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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 307 records · Page 17

FEA-Based Failure Analysis of Post-Buckled Composite Multi-Hat Stiffened Panel Under Static Compression

The aerospace industry uses composite multi-hat stiffened panels for skins because of their high strength-to-weight and stiffness-to-weight ratios. However, laminated composites with initial flaws are susceptible to delamination under buckling loads. The goal is to ensure damage initiation occurs past the buckled state, only stable damage progression at loads below the ultimate compressive load, and debonding failure past the ultimate compressive load. This approach reduces weight and addresses a potential design review for future aircraft repairs. The need exists to better understand damage initiation and growth mechanisms in composite structures while assisting in the design, analysis, and sustainment methods. Teflon inserts simulate damage defects during manufacturing, while barely visible impact helps capture human error during manufacturing. This work shows the interaction between the skin-stringer and ply-ply separations at the post-buckled state for both defect events using Abaqus Virtual Crack Closure Technique (VCCT). The initial configuration for the Teflon case was to leave the Teflon region unbonded, and the initial impact damage region approximation came from the experimental data and was considered the initial configuration. When compared against the experimental data produced through the NASA Advanced Composites Project (ACP), the present model captured damage transition from skin-hat to ply1-ply2. The model validations were within ~5% of the experimental data.

composite↗

Is "Sleepy Supervision" the New "Drowsy Driving"?

Human error has been implicated as a causal factor in a large proportion of road accidents. Automated driving systems purport to mitigate this risk, but self-driving systems that allow a driver to entirely disengage from the driving task also require the driver to monitor the environment and take control when necessary. Given that sleep loss impairs monitoring performance and there is a high prevalence of sleep deficiency in modern society, we hypothesized that supervising a self-driving vehicle would unmask latent sleepiness compared to manually controlled driving among individuals following their typical sleep schedules. We found that participants felt sleepier, had more involuntary transitions to sleep, had slower reaction times and more attentional failures, and showed substantial modifications in brain synchronization during and following an autonomous drive compared to a manually controlled drive. Our findings suggest that the introduction of partial self-driving capabilities in vehicles has the potential to paradoxically increase accident risk.

sleepiness↗

Quantitative Phenotypic Analysis of Arabidopsis Thaliana Grown in Microgravity Using Soap, an Applied Artificial Intelligence

Phenotypic analysis is an essential step in studying the gravitropic responses and gravitational stress experienced by plants grown in microgravity. Many of the phenotypic traits analyzed in gravitropism studies, such as root length, leaf area, secondary root count, and number of root hairs, currently rely upon manual measurement methods for quantification. However, new advances in data analysis technology using artificial intelligence offer an opportunity for more efficient phenotypic analysis and a reduction of time spent in the data collection phase. In this project, the ability of a new artificially intelligent data collection software, SOAP (Simple Object Access Protocol), to collect and quantify phenotypic traits of Arabidopsis thaliana will be assessed. This project will test the measurements taken by an initial draft of the software. SOAP will take measurements of shoot length, a key phenotype used to assess A. thaliana stress response when grown in microgravity conditions. Shoot length measurements made by SOAP will be compared against a series of manual shoot length measurements. The comparison between the two methods of data measurement will provide valuable insight into the relative accuracy of SOAP and the margin of human error when conducting lab measurements.

