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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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At least 1,171 records · Page 65
All sourcesNASA NTRSDOE OSTI
NASA NTRS1975

Application of active controls technology to aircraft bide smoothing systems

A critical review of past efforts in the design and testing of ride smoothing and gust alleviation systems is presented. Design trade offs involving sensor types, choice of feedback loops, human comfort, and aircraft handling-qualities criteria are discussed. Synthesis of a system designed to employ direct-lift and side-force producing surfaces is reported. Two STOL aircraft and an executive transport are considered. Theoretically predicted system performance is compared with hybrid simulation and flight test data. Pilot opinion rating, pilot workload, and passenger comfort rating data for the basic and augmented aircraft are included.

Lapins, M.↗
NASA NTRS1975

The human controller in car following

The man machine interface between the human driver and his automobile during car following tasks was examined. A direct connection between models of the human operator and the theory of optimal control was established for car following situations involving both linear and nonlinear car dynamics. Results obtained from several types of mathematical models are discussed. Conventional parameter identification techniques were used to obtain the parameters of these models by comparing their performance to data obtained by aerial photogrammetry. The results indicate that there are two general classes of model structures: models assumed to have preview information and models without preview.

Burnham, G. O.↗
NASA NTRS1999

Effects of Promethazine on Performance During Simulated Shuttle Landings

Promethazine (PMZ) is the antimotion sickness drug of choice in the U.S. Space Shuttle program; however, virtually nothing is known about the bioavailability and performance effects of this drug in the microgravity environment. PMZ has detrimental side effects on human performance on Earth that could affect Shuttle operations. In a recent ground-based study we examined: 1) the effects of promethazine (PMZ) on Shuttle landing performance using the portable inflight landing operations trainer (PILOT), and 2) saliva and urine samples to determine the pharmacokinetics of PMZ. The PILOT performance data is presented here.

Harm, D. L.↗
NASA NTRS2007

Automated Recognition of 3D Features in GPIR Images

A method of automated recognition of three-dimensional (3D) features in images generated by ground-penetrating imaging radar (GPIR) is undergoing development. GPIR 3D images can be analyzed to detect and identify such subsurface features as pipes and other utility conduits. Until now, much of the analysis of GPIR images has been performed manually by expert operators who must visually identify and track each feature. The present method is intended to satisfy a need for more efficient and accurate analysis by means of algorithms that can automatically identify and track subsurface features, with minimal supervision by human operators. In this method, data from multiple sources (for example, data on different features extracted by different algorithms) are fused together for identifying subsurface objects. The algorithms of this method can be classified in several different ways. In one classification, the algorithms fall into three classes: (1) image-processing algorithms, (2) feature- extraction algorithms, and (3) a multiaxis data-fusion/pattern-recognition algorithm that includes a combination of machine-learning, pattern-recognition, and object-linking algorithms. The image-processing class includes preprocessing algorithms for reducing noise and enhancing target features for pattern recognition. The feature-extraction algorithms operate on preprocessed data to extract such specific features in images as two-dimensional (2D) slices of a pipe. Then the multiaxis data-fusion/ pattern-recognition algorithm identifies, classifies, and reconstructs 3D objects from the extracted features. In this process, multiple 2D features extracted by use of different algorithms and representing views along different directions are used to identify and reconstruct 3D objects. In object linking, which is an essential part of this process, features identified in successive 2D slices and located within a threshold radius of identical features in adjacent slices are linked in a directed-graph data structure. Relative to past approaches, this multiaxis approach offers the advantages of more reliable detections, better discrimination of objects, and provision of redundant information, which can be helpful in filling gaps in feature recognition by one of the component algorithms. The image-processing class also includes postprocessing algorithms that enhance identified features to prepare them for further scrutiny by human analysts (see figure). Enhancement of images as a postprocessing step is a significant departure from traditional practice, in which enhancement of images is a preprocessing step.

