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NASA NTRS2008

Evolution of the Mobile Information SysTem (MIST)

The Mobile Information SysTem (MIST) had its origins in the need to determine whether commercial off the shelf (COTS) technologies could improve intervehicular activities (IVA) on International Space Station (ISS) crew maintenance productivity. It began with an exploration of head mounted displays (HMDs), but quickly evolved to include voice recognition, mobile personal computing, and data collection. The unique characteristic of the MIST lies within its mobility, in which a vest is worn that contains a mini-computer and supporting equipment, and a headband with attachments for a HMD, lipstick camera, and microphone. Data is then captured directly by the computer running Morae(TM) or similar software for analysis. To date, the MIST system has been tested in numerous environments such as two parabolic flights on NASA's C-9 microgravity aircraft and several mockup facilities ranging from ISS to the Altair Lunar Sortie Lander. Functional capabilities have included its lightweight and compact design, commonality across systems and environments, and usefulness in remote collaboration. Human Factors evaluations of the system have proven the MIST's ability to be worn for long durations of time (approximately four continuous hours) with no adverse physical deficits, moderate operator compensation, and low workload being reported as measured by Corlett Bishop Discomfort Scale, Cooper-Harper Ratings, and the NASA Total Workload Index (TLX), respectively. Additionally, through development of the system, it has spawned several new applications useful in research. For example, by only employing the lipstick camera, microphone, and a compact digital video recorder (DVR), we created a portable, lightweight data collection device. Video is recorded from the participants point of view (POV) through the use of the camera mounted on the side of the head. Both the video and audio is recorded directly into the DVR located on a belt around the waist. This data is then transferred to another computer for video editing and analysis. Another application has been discovered using simulated flight, in which, a kneeboard is replaced with mini-computer and the HMD to project flight paths and glide slopes for lunar ascent. As technologies evolve, so will the system and its application for research and space system operations.

Litaker, Harry L., Jr.↗

DOE OSTI2025

Benchmark Tracking System for Performance Monitoring

Benchmarking is essential for high-performance software development, particularly for monitoring performance across code iterations. This project focused on enhancing the benchmarking process for Lamellar, an asynchronous runtime for High-Performance Computing (HPC) systems developed at Pacific Northwest National Laboratory. Prior to this work, benchmark results were difficult to track and compare across code versions, presenting significant challenges in identifying performance regressions and long-term trends. The primary objective was to establish a systematic, reproducible approach for measuring performance and detecting regressions following code commits. Our methodology involved three key components: standardizing benchmark outputs, implementing data versioning, and developing analysis tools. We standardized the benchmark output format to JSON Line records containing specific fields (execution time, hardware specifications, and environmental variables). To address data management challenges, we evaluated several options and eventually chose a git repository dedicated to benchmark data. We developed a suite of Python tools that processed benchmark results, enriched them with metadata, and facilitated search in the repository. The resulting system enables more efficient filtering and comparison of performance metrics across commit histories, hardware configurations, and benchmark variants through a unified query interface. Our implementation reduces computational overhead by first checking for existing results through configuration matching before initiating new benchmark runs, thereby conserving resources. The system has been validated by Lamellar developers. It organizes results by benchmark type and build configurations for efficient retrieval. Future developments include a planned Large Language Model interface for predicting benchmark performance, incorporating the criterion package for statistical analysis, which will enable automated detection of statistically significant performance changes, and integration with continuous integration pipelines. Despite these enhancements being reserved for future work, this project has successfully provided the Lamellar development team with a framework for maintaining consistent performance standards and identifying optimization opportunities across workloads and hardware environments.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Elastic Resource Management for Deep Learning Applications in a Container Cluster

