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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 1,297 records · Page 72

All sources NASA NTRS DOE OSTI

NASA NTRS2020

ISEE System Technical Report

The Immersive Simulations and Engineering Environment (ISEE) Laboratory at Kennedy Space Center is a tool used to assist with operation simulation, for Human Factors operation activities, assisting future missions. The simulations created are important because they ensure that simulated operations are performed for customers, to assist with requirements. Simultaneously, each simulation will allow stakeholders to determine any and all risk associated with the Human Factors involved in a specific assignment. My internship consists of multiple project elements. The first of which, was to assist the Integrations branch chief in developing a growth rate algorithm proof. The integral part of this project, involved learning to powerup and perform the operational procedures of the ISEE lab, capturing and creating characters used in the CAD model virtual environment. In doing so, this led to use the software to model and 3D print screw cap structures for mock-up. The structures will be used to manipulate weight change out used in mock-up design and construction. These structures will also be used in future mock-up models constructed in the lab.

Darryl A J Minor↗

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. 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. Since priming transients are 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 system and the results of numerical model validation is presented. The model is shown to have very good agreement with test data.

Brian S Lusby↗

DOE OSTI2018

Deep Learning for Unsupervised Insider Threat Detection in Structured Cyber Security Data Streams

Analysis of an organization's computer network activity is a key component of early detection and mitigation of insider threat, a growing concern for many organizations. Raw system logs are a prototypical example of streaming data that can quickly scale beyond the cognitive power of a human analyst. As a prospective filter for the human analyst, we present an online unsupervised deep learning approach to detect anomalous network activity from system logs in real time. Our models decompose anomaly scores into the contributions of individual user behavior features for increased interpretability to aid analysts reviewing potential cases of insider threat. Using the CERT Insider Threat Dataset v6.2 and threat detection recall as our performance metric, our novel deep and recurrent neural network models outperform Principal Component Analysis, Support Vector Machine and Isolation Forest based anomaly detection baselines. For our best model, the events labeled as insider threat activity in our dataset had an average anomaly score in the 95.53 percentile, demonstrating our approach's potential to greatly reduce analyst workloads.

Deep Learning, Insider Threat↗

NASA NTRS2000

Visual motion integration for perception and pursuit

To examine the relationship between visual motion processing for perception and pursuit, we measured the pursuit eye-movement and perceptual responses to the same complex-motion stimuli. We show that humans can both perceive and pursue the motion of line-figure objects, even when partial occlusion makes the resulting image motion vastly different from the underlying object motion. Our results show that both perception and pursuit can perform largely accurate motion integration, i.e. the selective combination of local motion signals across the visual field to derive global object motion. Furthermore, because we manipulated perceived motion while keeping image motion identical, the observed parallel changes in perception and pursuit show that the motion signals driving steady-state pursuit and perception are linked. These findings disprove current pursuit models whose control strategy is to minimize retinal image motion, and suggest a new framework for the interplay between visual cortex and cerebellum in visuomotor control.

NASA Center ARC↗

DOE OSTI2024

4th Big Data for Nuclear Power Plants Workshop 2023

The Ohio State University and Idaho National Laboratory organized the 4 th Big Data for Nuclear Power Plants Workshop in November, 2023 in Columbus, Ohio. Workshop topics were chosen to understand the challenges and gaps that need to be addressed to maximize the impact of data on the nuclear industry, as well as the associated applications and risks. Discussions were focused around six specific application areas: Operation and Maintenance; Machine Learning in Nuclear Materials and Advanced Manufacturing; Cybersecurity; High-Performance Computing and Massive Computation; Big Data and Digital Twins; and Nuclear Non-Proliferation. The opportunities, challenges, and risks identified in the six focus areas explored in this workshop are diverse, but some common themes emerge, such as the importance of data integrity, quality, coverage, privacy, and traceability. Big data and AI/ML tools can be leveraged to reduce costs, optimize human tasking, and reduce human error across various application areas. In order for the nuclear industry to benefit from big data and advanced analytic capabilities, it is essential to address challenges and risks, such as data privacy, model reliability, and computational resource availability. Learning from other industries that have successfully implemented big data and AI/ML technologies, like the aerospace industry, can help the nuclear industry successfully integrate these technologies.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2024