Park, Han↗
NASA NTRS2015

Urine Pretreatment History and Perspective in NASA Human Spaceflight

Urine pretreatment is a technology that may seem to have small mass impacts in future spaceflight missions, but can have significant impacts on reliability, life, and performance of the rest of the wastewater management and recovery systems. NASA has experience with several different urine pretreatment systems, including those flow on the space shuttle, evaluated for NASA waste collection systems or used in Russian commodes on ISS, or developed by NASA or industry as alternatives. Each has had unique requirements for shelf life, operational life, and the life or conditions of the stored, treated urine. Each was evaluated under different test conditions depending on mission, and depending on testing experience developed over NASA's history. Those that were flown led to further lessons learned about hardware compatibility and control. As NASA looks forward to human spaceflight missions beyond low Earth orbit, these techniques need to be evaluated in new light. Based on published design reference missions, candidate requirements can be derived for future systems. Initial comparisons between these requirements and previous performance or test results can be performed. In many cases these comparisons reveal data gaps. Successful previous performance is not enough to address current needs.

Anderson, Molly↗
NASA NTRS2016

Modeling Relationships Between Flight Crew Demographics and Perceptions of Interval Management

The Interval Management Alternative Clearances (IMAC) human-in-the-loop simulation experiment was conducted to assess interval management system performance and participants' acceptability and workload while performing three interval management clearance types. Twenty-four subject pilots and eight subject controllers flew ten high-density arrival scenarios into Denver International Airport during two weeks of data collection. This analysis examined the possible relationships between subject pilot demographics on reported perceptions of interval management in IMAC. Multiple linear regression models were created with a new software tool to predict subject pilot questionnaire item responses from demographic information. General patterns were noted across models that may indicate flight crew demographics influence perceptions of interval management.

Remy, Benjamin↗
NASA NTRSDate not supplied

Mars Space Suit Materials Testing Using SHERLOC Calibration Target Data: The Max-CF Project

The Mars 2020/“Perseverance” rover carries a suite of space suit materials as part of the SHERLOC* calibration target [1]. The materials are periodically analyzed by SHERLOC as part of a regular calibration routine and are generating a rich data set regarding their degradation in the martian surface environment. The Maximization of Calibration Fabrics (Max-CF) project will effectively turn SHERLOC data into a measure of space suit material service lifetimes by exposing a second set of materials in a Mars chamber, replicating SHERLOC measurements using the analogous ACRONM** instrument at JSC, and then performing materials testing to include tensile testing. These data can be used to inform space suit design and/or materials development, improving crew safety for future Mars missions. This will partially address NASA’s Strategic Knowledge Gap 8 (Mars Surface Technology) which identifies a need to develop technologies to “sustain humans on the surface of Mars [and] enable human mobility and exploration” [2]. This abstract describes the overall Max-CF project and progress on the laboratory-based study to date.

M Fries↗
NASA NTRS2023

Psychophysiological Research Methods to Assess Airline Flight Crew Resilient Performance in High-Fidelity Flight Simulation Scenarios

New concepts in aviation system safety thinking have emerged to consider not only what may go wrong, but also what can be learned when things go right. This approach forms a more comprehensive approach to system safety thinking. A need exists for methods to enable a better understanding of human contributions to aviation safety and how they may inform Safety Management Systems (SMS). A high-fidelity 737-800 simulation study was conducted to study how current type-rated commercial airline flight crews anticipate, monitor, respond to, and learn from expected and unexpected disturbances during line operations. A number of dependent measures were collected that included traditional SMS data types, but also non-traditional safety data to include multiple psychophysiological metrics. This paper describes the psychophysiological measures results that evinced the capability of measures to help identify resilient flight crews. Implications for future research and design of future In-time Aviation Safety Management Systems are discussed.

Psychophysiology↗
DOE OSTI2016

Human Microdosing with Carcinogenic Polycyclic Aromatic Hydrocarbons: In Vivo Pharmacokinetics of Dibenzo[ def,p ]chrysene and Metabolites by UPLC Accelerator Mass Spectrometry

