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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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NASA NTRS2017

Playbook Data Analysis Tool: Collecting Interaction Data from Extremely Remote Users

Typically, user tests for software tools are conducted in person. At NASA, the users may be located at the bottom of the ocean in a pressurized habitat, above the atmosphere in the International Space Station, or in an isolated capsule on a simulated asteroid mission. The Playbook Data Analysis Tool (P-DAT) is a human-computer interaction (HCI) evaluation tool that the NASA Ames HCI Group has developed to record user interactions with Playbook, the group's existing planning-and-execution software application. Once the remotely collected user interaction data makes its way back to Earth, researchers can use P-DAT for in-depth analysis. Since a critical component of the Playbook project is to understand how to develop more intuitive software tools for astronauts to plan in space, P-DAT helps guide us in the development of additional easy-to-use features for Playbook, informing the design of future crew autonomy tools.P-DAT has demonstrated the capability of discreetly capturing usability data in amanner that is transparent to Playbook’s end-users. In our experience, P-DAT data hasalready shown its utility, revealing potential usability patterns, helping diagnose softwarebugs, and identifying metrics and events that are pertinent to Playbook usage aswell as spaceflight operations. As we continue to develop this analysis tool, P-DATmay yet provide a method for long-duration, unobtrusive human performance collectionand evaluation for mission controllers back on Earth and researchers investigatingthe effects and mitigations related to future human spaceflight performance.

in-flight monitoring↗

NASA NTRS2015

Extension of an Object-Oriented Optimization Tool: User's Reference Manual

The National Aeronautics and Space Administration Armstrong Flight Research Center has developed a cost-effective and flexible object-oriented optimization (O (sup 3)) tool that leverages existing tools and practices and allows easy integration and adoption of new state-of-the-art software. This object-oriented framework can integrate the analysis codes for multiple disciplines, as opposed to relying on one code to perform analysis for all disciplines. Optimization can thus take place within each discipline module, or in a loop between the O (sup 3) tool and the discipline modules, or both. Six different sample mathematical problems are presented to demonstrate the performance of the O (sup 3) tool. Instructions for preparing input data for the O (sup 3) tool are detailed in this user's manual.

Multidisciplinary design optimization↗

NASA NTRS2005

A Search Engine That's Aware of Your Needs

Internet research can be compared to trying to drink from a firehose. Such a wealth of information is available that even the simplest inquiry can sometimes generate tens of thousands of leads, more information than most people can handle, and more burdensome than most can endure. Like everyone else, NASA scientists rely on the Internet as a primary search tool. Unlike the average user, though, NASA scientists perform some pretty sophisticated, involved research. To help manage the Internet and to allow researchers at NASA to gain better, more efficient access to the wealth of information, the Agency needed a search tool that was more refined and intelligent than the typical search engine. Partnership NASA funded Stottler Henke, Inc., of San Mateo, California, a cutting-edge software company, with a Small Business Innovation Research (SBIR) contract to develop the Aware software for searching through the vast stores of knowledge quickly and efficiently. The partnership was through NASA s Ames Research Center.

Source record↗

DOE OSTI2025

The meV-resolved Inelastic X-ray Scattering Beamline at NSLS-II: Design and Performance

The ultrahigh resolution inelastic X-ray scattering (IXS) beamline at NSLS-II is designed and built to achieve sub-meV resolution at a moderate energy of 9.13 keV for IXS experiments with high momentum resolution and high spectral contrast. The key instrument is a novel spectrometer featuring a new type of analyzer optics, which combines post-sample collimation with angular dispersive crystal optics. As the first user instrument of its kind, the spectrometer has demonstrated unique research capabilities in exploring low momentum transfer (Q), THz dynamics in soft material systems characterized by mesoscopic heterogeneity and complexity, such as liquid crystals and bio-membranes. Ongoing efforts to improve performance since the start of user operations have resulted in a state-of-the-art energy resolution in routine operations of less than 1.4 meV, with sharp Gaussian-like tails, making it a premier IXS spectrometer for studying the dynamics of soft materials, while also delivering competitive performance for investigating phonon dynamics in hard condensed matter systems, including a broad range of quantum materials.

