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DOE OSTI2024

AmpSuite

Seismic amplitudes offer vital information about explosion source characteristics, including discrimination and yield estimation. To take advantage of this, we developed an interactive Python package to measure, control data quality, generate broad area propagation models and perform discrimination and estimate yield. Propagation models are essential in support of transportable yield and broad area discrimination. The key benefit of this package will be its ability to continuously integrate data and new techniques. The AmpSuite framework will provide standardized, repeatable, and accurate model generation and characterization routines. The capability is crucial for monitoring agencies tasked with rapid and high-quality seismic event characterization. The AmpSuite software includes a series of independent modules to perform: • Direct Phase Amplitude Measurement and Storage • Coda Envelope Measurement and Storage • Data Quality Control • New Propagation Model Developments • Seismic Discrimination and Analysis • Yield Estimation and supporting utility software. The AmpSuite software provides comprehensive solutions for monitoring agencies seeking to optimize model generation and event analysis within a contemporary Python framework. Stakeholders (AFTAC) have begun to move towards the Python language for scientific analysis as a new workforce emerges.

Alfaro, Richard↗
NASA NTRS2021

The INTEGRAL view on Black Hole X-ray Binaries

INTEGRAL is an ESA mission in fundamental astrophysics that was launched in October 2002. It has been in orbit for over 18 years, during which it has been observing the high-energy sky with a set of instruments specifically designed to probe the emission from hard X-ray and softγ-ray sources. This paper is devoted to the subject of black hole binaries, which are among the most important sources that populate the high-energy sky. We present a review of the scientific literature based on INTEGRAL data, which has significantly advanced our knowledge in the field of relativistic astrophysics. We briefly summarise the state-of-the-art of the study of black hole binaries, with a particular focus on the topics closer to the INTEGRAL science. We then give an overview of the results obtained by INTEGRAL and by other observatories on a number of sources of importance in the field. Finally, we review the main results obtained over the past 18 years on all the black hole binaries that INTEGRAL has observed. We conclude with a summary of the main contributions of INTEGRAL to the field, and on the future perspectives

S. E. Motta↗
NASA NTRS2021

The INTEGRAL View on Black Hole X-ray Binaries

INTEGRAL is an ESA mission in fundamental astrophysics that was launched in October 2002. It has been in orbit for over 18 years, during which it has been observing the high-energy sky with a set of instruments specifically designed to probe the emission from hard X-ray and soft -ray sources. This paper is devoted to the subject of black hole binaries, which are among the most important sources that populate the high-energy sky. We present a review of the scientific literature based on INTEGRAL data, which has significantly advanced our knowledge in the field of relativistic astrophysics. We briefly summarise the state-of-the-art of the study of black hole binaries, with a particular focus on the topics closer to the INTEGRAL science. We then give an overview of the results obtained by INTEGRAL and by other observatories on a number of sources of importance in the field. Finally, we review the main results obtained over the past 18 years on all the black hole binaries that INTEGRAL has observed. We conclude with a summary of the main contributions of INTEGRAL to the field, and on the future perspectives.

S E Motta↗
DOE OSTI2024

Bias Correcting NOAA's High-Resolution Rapid Refresh (HRRR) Wind Resource Data for Grid Integration Applications [Slides]

