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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

A Cognitive Walkthrough of Multiple Drone Delivery Operations

Advances of early twenty-first century aviation and transportation technologies provide opportunities for enhanced aerial projects, and the overall integration of unmanned aircraft systems (UAS) into the National Airspace System (NAS) has applications across a wide range of operations. Through these, remote operators have learned to manage several UAS at the same time in a variety of operational environments. The present work details a component piece of an ongoing body of research into multi-UAS operations. Beginning in early 2020, NASA has collaborated with Uber Technologies to design and develop concepts of operations, roles and responsibilities, and ground control station (GCS) concepts to enable food delivery operations via multiple, small UAS (sUAS). A cognitive walkthrough was chosen as the method for data collection. This allowed information to be gathered from UAS subject matter experts (SMEs) that could further mature designs for future human-in-the-loop (HITL) simulations; in addition, it allowed information to be collected remotely during the stringent restrictions of the COVID-19 pandemic. Consequently, the described cognitive walkthrough activity utilized remote data collection protocols mediated through the usage of programs designed for presentation and telecommunications. Scenarios were designed, complete with airspace, contingencies, and remedial actions, to be presented to the SMEs. Information was collected using a combination of rating scales and open-ended questions. Results received from the SMEs revealed expected hazards, workloads, and information concerns inherent in the contingency scenarios. SMEs also provided insight into the design of GCS tools and displays as well as the duties and relationships of human operators (i.e., monitors) and automation (i.e., informers and flight managers). Implications of these findings are discussed.

unmanned aircraft systems↗
NASA NTRSDate not supplied

Learning About Routine Successful Pilot Techniques Using A Cued Retrospective Think-Aloud Task

Self-report can be a valuable method for collecting data about people’s goals and perceived motivations – data about aspects of crew thinking that are not otherwise readily observable. One of the challenges associated with collecting self-report data on routine successful performance, however, is that details may go unreported, be deemed unimportant, or may not be recalled. We report a study in which commercial airline flight crews participated in a video-cued retrospective think aloud after flying a high-fidelity simulated arrival into Charlotte airport. One day after flying the simulated arrival, crews were shown a video recording of their flight. The video was paused after each minute, and crew members were each asked to describe what they were doing and thinking during that interval. Reported data analysis focused on aspects of performance that are often ambiguously described as “pilot technique” or “airmanship,” in an attempt to provide more detail around these types of behaviors.

Jon Holbrook↗
NASA NTRSDate not supplied

EVA SPACESUIT INCIDENCE TRACKING

INTRODUCTION: Extravehicular Activity (EVA)suit-related injuries to crew during training and inflight operations are not uncommon. Systematic tracking of these issues has waxed and waned throughout NASA’s history. Given two new EVA suits in development and an increase in EVA training, the need for dutiful recording of this data is critical. The Suited User Incident Tracking System (SUITS) was developed in the last decade to track all suited exposures, recording exposure details and any related issues, pains, or injuries that arise. METHODS: SUITS data collected from 2017 to 2022 was analyzed for issue frequency and severity for each body location and plotted to visualize where issues were occurring. Clustering techniques using a k-modes approach were also applied to the data set to generate profiles of populations that experienced issues in the suit, and populations that did not. RESULTS:A key finding from SUITS is that discomfort and pain observed in the new planetary spacesuits are occurring in new body locations than those experienced in the microgravity space suit (Extravehicular Mobility Unit (EMU)).To date, the lower body and torso regions account for most pain reports in planetary spacesuits whereas most reports in EMU were shoulders and hands. DISCUSSION:SUITS will continue to be used to capture exposures for all suit types. As training suit availability improves and training cadence increases in preparation for planetary missions, it is critical to capture and assess all suit incidences. Further, a Suited Anomaly Assessment Team (SAAT) consisting of a broad range of EVA stakeholders was formed to share and act on SUITS data with the goal of developing robust solutions to issues/injuries as they arise. Understanding the types and locations of injuries that occur during suited operations will help inform future work related to EVA fitness training requirements, suit design, and modeling efforts to avoid injury. LEARNING OBJECTIVES: 1. Systematic tracking of suited exposures and issues is critical for understanding the complex interaction between the human and the EVA spacesuit. 2. As EVA suit issues/injuries arise it is important to share that data with a broad group to ensure robust strategies are developed.