The increasing demand for learning from massive datasets is restructuring our economy. Effective learning, however, involves nontrivial computing resources. Most businesses utilize commercial infrastructure providers (e.g., AWS) to host their computing clusters in the cloud, where various jobs compete for available resources. While cloud resource management is a fruitful research field that has made many advances in production, such as Kubernetes and YARN, few efforts have been invested to further optimize the system performance, especially for deep learning (DL) training jobs in a container cluster. This work introduces FlowCon, a system that is able to monitor the individual evaluation functions of DL jobs at runtime, and thus to make placement decisions on resource allocations elastically. Here, we present a detailed design and implementation of FlowCon and conduct intensive experiments over various DL models. The results demonstrate that FlowCon significantly improves DL job completion time and resource utilization efficiency, compared to default systems. According to the results, FlowCon is able to improve the completion time by up to 68.8% and meanwhile, reduce the makespan by 18.0%, in the presence of various DL job workloads.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2014

CO2 Washout Testing Using Various Inlet Vent Configurations in the Mark-III Space Suit

Requirements for using a space suit during ground testing include providing adequate carbon dioxide (CO2) washout for the suited subject. Acute CO2 exposure can lead to symptoms including headache, dyspnea, lethargy and eventually unconsciousness or even death. Symptoms depend on several factors including inspired partial pressure of CO2 (ppCO2), duration of exposure, metabolic rate of the subject and physiological differences between subjects. Computational Fluid Dynamic (CFD) analysis has predicted that the configuration of the suit inlet vent has a significant effect on oronasal CO2 concentrations. The main objective of this test was to characterize inspired oronasal ppCO2 for a variety of inlet vent configurations in the Mark-III suit across a range of workload and flow rates. Data and trends observed during testing along with refined CFD models will be used to help design an inlet vent configuration for the Z-2 space suit. The testing methodology used in this test builds upon past CO2 washout testing performed on the Z-1 suit, Rear Entry I-Suit (REI) and the Enhanced Mobility Advanced Crew Escape Suit (EM-ACES). Three subjects performed two test sessions each in the Mark-III suit to allow for comparison between tests. Six different helmet inlet vent configurations were evaluated during each test session. Suit pressure was maintained at 4.3 psid. Suited test subjects walked on a treadmill to generate metabolic workloads of approximately 2000 and 3000 BTU/hr. Supply airflow rates of 6 and 4 actual cubic feet per minute (ACFM) were tested at each workload. Subjects wore an oronasal mask with an open port in front of the mouth and were allowed to breathe freely. Oronasal ppCO2 was monitored real-time via gas analyzers with sampling tubes connected to the oronasal mask. Metabolic rate was calculated from the total oxygen consumption and CO2 production measured by additional gas analyzers at the air outlet from the suit. Realtime metabolic rate measurements were used to adjust the treadmill workload to meet target metabolic rates. This paper provides detailed descriptions of the test hardware, methodology and results, as well as implications for future inlet vent designs and ground testing.

Korona, F. Adam↗

NASA NTRS2014

CO2 Washout Testing Using Various Inlet Vent Configurations in the Mark-III Space Suit

Requirements for using a space suit during ground testing include providing adequate carbon dioxide (CO2) washout for the suited subject. Acute CO2 exposure can lead to symptoms including headache, dyspnea, lethargy and eventually unconsciousness or even death. Symptoms depend on several factors including inspired partial pressure of CO2 (ppCO2), duration of exposure, metabolic rate of the subject and physiological differences between subjects. Computational Fluid Dynamic (CFD) analysis has predicted that the configuration of the suit inlet vent has a significant effect on oronasal CO2 concentrations. The main objective of this test was to characterize inspired oronasal ppCO2 for a variety of inlet vent configurations in the Mark-III suit across a range of workload and flow rates. Data and trends observed during testing along with refined CFD models will be used to help design an inlet vent configuration for the Z-2 space suit. The testing methodology used in this test builds upon past CO2 washout testing performed on the Z-1 suit, Rear Entry I-Suit (REI) and the Enhanced Mobility Advanced Crew Escape Suit (EM-ACES). Three subjects performed two test sessions each in the Mark-III suit to allow for comparison between tests. Six different helmet inlet vent configurations were evaluated during each test session. Suit pressure was maintained at 4.3 psid. Suited test subjects walked on a treadmill to generate metabolic workloads of approximately 2000 and 3000 BTU/hr. Supply airflow rates of 6 and 4 actual cubic feet per minute (ACFM) were tested at each workload. Subjects wore an oronasal mask with an open port in front of the mouth and were allowed to breathe freely. Oronasal ppCO2 was monitored real-time via gas analyzers with sampling tubes connected to the oronasal mask. Metabolic rate was calculated from the total oxygen consumption and CO2 production measured by additional gas analyzers at the air outlet from the suit. Real-time metabolic rate measurements were used to adjust the treadmill workload to meet target metabolic rates. This paper provides detailed descriptions of the test hardware, methodology and results, as well as implications for future inlet vent designs and ground testing.