43 PARTICLE ACCELERATORS↗

NASA NTRSDate not supplied

Creating a knowledge graph to connect scientific publications and datasets for improving discovery of GES DISC’s data and services

The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) archives and distributes to the public hundreds of Earth Science data collections. These collections are used in research, resulting in thousands of scientific papers published each year. As new users come to GES DISC for the data, it is important for them to understand how these data were used in the prior research. For this we are creating the Knowledge Graph that connects research paper citation and the data collection metadata. The relationships created in the graph have potential for the Web applications that utilize this information to directly connect the paper research to the GES DISC datasets and services. We will demonstrate these relationships using the Web application prototype.

Nathaniel Ross Crosby↗

NASA NTRS2020

On Development of Modern Software Interface to Glenn Research Center’s Communication Analysis Suite

NASA’s Space Communications and Navigation (SCaN) program analyzes space communication channels involving satellites in any Earth orbit and deep space for a multitude of operations. Specifically, the SCaN program will power the future of lunar communications in the next decade and beyond. A web based user interface of the static link analysis component of the Glenn Research Center’s Communication Analysis Suite (GCAS) was developed. It is operated through a newly designed front-end application with an easy to use and intuitive web-based user interface that provides accurate satellite communications link analysis capabilities.

link analysis↗

NASA NTRS1990

NASA/DOD Aerospace Knowledge Diffusion Research Project. Paper 5: Aerospace librarians and technical information specialists as information intermediaries: A report of phase 2 activities of the NASA/DOD Aerospace Knowledge Diffusion Research Project

The flow of U.S. government-funded and foreign scientific and technical information (STI) through libraries and related facilities to users in government and industry is examined, summarizing preliminary results of Phase 2 of the NASA/DOD Aerospace Knowledge Diffusion Research Project (NAKDRP). The design and objectives of NAKDRP are reviewed; the NAKDRP model of STI transfer among producers, STI intermediaries, surrogates (technical report repositories or clearinghouses), and users is explained and illustrated with diagrams; and particular attention is given to the organization and operation of aerospace libraries. In a survey of North American libraries it was found that 25-30 percent of libraries regularly receive technical reports from ESA and the UK; the corresponding figures for Germany and for France, Sweden, and Japan are 18 and 5 percent, respectively. Also included is a series of bar graphs showing the librarians' assessments of the quality and use of NASA Technical Reports.

Pinelli, Thomas E.↗

DOE OSTI2025

NSUF FY 2024 Annual Report: Microscopy and Characterization Suite (MaCS) and National Synchrotron Light Source-II (NSLS-II)

The Microscopy and Characterization Suite (MaCS) laboratory at the Center for Advanced Energy Studies (CAES) and the National Synchrotron Light Source-II (NSLS-II) at Brookhaven National Laboratory (BNL) partner with the Nuclear Science User Facilities (NSUF). This partnership provides funding that allows researchers to access these facilities at no cost for studying irradiation effects on nuclear fuels and materials. Through NSUF, both MaCS and NSLS-II support post-irradiation examination (PIE) and irradiation activities for NSUF Rapid Turnaround Experiments (RTE) and NSUF Consolidated Innovative Nuclear Research (CINR) awards. This report details the work completed at these facilities for NSUF competitively selected awards during fiscal year 2024.

