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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 595 records · Page 33

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NASA NTRSDate not supplied

Reach Performance Using Touchscreens Under G and Vibration Conditions

This presentation summarizes prior results from human-in-the-loop experiments that measured the accuracy and precision of human reaches to a touchscreen under a range of altered gravitational and vibrational conditions. From the data, this presentation proposes a method for estimating the worst-case reach accuracy and precision during lunar landings with an eye towards supporting engineering design decisions about human control interfaces and crew operations for lunar missions.

human performance↗

NASA NTRS1999

Human Reliability Analysis: An Overview

Human/process error is potentially a large contributor to failures of aerospace systems. For some systems, such as the space shuttle main engine, large amounts of data are available, and accurate failure rates can be determined empirically. For such systems, the human error is implicit in the empirical failure rate and does not need to be quantified separately. However, for other systems, such as the solid rocket boosters, large amounts of data are not available and the failure rates must be determined by more theoretical means. When empirical data is lacking, structural models and engineering judgment must be employed. In this case, the human/process error must be modeled explicitly. An extensive literature review was performed to determine what methods already exist for modeling human error for aerospace systems. No methods that apply directly were found, although there are a number of methods that have been developed specifically for the nuclear power industry that could probably be modified for space applications. The results of the literature review are presented, as well as recommendations for future research.

Navard, Sharon E.↗

DOE OSTI2018

EMT-related long non-coding RNA in hepatocellular carcinoma: A study with TCGA database

Highlights: • Integrated analysis identifies EMT-associated lncRNA in HCC. • Candidate lncRNA-associated genes are enriched in EMT-linked pathways. • LncRNA WDFY3-AS3, MIAT, and MEG3 contribute to the EMT phenotype of HCC cells. Accumulating evidence suggest that dysregulated expression of long non-coding RNA (lncRNA) plays a critical role in human tumorigenesis. However, little is known about the lncRNA implicated in the epithelial-to-mesenchymal transition (EMT) process. In this study, we performed data mining in The Cancer Genome Atlas (TCGA) hepatocellular carcinoma (HCC) data set and identified the a spectrum of differentially expressed lncRNAs implicated the EMT process of HCC, and functionally validated their roles in LM3 cells. Especially, lncRNA WDFY3-AS2-, LINC00472-, MIAT-, and MEG3-associated genes were significantly enriched in EMT-linked pathways. Loss-of-function study showed that genetic silencing of WDFY3-AS3, MIAT, and MEG3, but not LINC00472, resulted in reduced N-cadherin expression, cell migration, and cell invasion. Collectively, our results identify several lncRNAs that regulate the EMT process of HCC, which provides critical information for HCC tumorigenesis and potential therapeutic targets.

60 APPLIED LIFE SCIENCES↗

NASA NTRS1985

Automated Portable Test System (APTS) - A performance envelope assessment tool

The reliability and stability of microcomputer-based psychological tests are evaluated. The hardware, test programs, and system control of the Automated Portable Test System, which assesses human performance and subjective status, are described. Subjects were administered 11 pen-and-pencil and microcomputer-based tests for 10 sessions. The data reveal that nine of the 10 tests stabilized by the third administration; inertial correlations were high and consistent. It is noted that the microcomputer-based tests display good psychometric properties in terms of differential stability and reliability.

Kennedy, R. S.↗

NASA NTRS1994

Development of a prototype real-time automated filter for operational deep space navigation

Operational deep space navigation has been in the past, and is currently, performed using systems whose architecture requires constant human supervision and intervention. A prototype for a system which allows relatively automated processing of radio metric data received in near real-time from NASA's Deep Space Network (DSN) without any redesign of the existing operational data flow has been developed. This system can allow for more rapid response as well as much reduced staffing to support mission navigation operations.

Masters, W. C.↗

NASA NTRS1998

Procedures of Exercise Physiology Laboratories

This manual describes the laboratory methods used to collect flight crew physiological performance data at the Johnson Space Center. The Exercise Countermeasures Project Laboratory is a standard physiology laboratory; only the application to the study of human physiological adaptations to spaceflight is unique. In the absence of any other recently published laboratory manual, this manual should be a useful document staffs and students of other laboratories.

