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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.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Hardening DOE R&D Software Tools for Web-based Visualization SBIR Phase I Final Report

Ubiquitous web-based visualization is essential to delivering large-scale data visualization to various stakeholders, from the scientist to the board member. These stakeholders will not tolerate a stalled application or a pop-up window asking them to wait for the processing to complete. They require a responsive and interactive visualization environment with high-quality imagery suitable for detailed analysis and boardroom presentations. At Kitware, Inc., we have accomplished web visualization to this point, leveraging state-of-the-art tools like HTML5, CSS3, SVG, Canvas, and WebGL. Solutions that leverage a combination of these technologies are necessary to handle workloads that vary significantly in data size efficiently. However, it is not always practical to move large data to the web client for visualization. Kitware's ParaView as a Service combines client-side visualization using both distributed processing and remote rendering on big data impractical to move. Existing distributed processing and remote rendering solution's interactivity is below the expectations of web-based applications. Our project examined proposed solutions to the areas outlined above in ParaView as a Service. We have investigated concurrent pipelines, streaming images, progressive rendering, and optimization of algorithms and data movement to address these concerns. For the Phase I project, we completed the proposed work plan. As a result, the project produced three prototypes of essential importance for web visualization and the ParaView as a Service community. We created a simple desktop application for an interactive streamline placement prototype, a web-based interactive streamline placement prototype, and a web-based progressive rendering utilizing raytracing prototype. These prototypes relied on the hardening of emerging software toolkits funded by the Department of Energy (DOE) Advanced Scientific Computing Research (ASCR) program (such as ParaView, VTK-m, and Mochi). We blended these components into web-based visualization prototypes that meet the industry's expectations for interactivity and responsiveness. The Phase I project had four essential focus areas: 1. Develop prototype ParaView as a Service backend server using asynchronous, non-blocking design principles. 2. Develop a prototype web application that uses the ParaView as a Service backend server for remote data visualization. 3. Implement image streaming with encoding/compression and progressive rendering capabilities in the proposed platform. 4. Evaluate the prototype developed and summarize observations, including the challenges and pitfalls of our approach. After our successful completion of Phase I, we are strongly positioned to propose a successful Phase II project.

Geveci, Berk↗
NASA NTRS1985

Assessing subjective workload assessment - A comparison of SWAT and the NASA-bipolar methods

The Subjective Workload Assessment Technique (SWAT) and the NASA weighted-bipolar method used for evaluating subjective workload assessment are compared. The application of these methods to the rating of single- and dual-task trials of tracking and spatial transformation is described. The methods used to collect the ratings for the SWAT and bipolar technique are examined. Analysis of the transformation-tracking data reveal that the two assessment techniques produce similar results and both measure the differences in task difficulty. The positive and negative characteristics of each technique are analyzed.

Vidulich, M. A.↗
NASA NTRS1994

Strategic workload management and decision biases in aviation

Thirty pilots flew three simulated landing approaches under conditions of low, medium, and high workload. Workload conditions were created by varying time pressure and external communications requirements. Our interest was in how the pilots strategically managed or adapted to the increasing workload. We independently assessed the pilot's ranking of the priority of different discrete tasks during the approach and landing. Pilots were found to sacrifice some aspects of primary flight control as workload increased. For discrete tasks, increasing workload increased the amount of time in performing the high priority tasks, decreased the time in performing those of lowest priority, and did not affect duration of performance episodes or optimality of scheduling of tasks of any priority level. Individual differences analysis revealed that high-performing subjects scheduled discrete tasks earlier in the flight and shifted more often between different activities.

Raby, Mireille↗
NASA NTRS2011

Terminal - Tactical Separation Assured Flight Environment (T-TSafe)

The Tactical Separation Assured Flight Environment (TSAFE) has been previously tested as a conflict detection and resolution tool in the en-route phase of flight. Fast time simulations of a terminal version of this tool called Terminal TSAFE (T-TSAFE) have shown promise over the current conflict detection tools. It has shown to have fewer false alerts (as low as 2 per hour) and better prediction to conflict time than Conflict Alert. The tool will be tested in the simulated terminal area of Los Angeles International Airport, in a Human-in-the-loop experiment to identify controller procedures and information requirements. The simulation will include comparisons of T-TSAFE with NASA's version of Conflict Alert. Also, some other variables such as altitude entry by the controller, which improve T-TSAFE's predictions for conflict detection, will be tested. T-TSAFE integrates features of current conflict detection tools such as Automated Terminal Proximity Alert used to alleviate compression errors in the final approach phase. Based on fast-time simulation analysis, the anticipated benefits of T-TSAFE over Conflict Alert include reduced false/missed alerts and increased time to predicted loss of separation. Other metrics that will be used to evaluate the tool's impact on the controller include controller intervention, workload, and situation awareness.