Korona, F. Adam↗

NASA NTRS2014

Carbon Dioxide Washout Testing Using Various Inlet Vent Configurations in the Mark-III Space Suit

Requirements for using a space suit during ground testing include providing adequate carbon dioxide (CO2) washout for the suited subject. Acute CO2 exposure can lead to symptoms including headache, dyspnea, lethargy, and eventually unconsciousness or even death. Symptoms depend on several factors including inspired partial pressure of CO2 (ppCO2), duration of exposure, metabolic rate of the subject, and physiological differences between subjects. Computational Fluid Dynamics (CFD) analysis has predicted that the configuration of the suit inlet vent has a significant effect on oronasal CO2 concentrations. The main objective of this test was to characterize inspired oronasal ppCO2 for a variety of inlet vent configurations in the Mark-III suit across a range of workload and flow rates. Data and trends observed during testing along with refined CFD models will be used to help design an inlet vent configuration for the Z-2 space suit. The testing methodology used in this test builds upon past CO2 washout testing performed on the Z-1 suit, Rear Entry I-Suit, and the Enhanced Mobility Advanced Crew Escape Suit. Three subjects performed two test sessions each in the Mark-III suit to allow for comparison between tests. Six different helmet inlet vent configurations were evaluated during each test session. Suit pressure was maintained at 4.3 psid. Suited test subjects walked on a treadmill to generate metabolic workloads of approximately 2000 and 3000 BTU/hr. Supply airflow rates of 6 and 4 actual cubic feet per minute were tested at each workload. Subjects wore an oronasal mask with an open port in front of the mouth and were allowed to breathe freely. Oronasal ppCO2 was monitored real-time via gas analyzers with sampling tubes connected to the oronasal mask. Metabolic rate was calculated from the CO2 production measured by an additional gas analyzer at the air outlet from the suit. Real-time metabolic rate measurements were used to adjust the treadmill workload to meet target metabolic rates. This paper provides detailed descriptions of the test hardware, methodology and results, as well as implications for future inlet vent designs and ground testing.

Korona, F. Adam↗

NASA NTRS1975

The analysis of the pilot's cognitive and decision processes

Articles are presented on pilot performance in zero-visibility precision approach, failure detection by pilots during automatic landing, experiments in pilot decision-making during simulated low visibility approaches, a multinomial maximum likelihood program, and a random search algorithm for laboratory computers. Other topics discussed include detection of system failures in multi-axis tasks and changes in pilot workload during an instrument landing.

Curry, R. E.↗

NASA NTRS2016

The Man-machine Integration Design and Analysis System (MIDAS) Software Training Documentation

This document is a training manual for MIDAS v5 that takes an user through the hardware and software requirements for the MIDAS V5 software, the steps required to download the software, and the steps that a user needs to take to create a MIDAS simulation. The training guide also illustrates how the models interact to generate MIDAS predictions of operator performance along task, workload, and situation awareness timelines and provides the test routines that were conducted to verify the operation of the integrated MIDAS models. The training guide shows the user how the MIDAS task model interacts with and controls an anthropometric model through its use of behavioral primitives. The training documentation also illustrates one approach that has been used to filter and analyze MIDAS output.

