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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

HERMA-Heartbeat Microwave Authentication

Systems and methods for identifying and/or authenticating individuals utilizing microwave sensing modules are disclosed. A HEaRtbeat Microwave Authentication (HERMA) system can enable the active identification and/or authentication of a user by analyzing reflected RF signals that contain a person's unique characteristics related to their heartbeats. An illumination signal is transmitted towards a person where a reflected signal captures the motion of the skin and tissue (i.e. displacement) due to the person's heartbeats. The HERMA system can utilize existing transmitters in a mobile device (e.g. Wi-Fi, Bluetooth, Cellphone signals) as the illumination source with at least one external receive antenna. The received reflected signals can be pre-processed and analyzed to identify and/or authenticate a user.

Lux, James Paul↗
NASA NTRSDate not supplied

Preliminary Steps in Developing Rapid Aero Modeling Technology

The Rapid Aero Modeling (RAM) approach is a method to efficiently and automatically obtain aerodynamic models during testing, significantly saving time and resources. Motivation for this technology results from demand for experimental efficiency and model fidelity that has increased with growing aircraft complexity and aerodynamic nonlinearities. These issues are typical in the responses presented by a class of vehicles categorized as Urban Air Mobility aircraft where many features from both airplane and rotorcraft are present. For UAM configurations, with typically many more factors than conventional aircraft, traditional test methods can lead to increased costs and missed interactions. RAM guides the test to obtain high-fidelity, statistically rigorous aircraft models, and the approach is applicable to computational, ground, or flight-test experiments. It combines concepts from Design of Experiment theory and Aircraft System Identification theory that allow the user the freedom to choose, in advance of the test, a specific level of fidelity typically, in terms of prediction error. RAM only collects data required to meet the user-specified fidelity and fidelity is only limited by the facility and test article capabilities. An initial wind tunnel test to support development of RAM was conducted to assess potential metrics, algorithms, and procedures. This paper presents results from initial tests for the development of RAM technology and highlights some of the unique features of RAM applied toa conventional configuration during a ground-based, static, wind-tunnel test.

Patrick C Murphy↗
NASA NTRSDate not supplied

Rapid Aero Modeling for Urban Air Mobility Aircraft in Wind-Tunnel Tests

Rapid Aero Modeling (RAM) applied to wind tunnel testing, RAM-T, is an approach to efficiently and automatically obtain aerodynamic models during testing. The approach saves time and resources by responding to the demand for experimental efficiency and model fidelity. Motivation for this demand is more acute when investigating a class of vehicles categorized as Urban Air Mobility (UAM) aircraft where many features from both aircraft and rotorcraft are present. RAM-T provides a feedback loop around the test facility to guide the test toward high-fidelity, statistically rigorous aircraft models. The general RAM approach is applicable to computational or physical experiments. It combines concepts from design of experiment theory and aircraft system identification theory that allow the user the freedom to choose, in advance of the test, a specific level of fidelity in terms of prediction error. RAM only collects data required to meet the user-specified fidelity and fidelity is only limited by the facility and test article capabilities. This paper presents results from tests conducted for development of an automated RAM-T technology. The results highlight some of the unique features of RAM applied to eVTOL configurations.

Aerodynamics↗
DOE OSTI2024

A high fidelity and user-friendly equation-oriented optimization model for carbon capture using a novel water-lean solvent

Research Triangle Institute (RTI) International and SLB have developed a novel water-lean solvent technology for carbon capture, demonstrating low specific reboiler duty (SRD) values at capture rates exceeding 90%. At the Technology Centre Mongstad (TCM) pilot plant, the technology achieved an SRD of 2.55 GJ/t-CO2 at 95% capture, utilizing an intercooler and a 5°C temperature approach in the lean/rich solvent cross exchanger. To meet varying carbon capture targets for Front End Engineering and Design (FEED) studies and to enable real-time optimization and advanced process control, an efficient optimization model is required. This model needs to minimize energy demand for a given capture rate and determine optimal operating parameters in response to fluctuating flue gas conditions. While an existing Aspen Plus simulation model, developed by RTI and SLB, accurately matches TCM plant data, its sequential modular (SM) strategy is too slow for real-time applications due to recycle streams and tight heat integration inherent in solvent-based carbon capture processes. Although an equation-oriented (EO) modeling strategy is more suitable for optimizing these processes, its adoption has been limited by several factors: feature limitations in Aspen Plus EO mode (e.g., lack of balance block support), a less user-friendly interface for variable identification and loop solving, complex troubleshooting of convergence issues, and the necessity for accurate initial values.