Verma, Savita Arora↗
DOE OSTI2020

Automatic log analysis with NLP for the CMS workflow handling

The central Monte-Carlo production of the CMS experiment utilizes the WLCG infrastructure and manages daily thousands of tasks, each up to thousands of jobs. The distributed computing system is bound to sustain a certain rate of failures of various types, which are currently handled by computing operators a posteriori. Within the context of computing operations, and operation intelligence, we propose a Machine Learning technique to learn from the operators with a view to reduce the operational workload and delays. This work is in continuation of CMS work on operation intelligence to try and reach accurate predictions with Machine Learning. We present an approach to consider the log files of the workflows as regular text to leverage modern techniques from Natural Language Processing (NLP). In general, log files contain a substantial amount of text that is not human language. Therefore, different log parsing approaches are studied in order to map the log files’ words to high dimensional vectors. These vectors are then exploited as feature space to train a model that predicts the action that the operator has to take. This approach has the advantage that the information of the log files is extracted automatically and the format of the logs can be arbitrary. In this work the performance of the log file analysis with NLP is presented and compared to previous approaches.

Layer, Lukas↗
DOE OSTI2023

Quantifying automated vehicle benefits in reducing driving stress: a simulation experiment approach

Driving is a stressful activity because of the mental workload required to maneuver a vehicle in certain travel contexts, such as congested traffic, multi-modal networks requiring complex interaction with surrounding vehicles, and aggressive driving. Autonomous vehicles (AVs), on the other hand, can reduce the mental workload by performing most of the driving tasks and providing users with a comfortable ride. This study develops a pathway model to relate different health determinants, including travel reliability, safety, driving comfort, and value of time, to Autonomous vehicles driving and studies their impact on the value of driving stress. A case study example of Autonomous vehicles simulation is used to determine the impact of these health determinants. The value of driving stress in Autonomous vehicles is estimated as a function of the value of these individual health determinants. The results show that the perception of safe or unsafe driving in Autonomous vehicles is the most important factor in changing the perception of driving stress in Autonomous vehicles. Similarly, perceptions of comfortable driving in Autonomous vehicles and reduced workload with a higher value of time also reduce driving stress in Autonomous vehicles. These results allow Autonomous vehicles adoption models to explicitly consider driving stress reduction as a benefit and can improve understanding of Autonomous vehicles adoption, which may require quantitative analysis of underlying motivating benefits, including driving stress reduction.