Brian F. Gore↗

NASA NTRS2014

CO2 Washout Testing Using Various Inlet Vent Configurations in the Mark-III Space Suit

Requirements for using a space suit during ground testing include providing adequate carbon dioxide (CO2) washout for the suited subject. Acute CO2 exposure can lead to symptoms including headache, dyspnea, lethargy and eventually unconsciousness or even death. Symptoms depend on several factors including inspired partial pressure of CO2 (ppCO2), duration of exposure, metabolic rate of the subject and physiological differences between subjects. Computational Fluid Dynamic (CFD) analysis has predicted that the configuration of the suit inlet vent has a significant effect on oronasal CO2 concentrations. The main objective of this test is to characterize inspired oronasal ppCO2 for a variety of inlet vent configurations in the Mark-III space suit across a range of workload and flow rates. As a secondary objective, results will be compared to the predicted CO2 concentrations and used to refine existing CFD models. These CFD models will then be used to help design an inlet vent configuration for the Z-2 space suit, which maximizes oronasal CO2 washout. This test has not been completed, but is planned for January 2014. The results of this test will be incorporated into this paper. The testing methodology used in this test builds upon past CO2 washout testing performed on the Z-1 suit, Rear Entry I-Suit (REI) and the Enhanced Mobility Advanced Crew Escape Suit (EM-ACES). Three subjects will be tested in the Mark-III space suit with each subject performing two test sessions to allow for comparison between tests. Six different helmet inlet vent configurations will be evaluated during each test session. Suit pressure will be maintained at 4.3 psid. Subjects will wear the suit while walking on a treadmill to generate metabolic workloads of approximately 2000 and 3000 BTU/hr. Supply airflow rates of 6 and 4 actual cubic feet per minute (ACFM) will be tested at each workload. Subjects will wear an oronasal mask with an open port in front of the mouth and will be allowed to breathe freely. Oronasal ppCO2 will be monitored real-time via gas analyzers with sampling tubes connected to the oronasal mask. Metabolic rate will be calculated from the total oxygen consumption and CO2 production measured by additional gas analyzers at the air outlet from the suit. Real-time metabolic rate measurements will be used to adjust the treadmill workload to meet target metabolic rates. This paper provides detailed descriptions of the test hardware, methodology and results, as well as implications for future inlet vent design and ground testing in the Mark-III.

Korona, F. Adam↗

NASA NTRSDate not supplied

Human-Autonomy Teaming Research in Support of m:N Operations

Since 2019, the NASA and industry partners have been involved in research focused on a novel paradigm for operations of remotely piloted aircraft. This paradigm involves multiple people sharing a fleet of multiple vehicles between them. Referred to as m:N (pronounced “em-to-en”), this configuration describes a ratio where m is the number of operators and N is the number of vehicles. Through force and asset multiplication, the m:N concept seeks to enable a scalable and resilient operation of remotely crewed vehicles. The primary means of obtaining such a robust operation is through allowing a flexible crew of variable size to dynamically attend to the needs of assets in while performing real-time operator workload management. It is in that sense that assets are shared between operators: as needed (such as in events of elevated workload) an operator in an m:N context can “handoff” the responsibility for some amount of assets, nh < N, to be absorbed by the m – 1 crew members on staff. At some time later, these nh assets could be returned to their original owner or they may be further distributed to other crew if called for by the mission. During this panel, I will elaborate on the research activity undertaken by the Human-Autonomy Teaming (HAT) Laboratory at NASA Ames Research Center over the previous three years. The studies conducted by the HAT Lab range from interviews with subject matter experts, a cognitive walkthrough, a task analysis, and two simulation experiments to-date. During experimentation, pilots made use of an advanced Ground Control Station developed by the HAT Lab and industry partners to simulate m:N operations in two large, metropolitan areas of Southern California: Los Angeles and San Diego. Further experimentation planned over the next few years. Results from our research to-date indicates that pilots of a moderately sized fleet of about a dozen remotely crewed aircraft adequately maintained safety performance and situation awareness of their aircraft, even when presented with unexpected situations of heightened workload.