carbon capture↗
DOE OSTI2024

Workflow for Developing and Operating Subsurface Hydrogen Storage Facilities in Porous Reservoirs

Long-duration (seasonal) storage of natural gas (NG), which primarily consists of methane (CH 4 ), has been practiced for more than a hundred years at underground gas storage (UGS) facilities that use depleted hydrocarbon reservoirs, saline aquifers, and salt caverns. To enable hydrogen (H 2 ) to be used as a long-duration, energy-storage medium, similar facilities are envisioned for underground H 2 storage (UHS) of either H 2 or H 2 /NG mixtures. Experience with UGS can be used to guide recommended practices for developing and operating UHS facilities in porous reservoirs. The most important factors (formation/fluid properties and engineering choices) that influence the performance of UHS reservoirs have been identified and quantified in previous studies. These factors and choices influence phenomena that determine the sweep efficiency of the stored working gas. These phenomena include viscous fingering, hysteretic capillary trapping, and gravity override of the working gas, as well as the upconing of nonproductive fluid that determine the sweep efficiency of the stored working gas. This report describes initial recommended-practices and a project-development workflow for UHS facilities that utilize porous reservoirs, based on the current state-of-knowledge about H 2 behavior in the subsurface. The workflow sequentially addresses all aspects of UHS project development, including the identification of H 2 sources and users, site ranking and down-selection, geologic and reservoir-engineering characterization, reservoir design, testing, risk management, commissioning, operations, and monitoring for a UHS facility. The goal is to enable UHS facilities to be developed in an efficient and timely manner, while carefully managing project risks. This workflow is similar to that which has been developed for UGS facilities (see Figure 1 of API, 2022), with the addition of tasks and subtasks specific to H 2 and UHS. The project-development workflow is broken down into three major stages: (1) define the H 2 use case; (2) rank, down-select, and characterize potential, candidate UHS sites; and (3) reservoir design, integrity testing, risk assessment, commissioning, operations, and monitoring for selected UHS sites. Each major stage is further broken down into tasks and subtasks, which are described at a high level. This report also provides more detailed descriptions of all tasks and subtasks that involve reservoir analysis and testing.

08 HYDROGEN↗
NASA NTRS1987

Fault-tolerant computer architecture based on INMOS transputer processor

Redundant processing was used for several years in mission flight systems. In these systems, more than one processor performs the same task at the same time but only one processor is actually in real use. A fault-tolerance computer architecture based on the features provided by INMOS Transputers is presented. The Transputer architecture provides several communication links that allow data and command communication with other Transputers without the use of a bus. Additionally the Transputer allows the use of parallel processing to increase the system speed considerably. The processor architecture consists of three processors working in parallel keeping all the processors at the same operational level but only one processor is in real control of the process. The design allows each Transputer to perform a test to the other two Transputers and report the operating condition of the neighboring processors. A graphic display was developed to facilitate the identification of any problem by the user.

Ortiz, Jorge L.↗
DOE OSTI2017

Kmer-SSR: a fast and exhaustive SSR search algorithm

Motivation: One of the main challenges with bioinformatics software is that the size and complexity of datasets necessitate trading speed for accuracy, or completeness. To combat this problem of computational complexity, a plethora of heuristic algorithms have arisen that report a ‘good enough’ solution to biological questions. However, in instances such as Simple Sequence Repeats (SSRs), a ‘good enough’ solution may not accurately portray results in population genetics, phylogenetics and forensics, which require accurate SSRs to calculate intra- and inter-species interactions. Results: We present Kmer-SSR, which finds all SSRs faster than most heuristic SSR identification algorithms in a parallelized, easy-to-use manner. The exhaustive Kmer-SSR option has 100% precision and 100% recall and accurately identifies every SSR of any specified length. To identify more biologically pertinent SSRs, we also developed several filters that allow users to easily view a subset of SSRs based on user input. Kmer-SSR, coupled with the filter options, accurately and intuitively identifies SSRs quickly and in a more user-friendly manner than any other SSR identification algorithm. Availability and implementation: The source code is freely available on GitHub at https://github. com/ridgelab/Kmer-SSR.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2020

Evaluation of Low Cost, User-Centered Alerting Devices for the Mitigation of Flight Crew Spatial Disorientation