Many weather years of high-quality wind data are widely accepted in the grid integration community to be important for studying wind energy technical potential, energy system operations, and grid resilience. NREL makes high-quality wind and solar resource data available. NREL's Grid-Atmosphere workshop (March 2024) identified NREL National Solar Radiation Database as widely used in grid integration modeling, but there is less agreement on commonly used wind datasets. One important factor identified by ESIG's 2023 report 'Weather Dataset Needs for Planning and Analyzing Modern Power Systems' for gold standard wind data is regular updates. To address the need for regular updates, NREL's team can now process all currently available and regularly updated High-Resolution Rapid Refresh (HRRR) outputs. HRRR is an hourly-updated operational forecast product produced by the National Oceanic and Atmospheric Administration (NOAA) (Dowell et al., 2022). One barrier to NREL using HRRR is systematic bias and consistency with NREL's existing wind datasets (e.g. WIND Toolkit, 'WTK') across weather years. To address this barrier, we show that the HRRR can be interpolated and bias-corrected to be consistent with NRE's existing datasets. We call the new dataset BC-HRRR (bias-corrected HRRR). As with historical datasets like the WTK, BC-HRRR is intended for use in grid integration modeling (e.g., capacity expansion, production cost, and resource adequacy modeling). BC-HRRR's (2015-present) consistency with WTK (2007-2013) allows NREL to extend internal grid integration tooling with 15+ weather years of wind data with low-overhead extensibility to future years as they are made available by NOAA. The rest of this slide deck documents the BC-HRRR processing methods, validation, and its implications for intended use.

17 WIND ENERGY↗
NASA NTRS2006

A Possible Magnetar Nature for IGR J16358-4726

We present detailed spectral and timing analysis of the hard x-ray transient IGR J16358-4726 using multi-satellite archival observations. A study of the source flux time history over 6 years, suggests that this transient outbursts can be occurring in intervals of at most 1 year. Joint spectral fits using simultaneous Chandra/ACIS and INTEGRAL/ISGRI data reveal a spectrum well described by an absorbed cut-off power law model plus an Fe line. We detected the pulsations initially reported using Chandra/ACIS also in the INTEGRAL/ISGRI light curve and in subsequent XMM-Newton observations. Using the INTEGRAL data we identified a pulse spin up of 94 s (P = 1.6 x 10(exp -4), which strongly points to a neutron star nature for IGR J16358-4726. Assuming that the spin up is due to disc accretion, we estimate that the source magnetic field ranges between 10(sup 13) approximately 10(sup 15) depending on its distance, possibly supporting a magnetar nature for IGR J16358-4726.

Patel, S.↗
NASA NTRSDate not supplied

AAM NC ATI TechTalk - Aerograph Architecture v1

Aerograph is NASA’s data management system for Advanced Air Mobility. Its mission is to support AAM research by providing a reliable and secure system that collects, stores, protects, and shares AAM data. Its vision is to provide a system that AAM research scientists, aerospace engineers, data scientists, and analysts trust for obtaining NC data and performing key analyses. The types of data Aerograph manages involves data related to flight test events, including: Aircraft Performance and Characterization (e.g., position reports) Airspace (e.g., operation intent, waypoints, and constraints) Environment (e.g., surface and wind weather) Infrastructure (e.g., surveillance coverage) Derivative Analytical Artifacts (e.g., glide path performance chart, 3D position chart, Integrated Data Product)

Aerograph↗
NASA NTRS2001

Integrated Component-based Data Acquisition Systems for Aerospace Test Facilities

The Multi-Instrument Integrated Data Acquisition System (MIIDAS), developed by the NASA Langley Research Center, uses commercial off the shelf (COTS) products, integrated with custom software, to provide a broad range of capabilities at a low cost throughout the system s entire life cycle. MIIDAS combines data acquisition capabilities with online and post-test data reduction computations. COTS products lower purchase and maintenance costs by reducing the level of effort required to meet system requirements. Object-oriented methods are used to enhance modularity, encourage reusability, and to promote adaptability, reducing software development costs. Using only COTS products and custom software supported on multiple platforms reduces the cost of porting the system to other platforms. The post-test data reduction capabilities of MIIDAS have been installed at four aerospace testing facilities at NASA Langley Research Center. The systems installed at these facilities provide a common user interface, reducing the training time required for personnel that work across multiple facilities. The techniques employed by MIIDAS enable NASA to build a system with a lower initial purchase price and reduced sustaining maintenance costs. With MIIDAS, NASA has built a highly flexible next generation data acquisition and reduction system for aerospace test facilities that meets customer expectations.