multi-vehicle control↗

NASA NTRS1993

The influence of air traffic control message length and timing on pilot communication

The present paper outlines an approach to air traffic control (ATC) communication that is based on theories of dialogue organization and describes several steps or phases in routine controller-pilot communication. The introduction also describes several kinds of communication problems that often disrupt these steps, as well as how these problems may be caused by factors related to ATC messages, the communication medium (radio vs. data link) and task workload. Next, a part-task simulation study is described. This study focused on how problems in radio communication are related to message factors. More specifically, we examined if pilots are more likely to misunderstanding longer ATC messages. A more general goal of the study is to show that communication analysis can help trace where problem occur and why.

Morrow, Daniel↗

DOE OSTI2025

The water use of data center workloads: A review and assessment of key determinants

The global importance of data center water use is increasing with the rapid growth of digitalization and artificial intelligence. This study analyzes the factors influencing workload-level water use, measured in liters consumed per workload, to guide water-saving strategies in data centers. Our findings reveal workload-level water use variations exceeding 10,000-fold, driven by over 1000-fold differences in water consumption per kilowatt hour of server electricity consumed and approximately 10-fold differences in server workload efficiency. Key determinants are ranked as server efficiency, electrical grid water consumption factors, server utilization, cooling system type, infrastructure efficiency, climate zone, inactive server percentage, and server refresh cycle. Notably, there is no single recipe for minimizing water use; instead, optimal outcomes depend on tailored combinations of these factors. This analysis addresses critical knowledge gaps by identifying the determinants of data center water use and exploring their achievable minima under diverse site-specific constraints.

Data centers↗

DOE OSTI2019

Exploring GlideinWMS and HTCondor scalability frontiers for an expanding CMS Global Pool

The CMS Submission Infrastructure Global Pool, built on Glidein-WMS andHTCondor, is a worldwide distributed dynamic pool responsible for the allocation of resources for all CMS computing workloads. Matching the continuously increasing demand for computing resources by CMS requires the anticipated assessment of its scalability limitations. In addition, the Global Plmust be able to expand in a more heterogeneous environment, in terms of resource provisioning (combining Grid, HPC and Cloud) and workload submissi.A dedicated testbed has been set up to simulate such conditions with the purpose of finding potential bottlenecks in the software or its configuration. This report provides a thorough description of the various scalabilitydimensions in size and complexity that are being explored for the future Global Pool, along with the analysis and solutions to the limitations proposed with the support of the GlideinWMS and HTCondor developer teams.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1976

Digital data processing system dynamic loading analysis

Simulation and analysis of the Space Shuttle Orbiter Digital Data Processing System (DDPS) are reported. The mated flight and postseparation flight phases of the space shuttle's approach and landing test configuration were modeled utilizing the Information Management System Interpretative Model (IMSIM) in a computerized simulation modeling of the ALT hardware, software, and workload. System requirements simulated for the ALT configuration were defined. Sensitivity analyses determined areas of potential data flow problems in DDPS operation. Based on the defined system requirements and the sensitivity analyses, a test design is described for adapting, parameterizing, and executing the IMSIM. Varying load and stress conditions for the model execution are given. The analyses of the computer simulation runs were documented as results, conclusions, and recommendations for DDPS improvements.