Bishop, Phillip A.↗

NASA NTRS2005

Scheme for Entering Binary Data Into a Quantum Computer

A quantum algorithm provides for the encoding of an exponentially large number of classical data bits by use of a smaller (polynomially large) number of quantum bits (qubits). The development of this algorithm was prompted by the need, heretofore not satisfied, for a means of entering real-world binary data into a quantum computer. The data format provided by this algorithm is suitable for subsequent ultrafast quantum processing of the entered data. Potential applications lie in disciplines (e.g., genomics) in which one needs to search for matches between parts of very long sequences of data. For example, the algorithm could be used to encode the N-bit-long human genome in only log2N qubits. The resulting log2N-qubit state could then be used for subsequent quantum data processing - for example, to perform rapid comparisons of sequences.

Williams, Colin↗

NASA NTRS2004

Role of EIS in Materials and Coatings Selection for NASA's Launch Facilities

Corrosion studies began at NASA's John F. Kennedy Space Center (KSC) in 1966, during the Gemini/Apollo Programs, with the evaluation of long-term anti-corrosion coatings for carbon steel structures. NASAIKSC's Atmospheric Exposure Test Site was established at that time on the beach near the launch pad. In the years that followed, numerous studies at the site have identified materials, coatings, and maintenance procedures for launch hardware and equipment exposed to the highly corrosive environment at the launch pad. The atmosphere at the launch pad is highly corrosive due to the proximity of the Atlantic Ocean, high heat from rocket exhaust, and since the introduction of the Space Shuttle, the acidic combustion products of the Solid Rocket Boosters (SRBs). Currently, NASAIKSC maintains about $2 billion worth of unique equipment and facilities, not including the orbiters, each valued at about $1.8 billion. Among the items: two launch complexes, two crawler transporters, three mobile launch platforms, and specialized testing equipment. Atmospheric exposure provides very valuable data but it takes a long time and relies on human visual inspection. NASA Technical Standard for Protective Coatings requires 18 months of good performance at the Atmospheric Exposure Test Site for preliminary approval and continued good performance for 5 years for final approval of a coating system. The use of electrochemical impedance spectroscopy (EIS) was introduced at KSC in 1989 as a supplement to the traditional dc electrochemical techniques and atmospheric exposure studies. This paper presents and overview of several projects in which EIS was used in order to select materials and coatings to be used at NASA's launch facilities [1-2].

Calle, Luz Marina↗

NASA NTRSDate not supplied

Crew Scheduling Performance

As NASA considers long-duration exploration missions (LDEMs), it is envisioned that crew will behave more autonomously as compared to low-Earth orbit missions. The necessary shift of Ops Planners’ complete management of scheduling and planning to provide flexibility for crew to manage their own schedule in real-time requires significant research and investigation in evaluation of concepts of operations, of software tools to support tasks, and of crew performance to complete scheduling tasks. Our research objective is to characterize the human performance envelope for the task of planning and scheduling (crew self-scheduling), develop countermeasures to mitigate adverse performance effects due to plan complexity, and inform performance standards and guidelines based on research results. In our efforts to understand and characterize scheduling performance of crew members, we have conducted subject matter expert interviews to obtain feedback on scheduling plan complexity drivers and plan goodness. Following the pilot study conducted last year, we designed a study and have begun remote human subject testing to evaluate non-expert human performance, workload, and situational awareness for the task of planning and scheduling. This study investigates the effects of the number and type of constraints on human performance, and the differences in scheduling metrics between scheduling and rescheduling tasks. Subject testing is currently in progress, and we aim to collect data from approximately thirty subjects. We will summarize the methods used and impacts of the number and type of scheduling constraints. We will also present lessons learned as well as relevant results of the study.

crew scheduling↗

NASA NTRS2020

Fit2Fly: A Proof of Concept for Testing the Commercial Feasibility of Unmanned Aerial System Operations