Arabidopsis↗

Limitations and Feasibility of Mini X-Ray Devices in Space Environments

LIMITATIONS AND FEASIBILITY OF MINI X-RAY DEVICES IN SPACE ENVIRONMENTS As space exploration advances toward long-duration missions, reliable medical diagnostic tools become increasingly critical. The miniature x-ray (XR) technology demonstrations by the Exploration Medical Capability (ExMC) and the Exploration Medical Integrated Product Team (XMIPT) aim to assess the feasibility and utility of miniature XR devices in spaceflight. This abstract explores the limitations of current miniature XR systems, the challenges of training crew members, the potential role of clinical decision support systems (CDSS), and the feasibility of ground-based image interpretation. We also propose the integration of miniature XR into other ExMC efforts aimed at identifying the capabilities and resources needed for future exploration class missions. One of the primary challenges with miniature XR devices is the ability to achieve specific anatomical views, particularly in the confined and weightless conditions of a spacecraft. Operators may struggle to acquire diagnostic-quality images when space is limited for proper patient positioning and the volume of the imaging device. Since space radiation and detector limitations may further impact image quality, the flexibility of the operating procedures of these devices will be critical for their success in space applications. CHALLENGES IN TRAINING CREW TO OPERATE IMAGING DEVICES Training in the skills necessary to acquire diagnostic-quality scans may be a barrier for non-clinician crewmembers. The curriculum developed for crew medical officers (CMOs) will require simplification and adaptation to fit into the highly truncated pre-flight training period. Therefore, hands-on familiarization and simulation, both pre-flight and just-in-time training during missions, will be crucial to ensuring the crew can operate the devices in real-life situations. The ability to adjust acquisition parameters must be simplified or made automatic through exam selections on equipment user interfaces, and subject and operator positioning should be assisted with laser guidance and pictorial guides. POTENTIAL FOR CDSS OR ARTIFICIAL INTELLIGENCE (AI)-ASSISTED CDSS CDSS and AI-assisted CDSS offer significant promise in assisting crew members with limited medical training. These systems could provide real-time feedback on image quality and interpretation, helping to mitigate the risks of human error during space missions. Integrating procedural guidance tools, such as virtual and augmented reality, will support crewmembers in accurately positioning patients and obtaining high-quality images. However, the success of such systems will depend on the development of robust training datasets, integration with spaceflight-rated hardware, and the medical decision-making capabilities of operators. FEASIBILITY OF GROUND INTERPRETATION AND DATA TRANSMISSION Reliance on ground-based interpretation may prove difficult for acute care during exploration class-missions due to delays in transmission with increasing distance from Earth or complete communication blackout periods. In such instances where immediate interpretation for clinical intervention is required, crew must be able to interpret the images independently or utilize AI-based assistance to do so. File sizes for XR exams can also be large if numerous images are acquired and bandwidth constraints may limit data transmissions for both radiography and ultrasound exams. FUTURE WORK AND INTEGRATION INTO THE EVIDENCE LIBRARY Future work proposes integrating miniature XR devices into NASA’s Evidence Library to address medical conditions identified as significant contributors to crew morbidity and mortality. The possibility of combining miniature XR with other imaging modalities, such as ultrasound devices, is also under investigation. In conclusion, while miniature XR technology holds potential for extraterrestrial medical systems, there are significant challenges to overcome. Training, integration of AI tools, dedicated exam protocols for microgravity, and improved data transmission systems will be key to realizing the full benefits of miniature XR technology in space.

A M Nelson↗

Applying Generative-AI to NASA Documentation and Processes

This research and development project leverages generative-AI to assist in the generation of software process documentation based on NASA standards. By utilizing fine-tuned AI models, the proposed system will analyze NASA's software guidelines, helping to translate them into well-structured, compliant process documents. This assistance can reduce the manual effort required to produce such documentation, enhance consistency, and assure alignment with NASA's stringent software development and operational requirements. In addition to assisting in the generation of software process documentation, the project explores how generative-AI can help create audit checklists as well as assess the compliance of NASA provider documentation against applicable NASA standards. This approach would support the compliance auditing process, providing real-time insights and assessments. The intended result will be a streamlined process, potentially including a Python-based tool and database, that improves audit efficiency, reduces human error, lowers manpower costs and required manhours, and assures continuous compliance with NASA and industry evolving standards for safety-critical software development. Future task might be to investigate the software industry approach and standards for potential collaboration.