Two MCNP Models for Computational Performance Benchmarking

The purpose of this report is to describe two non-trivial MCNP models and execution configurations that are suitable to characterizing computational performance. To that end, this report uses a constructive solid geometry (CSG) representation of the Oak Ridge National Laboratory (ORNL) Pool Critical Assembly (PCA) [1–3] to perform a k-eigenvalue calculation and an unstructured mesh (UM) representation of the International Commission on Radiological Protection (ICRP) publication 145 (ICRP145) male human phantom [4, 5] to perform a fixed-source calculation assuming that a 1 MeV photon source is distributed throughout the phantom’s liver.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

Demeter calibration and uncertainty analysis

Demeter is a community spatial downscaling model that disaggregates land use and land cover changes projected by integrated human-Earth system models. Demeter has not been intensively calibrated, and we still lack a good knowledge about its sensitivity to key parameters and the parameter uncertainties. We used long-term global satellite-based land cover records to calibrate key Demeter parameters. The results identified the optimal parameter values and showed that the parameterization substantially improved the model’s performance. The parameters of intensification ratio and selection threshold were the most sensitive and needed to be carefully tuned, especially for regional applications. Further, small parameter uncertainties after calibration can be inflated when propagated into future scenarios, suggesting that users should consider the parameterization equifinality to better account for the uncertainties in the Demeter downscaled products. Our study provides a key reference for Demeter users, and ultimately contribute to reducing the uncertainties in Earth system model simulations.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1975

A multiloop approach to modeling motion sensor responses

By using a least squares identification algorithm, a multiloop approach is taken to effectively model the response characteristics of the motion sensors. The inputs to the model include the possible sources of information provided to the human via his motion sensing system. One input models the response of the angular acceleration sensors (second derivative of position) and the second input models the response of the linear sensors (sine of position). The third input is the visual display error provided to the human in the closed loop tracking experiment. Data from a roll axis tracking simulation were analyzed. The major source of pilot lead under the motion mode of operation is discussed for control of plants in which motion information improved performance and in which there was no improvement in performance.

Junker, A. M.↗

NASA NTRS2014

Pharmacokinetic Modeling of Intranasal Scopolamine in Plasma Saliva and Urine

An intranasal gel formulation of scopolamine (INSCOP) was developed for the treatment of Space Motion Sickness. The bioavailability and pharmacokinetics (PK) were evaluated under the Food and Drug Administration guidelines for clinical trials for an Investigative New Drug (IND). The aim of this project was to develop a PK model that can predict the relationship between plasma, saliva and urinary scopolamine concentrations using data collected from the IND clinical trial with INSCOP. METHODS: Twelve healthy human subjects were administered three dose levels (0.1, 0.2 and 0.4 mg) of INSCOP. Serial blood, saliva and urine samples were collected between 5 min to 24 h after dosing and scopolamine concentrations measured by using a validated LC-MS-MS assay. Pharmacokinetic Compartmental models, using actual dosing and sampling times, were built using Phoenix (version 1.2). Model discrimination was performed, by minimizing the Akaike Information Criteria (AIC), maximizing the coefficient of determination (r²) and by comparison of the quality of fit plots. RESULTS: The best structural model to describe scopolamine disposition after INSCOP administration (minimal AIC =907.2) consisted of one compartment for plasma, saliva and urine respectively that were inter-connected with different rate constants. The estimated values of PK parameters were compiled in Table 1. The model fitting exercises revealed a nonlinear PK for scopolamine between plasma and saliva compartments for K21, Vmax and Km. CONCLUSION: PK model for INSCOP was developed and for the first time it satisfactorily predicted the PK of scopolamine in plasma, saliva and urine after INSCOP administration. Using non-linear PK yielded the best structural model to describe scopolamine disposition between plasma and saliva compartments, and inclusion of non-linear PK resulted in a significant improved model fitting. The model can be utilized to predict scopolamine plasma concentration using saliva and/or urine data that allows non-invasive assessment of pharmacotherapeutics of scopolamine in space and other remote environments without requiring blood sampling.