The National Aeronautics and Space Administration (NASA) is conducting research into technologies which have the potential to reduce flight crew Spatial Disorientation (SD). While flight deck technology has advanced rapidly over the past fifty (50) years, the reported occurrences of flight crew SD have not decreased. The Cost-Effective Devices for Alerting Research (CEDAR) effort has focused on the identification and development of low cost, user-centered alerting solutions for the purpose of mitigating the occurrence of flight crew SD. This effort seeks to evaluate both existing technologies as well as new and emerging technologies which have a viable path to implementation in commercial aviation within the next five (5) years. This research is intended to develop a proof-of-concept for real-time SD mitigation which could eventually be utilized to improve safety in future air transport operations. NASA has partnered with the United States Naval Aeromedical Research Unit in Dayton, OH (NAMRU-D) to conduct flight crew SD research utilizing their Disorientation Research Device (DRD), dubbed “The Kraken”. This high-tech simulator features never-before-seen capabilities for side-by-side commercial aviation flight crew SD research, and is capable of re-creating the forces necessary to induce SD illusions in a safe and repeatable manner. Prototype SD mitigation solutions were incorporated into this simulator for scenario-based testing and evaluation using airline pilots within a contextually representative operational environment. SD mitigation technology prototypes designed to provide haptic feedback for both alerting and guidance, as well as innovative visual and aural alerting displays were evaluated. In December 2014, as a result of analyzing eighteen (18) loss-of-control events, the Commercial Aviation Safety Team (CAST) recommended research into flight deck technologies that have potential to mitigate the problems and contributing factors that lead to flight crew loss of airplane state awareness (ASA) and conditions likely to produce SD. The aviation community (government, industry and academia) have been charged with conducting research into cost-effective, user-centered flight deck alerting systems to alert flight crews; especially for the two conditions that produced SD (sub-threshold rolls and the somatogravic illusion). Somatogravic illusions are defined as illusions in which “there is a false perception of attitude on exposure to a force vector that differs in direction and/or magnitude from the normal gravitational force”. The sub-threshold roll illusion (aka the “leans” illusion) is a false sensation of roll attitude. A prolonged roll of less than two degrees becomes physiologically imperceptible to the pilot, and can lead to an incorrect perception of aircraft orientation. The sub-threshold roll illusion forms the entry point for the “graveyard spiral”, a maneuver in which the pilot’s corrective action (based on their false perception of aircraft orientation) causes the aircraft to spiral down into the ground. In both of these SD illusions, it is when the pilot attempts to correct the aircraft’s attitude (based on a false perception of its state) that problems arise, sometimes with lethal consequences.

Ronald J Daiker↗
DOE OSTI2021

Advances in scientific literature mining for interpreting materials characterization

Abstract Using synchrotron light sources, such as the National Synchrotron Light Source II at Brookhaven National Laboratory, scientists in fields as diverse as physics, biology, and materials science, identify the atomic structure, chemical composition, or other important properties of varied specimens. x-ray spectroscopy from light sources is particularly valuable for materials research with vast information available about reference spectra in the scientific literature. However, as the technique is applicable to many science domains, searching for information about select x-ray spectroscopy spectra is impeded by the sheer number of publications. Moreover, useful information about the context of an experiment or figures presented in papers can be buried among the details, which takes time to assess. This work presents a scientific literature mining system that supports data acquisition, information extraction, and user interaction for referencing x-ray spectra identification and spectral interpretation. The goal is to provide efficient access to useful spectral data to researchers who may spend only a few days at a synchrotron light source. With this system, users browse a classification tree for papers arranged according to x-ray spectroscopic methods, chemical elements, and x-ray absorption spectroscopy edges. Relevant figures are extracted with sentences from the paper that explain them, known as ‘figure explanatory text.’ Notably, this system focuses on semantic aspects (logical analysis) to find figure explanatory text using deep contextualized word embeddings techniques and contains an interface to obtain labeled data from domain experts that is used to evaluate and improve the model.

Park, Gilchan (ORCID:0000000201536646)↗
NASA NTRS2007

Deep Space Network Antenna Logic Controller

The Antenna Logic Controller (ALC) software controls and monitors the motion control equipment of the 4,000-metric-ton structure of the Deep Space Network 70-meter antenna. This program coordinates the control of 42 hydraulic pumps, while monitoring several interlocks for personnel and equipment safety. Remote operation of the ALC runs via the Antenna Monitor & Control (AMC) computer, which orchestrates the tracking functions of the entire antenna. This software provides a graphical user interface for local control, monitoring, and identification of faults as well as, at a high level, providing for the digital control of the axis brakes so that the servo of the AMC may control the motion of the antenna. Specific functions of the ALC also include routines for startup in cold weather, controlled shutdown for both normal and fault situations, and pump switching on failure. The increased monitoring, the ability to trend key performance characteristics, the improved fault detection and recovery, the centralization of all control at a single panel, and the simplification of the user interface have all reduced the required workforce to run 70-meter antennas. The ALC also increases the antenna availability by reducing the time required to start up the antenna, to diagnose faults, and by providing additional insight into the performance of key parameters that aid in preventive maintenance to avoid key element failure. The ALC User Display (AUD) is a graphical user interface with hierarchical display structure, which provides high-level status information to the operation of the ALC, as well as detailed information for virtually all aspects of the ALC via drill-down displays. The operational status of an item, be it a function or assembly, is shown in the higher-level display. By pressing the item on the display screen, a new screen opens to show more detail of the function/assembly. Navigation tools and the map button allow immediate access to all screens.