As autonomous Unmanned Aerial Systems (UAS) become more prevalent, improvements in airworthiness assessments, data security, establishing vehicle trust, and more will become necessary to make fleet operations of these systems routine. Currently, these are verified for every UAS vehicle through a time-intensive manual inspection performed by human individuals. This process becomes infeasible when introduced into large-scale operations, so the Fit2Fly project is attempting to address these concerns. Fit2Fly is a multi-year project with a large scope, so we chose to narrow our focus to building a proof-of-concept feasibility simulation in tandem with physical UAS demonstration. This work resulted in a software simulation capable of running asynchronous commercial operations with persistent data modeling in coordination with several autonomous drones using integrated radio and GPS configurations.

Ryan Bonk↗

NASA NTRS2013

An Assessment of Environmental Health Needs

Environmental health fundamentally addresses the physical, chemical, and biological risks external to the human body that can impact the health of a person by assessing and controlling these risks in order to generate and maintain a health-supportive environment. In manned spacecraft, environmental health risks are mitigated by a multi-disciplinary effort, employing several measures including active and passive controls, by establishing environmental standards (SMACs, SWEGs, microbial and acoustics limits), and through environmental monitoring. Human Health and Performance (HHP) scientists and Environmental Control and Life Support (ECLS) engineers consider environmental monitoring a vital component to an environmental health management strategy for maintaining a healthy crew and achieving mission success. ECLS engineers use environmental monitoring data to monitor and confirm the health of ECLS systems, whereas HHP scientists use the data to manage the health of the human system. Because risks can vary between missions and change over time, environmental monitoring is critical. Crew health risks associated with the environment were reviewed by agency experts with the goal of determining risk-based environmental monitoring needs for future NASA manned missions. Once determined, gaps in environmental health knowledge and technology, required to address those risks, were identified for various types of exploration missions. This agency-wide assessment of environmental health needs will help guide the activities/hardware development efforts to close those gaps and advance the knowledge required to meet NASA manned space exploration objectives. Details of the roadmap development and findings are presented in this paper.

Macatangay, Ariel V.↗

DOE OSTI2017

Parallel peak pruning for scalable SMP contour tree computation

As data sets grow to exascale, automated data analysis and visualisation are increasingly important, to intermediate human understanding and to reduce demands on disk storage via in situ analysis. Trends in architecture of high performance computing systems necessitate analysis algorithms to make effective use of combinations of massively multicore and distributed systems. One of the principal analytic tools is the contour tree, which analyses relationships between contours to identify features of more than local importance. Unfortunately, the predominant algorithms for computing the contour tree are explicitly serial, and founded on serial metaphors, which has limited the scalability of this form of analysis. While there is some work on distributed contour tree computation, and separately on hybrid GPU-CPU computation, there is no efficient algorithm with strong formal guarantees on performance allied with fast practical performance. Here in this paper, we report the first shared SMP algorithm for fully parallel contour tree computation, withfor-mal guarantees of O(lgnlgt) parallel steps and O(n lgn) work, and implementations with up to 10x parallel speed up in OpenMP and up to 50x speed up in NVIDIA Thrust.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

An Approach to Dependence Assessment in Human Reliability Analysis: Application of Lag and Linger Effects

Dependence assessment refers to an approach used in human reliability analysis (HRA) to adjust a human error probability (HEP) for the following action by considering the impact of the preceding action. It has been known to significantly affect the overall results of probabilistic safety assessment (PSA). If the dependence assessment is not adequate, the result could be unconvincing for explaining the operator failures in the context of PSA. To date, several methods and some recent research have identified suggestions for treating dependence issues in HRA; however, these are still exclusively based on the intrinsic approach of the Technique for Human Error Rate Prediction (THERP), an HRA method. THERP inevitably has a challenge with the subjectivity of expert evaluation as well as the requirement for PSA and HRA expertise with resource-intensive and time-consuming processes. This paper suggests an approach to dependence assessment that could not only minimize the influence of expert judgment, but also saves time to perform the analysis with reasonable manpower. It modifies existing HRA methods with considering lag and linger effects to apply dependence effects for them. Based on a representative HRA method, i.e., Standardized Plant Analysis Risk - HRA (SPAR-H), guidance for how to apply lag and linger effects for the HRA method is suggested. Then, an investigation is carried out to compare quantification results of the revised HRA method with that of the original approach based on experimental data.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2025