Wu, L.↗

NASA NTRS2016

Post-Flight Analysis of GPSR Performance During Orion Exploration Flight Test 1

On 5 December 2014, the first test flight of the Orion Multi-Purpose Crew Vehicle executed a unique and challenging flight profile including an elevated re-entry velocity and steeper flight path angle to envelope lunar re-entry conditions. A new navigation system including a single frequency (L1) GPS receiver was evaluated for use as part of the redundant navigation system required for human space flight. The single frequency receiver was challenged by a highly dynamic flight environment including flight above low Earth orbit, as well as single frequency operation with ionospheric delay present. This paper presents a brief description of the GPS navigation system, an independent analysis of flight telemetry data, and evaluation of the GPSR performance, including evaluation of the ionospheric model employed to supplement the single frequency receiver. Lessons learned and potential improvements will be discussed.

Barker, Lee↗

NASA NTRSDate not supplied

Multifaceted Considerations for Fission Surface Power Radiation Shielding Design

The purpose of the Fission Surface Power (FSP) nuclear system is to provide energy on the Moon and Mars for supporting their exploration and colonization. The FSP design and deployment can leverage the past research and development work in areas, such as reactor design, but such crucial components as radiation shielding and instrumentation still need material and manufacturing studies, modeling, and testing. The shielding components are needed for the protection of humans, electronics, and sensitive components. They are essential system components, but they are often the heaviest components of the system for which each kilogram matters. Different material combinations and layouts are possible. The studies presented were focused on the evaluation of several options. The initial analysis included their performance assessment, initial temperature distribution evaluation and manufacturability considerations. Several feasible shield design options were identified and discussed in this paper, as well.

Fission Surface Power↗

NASA NTRS2011

Gravito-Inertial Force Resolution in Perception of Synchronized Tilt and Translation

Natural movements in the sagittal plane involve pitch tilt relative to gravity combined with translation motion. The Gravito-Inertial Force (GIF) resolution hypothesis states that the resultant force on the body is perceptually resolved into tilt and translation consistently with the laws of physics. The purpose of this study was to test this hypothesis for human perception during combined tilt and translation motion. EXPERIMENTAL METHODS: Twelve subjects provided verbal reports during 0.3 Hz motion in the dark with 4 types of tilt and/or translation motion: 1) pitch tilt about an interaural axis at +/-10deg or +/-20deg, 2) fore-aft translation with acceleration equivalent to +/-10deg or +/-20deg, 3) combined "in phase" tilt and translation motion resulting in acceleration equivalent to +/-20deg, and 4) "out of phase" tilt and translation motion that maintained the resultant gravito-inertial force aligned with the longitudinal body axis. The amplitude of perceived pitch tilt and translation at the head were obtained during separate trials. MODELING METHODS: Three-dimensional mathematical modeling was performed to test the GIF-resolution hypothesis using a dynamical model. The model encoded GIF-resolution using the standard vector equation, and used an internal model of motion parameters, including gravity. Differential equations conveyed time-varying predictions. The six motion profiles were tested, resulting in predicted perceived amplitude of tilt and translation for each. RESULTS: The modeling results exhibited the same pattern as the experimental results. Most importantly, both modeling and experimental results showed greater perceived tilt during the "in phase" profile than the "out of phase" profile, and greater perceived tilt during combined "in phase" motion than during pure tilt of the same amplitude. However, the model did not predict as much perceived translation as reported by subjects during pure tilt. CONCLUSION: Human perception is consistent with the GIF-resolution hypothesis even when the gravito-inertial force vector remains aligned with the body during periodic motion. Perception is also consistent with GIF-resolution in the opposite condition, when the gravito-inertial force vector angle is enhanced by synchronized tilt and translation.