Ross, Richard W.↗
NASA NTRS2021

Verifying Mars 2020 Sampling and Caching Robotic Functions with Position Budgeting Process and Tool

The Mars 2020 Perseverance Rover was launched on July 30th, 2020 with one of the most complex robotic systems ever implemented on an interplanetary mission. Much of this robotic complexity resides in the Rover Sampling and Caching Subsystem (SCS) to enable collection of Martian samples for eventual return to earth and preparation of surfaces for close-up surface science observations. Two robotic arms are used by SCS: the large Robotic Arm (RA) positions the coring drill and science instruments mounted to the Turret for surface interactions, and the smaller Sample Handling Assembly (SHA) manipulates Sample Tube Assemblies (STA) within the Adaptive Caching Assembly (ACA) to prepare them for sample collection, processing, and hermetic sealing. The robotic arms interact with the Martian surface and other SCS components in many ways and in a variety of configurations, with positioning accuracy requirements ranging from tens of millimeters for some surface interactions down to sub-millimeter accuracy for some ACA interactions.This paper describes the process and tool used to calculate the SCS robotic interaction positioning budgets and verify the as-built hardware when delivered. To ensure that these robotic systems are able to perform their tasks, each robotic interaction with another element was broken down into its composite functions. To calculate a positioning budget margin for each function, an allowable was defined and then compared to the list of error sources that contribute to misalignment. Across the subsystem, over 250 functions were identified to be assessed, with almost 500 error sources feeding into their budget calculations. In addition to using as-built values in the budgets for SCS Verification and Validation (V&V) after the hardware was complete, these budgets were populated with design data during the design phase to identify areas of concern and guide hardware design to ensure positive position budget margins.Because of the size of the SCS team that had inputs to the positioning budgets and the sheer number of items in the budgets that needed to be created, updated, and verified, having a tool that would allow for simultaneous access and robust data integrity and processing was imperative. To accomplish this, a web-based MySQL database was created that allowed users to create function position budgets, link individual errors and allowables to them, and view function position budget margin reports. Each error and allowable records data for lateral, normal, angular, and clocking errors, with the ability to add as-built data for up to four different hardware builds. Margin reports can be generated for either design values alone or replacing design data with as-built data when available. These as-built reports are used for final verification of the SCS positioning requirements. Ultimately, the SCS positioning budget process and database tool led to successful interactions during test and an SCS robotic system that is ready to perform sample acquisition and caching on the surface of Mars.

Williams, Jeffrey↗
NASA NTRSDate not supplied

NASA's Implementation of Cloud Services for Human Space Flight

Cloud is a tried-and-true technology used throughout United States government agencies, including the National Aeronautics and Space Administration (NASA). With reliable results and infrequent downtimes, cloud allows for secure remote access, customizability, and streamlined monitoring options, creating an environment for better data integrity and availability. As NASA increasingly migrates functions to the cloud, the Space Communications and Navigation Program (SCaN) program has been investigating how this capability can be leveraged to provide communication services to its users and customers. Currently, missions such as NASA-ISRO Synthetic Aperture Radar (NISAR), Plankton, Aerosol, Cloud, ocean Ecosystem (PACE), and Roman Space Telescope (RST) are planned to incorporate cloud into their data delivery architecture. However, SCaN is looking to expand further. This conversion to using cloud services allows for greater availability of mission data for both robotic and human space flight (HSF)missions. The SCaN program and the Near Space Network (NSN) are working to consolidate resources and create a cloud environment suitable for the entirety of the SCaN program network architecture. SCaN is in the process of finalizing its cloud architecture and soon will be implementing cloud services. The new services used will adhere to federal regulations including Federal Risk and Authorization Management Program (FedRAMP), which is built upon National Institute of Standards and Technology (NIST)documentation. While keeping in mind these security requirements, an auxiliary objective of the cloud integration is to ensure the most cost-efficient solution; providing a scalable, robust and resilient system. Using cloud services, NASA will gain access to better centralized monitoring and management features, along with customizable services on a pay-per-use plan. With the ever-growing NASA mission data volume needs, maintaining ample storage space is another major constraint. Processing and storing such large amounts of data, on the order of terabytes a day, requires dynamic processing capability which is inherently a strength of cloud computing. By routing this data from ground stations through the cloud, there will be greater ease of access for both SCaN and the user community. Artificial intelligence and other built-in cloud functions can also enhance efficiency, improving data processing time. Thereby also allowing for better data availability. As we look to the future of cloud services, NASA will continue to leverage capabilities that will benefit NASA’s ability to provide cost-effective communication services. This paper further outlines the evolution of cloud use by SCaN in the context of Human Space Flight.