Metabolism is a key health risk factor following exposures to pro-carcinogenic polycyclic aromatic hydrocarbons (PAHs) such as dibenzo[def,p]chrysene (DBC), an IARC classified 2A probable human carcinogen. Human exposure to PAHs occurs primarily from the diet in non-smokers. However, little data is available on the metabolism and pharmacokinetics in humans of high molecular weight PAHs (≥4 aromatic rings), including DBC. We previously determined the pharmacokinetics of DBC in human volunteers orally administered a micro-dose (29 ng; 5 nCi) of [14C]-DBC by accelerator mass spectrometry (AMS) analysis of total [14C] in plasma and urine. In the current study, we utilized a novel “moving wire” interface between ultra-performance liquid chromatography (UPLC) and AMS to detect and quantify parent DBC and its major metabolites. The major [14C] product identified in plasma was unmetabolized [14C]-DBC itself, (Cmax= 18.5 ± 15.9 fg/mL, Tmax= 2.1 ± 1.0 h), whereas the major metabolite was identified as [14C]-(+/-)-DBC-11,12-diol (Cmax= 2.5 ± 1.3 fg/mL, Tmax= 1.8 h). Several minor species of [14C]-DBC metabolites were also detected for which no reference standards were available. Free and conjugated metabolites were detected in urine with [14C]-(+/-)-DBC-11,12,13,14-tetraol isomers identified as the major metabolites, 56.3% of which were conjugated (Cmax= 35.8 ± 23.0 pg/pool, Tmax= 6-12 h pool). [14C]-DBC-11,12-diol, of which 97.5% was conjugated, was also identified in urine (Cmax= 29.4 ± 11.6 pg/pool, Tmax= 6-12 h pool). Parent [14C]-DBC was not detected in urine. This is the first dataset to assess metabolite profiles and associated pharmacokinetics of a carcinogenic PAH in human volunteers at an environmentally relevant dose, providing the data necessary for translation of high dose animal models to humans for translation of environmental health risk assessment.

Madeen, Erin P.↗
DOE OSTI2014

Finding Waldo: Learning about Users from their Interactions

Visual analytics is inherently a collaboration between human and computer. However, in current visual analytics systems, the computer has limited means of knowing about its users and their analysis processes. While existing research has shown that a user’s interactions with a system reflect a large amount of the user’s reasoning process, there has been limited advancement in developing automated, real-time techniques that mine interactions to learn about the user. In this paper, we demonstrate that we can accurately predict a user’s task performance and infer some user personality traits by using machine learning techniques to analyze interaction data. Specifically, we conduct an experiment in which participants perform a visual search task and we apply well-known machine learning algorithms to three encodings of the users interaction data. We achieve, depending on algorithm and encoding, between 62% and 96% accuracy at predicting whether each user will be fast or slow at completing the task. Beyond predicting performance, we demonstrate that using the same techniques, we can infer aspects of the user’s personality factors, including locus of control, extraversion, and neuroticism. Further analyses show that strong results can be attained with limited observation time, in some cases, 82% of the final accuracy is gained after a quarter of the average task completion time. Overall, our findings show that interactions can provide information to the computer about its human collaborator, and establish a foundation for realizing mixed- initiative visual analytics systems.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2003

Using Computational Cognitive Modeling to Diagnose Possible Sources of Aviation Error

We present a computational model of a closed-loop, pilot-aircraft-visual scene-taxiway system created to shed light on possible sources of taxi error. Creating the cognitive aspects of the model using ACT-R required us to conduct studies with subject matter experts to identify experiential adaptations pilots bring to taxiing. Five decision strategies were found, ranging from cognitively-intensive but precise, to fast, frugal but robust. We provide evidence for the model by comparing its behavior to a NASA Ames Research Center simulation of Chicago O'Hare surface operations. Decision horizons were highly variable; the model selected the most accurate strategy given time available. We found a signature in the simulation data of the use of globally robust heuristics to cope with short decision horizons as revealed by errors occurring most frequently at atypical taxiway geometries or clearance routes. These data provided empirical support for the model.

Pilots↗
DOE OSTI2021

A Statistical Evaluation of Combining Human Productivity Metrics in the Indoor Environment

The potential of improving human productivity by providing healthy indoor environments has been a consistent interest in the building field for decades. This research field's long-standing challenge is to measure human productivity given the complex nature of office work. Previous studies have diversified productivity metrics, allowing greater flexibility in collecting human data; however, this diversity complicates the ability to combine productivity metrics from disparate studies within a meta-analysis. This study aims to categorize existing productivity metrics and statistically assess which categories show similar behavior when used to measure the impacts of indoor environmental quality. The 106 productivity metrics compiled were grouped into six productivity metric categories: neurobehavioral speed, accuracy, neurobehavioral response time, call handling time, self-reported productivity, and performance score. Then, this study set neurobehavioral speed as the baseline category given its fitness to the efficiency-based definition of productivity (i.e., output versus input) and conducted three statistical analyses with the other categories to evaluate their similarity. As results, the categories of neurobehavioral response time, self-reported productivity, and call handling time were found to have statistical similarity with neurobehavioral speed. This study contributes to creating a constructive research environment for future meta-analyses to understand which human productivity metrics can be combined with each other.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2006

