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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

Climate Analytics as a Service

Climate science is a big data domain that is experiencing unprecedented growth. In our efforts to address the big data challenges of climate science, we are moving toward a notion of Climate Analytics-as-a-Service (CAaaS). CAaaS combines high-performance computing and data-proximal analytics with scalable data management, cloud computing virtualization, the notion of adaptive analytics, and a domain-harmonized API to improve the accessibility and usability of large collections of climate data. MERRA Analytic Services (MERRA/AS) provides an example of CAaaS. MERRA/AS enables MapReduce analytics over NASA's Modern-Era Retrospective Analysis for Research and Applications (MERRA) data collection. The MERRA reanalysis integrates observational data with numerical models to produce a global temporally and spatially consistent synthesis of key climate variables. The effectiveness of MERRA/AS has been demonstrated in several applications. In our experience, CAaaS is providing the agility required to meet our customers' increasing and changing data management and data analysis needs.

big data↗
NASA NTRSDate not supplied

Classification of Notices to Airmen using Natural Language Processing

This paper establishes the feasibility of using Natural Language Processing (NLP) to classify NOTAMs or Notices to Airmen – a pilot messaging framework to gather real-time situational awareness. Present day air mobility operations heavily rely on NOTAMs. However, pilots often have difficulty interpreting NOTAMs due to the sheer volume of inapplicable messages and unclear abbreviations. Using NLP, the presented study analyzes the accuracy of classifying NOTAMs and, thereby, the efficiency of generating actionable interpretations in real time. To this effect, efficacies of four NLP neural network architectures were analyzed, including three Recurrent Neural Networks (RNNs) with GloVe, Word2Vec, and FastText word embeddings, and one trained Bi-Directional Encoder Representations from Transformers (BERT) model. The four neural networks were trained and evaluated on three open-source datasets of varying text lengths, vocabularies, and grammars, taken from e-commerce product descriptions, social media tweets, and unstructured descriptions for data and analytics services on open data marketplaces such as NASA’s Data and Reasoning Fabric (DRF) platform. This provided cross-analysis of each neural network architecture’s performance per text type. The best performing architecture, BERT, was then fine-tuned on a collection of open-source NOTAM data. Post-training, a real-time NOTAM classification service was implemented to draw inference on new NOTAMs using the trained model, which demonstrated close to 99% accuracy in classification. This modular classification service is envisioned to be integrated with a data and analytics delivery platform, such as the DRF, thus availing real-time contextualization of NOTAMs to air mobility clients, humans, and machines for enhanced decision making.

Aiden C. Szeto↗
NASA NTRSDate not supplied

Classification of Notices to Airmen using Natural Language Processing

This paper establishes the feasibility of using Natural Language Processing (NLP) to classify NOTAMs or Notices to Airmen – a pilot messaging framework to gather real-time situational awareness. Present day air mobility operations heavily rely on NOTAMs. However, pilots often have difficulty interpreting NOTAMs due to the sheer volume of inapplicable messages and unclear abbreviations. Using NLP, the presented study analyzes the accuracy of classifying NOTAMs and, thereby, the efficiency of generating actionable interpretations in real time. To this effect, efficacies of four NLP neural network architectures were analyzed, including three Recurrent Neural Networks (RNNs) with GloVe, Word2Vec, and FastText word embeddings, and one trained Bi-Directional Encoder Representations from Transformers (BERT) model. The four neural networks were trained and evaluated on three open-source datasets of varying text lengths, vocabularies, and grammars, taken from e-commerce product descriptions, social media tweets, and unstructured descriptions for data and analytics services on open data marketplaces such as NASA’s Data and Reasoning Fabric (DRF) platform. This provided cross-analysis of each neural network architecture’s performance per text type. The best performing architecture, BERT, was then fine-tuned on a collection of open-source NOTAM data. Post-training, a real-time NOTAM classification service was implemented to draw inference on new NOTAMs using the trained model, which demonstrated close to 99% accuracy in classification. This modular classification service is envisioned to be integrated with a data and analytics delivery platform, such as the DRF, thus availing real-time contextualization of NOTAMs to air mobility clients, humans, and machines for enhanced decision making.

Aiden Szeto↗
NASA NTRS1993

Analysis of the TDRS multiple access system for possible use as an attitude control system sensor

A member of the constellation of TDR satellites (TDRS) has experienced a failure of its prime earth sensor. Failure of the remaining earth sensor could result in the inability of the satellite to control its attitude and provide user services. Loss of the satellite would be a serious event. The multiple access (MA) antenna array on the TDRS has been proposed for use as a backup sensor for the attitude control system. This paper describes our analysis of the performance of the MA array as an interferometer used for accurate attitude determination. A least squares fit of a plane to the MA phase information appears to represent the TDRS body roll and pitch within about 0.1 deg. This is sufficient for SGL pointing and MA and SSA user services. Analytic improvements that include ionospheric correction may yield sufficient accuracy for KSA user services.