cloud storage↗
DOE OSTI2026

Ten questions concerning Large Language Models (LLMs) for building applications

Large Language Models (LLMs) are emerging as powerful AI tools capable of transforming how building information is collected, processed, analyzed, and applied across diverse research areas. Their capabilities can help building operators, facility managers and other stakeholders such as designers, architects and engineers by providing actionable insights for decision-making across planning, construction, operations, and maintenance of buildings and facilities. This paper explores ten key questions concerning the role of LLMs in shaping sustainable, intelligent, and human-centric buildings. From fundamental definitions to advanced applications, we examine how LLMs facilitate decision-making across the life cycle of buildings and energy systems. LLMs can enhance life cycle assessments (LCA), building energy simulations, and real-time data integration, empowering more efficient and adaptive human-AI environments. They can also contribute to streamlining regulatory compliance, improving post-occupancy evaluations, and fostering more inclusive and participatory design processes. Additionally, this paper addresses the ethical challenges posed by LLMs, such as bias, data privacy, and environmental impacts, and explores their potentials in advancing intelligent digital twins (DT) for ongoing building operations and maintenance. Built upon our applied research using LLMs and the review of tools, datasets, and research gaps, we provide a forward-looking perspective on how LLMs can drive innovation, collaboration, and productivity in the built environment while supporting ethical and effective implementation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1983

A feasibility study: Forest Fire Advanced System Technology (FFAST)

The National Aeronautics and Space Administration/Jet Propulsion Laboratory and the United States Department of Agriculture Forest Service completed a feasibility study that examined the potential uses of advanced technology in forest fires mapping and detection. The current and future (1990's) information needs in forest fire management were determined through interviews. Analysis shows that integrated information gathering and processing is needed. The emerging technologies that were surveyed and identified as possible candidates for use in an end to end system include ""push broom'' sensor arrays, automatic georeferencing, satellite communication links, near real or real time image processing, and data integration. Matching the user requirements and the technologies yielded a ""strawman'' system configuration. The feasibility study recommends and outlines the implementation of the next phase for this project, a two year, conceptual design phase to define a system that warrants continued development.

Mcleod, R. G.↗
NASA NTRS1990

Thematic Conference on Remote Sensing for Exploration Geology - Methods, Integration, Solutions, 7th, Calgary, Canada, Oct. 2-6, 1989, Proceedings. Volumes 1 & 2

Recent advances in airborne and satellite remote-sensing technology for application to geological exploration are discussed in reviews and reports. Sections are devoted to basement tectonics and their surface expressions, spectral geology, hydrocarbon exploration applications, radar applications and future systems, engineering and environment issues, geobotanical remote sensing, advanced image processing, data integration and mapping, and mineral exploration. Extensive diagrams, graphs, and sample images are provided.