NASA Exploration Launch Projects Overview: The Crew Launch Vehicle and the Cargo Launch Vehicle Systems

The U.S. Vision for Space Exploration (January 2004) serves as the foundation for the National Aeronautics and Space Administration's (NASA) strategic goals and objectives. As the NASA Administrator outlined during his confirmation hearing in April 2005, these include: 1) Flying the Space Shuttle as safely as possible until its retirement, not later than 2010. 2) Bringing a new Crew Exploration Vehicle (CEV) into service as soon as possible after Shuttle retirement. 3) Developing a balanced overall program of science, exploration, and aeronautics at NASA, consistent with the redirection of the human space flight program to focus on exploration. 4) Completing the International Space Station (ISS) in a manner consistent with international partner commitments and the needs of human exploration. 5) Encouraging the pursuit of appropriate partnerships with the emerging commercial space sector. 6) Establishing a lunar return program having the maximum possible utility for later missions to Mars and other destinations. In spring 2005, the Agency commissioned a team of aerospace subject matter experts to perform the Exploration Systems Architecture Study (ESAS). The ESAS team performed in-depth evaluations of a number of space transportation architectures and provided recommendations based on their findings? The ESAS analysis focused on a human-rated Crew Launch Vehicle (CLV) for astronaut transport and a heavy lift Cargo Launch Vehicle (CaLV) to carry equipment, materials, and supplies for lunar missions and, later, the first human journeys to Mars. After several months of intense study utilizing safety and reliability, technical performance, budget, and schedule figures of merit in relation to design reference missions, the ESAS design options were unveiled in summer 2005. As part of NASA's systems engineering approach, these point of departure architectures have been refined through trade studies during the ongoing design phase leading to the development phase that begins in 2008. Comprehensive reviews of engineering data and business assessments by both internal and independent reviewers serve as decision gates to ensure that systems can fully meet customer and stakeholder requirements. This paper provides the current CLV and CaLV configuration designs and gives examples of the progress being made during the first year of this significant effort. Safe, reliable, cost-effective space transportation systems are a foundational piece of America s future in space and the next step in realizing the plan for revitalizing lunar capabilities on the passageway to the human exploration of Mars. While building on legacy knowledge and heritage hardware for risk reduction, NASA will apply lessons learned from developing these new launch vehicles to the growth path for future missions. The elements for mission success and continued U.S. leadership in space have been assembled over the past year. As NASA designs and develops these two new systems over the next dozen years, visible progress, such as that reported in this paper, may sustain the national will to stay the course across political administrations and weather the inevitable trials that will be experienced during this challenging endeavor.

Snoddy, Jimmy R.↗
NASA NTRSDate not supplied

Next Generation Exercise Device (NGED): Advancing Exercise Capabilities for Future Space Missions Through Biomechanical Modeling