Lagas, J. J.↗

NASA NTRS1988

Computational human factors in human-machine engineering - The Army-NASA aircrew/aircraft integration (A3I) program

The A3I program is a joint US Army-NASA exploratory program to develop a rational predictive methodology for helicopter cockpit system design, including mission requirements and training-system implications, that integrates human factors engineering with other vehicle system design disciplines at an early stage in the development process. The program will produce a prototye human factors/computer-aided engineering (HF/CAE) workstation suite for use by design professionals. This interactive environment will include computational and expert systems for the analysis and estimation of the impact of cockpit design and mission specification on system performance by considering the performance consequences from the human component of the system, especially as an integral part of the overall system operation, and from the very beginning of the design process. The central issues of pilot workload, performance, and training needs, and appropriate uses of automation are interrelated to affect all integrated design considerations in future man-machine systems. The goal is to aid designers in understanding these complex interactions and in optimally matching human capabilities with advanced cockpit systems.

Hartzell, E. James↗

NASA NTRSDate not supplied

Handling Qualities Assessment of Manual Lunar Landing with Display Augmentation

Research and development is being conducted to support data-driven design decisions for manual control and human involvement in the lunar landing task under the Human Landing System (HLS) program within the Artemis campaign. A human-in-the-loop simulator evaluation of the manual control of a lunar landing vehicle in the final approach and landing phase was conducted at NASA Langley Research Center in the Lunar Flight Deck simulator using the Altair Design and Analysis Cycle (DAC)-2 government reference vehicle. The objective was to perform a direct comparison of control law types with display aiding for various rotational control powers being considered under HLS. Ten subjects (four NASA test pilots and six current pilot astronauts) provided Cooper-Harper ratings, NASA Task Load Index workload ratings, and qualitative comments. The piloting task was to assume manual control of the vehicle (including vertical descent rate) at 150 m above the landing zone, fly to a redesignated landing target (which was up to 75 m radially from the center of the landing zone) and to touch down within a position accuracy of 5m. The data showed that the display augmentation in the form of a “hover cue” significantly improved the pilot’s ability to control translation and create satisfactory handling qualities for otherwise sluggish configurations; however, the investigation also showed that display augmentation is not a panacea. Handling qualities problems, including pilot-induced oscillations, and higher workload for the lowest control powers can still be evident.

Lynda J. Kramer↗

NASA NTRSDate not supplied

Handling Qualities Assessment of Manual Lunar Landing with Display Augmentation

Lynda Kramer↗

NASA NTRSDate not supplied

Ensuring Safe Decision-Making on the Moon and Mars: Cognitive Performance Assessment for Exploration Class Mission EVA

Extravehicular activity (EVA) is one of the most dangerous and cognitively demanding actions that astronauts can execute, and the cognitive demands associated with future partial gravity EVAs on the Moon and Mars are expected to be higher compared to microgravity EVAs currently conducted from the International Space Station. Decrements in cognitive performance present an important risk to crew safety during exploration mission class EVA. Yet there is currently insufficient data to characterize cognitive performance prior to, during, and following EVA. Furthermore, it is still unclear which cognitive domains are most important for conducting mission critical decisions with crew safety implications. To address this gap, we conducted a cognitive task analysis (CTA) of EVA to characterize the procedures, the cognitive demands required, and the critical safety decisions associated with decrements in cognitive performance. We conducted a cognitive task analysis with 15 astronauts and subject matter experts in EVA operations and research. Interviews focused on surface exploration EVA and elicited feedback from experts on the cognitive skills required for specific EVA tasks, including cognitive strategies, critical cues, and decision-making strategies. A cognitive demands table was assembled to consolidate and synthesize the information from all interviews. The information from this cognitive task analysis informs ongoing exploration EVA for Moon to Mars. This work identifies the specific cognitive challenges that astronauts are likely to encounter during surface exploration EVA, and provides the foundation for: (1) prioritized and targeted cognitive performance measurement and functional performance tests, (2) EVA simulation design at varying levels of cognitive workload, and (3) the development of training and other technologies that can improve safe decision-making and inform EVA planning on future spaceflight missions to the Moon and Mars.

Steven R Anderson↗