N Newby↗
NASA NTRSDate not supplied

Fiber-Based Multi-Resolution Imaging and Multidimensional X-ray Diagnostics for Ejecta Dynamics in Plume Surface Interactions

The interaction of a rocket exhaust plume with a particulate-laden surface creates a complex, multiphase flow field that can destabilize the vehicle and damage nearby equipment. This study investigates two methods for capturing the particulate dynamics of plume-surface interaction (PSI): optical fiber-based multi-resolution Mie scattering and multi-dimensional X-ray radiography. Mie scattering was used to track PSI-interacted particles, trace their paths, and measure velocities. While effective for the jet periphery and early PSI stages, the technique becomes limited as the scattering cross-section increases over time due to particle displacement from the soil bed, causing the core to become optically dense and appear as a luminous, opaque region. To address this, X-ray radiography was explored as a complementary method for visualizing the optically dense core. PSI experiments were conducted with both reacting and non-reacting jets to evaluate these approaches across a range of optical and flow parameters. The results demonstrated the capability of the fiber-based multi-resolution imaging system to capture simultaneous fields of view at varying magnifications (1x, 2x, 4x), and the ability of X-ray imaging to penetrate the optically dense plume, revealing flow structures that would otherwise be obscured in scattering-based methods. Data were collected for various PSI parameters, including three different heights above the surface, to analyze the ejecta properties and the plume’s temporal evolution. These results provide the first imaging strategy capable of resolving flow structures over a wide spatial dynamic range while also offering the first visualization of the optically dense core.

Ejecta↗
DOE OSTI2022

Fibro: a fiber optic data processing software for unconventional reservoirs

Various embodiments of the present disclosure are directed to systems and methods for data collection using fiber-optic cable in a well, and analysis of the data to determine instantaneous frequency, instantaneous phase, instantaneous amplitude, and/or dominant frequency. These measures can be used to determine parameters associated with the operation of the well. The parameters can be used to control the operation of the well and/or the fracturing process.

Ghahfarokhi, Payam Kavousi↗
DOE OSTI2023

Transparent application-layer/os deeper packet inspector

A computer-implemented method of deep packet inspection (DPI) in a network is provided. The method comprises collecting data packets comprising a number of traffic flows from a number of devices via a number of traffic taps and classifying each traffic flow according to data about network protocol layers of the packets comprising the traffic flow. Application layer metadata is extracted from the packets. Traffic flow classification data and the extracted metadata are ingested into a data cluster and normalized. The normalized classification data and extracted metadata is then correlated to other data sets.

Urias, Vincent↗
DOE OSTI2023

Results of FY 2023 Alloy 617 and Alloy 709 High-Temperature Crack-Growth Testing

This report summarizes the work performed at Idaho National Laboratory under the “Creep, fatigue and creep-fatigue crack growth tests” task of the “Long-Term VHTR Material Qualification – INL” work package. Work was performed this year to validate the crack growth monitoring setup used with the test frames against both continuous crack length monitoring using an optical camera, as well as post-mortem analysis of marker bands on the fracture surface. Delays prevented the use of a gauge to measure load-line displacement for early tests, and so the creep-fatigue crack growth setup was evaluated using the actuator displacement for a load-line displacement setup. While not ideal, this allowed examination of the shortcomings with the current software setup that was originally designed for performing stress corrosion crack growth rate studies. The method for data collection was modified to link the crack growth monitoring software with Instron’s Wave Matrix software. Once the load-line displacement gauge arrived, the crack growth equipment was successfully modified to permit continuous monitoring of both load-line displacement and crack length. This is critical for creep-fatigue and creep crack growth rate studies for ductile material, as it permits the C* and Ct analyses. Test results are shown for Alloy 617 fatigue and creep-fatigue (without the gauge for load-line displacement measurements), as well as creep-fatigue of Alloy 709, which was performed with the completed test setup, allowing for crack length and load-line displacement monitoring.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2018

Lessons and Recommendations for Board-Level Testing with Protons

Protons with sufficiently high energy, provided in a broad field covering on the order of 0.1m2 can be used to perform board-level testing for single event effects (SEE). NASA has used this approach for board-level testing over the last 20 years. Although many difficulties inherent in SEE testing are simplified when using a board-level test, including reduced cost, the method is inherently risky because of the limited value of the collected data and the potential to make critical mistakes when performing SEE testing this way, leading to data of less value. Historically, NASA’s approach to proton board-level testing has been limited to lower criticality applications. However, with users both inside and outside NASA using this method for higher levels of mission assurance, we have put together a set of lessons and recommendations to improve the value of data collected using this method. Focus areas covered include test preparation, test execution, and interpretation of results.