Khattak, Zulqarnain H.↗
NASA NTRS2007

Cost-Benefit Analysis for Alternatives to Aliphatic Isocyanate Polyurethanes

NASA and Air Force Space Command (AFSPC) have similar missions and therefore similar facilities and structures in similar environments. The standard practice for protecting metallic substrates in atmospheric environments is the application of an applied coating system. The most common topcoats used in coating systems are polyurethanes that contain isocyanates. Isocyanates are classified as potential human carcinogens and are known to cause cancer in animals. The primary objective of this effort was to demonstrate and validate alternatives to aliphatic isocyanate polyurethanes resulting in one or more isocyanate-free coatings qualified for use at AFSPC and NASA installations participating in this project. This Cost-Benefit Analysis (CBA) quantifies the estimated capital and process costs of coating alternatives and cost savings relative to the current coatings. The estimates in this CBA are to be used for assessing the relative merits of the selected alternatives. The actual economic effects at any specific facility will depend on the alternative material or technology implemented, the number of actual applications converted, future workloads, and other factors . The participants initially considered eighteen (18) alternative coatings as described in the Potential Alternatives Report entitled Potential Alternatives Report for Validation of Alternatives to Aliphatic Isocyanate Polyurethanes, prepared by ITB. Of those, 8 alternatives were selected for testing in accordance with the Joint Test Protocol entitled Joint Test Protocol for Validation of Alternatives to Aliphatic Isocyanate Polyurethanes, and the Field Test Plan entitled Field Evaluations Test Plan for Validation of Alternatives 10 Aliphatic Isocyanate Polyurethanes, both of which were prepared by ITB. A joint Test Report entitled Joint Test Report for Validation of Alternatives to Aliphatic Isocyanate Polyurethanes, prepared by ITB, documents the results of the laboratory and field testing, as well as any test modifications made during the execution of the testing. The coatings selected for evaluation in this CBA are shown in the table below. Only one control coating system is considered in this analysis. These coatings were either downselected for Phase II or performed well enough to be included in the Qualified Products List in the NASA technical standard NASA-STD-5008, Protective Coating of Carbon Steel, Stainless Steel, and Aluminum on Launch Structures, Facilities, and Ground Support Equipment.

Lewis, Pattie↗
NASA NTRS1997

Design and Operational Evaluation of the Traffic Management Advisor at the Ft. Worth Air Route Traffic Control Center

NASA and the FAA have designed and developed and an automation tool known as the Traffic Management Advisor (TMA). The system was operationally evaluated at the Ft. Worth Air Route Traffic Control Center (ARTCC). The TMA is a time-based strategic planning tool that provides Traffic Management Coordinators and En Route Air Traffic Controllers the ability to efficiently optimize the capacity of a demand impacted airport. The TMA consists of trajectory prediction, constraint-based runway scheduling, traffic flow visualization and controllers advisories. The TMA was used and operationally evaluated for forty-one rush traffic periods during a one month period in the Summer of 1996. The evaluations included all shifts of air traffic operations as well as periods of inclement weather. Performance data was collected for engineering and human factor analysis and compared with similar operations without the TMA. The engineering data indicates that the operations with the TMA show a one to two minute per aircraft delay reduction during rush periods. The human factor data indicate a perceived reduction in en route controller workload as well as an increase in job satisfaction. Upon completion of the evaluation, the TMA has become part of the normal operations at the Ft. Worth ARTCC.

Swenson, Harry N.↗
NASA NTRS1999

Re-Design and Beat Testing of the Man-Machine Integration Design and Analysis System: MIDAS

The Man-machine Design and Analysis System (MIDAS) is a human factors design and analysis system that combines human cognitive models with 3D CAD models and rapid prototyping and simulation techniques. MIDAS allows designers to ask 'what if' types of questions early in concept exploration and development prior to actual hardware development. The system outputs predictions of operator workload, situational awareness and system performance as well as graphical visualization of the cockpit designs interacting with models of the human in a mission scenario. Recently, MIDAS was re-designed to enhance functionality and usability. The goals driving the redesign include more efficient processing, GUI interface, advances in the memory structures, implementation of external vision models and audition. These changes were detailed in an earlier paper. Two Beta test sites with diverse applications have been chosen. One Beta test site is investigating the development of a new airframe and its interaction with the air traffic management system. The second Beta test effort will investigate 3D auditory cueing in conjunction with traditional visual cueing strategies including panel-mounted and heads-up displays. The progress and lessons learned on each of these projects will be discussed.

Shively, R. Jay↗
NASA NTRS1995

Characterizing parallel file-access patterns on a large-scale multiprocessor

High-performance parallel file systems are needed to satisfy tremendous I/O requirements of parallel scientific applications. The design of such high-performance parallel file systems depends on a comprehensive understanding of the expected workload, but so far there have been very few usage studies of multiprocessor file systems. This paper is part of the CHARISMA project, which intends to fill this void by measuring real file-system workloads on various production parallel machines. In particular, we present results from the CM-5 at the National Center for Supercomputing Applications. Our results are unique because we collect information about nearly every individual I/O request from the mix of jobs running on the machine. Analysis of the traces leads to various recommendations for parallel file-system design.

