission (U.S. NRC), Korea Atomic Energy Research Institute (KAERI) and Idaho National Laboratory (INL) have led lots of empirical research regarding the HRA data collection. The U.S. NRC and KAERI have mainly carried out full-scope simulator research collecting HRA data through experiments using full-scope simulators with actual operators. In contrast, INL has experimentally collected the data using simplified simulators and student operators. INL has proposed the Simplified Human Error Experimental Program (SHEEP) framework to complement full-scope data collection efforts by suggesting a way to infer full-scope data based on experimental data collected from students operating simplified simulators, specifically the Rancor Microworld Simulator (Rancor) and the Compact Nuclear Simulator (CNS). The aim of the SHEEP framework is to lower the entry point for collecting useful HRA data by securing large sample sizes at a reasonable amount of cost and labor while also guaranteeing a high degree of freedom when designing experiments. The authors’ previous research investigated whether data collected from the SHEEP framework could support a representative full-scope study. Besides, human performance differences between professional and student operators when using Rancor and CNS have been analyzed to understand the lack of fidelity of the simplified simulators and student operators within the SHEEP study. As a follow up research, this study experimentally investigates students’ learning effects and the performance trends over a certain period when using Rancor. This study aims to find out 1) how much training or education is required to collect HRA data from non-experts (i.e., students) when using Rancor and 2) how much differences there are in human performance measures between students and professional operators. In this study, a longitudinal experiment is developed. The four experiment trials with two weeks interval are carried out for sixteen undergraduate students majoring nuclear engineering at Chosun University. Totally four scenarios randomly selected from ten Rancor scenarios are used in each experiment trial. Four human performance measurements (i.e., workload, situation awareness, time and error) are considered in the experiment. Lastly, the trend of students’ performance is compared with operator data having been collected from the previous experiment.
What can we do, preparing for these pioneers, to insure that these expected vibrations will not jeopardize their lives nor their missions? This paper will describe one approach, of attempting to simulate the expected and more than the expected complex wave form vibrations to determine tolerance and pilot control capabilities, to attempt to find solutions in simulation before the first flights in reality. The experimental work to be described was done in November, 1959, and June, 1960, on the Johnsville Navy human centrifuge, at the Aviation Medical Acceleration Laboratory, U.S. Naval Air Development Center, Johnsville, Pennsylvania, and in June, 1960, on the North American "G-seat", the vertical accelerator of the North American Aviation Co., Inc., Columbus, Ohio, while the author was Jostle Program Officer at the Aviation Medical Acceleration Laboratory. The experimental work was the subject of the confidential reports NADC-MA-L6005 and NADC-MA-6128, U.S. Naval Air Development Center, and NA60H-444, North American Aviation, Inc., Columbus. Unclassified aspects can now be reported.
A set of 36 relatively independent categories of human performance were identified. These categories encompass human performance in the cognitive, perceptual, and psychomotor areas, and include diagnostic measures and sensitive performance metrics. Then a prototype standardized test battery was constructed, and research was conducted to obtain information on the sensitivity of the tests to stress, the sensitivity of selected categories of performance degradation, the time course of stress effects on each of the selected tests, and the learning curves associated with each test. A research project utilizing a three factor partially repeated analysis of covariance design was conducted in which 60 male subjects were exposed to variations in noise level and quality during performance testing. Effects of randomly intermittent noise on performance of the reaction time tests were observed, but most of the other performance tests showed consistent stability. The results of 14 analyses of covariance of the data taken from the performance of the 60 subjects on the prototype standardized test battery provided information which will enable the final development and test of a standardized test battery and the associated development of differential sensitivity metrics and diagnostic classificatory system.