99 GENERAL AND MISCELLANEOUS↗

NASA NTRS1990

Providing structural modules with self-integrity monitoring software user's manual

National Aeronautics and Space Administration (NASA) Contract NAS7-961 (A Small Business Innovation and Research (SBIR) contract from NASA) involved research dealing with remote structural damage detection using the concept of substructures. Several approaches were developed. The main two were: (1) the module (substructure) transfer function matrix (MTFM) approach; and (2) modal strain energy distribution method (MSEDM). Either method can be used with a global structure; however, the focus was on substructures. As part of the research contract, computer software was to be developed which would implement the developed methods. This was done and it was used to process all the finite element generated numerical data for the research. The software was written for the IBM AT personal computer. Copies of it were placed on floppy disks. This report serves as a user's manual for the two sets of damage detection software. Sections 2.0 and 3.0 discuss the use of the MTFM and MSEDM software, respectively.

Source record↗

NASA NTRS2006

User Interactive Software for Analysis of Human Physiological Data

Ambulatory physiological monitoring has been used to study human health and performance in space and in a variety of Earth-based environments (e.g., military aircraft, armored vehicles, small groups in isolation, and patients). Large, multi-channel data files are typically recorded in these environments, and these files often require the removal of contaminated data prior to processing and analyses. Physiological data processing can now be performed with user-friendly, interactive software developed by the Ames Psychophysiology Research Laboratory. This software, which runs on a Windows platform, contains various signal-processing routines for both time- and frequency- domain data analyses (e.g., peak detection, differentiation and integration, digital filtering, adaptive thresholds, Fast Fourier Transform power spectrum, auto-correlation, etc.). Data acquired with any ambulatory monitoring system that provides text or binary file format are easily imported to the processing software. The application provides a graphical user interface where one can manually select and correct data artifacts utilizing linear and zero interpolation and adding trigger points for missed peaks. Block and moving average routines are also provided for data reduction. Processed data in numeric and graphic format can be exported to Excel. This software, PostProc (for post-processing) requires the Dadisp engineering spreadsheet (DSP Development Corp), or equivalent, for implementation. Specific processing routines were written for electrocardiography, electroencephalography, electromyography, blood pressure, skin conductance level, impedance cardiography (cardiac output, stroke volume, thoracic fluid volume), temperature, and respiration

Cowings, Patricia S.↗

NASA NTRS2017

Evolution of NASA's Earth Science Digital Object Identifier Registration System

NASA's Earth Science Data and Information System (ESDIS) Project has implemented a fully automated system for assigning Digital Object Identifiers (DOIs) to Earth Science data products being managed by its network of 12 distributed active archive centers (DAACs). A key factor in the successful evolution of the DOI registration system over last 7 years has been the incorporation of community input from three focus groups under the NASA's Earth Science Data System Working Group (ESDSWG). These groups were largely composed of DOI submitters and data curators from the 12 data centers serving the user communities of various science disciplines. The suggestions from these groups were formulated into recommendations for ESDIS consideration and implementation. The ESDIS DOI registration system has evolved to be fully functional with over 5,000 publicly accessible DOIs and over 200 DOIs being held in reserve status until the information required for registration is obtained. The goal is to assign DOIs to the entire 8000+ data collections under ESDIS management via its network of discipline-oriented data centers. DOIs make it easier for researchers to discover and use earth science data and they enable users to provide valid citations for the data they use in research. Also for the researcher wishing to reproduce the results presented in science publications, the DOI can be used to locate the exact data or data products being cited.

DOI; digital object identifier; mappin↗

NASA NTRS1985

Studies of lightning data in conjunction with geostationary satellite data

Since January, work has been proceeding on the first phase of this project: the creation of an extensive real-time lightning data base accessible via the Space Science and Engineering Center McIdas system. The purpose of this endeavor is two-fold: to enhance the availability and ease of access to lightning data among the various networks, governmental and research agencies; and to test the feasiblity and desirability of such efforts in succeeding years. The final steps in the creation of the necessary communications links, hardware, and software are in the process of being completed. Operations ground rules for access among the various users have been discussed and are being refined. While the research planned for the last year of the project will rely for the most part on archived, quality-controlled data from the various networks, the real-time data will provide a valuable first-look at potentially interesting case studies. For this purpose, tools are being developed on McIdas for display and analysis of the data as they become available. In conjunction with concurrent GOES real-time imagery, strike locations can be plotted, gridded and contoured, or displayed in various statistical formats including frequency distributions, histograms, and scatter plots. The user may also perform these functions in relation to arbitrarily defined areas on the satellite image. By mid-May these preparations for the access and analysis of real-time lightning data are expected to be complete.