BACKGROUND As space exploration extends to long-duration missions on the Moon and Mars, maintaining astronaut health and fitness becomes increasingly critical. The Next Generation Exercise Device (NGED), developed and tested by the HumanWorks Lab in NASA Johnson Space Center's (JSC) Software, Robotics, and Simulation Division, aims to address this challenge through innovative approaches. This study presents the development and evaluation of an NGED system, focusing on its adaptability to various mission scenarios, including prospective use in a Lunar Pressurized Rover (LPR). Central to this project is the application of biomechanical modeling to optimize exercise efficacy and safety in microgravity and partial gravity environments. The project is a collaborative effort with the Human Health and Performance group at Johnson Space Center, ensuring a comprehensive approach to astronaut well-being that integrates biomechanical principles with practical exercise solutions. The NGED represents the next generation of exercise capabilities for missions in space, on the Moon and Mars, with a specific focus on applications such as the LPR. METHODS AND RESULTS Data collection for NGED development was conducted with two motor-driven Beyond Power Voltra I [1] systems and a custom test structure to allow placement of the cable-based devices on the ground, at shoulder height, and overhead. The collection was performed in JSC’s Prototype Immersive Technology (PIT) Lab, utilizing an OptiTrack motion capture system and AMTI force platform, to enable detailed biomechanical analysis via OpenSim [2,3]. Motion capture data were collected for three subjects representing different body types and statures. The marker set used was an enhanced version of the full-body Plug-in Gait marker set [4], with additional markers strategically placed for the primary objective of informing exercise volume requirements. Subjects performed a series of 17 exercises, carefully selected to engage various muscle groups, including novel spaceflight exercises such as skiing (ergometer style), lateral pulldowns, wood chops, triceps extensions, and flies, with load variations ranging from 10 to 90 pounds to maintain kinematic form. This comprehensive approach allowed for a thorough evaluation of the NGED's performance across a wide range of motions and loads. The biomechanical modeling and analysis were conducted using a modified OpenSim Full Body Rajagopal Model [4,5] and also scaled to the maximum and minimum anthropometry provided in NASA-STD-3001 [6]. Volumetric convex hulls were generated based on model marker trajectories and aggregated into geometric assemblies. These can be placed in models of vehicle designs to assess fit to protect for exercise as well as to adapt NGED exercise to fit available space. Preliminary findings from the collection indicate that the NGED prototype demonstrates significant adaptability across varying user anthropometrics and exercise types. The device showed consistent performance in load-bearing exercises, with subjects able to perform exercises effectively while maintaining proper biomechanical form. CONCLUSION NGED represents a forward-looking advancement in exercise capabilities for future space missions. In the future, this system can be used to capture valuable metrics (e.g., isometric mid-thigh pull for force output measurements, assessments of postural muscle strength, overall isometric strength). Its versatility in accommodating various exercises and user physiques, coupled with the ability to provide targeted biomechanical loading, makes it a promising approach for maintaining astronaut health during long-duration missions to the Moon and Mars. Future work will focus on refining the NGED based on initial biomechanical findings, leveraging the detailed insights provided by motion capture and analysis techniques. Particular emphasis will be placed on optimizing its use within the confined spaces of a LPR and other space habitats. This work contributes significantly to NASA's goals of supporting human health and performance in deep space exploration, paving the way for sustainable long-term presence beyond Low Earth Orbit through advanced, biomechanically-informed exercise solutions.

C Wang↗
NASA NTRS2017

Utilization of the International Space Station for Crew Autonomous Scheduling Test (CAST)

The United States space policy is evolving toward missions beyond low Earth orbit. In an effort to meet that policy, NASA has recognized Autonomous Mission Operations (AMO) as a valuable capability. Identified within AMO capabilities is the potential for autonomous planning and replanning during human spaceflight operations. That is allowing crew members to collectively or individually participate in the development of their own schedules. Currently, dedicated mission operations planners collaborate with international partners to create daily plans for astronauts aboard the International Space Station (ISS), taking into account mission requirements, ground rules, and various vehicle and payload constraints. In future deep space operations the crew will require more independence from ground support due to communication transmission delays. Furthermore, crew members who are provided with the capability to schedule their own activities are able to leverage direct experience operating in the space environment, and possibly maximize their efficiency. CAST (Crew Autonomous Scheduling Test) is an ISS investigation designed to analyze three important hypotheses about crew autonomous scheduling. First, given appropriate inputs, the crew is able to create and execute a plan in a reasonable period of time without impacts to mission success. Second, the proximity of the planner, in this case the crew, to the planned operations increases their operational efficiency. Third, crew members are more satisfied when given a role in plan development. This paper presents the results from a single astronaut test subject who participated in five CAST sessions. The details on the operational philosophy of CAST are discussed, including the approach to crew training, selection criteria for test days, and data collection methods. CAST is a technology demonstration payload sponsored by the ISS Research Science and Technology Office, and performed by experts in Mission Operations Planning from the Flight Operations Directorate at NASA Johnson Space Center, and researchers across multiple NASA centers. It is hoped the results of this investigation will guide NASA's implementation of autonomous mission operations for long duration human space missions to Mars and beyond.