Wood, Scott J.↗

DOE OSTI2024

Estimating the Contributions to Human Error Probability from the Convolution of the Distribution of Time Available and Time Required

As part of their duties, Human Reliability Analysis must often evaluate if crews in nuclear power plants (NPPs) can complete tasks associated with a human-failure event within time limits. For example, the time required in NPP scenarios is determined by systematic and structured walkthroughs, feasibility studies, recorded times from training exercises, and interviews with experienced operators and experts. Typically, a point estimate is derived for the estimate (mean, maximum, or 95th percentile of time required). Using point-estimate values can mask the risk associated with variability among crews, plant conditions and set-up, environmental conditions, and other impact factors under which these actions are executed. While point estimates for time required and time available have served the industry well, without considering the uncertainty they could lead to biased understanding about the risk. The Integrated Human Event Analysis System - General Methodology (IDHEAS-G) model (developed by the US Nuclear Regulatory Commission, NRC) for human error probability calculates human error probability by summing two probabilities: insufficient time and cognitive error. As such, the model takes a more holistic approach by considering the full distributions for time required and time available to calculate the human error probability because the time available to complete the task is insufficient. In this study, we expand on the work of the NRC and discuss methods for estimating these time considerations. For example, for the time required, the impact of Performance Influencing Factors (PIFs) on the distribution was divided into impacts that are aleatory in nature, such as crew-to-crew variability, and those that are epistemic (i.e., the PIFs). Starting with the factors that introduce aleatory uncertainty, a first-order distribution was developed from a large set of time required (i.e., NPP task completion times) data for the range of operator actions that occur in the NPP control room under simulated accident conditions. The first-order distribution can then be adjusted to account for epistemic uncertainty using research associated with the impact of applicable PIFs on the time required. We also develop guidance for analysts to address the probability distributions for the time available. The guidance we developed on how to estimate time required and time available distributions is based on the identification of pertinent research and data, data analyses, and expert knowledge elicitation.

human error probability, human performance, time e↗

NASA NTRS1995

A user-system interface agent

Agent-based technologies answer to several challenges posed by additional information processing requirements in today's computing environments. In particular, (1) users desire interaction with computing devices in a mode which is similar to that used between people, (2) the efficiency and successful completion of information processing tasks often require a high-level of expertise in complex and multiple domains, (3) information processing tasks often require handling of large volumes of data and, therefore, continuous and endless processing activities. The concept of an agent is an attempt to address these new challenges by introducing information processing environments in which (1) users can communicate with a system in a natural way, (2) an agent is a specialist and a self-learner and, therefore, it qualifies to be trusted to perform tasks independent of the human user, and (3) an agent is an entity that is continuously active performing tasks that are either delegated to it or self-imposed. The work described in this paper focuses on the development of an interface agent for users of a complex information processing environment (IPE). This activity is part of an on-going effort to build a model for developing agent-based information systems. Such systems will be highly applicable to environments which require a high degree of automation, such as, flight control operations and/or processing of large volumes of data in complex domains, such as the EOSDIS environment and other multidisciplinary, scientific data systems. The concept of an agent as an information processing entity is fully described with emphasis on characteristics of special interest to the User-System Interface Agent (USIA). Issues such as agent 'existence' and 'qualification' are discussed in this paper. Based on a definition of an agent and its main characteristics, we propose an architecture for the development of interface agents for users of an IPE that is agent-oriented and whose resources are likely to be distributed and heterogeneous in nature. The architecture of USIA is outlined in two main components: (1) the user interface which is concerned with issues as user dialog and interaction, user modeling, and adaptation to user profile, and (2) the system interface part which deals with identification of IPE capabilities, task understanding and feasibility assessment, and task delegation and coordination of assistant agents.