Guertin, Steven M.↗
DOE OSTI2025

Demonstration of an AI-driven workflow for dynamic x-ray spectroscopy

X-ray absorption near edge structure (XANES) spectroscopy is a powerful technique for characterizing the chemical state and symmetry of individual elements within materials, but requires collecting data at many energy points which can be time-consuming. While adaptive sampling methods exist for efficiently collecting spectroscopic data, they often lack domain-specific knowledge about the structure of XANES spectra. Here we demonstrate a knowledge-injected Bayesian optimization approach for adaptive XANES data collection that incorporates understanding of spectral features like absorption edges and pre-edge peaks. We show this method accurately reconstructs the absorption edge of XANES spectra using only 15–20% of the measurement points typically needed for conventional sampling, while maintaining the ability to determine the x-ray energy of the sharp peak after the absorption edge with errors less than 0.03 eV, the absorption edge with errors less than 0.1 eV; and overall root-mean-square errors less than 0.005 compared to traditionally sampled spectra. Our experiments on battery materials and catalysts demonstrate the method’s effectiveness for both static and dynamic XANES measurements, improving data collection efficiency and enabling better time resolution for tracking chemical changes. This approach advances the degree of automation in XANES experiments, reducing the common errors of under- or over-sampling points near the absorption edge and enabling dynamic experiments that require high temporal resolution or limited measurement time.

Bayesian optimization↗
DOE OSTI2025

Time Distribution Analysis for Task Primitives to Support Dynamic Human Reliability Analysis

To support data collection for dynamic human reliability analysis (HRA), this study investigates time distributions for task primitives defined in the Goals, Operators, Methods, and Selection rules (GOMS)–Human Reliability Analysis (HRA) method and Human Reliability data EXtraction (HuREX). GOMS-HRA was developed to provide cognition-based time and human error probability (HEP) information for dynamic HRA calculations within the Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER) framework, while HuREX is a comprehensive HRA data collection method developed by the Korea Atomic Energy Research Institute (KAERI). In this paper, we examine time distributions by using experimental data collected from the Simplified Human Error Experimental Program (SHEEP) study, which proposes an HRA data collection framework to complement full-scope simulator research and gather input data for dynamic HRA by using simplified simulators such as the Rancor Microworld simulator. This paper investigates whether the time required for GOMS-HRA and HuREX task primitives fits 13 statistical distributions. Additionally, we compare and discuss the time distributions obtained from both student operators and professional operators. The result was that this study identified several time distributions for five GOMS-HRA and four HuREX task primitives. In the future, the results of this study are expected to provide objective reference data on the elapsed time for task primitives and aid in realistically simulating scenarios within dynamic HRA.

Dynamic Human Reliability Analysis↗
DOE OSTI2025

Denoising Autoencoder for Reconstructing Sensor Observation Data and Predicting Evapotranspiration: Noisy and Missing Values Repair and Uncertainty Quantification