NASA Standards↗

NUTRON NESHAPs Dashboard

My project aims to enhance the Nuclear Material Tracking Application (NUTRON) software by integrating a tool for the National Emission Standards for Hazardous Air Pollutants (NESHAP) emissions calculations and presenting this data on a dashboard. Inefficiencies in the current NESHAP calculation process were addressed, which will result in more timely regulatory compliance efforts. Key improvements include revising the transfer request system, incorporating effective dose calculations, and developing a data visualization dashboard into NUTRON. The project involved creating a wireframe, preparing an Engineering Calculations and Analysis Report (ECAR), stakeholder meetings, and providing supplemental documentation. Key findings indicate that the proposed modifications will streamline the NESHAP calculation process, reduce human error, and provide REC personnel with accurate and timely data for material use determinations and dose estimations. Future work focuses on completing the NUTRON modifications and fully integrating the new features, ensuring a more efficient and reliable system for tracking and reporting nuclear material transfers.

99 - GENERAL AND MISCELLANEOUS↗

From Obsolete to Optimal (ATR Demineralized Water System)

My project was migrating a Human-Machine Interface (HMI) and Programmable Logic Controller (PLC) program from legacy software to a modern platform, enhancing operational efficiency and eliminating unsupported, obsolete equipment. Initially, I used a migration tool to transfer the programs to the new software, then manually updated variables to align with the new PLC. I optimized the PLC code by leveraging new scaling features in the I/O cards, removing over 45 obsolete rungs, and enhancing clarity with functional tag aliases. Next, I modernized the HMI's visuals with an updated color scheme and 3D buttons. I developed multiple interface versions iteratively refining them based on operator feedback. I also designed and created a dedicated "Rounds" screen incorporating insights from a previous intern’s project to streamline daily rounds. To improve clarity, consistency, and efficiency I redesigned the entire interface. Adding visual indicators to enhance operational awareness: red is used for values outside normal specifications, green for normal operating modes, yellow for manual mode, and grey for offline units. Additionally, I added a dynamic visual representation of tank levels, creating PLC logic to show the level in inches as well as inches and feet. I then incorporated a navigation sidebar to facilitate efficient screen transitions. Risk of human error was mitigated by defining narrow input ranges for tank level shutoff and password protecting setpoint changes. I also fixed issues with datatypes that caused inaccuracies in the original code. Overall, this comprehensive upgrade significantly enhanced the HMI's functionality, user experience, and operational reliability.

47 - OTHER INSTRUMENTATION↗

A Conceptual Framework for Predicting Error in Complex Human-Machine Environments

We present a Goals, Operators, Methods, and Selection Rules-Model Human Processor (GOMS-MHP) style model-based approach to the problem of predicting human habit capture errors. Habit captures occur when the model fails to allocate limited cognitive resources to retrieve task-relevant information from memory. Lacking the unretrieved information, decision mechanisms act in accordance with implicit default assumptions, resulting in error when relied upon assumptions prove incorrect. The model helps interface designers identify situations in which such failures are especially likely.

Freed, Michael↗

Biocybernetic Closed-Loop System for Mitigating Hazardous States of Awareness

The past century of passenger flight has seen continuous improvement in aviation safety by the aerospace industry. However, while commercial aviation accident rates have continued to decline, human error-related incident and accident rates remain remarkably constant across all types of aviation (Shappell, et al., 2007). Unfortunately, this level of human error is unacceptable when considering projections for increased traffic volume (FAA, 2009), and is likely to yield more incidents and accidents unless a more complete understanding of operator error is achieved and remediations are implemented. One area of interest highlighted by researchers is Hazardous States of Awareness (HSAs) that can result from deficiencies in the design and inappropriate use of human-machine interfaces. Identifying and mitigating HSAs is critical for reducing operator errors. One promising approach uses psychophysiological measures which enable automated systems to adapt to the operator?s state and modify modes of operation to support optimal human performance (Scerbo, 2007). This paper will survey previous research and describe future directions for the application of psychophysiological measures of operators derived from cortical and autonomic assessment to perform real-time adaptive modulation of human-automation task mode mixes. The authors will present a summary of previous work done at NASA LaRC and Old Dominion University using a Psychophysiologically Adaptive System (PAS) in which the level of automation of the NASA Multi-Attribute Task Battery was modulated based on Engagement Indices derived from the users? electroencephalogram (Pope, Bogart, & Bartolome, 1995; for review see, Scerbo, Freeman, & Mikulka, 2003). Future theoretical and methodological directions for this type of closed-loop research will be discussed. Specifically, the capacity for this type of PAS to maintain effective operator state and to enable validation of candidate physiological indices will be described. Consideration will also be given to critical system characteristics (e.g., engagement indices, methods for invoking changes among system states, individual differences among users, etc.) that have been or still need to be studied. The potential of the PAS approach for interactive system design and prototyping will also be described. Examples of adaptive automation flight deck concepts in recent experiments will be highlighted and discussed.