Source record↗
NASA NTRS2020

Monitoring Water-Related Ecosystems with Earth Observation Data in Support of Sustainable Development Goal (SDG) 6 Reporting

Lack of national data on water-related ecosystems is a major challenge to achieving the Sustainable Development Goal (SDG) 6 targets by 2030. Monitoring surface water extent, wetlands, and water quality from space can be an important asset for many countries in support of SDG 6 reporting. We demonstrate the potential for Earth observation (EO) data to support country reporting for SDG Indicator 6.6.1, ‘Change in the extent of water-related ecosystems over time’ and identify important considerations for countries using these data for SDG reporting. The spatial extent of water-related ecosystems, and the partial quality of water within these ecosystems is investigated for seven countries. Data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat 5, 7, and 8 with Shuttle Radar Topography Mission (SRTM) are used to measure surface water extent at 250 m and 30 m spatial resolution, respectively, in Cambodia, Jamaica, Peru, the Philippines, Senegal, Uganda, and Zambia. The extent of mangroves is mapped at 30 m spatial resolution using Landsat 8 Operational Land Imager (OLI), Sentinel-1, and SRTM data for Jamaica, Peru, and Senegal. Using Landsat 8 and Sentinel 2A imagery, total suspended solids and chlorophyll-a are mapped over time for a select number of large surface water bodies in Peru, Senegal, and Zambia. All of the EO datasets used are of global coverage and publicly available at no cost. The temporal consistency and long time-series of many of the datasets enable replicability over time, making reporting of change from baseline values consistent and systematic. We find that statistical comparisons between different surface water data products can help provide some degree of confidence for countries during their validation process and highlight the need for accuracy assessments when using EO-based land change data for SDG reporting. We also raise concern that EO data in the context of SDG Indicator 6.6.1 reporting may be more challenging for some countries, such as small island nations, than others to use in assessing the extent of water-related ecosystems due to scale limitations and climate variability. Country-driven validation of the EO data products remains a priority to ensure successful data integration in support of SDG Indicator 6.6.1 reporting. Multi-country studies such as this one can be valuable tools for helping to guide the evolution of SDG monitoring methodologies and provide a useful resource for countries reporting on water-related ecosystems. The EO data analyses and statistical methods used in this study can be easily replicated for country-driven validation of EO data products in the future.

water-related ecosystems; surface water extent; ma↗
NASA NTRS2020

Monitoring Water-Related Ecosystems with Earth Observation Data in Support of Sustainable Development Goal (SDG) 6 Reporting

Lack of national data on water-related ecosystems is a major challenge to achieving the Sustainable Development Goal (SDG) 6 targets by 2030. Monitoring surface water extent, wetlands, and water quality from space can be an important asset for many countries in support of SDG 6reporting. We demonstrate the potential for Earth observation (EO) data to support country reporting for SDG Indicator 6.6.1, ‘Change in the extent of water-related ecosystems over time’ and identify important considerations for countries using these data for SDG reporting. The spatial extent of water-related ecosystems, and the partial quality of water within these ecosystems is investigated for seven countries. Data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat 5, 7, and 8 with Shuttle Radar Topography Mission (SRTM) are used to measure surface water extent at 250 m and 30 m spatial resolution, respectively, in Cambodia, Jamaica, Peru, the Philippines, Senegal, Uganda, and Zambia. The extent of mangroves is mapped at 30 m spatial resolution using Landsat 8 Operational Land Imager (OLI), Sentinel-1, and SRTM data for Jamaica, Peru, and Senegal. Using Landsat 8 and Sentinel 2A imagery, total suspended solids and chlorophyll-a are mapped overtime for a select number of large surface water bodies in Peru, Senegal, and Zambia. All of the EO datasets used are of global coverage and publicly available at no cost. The temporal consistency and long time-series of many of the datasets enable replicability over time, making reporting of change from baseline values consistent and systematic. We find that statistical comparisons between different surface water data products can help provide some degree of confidence for countries during their validation process and highlight the need for accuracy assessments when using EO-based land change data for SDG reporting. We also raise concern that EO data in the context of SDG Indicator 6.6.1reporting may be more challenging for some countries, such as small island nations, than others to use in assessing the extent of water-related ecosystems due to scale limitations and climate variability. Country-driven validation of the EO data products remains a priority to ensure successful data integration in support of SDG Indicator 6.6.1 reporting. Multi-country studies such as this one can be valuable tools for helping to guide the evolution of SDG monitoring methodologies and provide a useful resource for countries reporting on water-related ecosystems. The EO data analyses and statistical methods used in this study can be easily replicated for country-driven validation of EO data products in the future.