Auvine, B.↗

DOE OSTI2024

Emulation and detection of physical faults and cyber-attacks on building energy systems through real-time hardware-in-the-loop experiments

The increasing use of remote or mobile access, integrated wearable technologies, data exchange, and cloud-based data analytics in modern smart buildings is steering the building industry towards open communication technologies. The increased connectivity and accessibility could lead to more cyber-attacks in smart buildings. On the other hand, physical faults (e.g., HVAC -heating, ventilation, and air-conditioning faults) may have similar adverse impacts as those from the cyber-attacks on building energy systems, such as occupant discomfort, energy wastage, and equipment downtime. However, current physical behavior-based anomaly detection methods fail to differentiate between cyber-attacks and physical faults in building energy systems. Moreover, the challenge in collecting real-world threat data with ground truth has led researchers to rely on numerical models with user-defined assumptions, which may not accurately reflect real-world conditions due to the lack of in-situ experimental datasets. To address these challenges and gaps, this paper presents a flexible hardware-in-the-loop (HIL) testbed for generating cyber-attack and physical fault datasets and demonstrating threat detection algorithms in a real building automation system (BAS) environment. This testbed combines hardware (i.e., real BAS with local HVAC controllers and a physical network) with software (i.e., high-fidelity models to represent behaviors of building envelope and HVAC energy systems), enabling emulations of realistic threats. Five HIL experiments, including one baseline without any threats, two with physical faults, and two with cyber-attacks, were conducted to generate datasets containing detailed network traffic and system states. A joint classification framework, incorporating a network analyzer and a physical HVAC fault detector, was proposed to automatically detect cyber-physical abnormalities on BAS at both the network and the physical HVAC levels. The network analyzer comprises a conditional random fields (CRF) based command validator and a statistics-based detection strategy. The fault detector employs a weather and schedule-based pattern matching and feature-based principal component analysis (WPM-FPCA) method. Evaluation of the classification using four metrics from the multi-class confusion matrix revealed an average accuracy of 90.2%, recall of 89.7%, precision of 88.5% and F1-score of 89.2%. Finally, these results demonstrate that the proposed joint classification framework can effectively differentiate between specific types of cyber-attacks (e.g., device reinitialization attack, network Denial-of-Service attack) and physical faults (e.g., air handling unit operational fault, cooling coil valve stuck) in real time for improved building energy management.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

Automated Adsorption Workflow for Semiconductor Surfaces and the Application to Zinc Telluride

Surface adsorption is a crucial step in numerous processes, including heterogeneous catalysis, where the adsorption of key species is often used as a descriptor of efficiency. We present here an automated adsorption workflow for semiconductors which employs density functional theory calculations to generate adsorption data in a high-throughput manner. Starting from a bulk structure, the workflow performs an exhaustive surface search, followed by an adsorption structure construction step, which generates a minimal energy landscape to determine the optimal adsorbate-surface distance. An extensive set of energy-based, charge-based, geometric, and electronic descriptors tailored toward catalysis research are computed and saved to a personal user database. Finally, the application of the workflow to zinc telluride, a promising CO 2 reduction photocatalyst, is presented as a case study to illustrate the capabilities of this method and its potential as a material discovery tool.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