Ahlstrom, Harlow↗
DOE OSTI2017

Dual Microwave Radiometer Experiment Field Campaign Report

Passive microwave radiometers (MWRs) are the most commonly used and accurate instruments the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Research Facility has to retrieve cloud liquid water path (LWP). The MWR measurements (microwave radiances or brightness temperatures) are often used to derive LWP using climatological constraints, but are frequently also combined with measurements from radar and other instruments for cloud microphysical retrievals. Nominally this latter approach improves the retrieval of LWP and other cloud microphysical quantities (such as effective radius or number concentration), but this also means that when MWR data are poor, other cloud microphysical quantities are also negatively affected. Unfortunately, current MWR data is often contaminated by water on the MWR radome. This water makes a substantial contribution to the measured radiance and typically results in retrievals of cloud liquid water and column water vapor that are biased high. While it is obvious when the contamination by standing water is large (and retrieval biases are large), much of the time it is difficult to know with confidence that there is no contamination. At present there is no attempt to estimate or correct for this source of error, and identification of problems is largely left to users. Typically users are advised to simply throw out all data when the MWR “wet-window” resistance-based sensor indicates water is present, but this sensor is adjusted by hand and is known to be temperamental. In order to address this problem, a pair of ARM microwave radiometers was deployed to the University of Washington (UW) in Seattle, Washington, USA. The radiometers were operated such that one radiometer was scanned under a cover that (nominally) prevents this radiometer radome from gathering water and permits measurements away from zenith; while the other radiometer is operated normally – open or uncovered - with the radome exposed to the sky. The idea is that (1) the covered radiometer data can provide LWP (and water vapor) along the off-zenith slant path and (2) the two sets of measurements can be compared to identify when wet-radome contamination is occurring.

47 OTHER INSTRUMENTATION↗
NASA NTRS1986

Improved Spectrometer for Field Use

Proposed portable spectrometer for analyzing minerals in field generates spectral images like camera and process spectral data for real-time identification of materials. To identify unknown mineral, user locates significant peaks in displayed spectrum and matches them to spectrum in portfolio of reference spectra. Alternatively, user calls up display of prerecorded spectra in same wavelength region for comparison or allows spectrometer to determine best match automatically. New instrument makes it unnecessary to return data to laboratory or equipment trailer for processing.

Goetz, A. F. H.↗
NASA NTRS1994

Dual-use technologies for the mining, processing, and energy industries

Over the years, NASA has utilized several approaches towards transferring space technologies into the private sectors. Some of these approaches have been successful, others have had mixed results. The conventional approach usually involves identifying advanced NASA technologies and then searching for applications. Some approaches involve joint sponsorship, but mostly focus on technologies for space. The greatest success has occurred when market forces are used to determine technology initiatives. This paper describes an unconventional approach that was structured to drive out customer requirements for advanced technologies where NASA is also a customer on par with others. The approach used herein is best described as entrepreneurial deal-making. This approach is new and is working very well so far, but it is still too early, and the process is too immature, for quantitative evaluation of success. However, it is appropriate to share these experiences at this time in order to obtain feedback and improve our chances for success. In the needs identification stage, NASA is one of many users (customers), and in the subsequent development stage, NASA is one of many suppliers along with industry, academia, and other government organizations. This specific characteristic of the approach was a primary goal that was incorporated from inception. It was the viewpoint of the instigators (the authors) that if the activity was customer focused, it would: (1) have a higher probability for success since it will be driven by those who will reap the benefits; (2) be able to advocate and promote action if necessary, since it would be founded outside the federal government; (3) not be self-perpetuating; that is, if no common need could be found that had a reasonable return on investment, it would self-destruct; and (4) have increased stability from a broader base of support and not be dependent on NASA being the principal funding source. To date, the workshop activities have identified a collection of potential customers in NASA, other federal government, private industry, and academia who have common needs for advanced technologies.