Purakayastha, A.↗
NASA NTRS1995

Aircrew Discourse: Exploring Strategies of Information and Action Management

This paper explores methodology issues encountered in the analysis of flightcrew communications in aviation simulation research. Examples are provided by two recent studies which are compared on three issues: level of analysis, data definition, and interpretation of the results. The data discussed were collected in a study comparing two levels of aircraft automation. The first example is an investigation of how pilots' information transfer strategies differed as a function of automation during low and high-workload flight phases. The second study focuses on how crews managed actions in the two aircraft during a ten minute, high-workload flight segment. Results indicated that crews in the two aircraft differed in their strategies of information and action management. The differences are discussed in terms of their operational and research significance.

Irwin, Cheryl M.↗
NASA NTRS2004

Situation Awareness Implications of Adaptive Automation of Air Traffic Controller Information Processing Functions

The goal of this research was to define a measure of situation awareness (SA) in an air traffic control (ATC) task and to assess the influence of adaptive automation (AA) of various information processing functions on controller perception, comprehension and projection. The measure was also to serve as a basis for defining and developing an approach to triggering dynamic control allocations, as part of AA, based on controller SA. To achieve these objectives, an enhanced version of an ATC simulation (Multitask (copyright)) was developed for use in two human factors experiments. The simulation captured the basic functions of Terminal Radar Approach Control (TRACON) and was capable of presenting to operators four different modes of control, including information acquisition, information analysis, decision making and action implementation automation, as well as a completely manual control mode. The SA measure that was developed as part of the research was based on the Situation Awareness Global Assessment Technique (SAGAT), previous goal-directed task analyses of enroute control and TRACON, and a separate cognitive task analysis on the ATC simulation. The results of the analysis on Multitask were used as a basis for formulating SA queries as part of the SAGAT-based approach to measuring controller SA, which was used in the experiments. A total of 16 subjects were recruited for both experiments. Half the subjects were used in Experiment #1, which focused on assessing the sensitivity and reliability of the SA measurement approach in the ATC simulation. Comparisons were made of manual versus automated control. The remaining subjects were used in the second experiment, which was intended to more completely describe the SA implications of AA applied to specific controller information processing functions, and to describe how the measure could ultimately serve as a trigger of dynamic function allocations in the application of AA to ATC. Comparisons were made of the sensitivity of the SA measure to automation manipulations impacting both higher-order information processing functions, such as information analysis and decision making, versus lower-order functions, including information acquisition and action implementation. All subjects were exposed to all forms of AA of the ATC task and the manual control condition. The approach to AA used in both experiments was to match operator workload, assessed using a secondary task, to dynamic control allocations in the primary task. In total, the subjects in each experiment participated in 10 trials with each lasting between 45 minutes and 1 hour. In both experiments, ATC performance was measured in terms of aircraft cleared, conflicting, and collided. Secondary task (gauge monitoring) performance was assessed in terms of a hit-to-signal ratio. As part of the SA measure, three simulation freezes were conducted during each trial to administer queries on Level 1, 2, and 3 SA.

Kaber, David B.↗
NASA NTRS1992

DEPEND: A simulation-based environment for system level dependability analysis

The design and evaluation of highly reliable computer systems is a complex issue. Designers mostly develop such systems based on prior knowledge and experience and occasionally from analytical evaluations of simplified designs. A simulation-based environment called DEPEND which is especially geared for the design and evaluation of fault-tolerant architectures is presented. DEPEND is unique in that it exploits the properties of object-oriented programming to provide a flexible framework with which a user can rapidly model and evaluate various fault-tolerant systems. The key features of the DEPEND environment are described, and its capabilities are illustrated with a detailed analysis of a real design. In particular, DEPEND is used to simulate the Unix based Tandem Integrity fault-tolerance and evaluate how well it handles near-coincident errors caused by correlated and latent faults. Issues such as memory scrubbing, re-integration policies, and workload dependent repair times which affect how the system handles near-coincident errors are also evaluated. Issues such as the method used by DEPEND to simulate error latency and the time acceleration technique that provides enormous simulation speed up are also discussed. Unlike any other simulation-based dependability studies, the use of these approaches and the accuracy of the simulation model are validated by comparing the results of the simulations, with measurements obtained from fault injection experiments conducted on a production Tandem Integrity machine.

Goswami, Kumar↗
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↗