Chad L Stephens↗

Effect of contrast on human speed perception

This study is part of an ongoing collaborative research effort between the Life Science and Human Factors Divisions at NASA ARC to measure the accuracy of human motion perception in order to predict potential errors in human perception/performance and to facilitate the design of display systems that minimize the effects of such deficits. The study describes how contrast manipulations can produce significant errors in human speed perception. Specifically, when two simultaneously presented parallel gratings are moving at the same speed within stationary windows, the lower-contrast grating appears to move more slowly. This contrast-induced misperception of relative speed is evident across a wide range of contrasts (2.5-50 percent) and does not appear to saturate (e.g., a 50 percent contrast grating appears slower than a 70 percent contrast grating moving at the same speed). The misperception is large: a 70 percent contrast grating must, on average, be slowed by 35 percent to match a 10 percent contrast grating moving at 2 deg/sec (N = 6). Furthermore, it is largely independent of the absolute contrast level and is a quasilinear function of log contrast ratio. A preliminary parametric study shows that, although spatial frequency has little effect, the relative orientation of the two gratings is important. Finally, the effect depends on the temporal presentation of the stimuli: the effects of contrast on perceived speed appears lessened when the stimuli to be matched are presented sequentially. These data constrain both physiological models of visual cortex and models of human performance. We conclude that viewing conditions that effect contrast, such as fog, may cause significant errors in speed judgments.

Stone, Leland S.↗

Human-computer interaction in multitask situations

Human-computer interaction in multitask decisionmaking situations is considered, and it is proposed that humans and computers have overlapping responsibilities. Queueing theory is employed to model this dynamic approach to the allocation of responsibility between human and computer. Results of simulation experiments are used to illustrate the effects of several system variables including number of tasks, mean time between arrivals of action-evoking events, human-computer speed mismatch, probability of computer error, probability of human error, and the level of feedback between human and computer. Current experimental efforts are discussed and the practical issues involved in designing human-computer systems for multitask situations are considered.

Rouse, W. B.↗

Human Factors Process Task Analysis Liquid Oxygen Pump Acceptance Test Procedure for the Advanced Technology Development Center

A process task analysis effort was undertaken by Dynacs Inc. commencing in June 2002 under contract from NASA YA-D6. Funding was provided through NASA's Ames Research Center (ARC), Code M/HQ, and Industrial Engineering and Safety (IES). The John F. Kennedy Space Center (KSC) Engineering Development Contract (EDC) Task Order was 5SMA768. The scope of the effort was to conduct a Human Factors Process Failure Modes and Effects Analysis (HF PFMEA) of a hazardous activity and provide recommendations to eliminate or reduce the effects of errors caused by human factors. The Liquid Oxygen (LOX) Pump Acceptance Test Procedure (ATP) was selected for this analysis. The HF PFMEA table (see appendix A) provides an analysis of six major categories evaluated for this study. These categories include Personnel Certification, Test Procedure Format, Test Procedure Safety Controls, Test Article Data, Instrumentation, and Voice Communication. For each specific requirement listed in appendix A, the following topics were addressed: Requirement, Potential Human Error, Performance-Shaping Factors, Potential Effects of the Error, Barriers and Controls, Risk Priority Numbers, and Recommended Actions. This report summarizes findings and gives recommendations as determined by the data contained in appendix A. It also includes a discussion of technology barriers and challenges to performing task analyses, as well as lessons learned. The HF PFMEA table in appendix A recommends the use of accepted and required safety criteria in order to reduce the risk of human error. The items with the highest risk priority numbers should receive the greatest amount of consideration. Implementation of the recommendations will result in a safer operation for all personnel.