Wakim, Nagi T.↗

NASA NTRS2010

The Concept and Analytical Investigation of CO2 and Steam Co-Electrolysis for Resource Utilization in Space Exploration

CO2 acquisition and utilization technologies will have a vital role in designing sustainable and affordable life support and in situ fuel production architectures for human and robotic exploration of Moon and Mars. For long-term human exploration to be practical, reliable technologies have to be implemented to capture the metabolic CO2 from the cabin air and chemically reduce it to recover oxygen. Technologies that enable the in situ capture and conversion of atmospheric CO2 to fuel are essential for a viable human mission to Mars. This paper describes the concept and mathematical analysis of a closed-loop life support system based on combined electrolysis of CO2 and steam (co-electrolysis). Products of the coelectrolysis process include oxygen and syngas (CO and H2) that are suitable for life support and synthetic fuel production, respectively. The model was developed based on the performance of a co-electrolysis system developed at Idaho National Laboratory (INL). Individual and combined process models of the co-electrolysis and Sabatier, Bosch, Boudouard, and hydrogenation reactions are discussed and their performance analyses in terms of oxygen production and CO2 utilization are presented.

McKellar, Michael G.↗

NASA NTRS2014

Overview of the Contributing Factor Map and How it can Support your Research

The Contributing Factor Map (CFM) is a visual representation of a taxonomy of factors influencing human health and performance in space. This presentation will give an overview of its development and its structure. It will describe various uses of the CFM that can support researchers working within the Human Research Program (HRP) Architecture of Evidence-Risk-Gap-Task-Deliverable. For example, during the Risk phase, the CFM can be used as a "menu" to help formulate a qualitative model of the factors contributing to specific consequences of concern. It provides a reference set of factors from across the operational, vehicle design, and human domains that otherwise might not be considered if approaching a risk from a specific domain perspective. Using the CFM as a reference can increase awareness of potential cross-disciplinary collaborations for overall risk mitigation. The CFM can also be used as a framework for identifying gaps in knowledge about a risk. This identification can support the subsequent development of gaps and tasks comprising the research plan aimed at risk mitigation. Examples of these types of applications of the CFM will be discussed and information on the support available to researchers in using it will be provided.

Mindock, Jennifer A.↗

NASA NTRS2017

An ISRU Propellant Production System to Fully Fuel a Mars Ascent Vehicle

In-Situ Resource Utilization (ISRU) will enable the long term presence of humans beyond low earth orbit. Since 2009, oxygen production from the Mars atmosphere has been baselined as an enabling technology for Mars human exploration by NASA. However, using water from the Martian regolith in addition to the atmospheric CO2 would enable the production of both liquid Methane and liquid Oxygen, thus fully fueling a Mars return vehicle. A case study was performed to show how ISRU can support NASA's Evolvable Mars Campaign (EMC) using methane and oxygen production from Mars resources. A model was built and used to generate mass and power estimates of an end-to-end ISRU system including excavation and extraction water from Mars regolith, processing the Mars atmosphere, and liquefying the propellants. Even using the lowest yield regolith, a full ISRU system would weigh 1.7 mT while eliminating the need to transport 30 mT of ascent propellants from earth.

Mars Surface↗

NASA NTRS2018

Survey of Methods to Predict Controller Workload for Real-Time Monitoring of Airspace Safety

The Real Time Safety Monitoring (RTSM) approach allows for assessment and prediction of the safety margin in the National Airspace System (NAS) to help preempt incidents and accidents, rather than having to reactively mitigate them. In RTSM, the NAS is modeled using state variables, and safety metrics are defined in terms of these state variables. The safety metrics have been classified as weather-related, airspace-related, and human-related. Many of the formulated human-related safety metrics need an estimate of the controller workload for their computation. However, this computation is not trivial. Hence, in this report, we perform a literature survey to identify the different factors that enable the computation of controller workload and categorize these factors. Next, we describe studies undertaken to determine a minimal set of factors that pro- vide a correct assessment of controller workload. Lastly, we survey approaches for evaluating how well the selected factors correlate with the controllers' subjective assessment of their workload. Based on this survey, we present factors beneficial to computing and predicting controller workload in real time, and discuss the status of data sources necessary for these computations.

National Airspace System↗