Healy, Matthew↗
NASA NTRS2018

Discovery of Activities via Statistical Clustering of Fixation Patterns

Human behavior often consists of a series of distinct activities, each characterized by a unique pattern of interaction with the visual environment. This is true even in a restricted domain, such as a piloting an aircraft, where activities with distinct visual signatures might be things like communicating, navigating, and monitoring. We propose a novel analysis method for gaze-tracking data, to perform blind discovery of these hypothetical activities. The method is in some respects similar to recurrence analysis, but here we compare not individual fixations, but groups of fixations aggregated over a fixed time interval. The duration of this interval is a parameter that we will refer to as delta. We assume that the environment has been divided into a set of N different areas-of-interest (AOIs). For a given interval of time of duration delta, we compute the proportion of time spent fixating each AOI, resulting in an N-dimensional vector. These proportions can be converted to integer counts by multiplying by delta divided by the average fixation duration (another parameter that we fix at 280 milliseconds). We compare different intervals by computing the chi-square statistic. The p-value associated with the statistic is the likelihood of observing the data under the hypothesis that the data in the two intervals were generated by a single process with a single set of probabilities governing the fixation of each AOI. The method has been applied to approximately 100 hours of eye movement data collected from pilots in a high-fidelity B747 flight simulator, and the results have been compared to synthetic data in which the each activity is represented as first-order Markov process with random probabilities assigned to the AOIs. Randomly-generated synthetic activities can require thousands of fixations to be discriminated with statistical significance, while the human data can be clustered using averaging windows of some 10's of seconds, suggesting that the actual activities are much more narrowly focused than random Markov models.

activity analysis↗
NASA NTRSDate not supplied

Validation of Transient Spacecraft Refueling Model with Gateway Breadboard Test Data

The ability to refuel spacecraft on-orbit is a key enabling technology for deep space human exploration. On-orbit refueling requires priming a pressurized liquid propellant from a source tank into fluid transfer lines at vacuum conditions, which could result in excessive surge pressures beyond the system’s qualified operating limits and potentially damage hardware. Another source of potentially damaging surge pressures is the water hammer transient that occurs when the isolation valves are closed to pause or end the refueling operation. Therefore, it is imperative to employ numerical models during the development of flight hardware to parametrically characterize system performance over a wide range of operating conditions to minimize the risk of exceeding pressure limits during flight. Since rapid pressure transients can be difficult to model accurately, it is important to validate those models with test data. As part of the Gateway bipropellant refueling system development, a simplified fluidic breadboard system was created using water as a simulant for fuel to support early program risk reduction of refueling operations. The objectives of breadboard testing were to gather performance data to characterize and demonstrate critical refueling operations and to validate numerical models that can be extended to predicting flight system performance. A description of the breadboard test article and the results of numerical model validation is presented. The model is shown to have very good agreement with test data.

Refueling↗
DOE OSTI2014

Evaluation of the Lawrence Livermore Microbal Detection Array at the Statens Serum Institut CRADA No. TC02189

This was a collaborative effort between Lawrence Livermore National Security, LLC as manager and operator of Lawrence Livermore National Laboratory (LLNL) and Statens Serum Institut to evaluate and transition the Lawrence Livermore Microarray Detection Array (LLMDA) analysis software package, the Composite Likelihood Maximization method (CLiMax) to the SSI. The SSI is a public enterprise under the Danish Ministry of Health that operates a microbiology reference laboratory for the Danish population and analyzes tens to thousands of human clinical samples annually. SSI has been collaborating with the LLNL team for several years to use the LLMDA to analyze viral and bacterial infections from human clinical samples. The collaboration has resulted in two joint publications thus far, describing improvements to LLMDA sample preparation, and the utility of the LLMDA for detecting emerging viruses in clinical samples. Under our previous collaboration, SSI has performed LLMDA experiments at their facility and then transferred the raw LLMDA data to LLNL for analysis. SSI had purchased LLMDA microarrays directly from the manufacturer, Roche NimbleGen. The main purpose of the current collaboration was to adapt the CLiMax analysis software so that it could run on a computer located at SSI. Additional effort was budgeted for LLNL staff to assist SSI with the transition and the operation of the software. The primary deliverable is the CLiMax software, installed on a computer at SSI.

59 BASIC BIOLOGICAL SCIENCES↗