Abstract Machine learning (ML) methods applied in scientific research often deal with interrelated features in high‐dimensional data. Reducing data noise and redundancy is needed to increase prediction accuracy and efficiency especially when dealing with data from field sensors. We explored an unsupervised learning method, the denoising autoencoder (DAE), to extract the underlying data structure from noisy raw data in the context of predicting hydrologic quantities from multiple field sensors. These sensors have intrinsic instrumental noise and occasional malfunctions that cause missing values. Our DAE neural network reconstructed meteorological sensor data containing noise and missing values to predict evapotranspiration in a mountainous watershed. The DAE reconstructed the sensor variables with a mean coefficient of determination value of 0.77 across 15 dimensions representing individual sensors. It reduced variance and bias uncertainties compared to a classical autoencoder model. The reconstruction quality varied across dimensions depending on their cross‐correlation and alignment with the underlying data structure. Uncertainties arising from the model structure were overall higher than those resulting from data corruption. We attached the DAE structure to a downstream ET‐prediction neural network in three formats and achieved reasonably accurate ET predictions . The use of the DAE notably reduced variance uncertainty in ET prediction. However, excessive variance reduction may be accompanied by an increase in bias due to the intrinsic bias‐variance tradeoff. Our method of evaluating and reducing uncertainties in aggregated data from different sources can be used to improve predictive models, process understanding, and uncertainty quantification for better water resource management. Plain Language Summary We present a machine learning method, namely the denoising autoencoder, which reduces the effects of data noise and missing values typically present in scientific data sets collected through sensor measurements. This method selects the most relevant information from noisy raw data collected by the instruments and fills in missing values. To demonstrate the effectiveness of our method, we applied it to predict evapotranspiration, a hydrologic variable that represents the water moved from the land surface to the atmosphere through a combination of evaporation and plant water use (transpiration). We also used a random sampling technique (the Monte Carlo method) to compare the uncertainty in the predictions when using the raw and noisy data versus the reconstructed data. The denoising process produced more accurate predictions of evapotranspiration with less uncertainty. Improved predictions of evapotranspiration can lead to a better understanding and accounting of water budgets. This ML approach is broadly suitable for a wide variety of applications that involve noisy sensor data with missing values. Key Points We used a denoising autoencoder (DAE) neural network to reduce noise in meteorological and soil sensor observations by on average We used Monte Carlo sampling to estimate the bias and variance of all model outputs, including uncertainty sources from data and the model We attached the DAE component to a downstream neural network to predict ET with the variance reduced by , compared to that without the DAE

denoising autoencoder↗
DOE OSTI2023

Litterfall and Branchfall Mass Flux in Malaysia Lambir Hills GEM plots (2008-2010)

This data package includes two folders: Litterfall and Branchfall. The Litterfall folder includes three files: "GEM_Lambir_Hills_Litterfall_Mass_Flux_Data_2008_to_2010.csv" includes the litterfall data, the "GEM_Lambir_Hills_Litterfall_Metadata.xlx" includes the descripion of the columns in the data file, and the PDF file "GEM_Lambir_Hills_Litterfall_Methods_Description" includes a brief description of the litterfall sampling methods. The Branchfall Folder includes four files: the "GEM_Lambir_Hills_Branchfall_Data_2009_to_2010.csv" file includes the branchfall data, the "GEM_Lambir_Hills_Branchfall_Metadata_2009_to_2010.xlsx" includes the description of the columns in the csv data file, the "GEM_Lambir_Hills_Branchfall_Methods_Description.pdf" includes a brief description of the branchfall collection methods, and the "GEM_Lambir_Hills_Branchfall_Data_Metadata_Methods_TransectSums.xlx" includes data, metadata, methods description, and a 'TransectsSums' tab where the reader can find the sum of the branchfall data in each transect Litterfall and Branchfall data were collected to quantify canopy productivity and net primary productivity allocated to branch turnover, which are components of the total net primary productivity and ecosystem carbon budget. The methods follow the Global Ecosystems Monitoring (GEM) protocols (see gem.tropicalforests.ox.ac.uk). The data collection took place from 2008 to 2010 in two 1-ha GEM plots in Lambir Hills National Park, Sarawak, Malaysia, within the Lambir 52-ha ForestGEO plots. One of the plots was located on clay soil and the other on sandy loam. The site is an old-growth moist tropical forest dominated by Dipterocarpacea. The climate is moist tropical and aseasonal. Litterfall was collected biweekly from 25 litter traps per plot. Branchfall was estimated using four 100-m transects, which were surveyed every two months.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2018

Intercomparison of Field Methods for Acquiring Ground Reflectance at Railroad Valley Playa for Spectral Calibration of Satellite Data

Ground reflectance was acquired at the Railroad Valley Playa calibration site in Nevada USA using different methods of collection. The data was collected near the time and date of Landsat 8 OLI and Sentinel-2 satellite overpasses so an inter-comparison could be made with the reflectance products to determine which method was more suitable for vicarious calibration. The field spectrometers and reference panels were characterized before the field campaign. A continuous acquisition method was compared to stop and measure collections. Both acquisition methods were collected along an 80 m east-west transect as well as for a series of north-south transects over an 80 x 320 m area, with the stop and measure method being performed at random sampling locations. The measurements were performed using two field spectrometers by three teams of two people to compare the repeatability. The aim of the field campaign was to determine the variability due to the operator and the method of collection.