Comprehensive Evaluation of Agrivoltaics Research: Breadth, Depth, and Insights for Future Research

Agrivoltaics integrates agricultural production with solar energy generation to address challenges related to land use, food security, and renewable energy development. This study provides the most comprehensive evaluation to date of global agrivoltaic research, aiming to classify the literature, identify strengths and gaps, and guide future work. We systematically screened over 3000 English-language publications through 2023 for relevant agrivoltaic publications. A total of 670 studies were categorized in the InSPIRE Data Portal across five agrivoltaic activities and multiple hierarchical themes, including physical, biological, technological, social, and crosscutting domains. We found that research was concentrated on crop production, microclimate dynamics, and PV performance, with gaps in areas like human health, wildlife, policy, and standardized methodologies. Although the U.S. emphasizes animal grazing and habitat-based systems in practice, most U.S.-based studies focused disproportionately on crop production. The analysis revealed uneven geographic and topical representation and highlighted a lack of integrated, interdisciplinary approaches. This study concludes that while agrivoltaic research has grown rapidly, more coordinated efforts could support standardized data collection, address overlooked ecological and social impacts, and align research focus with real-world system implementation, ultimately improving the scalability and successful deployment of agrivoltaic systems.

14 SOLAR ENERGY↗

NASA NTRS2012

NASA-ONERA Collaboration on Human Factors in Aviation Accidents and Incidents

This is the first annual report jointly prepared by NASA and ONERA on the work performed under the agreement to collaborate on a study of the human factors entailed in aviation accidents and incidents, particularly focused on the consequences of decreases in human performance associated with fatigue. The objective of this agreement is to generate reliable, automated procedures that improve understanding of the levels and characteristics of flight-crew fatigue factors whose confluence will likely result in unacceptable crew performance. This study entails the analyses of numerical and textual data collected during operational flights. NASA and ONERA are collaborating on the development and assessment of automated capabilities for extracting operationally significant information from very large, diverse (textual and numerical) databases; much larger than can be handled practically by human experts.

Srivastava, Ashok N.↗

NASA NTRS2021

NASA Ames Fatigue Countermeasures Laboratory and AA FRMS - A Working Relationship

American Airlines and NASA Ames Research Center have a long-standing partnership to conduct human factors fatigue research in airline operations. Since 2016, using a mechanism known as a Space Act Agreement, NASA Ames’ Fatigue Countermeasures Laboratory has worked with the American’s Fatigue Risk Management team to gather sleep and alertness data from volunteer flight crew members. Operations studied include long-range transpacific flights, timing of inflight rest breaks during augmented flights, and rates of acclimation related to flights making theater changes. This mutually beneficial collaborative working arrangement allows American to conduct operations of specific interest under the FAA’s Alternative Means of Compliance process and provides NASA with a means to gather and analyze data that can be used to inform operational safety-related decisions. Earlier this year, results from the study of inflight rest breaks was published in the journal Aerospace Medicine and Human Performance. A total of 500 American pilots responded to a survey with landing crew reporting more and better-quality sleep during break 2 than break 3. Subsequent ratings of sleepiness and alertness at TOD were significantly better for crew who used break 2. Findings from this study were reported to the FAA leading to an inflight fatigue mitigation capability for many pilots in the industry. An upcoming study is to evaluate workload and alertness levels during Caribbean Turn (DFW-SJO-DFW) operations. For this study, the FRMS team and NASA will ask volunteers to collect data on sleep, workload, performance, and alertness using scientifically valid methods The information gained in this study will help inform how workload and fatigue interact with duty duration during short-haul, daytime operations.