Roberts, Barney B.↗
NASA NTRS2018

NeMO-Net - The Neural Multi-Modal Observation & Training Network for Global Coral Reef Assessment

In the past decade, coral reefs worldwide have experienced unprecedented stresses due to climate change, ocean acidification, and anthropomorphic pressures, instigating massive bleaching and die-off of these fragile and diverse ecosystems. Furthermore, remote sensing of these shallow marine habitats is hindered by ocean wave distortion, refraction and optical attenuation, leading invariably to data products that are often of low resolution and signal-to-noise (SNR) ratio. However, recent advances in UAV and Fluid Lensing technology have allowed us to capture multispectral 3D imagery of these systems at sub-cm scales from above the water surface, giving us an unprecedented view of their growth and decay. By combining spatial and spectral information from varying resolutions, we seek to augment and improve the classification accuracy of previously low-resolution datasets at large temporal scales.NeMO-Net, the first open-source deep convolutional neural network (CNN) and interactive learning and training software, currently being developed at NASA Ames, is aimed at assessing the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology. The latest iteration uses fully convolutional networks to segment and identify coral imagery taken by UAVs and satellites, including WorldView-2 and Sentinel. We present results taken from the Indian Ocean where classification accuracy has exceeded 91% for 24 geomorphological classes given ample training data. In addition, we utilize deep Laplacian Pyramid Super-Resolution Networks (LapSRN) to reconstruct high resolution information from low resolution imagery, trained from various UAV and satellite datasets. Finally, in the case of insufficient training data, we have developed an interactive online platform that allows users to easily segment and submit their classifications, which has been integrated with the current NeMO-Net workflow. Specifically, we present results from the Fiji islands in which preliminary user data has allowed for the accurate identification of 9 separate classes, despite issues such as cloud shadowing and spectral variation. The project is being supported by NASA's Earth Science Technology Office (ESTO) Advanced Information Systems Technology (AIST-16) Program.

Neural↗
DOE OSTI2025

WigglyRivers: A tool to characterize the multiscale nature of meandering channels

Channel sinuosity is ubiquitous along river networks, producing complex patterns that encapsulate and influence morphodynamic processes and ecosystem services. Accurately characterizing these patterns is challenging with traditional curvature-based algorithms. Here, in this study, we present WigglyRivers, a Python package that builds on existing wavelet-based methods to create an unsupervised meander identification and characterization tool. The package uses planimetric information the user provides or from the USGS’s High-Resolution National Hydrography Dataset to characterize individual reaches or entire river networks. WigglyRivers also includes a supervised river identification tool for manually selecting individual meandering features. Here, we provide examples of idealized river transects and show the capabilities of WigglyRivers. We also use the supervised identification tool to validate the unsupervised identification on river transects across the continental US. WigglyRivers is a tool to understand better the multiscale characteristics of river networks and the link between river geomorphology and river corridor connectivity.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2014

Sentiment of Search: KM and IT for User Expectations

User perceived value is the number one indicator of a successful implementation of KM and IT collaborations. The system known as "Search" requires more strategy and workflow that a mere data dump or ungoverned infrastructure can provide. Monitoring of user sentiment can be a driver for providing objective measures of success and justifying changes to the user interface. The dynamic nature of information technology makes traditional usability metrics difficult to identify, yet easy to argue against. There is little disagreement, however, on the criticality of adapting to user needs and expectations. The Systems Usability Scale (SUS), developed by John Brook in 1986 has become an industry standard for usability engineering. The first phase of a modified SUS, polls the sentiment of representative users of the JSC Search system. This information can be used to correlate user determined value with types of information sought and how the system is (or is not) meeting expectations. Sentiment analysis by way of the SUS assists an organization in identification and prioritization of the KM and IT variables impacting user perceived value. A secondary, user group focused analysis is the topic of additional work that demonstrates the impact of specific changes dictated by user sentiment.

Berndt, Sarah Ann↗
NASA NTRS1985

A Parametric Study of the Ibrahim Time Domain Modal Identification Algorithm

The accuracy of the Ibrahim time Domain (ITD) identification algorithm in extracting structural model parameters from free response functions was studied using computer simulated data for 65 positions on an isotropic, uniform thickness plate with mode shapes obtained by NASTRAN analysis. Natural frequencies were used to study identification results over ranges of modal parameter values and user selectable algorithm constants. Effects of superimposing various levels of noise onto the functions were investigated. No detrimental effects were observed when the number of computational degrees of freedom allowed in the algorithm was made many times larger than the minimum necessary for adequate identification. The use of a high number of degrees of freedom when analyzing experimental data, for the simultaneous identification of many modes in one computer run are suggested.

Pappa, R. S.↗