Diorio, Kimberly A.↗

Human Contribution to Safety: Human Performance is Not Just About Error

- When the only data that are available are about human failure, then data-driven designs only consider that humans fail. - Designs intended to "protect" the system from "error-prone" humans can design-out the capability for humans to effectively intervene/adapt, which is a far more common behavior.

Jon Holbrook↗

Human Reliability and the Cost of Doing Business

Most businesses recognize that people will make mistakes and assume errors are just part of the cost of doing business, but does it need to be? Companies with high risk, or major consequences, should consider the effect of human error. In a variety of industries, Human Errors have caused costly failures and workplace injuries. These have included: airline mishaps, medical malpractice, administration of medication and major oil spills have all been blamed on human error. A technique to mitigate or even eliminate some of these costly human errors is the use of Human Reliability Analysis (HRA). Various methodologies are available to perform Human Reliability Assessments that range from identifying the most likely areas for concern to detailed assessments with human error failure probabilities calculated. Which methodology to use would be based on a variety of factors that would include: 1) how people react and act in different industries, and differing expectations based on industries standards, 2) factors that influence how the human errors could occur such as tasks, tools, environment, workplace, support, training and procedure, 3) type and availability of data and 4) how the industry views risk & reliability influences ( types of emergencies, contingencies and routine tasks versus cost based concerns). The Human Reliability Assessments should be the first step to reduce, mitigate or eliminate the costly mistakes or catastrophic failures. Using Human Reliability techniques to identify and classify human error risks allows a company more opportunities to mitigate or eliminate these risks and prevent costly failures.

DeMott, Diana↗

Reliability Analysis and Standardization of Spacecraft Command Generation Processes

center dot In order to reduce commanding errors that are caused by humans, we create an approach and corresponding artifacts for standardizing the command generation process and conducting risk management during the design and assurance of such processes. center dot The literature review conducted during the standardization process revealed that very few atomic level human activities are associated with even a broad set of missions. center dot Applicable human reliability metrics for performing these atomic level tasks are available. center dot The process for building a "Periodic Table" of Command and Control Functions as well as Probabilistic Risk Assessment (PRA) models is demonstrated. center dot The PRA models are executed using data from human reliability data banks. center dot The Periodic Table is related to the PRA models via Fault Links.

human errors.↗

Model-based VQ for image data archival, retrieval and distribution

An ideal image compression technique for image data archival, retrieval and distribution would be one with the asymmetrical computational requirements of Vector Quantization (VQ), but without the complications arising from VQ codebooks. Codebook generation and maintenance are stumbling blocks which have limited the use of VQ as a practical image compression algorithm. Model-based VQ (MVQ), a variant of VQ described here, has the computational properties of VQ but does not require explicit codebooks. The codebooks are internally generated using mean removed error and Human Visual System (HVS) models. The error model assumed is the Laplacian distribution with mean, lambda-computed from a sample of the input image. A Laplacian distribution with mean, lambda, is generated with uniform random number generator. These random numbers are grouped into vectors. These vectors are further conditioned to make them perceptually meaningful by filtering the DCT coefficients from each vector. The DCT coefficients are filtered by multiplying by a weight matrix that is found to be optimal for human perception. The inverse DCT is performed to produce the conditioned vectors for the codebook. The only image dependent parameter used in the generation of codebook is the mean, lambda, that is included in the coded file to repeat the codebook generation process for decoding.

Manohar, Mareboyana↗

Improved Quick Disconnect (QD) Interface Through Fail Safe Parts Identification

An extensive review of existing Quick Disconnects (QDs) mating and demating operations was performed to determine which shuttle part interface identifications and procedures contribute to human factor errors. The research methods used consisted of interviews with engineers and technicians, examination of incident reports, critiques of video and audio tapes of QD operations, and attendance of a Hyper QD operational course. The data strongly suggests that there are inherit human factor errors involved in QD operations. To promote fail-safe operations, QD interface problem areas and recommendations were outlined and reviewed. It is suggested that dialogue, investigations and recommendations continue.

Blanch-Payne, Evelyn↗

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.↗