in-flight rest↗

NASA NTRS2015

Detection of Operator Performance Breakdown as an Automation Triggering Mechanism

Performance breakdown (PB) has been anecdotally described as a state where the human operator "loses control of context" and "cannot maintain required task performance." Preventing such a decline in performance is critical to assure the safety and reliability of human-integrated systems, and therefore PB could be useful as a point at which automation can be applied to support human performance. However, PB has never been scientifically defined or empirically demonstrated. Moreover, there is no validated objective way of detecting such a state or the transition to that state. The purpose of this work is: 1) to empirically demonstrate a PB state, and 2) to develop an objective way of detecting such a state. This paper defines PB and proposes an objective method for its detection. A human-in-the-loop study was conducted: 1) to demonstrate PB by increasing workload until the subject reported being in a state of PB, and 2) to identify possible parameters of a detection method for objectively identifying the subjectively-reported PB point, and 3) to determine if the parameters are idiosyncratic to an individual/context or are more generally applicable. In the experiment, fifteen participants were asked to manage three concurrent tasks (one primary and two secondary) for 18 minutes. The difficulty of the primary task was manipulated over time to induce PB while the difficulty of the secondary tasks remained static. The participants' task performance data was collected. Three hypotheses were constructed: 1) increasing workload will induce subjectively-identified PB, 2) there exists criteria that identifies the threshold parameters that best matches the subjectively-identified PB point, and 3) the criteria for choosing the threshold parameters is consistent across individuals. The results show that increasing workload can induce subjectively-identified PB, although it might not be generalizable-only 12 out of 15 participants declared PB. The PB detection method based on signal detection analysis was applied to the performance data and the results showed that PB can be identified using the method, particularly when the values of the parameters for the detection method were calibrated individually.

multi-task environment↗

DOE OSTI2021

Explaining and predicting human behavior and social dynamics in simulated virtual worlds: reproducibility, generalizability, and robustness of causal discovery methods

Ground Truth program was designed to evaluate social science modeling approaches using simulation test beds with ground truth intentionally and systematically embedded to understand and model complex Human Domain systems and their dynamics Lazer et al. (Science 369:1060–1062, 2020). Our multidisciplinary team of data scientists, statisticians, experts in Artificial Intelligence (AI) and visual analytics had a unique role on the program to investigate accuracy, reproducibility, generalizability, and robustness of the state-of-the-art (SOTA) causal structure learning approaches applied to fully observed and sampled simulated data across virtual worlds. In addition, we analyzed the feasibility of using machine learning models to predict future social behavior with and without causal knowledge explicitly embedded. In this paper, we first present our causal modeling approach to discover the causal structure of four virtual worlds produced by the simulation teams—Urban Life, Financial Governance, Disaster and Geopolitical Conflict. Our approach adapts the state-of-the-art causal discovery (including ensemble models), machine learning, data analytics, and visualization techniques to allow a human-machine team to reverse-engineer the true causal relations from sampled and fully observed data. We next present our reproducibility analysis of two research methods team’s performance using a range of causal discovery models applied to both sampled and fully observed data, and analyze their effectiveness and limitations. We further investigate the generalizability and robustness to sampling of the SOTA causal discovery approaches on additional simulated datasets with known ground truth. Our results reveal the limitations of existing causal modeling approaches when applied to large-scale, noisy, high-dimensional data with unobserved variables and unknown relationships between them. We show that the SOTA causal models explored in our experiments are not designed to take advantage from vasts amounts of data and have difficulty recovering ground truth when latent confounders are present; they do not generalize well across simulation scenarios and are not robust to sampling; they are vulnerable to data and modeling assumptions, and therefore, the results are hard to reproduce. Finally, when we outline lessons learned and provide recommendations to improve models for causal discovery and prediction of human social behavior from observational data, we highlight the importance of learning data to knowledge representations or transformations to improve causal discovery and describe the benefit of causal feature selection for predictive and prescriptive modeling.

97 MATHEMATICS AND COMPUTING↗