A framework to evaluate machine learning crystal stability predictions

The rapid adoption of machine learning in various scientific domains calls for the development of best practices and community agreed-upon benchmarking tasks and metrics. We present Matbench Discovery as an example evaluation framework for machine learning energy models, here applied as pre-filters to first-principles computed data in a high-throughput search for stable inorganic crystals. We address the disconnect between (1) thermodynamic stability and formation energy and (2) retrospective and prospective benchmarking for materials discovery. Alongside this paper, we publish a Python package to aid with future model submissions and a growing online leaderboard with adaptive user-defined weighting of various performance metrics allowing researchers to prioritize the metrics they value most. To answer the question of which machine learning methodology performs best at materials discovery, our initial release includes random forests, graph neural networks, one-shot predictors, iterative Bayesian optimizers and universal interatomic potentials. We highlight a misalignment between commonly used regression metrics and more task-relevant classification metrics for materials discovery. Accurate regressors are susceptible to unexpectedly high false-positive rates if those accurate predictions lie close to the decision boundary at 0 eV per atom above the convex hull. The benchmark results demonstrate that universal interatomic potentials have advanced sufficiently to effectively and cheaply pre-screen thermodynamic stable hypothetical materials in future expansions of high-throughput materials databases.

Riebesell, Janosh↗

DOE OSTI2021

RAVIS: Resource Forecast and Ramp Visualization for Situational Awareness of Variable Renewable Generation

The Resource Forecast and Ramp Visualization for Situational Awareness (RAVIS) is an innovative, open-source tool for visualizing variable renewable resource forecasts and alerts for significant up- and down-ramps in renewable generation and the consequent system net load. The modular dashboard of RAVIS contains configurable panes for viewing probabilistic time-series forecasts, ramp event alerts on the look-ahead timeline, and spatially resolved resource sites, and forecasts. For comprehensive situational awareness, the tool can add additional data layers from simulation and independent system operator (ISO) market clearing data---including electric line utilization, nodal price, and available generation flexibility---in response to continuously updated renewable forecasts. This paper introduces the RAVIS technology suite employed to provide optimum visualization and flexible design characteristics. The paper also illustrates some use cases of the tool using site-specific solar power forecast data obtained from the IBM Watt-Sun forecasting platform for the California ISO and Midcontinent ISO footprints. The source code for RAVIS is public (https://github.com/ravis-nrel/ravis), and the intended users are forecasters, utility planners, ISO operators, and researchers.

41 EE - Solar Energy Technologies Office (EE-4S)↗

DOE OSTI2021

Clippy

Clippy (CLI + PYthon) is a Python language interface to HPC resources. Precompiled binaries that execute on HPC systems are exposed as methods to a dynamically-created Clippy Python object, where they present a familiar interface to researchers, data scientists, and others. Clippy allows these users to interact with HPC resources in an easy, straightforward environment - at the REPL, for example, or within a notebook - without the need to learn complex HPC behavior and arcane job submission commands.

Bromberger, SethA.↗

DOE OSTI2022

Atmospheric Cold Plasma Jet Coating and Surface Treatment for Improved Adhesive Bonding Performance of Dissimilar Material Joints Subject to Harsh Environmental Exposure

The program goal was the development and demonstration of a novel material coating system using an innovative atmospheric cold microwave plasma jet to enable surface functionalization for corrosion protection, wear resistance and improved bonding strength. The technical approach was directed towards proof-of-concept demonstration of advanced point-of-manufacturing material bonding to improve adhesive joint performance subject to harsh environmental exposure. The assembled team, consisting of the researchers at the University of Illinois, end-users at General Motors and small business manufacturer Starfire Industries, successfully demonstrated a single, cost-effective, high-volume production process that meets the requirements of multi-material combinations relevant to the energy-intensive transportation industry (e.g. Al-steel, Mg-steel, Al-Mg and Al-CFRP joints for body-in-white structures) while eliminating offline pretreatment for Al and Mg alloy substrates that are energy intensive, have chemical waste disposal issues, and add cost. Technical demonstration of dissimilar material joining while maintaining bonding strength and cohesion after long-duration environmental exposure was accomplished for all materials of interest. This novel approach has broad applicability for manufacturing in automotive, aerospace, marine, railcar, and specialty consumer goods, etc.

36 MATERIALS SCIENCE↗