Raha Hakimdavar↗
NASA NTRS1994

Long duration biaxial cylinder testing of balloon grade polyethylene films with emphasis on automated data acquisition and control

Characterization of a 2-dimensional material constitutive model in the practical biaxial state for engineering utility of balloon envelope structural analysis is achievable with laboratory cylinder tests. Hoop (circumferential, and longitudinal strains are time-wise measured on axially loaded pressurized cylinders. Pre-programmed ramped loading changes as well as precise long term pressure control are achieved through cascaded proportional, integral derivative (PID) flow control loops that are part of an integrated data acquisition and process control system. Real time data reduction and analysis allow monitoring of unattended tests that have durations of up to a month. Measured and controlled parameters and variables are discussed; date analysis techniques are reviewed.

Martone, Michael↗
NASA NTRS2001

Secure Large-Scale Airport Simulations Using Distributed Computational Resources

To fully conduct research that will support the far-term concepts, technologies and methods required to improve the safety of Air Transportation a simulation environment of the requisite degree of fidelity must first be in place. The Virtual National Airspace Simulation (VNAS) will provide the underlying infrastructure necessary for such a simulation system. Aerospace-specific knowledge management services such as intelligent data-integration middleware will support the management of information associated with this complex and critically important operational environment. This simulation environment, in conjunction with a distributed network of supercomputers, and high-speed network connections to aircraft, and to Federal Aviation Administration (FAA), airline and other data-sources will provide the capability to continuously monitor and measure operational performance against expected performance. The VNAS will also provide the tools to use this performance baseline to obtain a perspective of what is happening today and of the potential impact of proposed changes before they are introduced into the system.

McDermott, William J.↗
NASA NTRS2012

Fermi LAT Search for Dark Matter in Gamma-Ray Lines and the Inclusive Photon Spectrum

Dark matter particle annihilation or decay can produce monochromatic gamma-ray lines and contribute to the diffuse gamma-ray background. Flux upper limits are presented for gamma-ray spectral lines from 7 to 200 GeV and for the diffuse gamma-ray background from 4.8 GeV to 264 GeV obtained from two years of Fermi Large Area Telescope data integrated over most of the sky. We give cross section upper limits and decay lifetime lower limits for dark matter models that produce gamma-ray lines or contribute to the diffuse spectrum, including models proposed as explanations of the PAMELA and Fermi cosmic-ray data.

Ackermann, M.↗
NASA NTRS2013

Exoplanet Transit Spectroscopy Using WFC3: WASP-12 b, WASP-17 b, and WASP-19 b

We report an analysis of transit spectroscopy of the extrasolar planets WASP-12 b, WASP-17 b, and WASP-19 b using the Wide Field Camera 3 (WFC3) on the Hubble Space Telescope (HST). We analyze the data for a single transit for each planet using a strategy similar, in certain aspects, to the techniques used by Berta et al., but we extend their methodology to allow us to correct for channel- or wavelength-dependent instrumental effects by utilizing the band-integrated time series and measurements of the drift of the spectrum on the detector over time. We achieve almost photon-limited results for individual spectral bins, but the uncertainties in the transit depth for the band-integrated data are exacerbated by the uneven sampling of the light curve imposed by the orbital phasing of HST's observations. Our final transit spectra for all three objects are consistent with the presence of a broad absorption feature at 1.4 nano meter most likely due to water. However, the amplitude of the absorption is less than that expected based on previous observations with Spitzer, possibly due to hazes absorbing in the NIR or non-solar compositions. The degeneracy of models with different compositions and temperature structures combined with the low amplitude of any features in the data preclude our ability to place unambiguous constraints on the atmospheric composition without additional observations with WFC3 to improve the signal-to-noise ratio and/or a comprehensive multi-wavelength analysis.

Atmospheres↗