Lau, Ian C.↗
NASA NTRS2018

Intercomparison of Field Methods for Acquiring Ground Reflectance at Railroad Valley Playa for Spectral Calibration of Satellite Data

Ground reflectance was acquired at the Railroad Valley Playa calibration site in Nevada USA using different methods of collection. The data was collected near the time and date of Landsat 8 OLI and Sentinel-2 satellite overpasses so an inter-comparison could be made with the reflectance products to determine which method was more suitable for vicarious calibration. The field spectrometers and reference panels were characterized before the field campaign. A continuous acquisition method was compared to stop and measure collections. Both acquisition methods were collected along an 80 m east-west transect as well as for a series of north-south transects over an 80 x 320 m area, with the stop and measure method being performed at random sampling locations. The measurements were performed using two field spectrometers by three teams of two people to compare the repeatability. The aim of the field campaign was to determine the variability due to the operator and the method of collection.

Lau, Ian C.↗
DOE OSTI2021

On the Utility of Transmission Color Analysis i: Differentiating Super-Earths and Sub-Neptunes

The majority of exoplanets found to date have been discovered via the transit method, and transmission spectroscopy represents the primary method of studying these distant worlds. Currently, in-depth atmospheric characterization of transiting exoplanets entails the use of spectrographs on large telescopes, requiring significant observing time to study each planet. Previous studies have demonstrated trends for solar system worlds using color–color photometry of reflectance spectra, as well as trends within transmission spectra for hot Jupiters. Building on these concepts, we have investigated the use of transmission color photometric analysis for efficient, coarse categorization of exoplanets and for assessing the nature of these worlds, with a focus on resolving the bulk composition degeneracy to aid in discriminating super-Earths and sub-Neptunes. We present our methodology and first results, including spectrum models, model comparison frameworks, and wave band selection criteria. We present our results for different transmission “color” metrics, filter selection methods, and numbers of filters. Assuming noise-free spectra of isothermal atmospheres in chemical equilibrium, with our pipeline, we are able to constrain atmospheric mean molecular weight in order to distinguish between super-Earth and sub-Neptune atmospheres with >90% overall accuracy using specific low-resolution filter combinations, . We also found that increasing the number of filters does not substantially impact this performance. This method could allow for broad characterization of large numbers of planets much more efficiently than current methods permit, enabling population- and system-level studies. Additionally, data collected via this method could inform follow-up observing time by large telescopes for more detailed studies of worlds of interest.

47 OTHER INSTRUMENTATION↗
NASA NTRS1978

HCMM satellite to take earth's temperature

The heat capacity mapping mission (HCMM), a low cost modular spacecraft built for the Applications Explorer Missions (AEM), was designed to allow scientists to determine the feasibility of using day/night thermal infrared remote sensor-derived data to: (1) discriminate various rock types and locate mineral resources; (2) measure and monitor surface soil moisture changes; (3) measure plant canopy temperatures at frequent intervals to determine transpiration of water and plant stress; and (4) measure urban heat islands. The design of the spacecraft (AEM-A), its payload, launch vehicle, orbit, and data collection and processing methods are described. Projects in which the HCMM data will be applied by 12 American and 12 foreign investigators are summarized.

Source record↗
NASA NTRS1978

The Chesapeake Bay Program: An opportunity to use an innovative monitoring technique

The goal of this program is to develop a management system that will protect and preserve the water quality of the Chesapeake Bay by effectively managing its uses and resources. To achieve this goal, three major objectives must be accomplished: (1) Determine what units of government have management responsibility for the environmental quality of the Chesapeake Bay, also to define how such management responsibility can best be structured so that communications and coordination can be improved between the respective units of government, research, educational institutions, concerned groups, and individuals. (2) Assess the principal factors having an adverse impact on the environmental quality of the Chesapeake Bay. Following this assessment and review of ongoing research, direct and coordinate research and abatement programs that will most effectively address these factors, and (3) analyze all environmental sampling data now being collected on the Chesapeake Bay and suggest and undertake methods for improving this data collection, and to establish a continuing capability for collecting storing, analyzing, and disseminating these data.

Mangiaracina, L.↗