Blevins, Bruce Allyn↗
DOE OSTI2025

Characterization of Tank 9H Annulus Sample in Support of Residual Material Inventory Determinations

The Savannah River National Laboratory (SRNL) was requested by Savannah River Mission Completion (SRMC) to provide sample preparation and characterization of the Tank 9H annulus sample in support of Residual Material Inventory Determinations. One Tank 9H sample in three vials [HTF-9-25-13, HTF-9-25-14 and HTF-9-25-15], with each vial containing approximately 200 mL of the Tank 9H annulus salt solution, were delivered to the SRNL Shielded Cells for sample preparation and characterizations in February 2025. The density of the “as-received” solution contained in each of the three Tank 9H annulus sample vials were determined followed by a solid-liquid separation on each one using 0.45-micron Nalgene® nylon filter membranes. The resulting filtrates were combined to form the Tank 9H annulus sample with a total volume of about 600 mL. The combined wet solid fractions, about a total of 4.8 grams of salt material, remaining on the filter membranes were air-dried in the Shielded Cells for 72 hours. The total weight of the air-dried solids was 2.1 grams. These air-dried solids were washed with deionized water (DI water) at a phase ratio of 60 mL DI water/gram of solids to recover insoluble solids, if any. No visible or measurable quantity of insoluble solids were recovered after DI water washing of the air-dried solids because the air-dried solids completely dissolved in the DI water. The solid fraction-wash water was not combined with the 600 mL of the filtrate solution, and the resulting solution was not screened or analyzed for radionuclides. Aliquot sample volumes of the undiluted Tank 9H annulus sample were sent to the SRNL analytical services groups for radionuclides, elementals, anions and total mercury analysis by various methods including radiochemical separations/counting methods, inductively coupled plasma-atomic emission spectroscopy (ICP-AES), and Inductively Coupled Plasma Mass Spectroscopy (ICP-MS) and special preparations. All sample analyses were performed in triplicate. This report presents the analytical characterization results for the Tank 9H annulus sample. The results are also reported where analytical methods yielded additional analytes, other than those requested by SRMC. In the characterization of the Tank 9H annulus sample, the detection limits for all the analytes, as specified in the Technical Task Request (TTR) and Task Technical and Quality Assurance Plan (TTQAP), were met.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Savannah River National Laboratory Participation in the International Atomic Energy Agency CPC Interlaboratory Comparison Exercise 2

International Atomic Energy Agency Safeguards Analytical Services (IAEA-SGAS) oversees coordinating the second Controlled Potential Coulometry Quality Control Interlaboratory Comparison (CPC QC ILC) on behalf of the Nuclear Material Laboratory (NML). The purpose of the exercise is to: (1) verify the ability of participating laboratories to measure the Pu concentration in the sample solutions, and (2) estimate the method performance (repeatability and intermediate reproducibility). Sample shipping coordination was performed by IAEA-SGAS. The test sample is a plutonium nitrate solution (estimated molarity of 3-5 M), delivered in two PTFE screw-capped quartz ampoules. Each participating laboratory is to receive two ampoules. Each ampoule holds approximately 8 mL of solution containing approximately 10 mg Pu/g. The gross weights of the ampoules were provided. The test sample is assumed to have an iron content below the level of significance for the CPC. The isotopic composition of the plutonium test sample was provided; however, no analysis date was provided. In addition, IAEA-SGAS provided analytical instructions to participants. On September 20, 2022, SRNL received the samples sent by IAEA-SGAS.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2026

Integrated System Planning: Emerging Software Requirements in the Power Industry

Power system planning software remains fragmented across organizational boundaries, with specialized tools for capacity expansion, production cost modeling, power flow, and dynamic analysis operating on incompatible data models and assumptions. This article argues that the fragmentation is not merely a technical problem but a predictable consequence of Conway's law: software architectures mirror the departmental structures within which they are developed. Regulatory milestones like Federal Energy Regulatory Commission (FERC) Order 888 formalized these divisions, but the roots trace back to the distinct engineering disciplines-mechanical, chemical, and electrical-that staffed generation and transmission planning departments in vertically integrated utilities. As the industry moves toward integrated system planning (ISP) that coordinates generation, transmission, and distribution investment decisions, the software ecosystem must evolve accordingly. We identify five categories of software requirements to enable this transition: coherent data inputs decoupled from individual applications, unified and extensible data schemas, modular component representations that support multiple abstraction levels, lifecycle management of planning datasets, and well-defined application programming interface (API) contracts that separate data exchange from algorithmic control. We examine how these requirements interact with three common workflow patterns-serial gate clearing, sequential multiapplication, and convergence oriented-and discuss the interface design principles each demands. We then outline a vision for platform-based planning architectures where specialized analytical services compose through standardized interfaces and where artificial intelligence (AI)/machine learning (ML) tools augment decision support within a disciplined software infrastructure. The practices proposed here offer a path from today's siloed tool collections toward collaborative planning ecosystems capable of handling the complexity of modern power system transformation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

NWAL Validation Report for U Assay by Potentiometric Titration (Modified Davies and Gray Technique) and U and PU Assay by Isotope Dilution Mass Spectrometry

SRNL Sensing & Metrology, previously Analytical Laboratory, is a member of the IAEA Network of Analytical Laboratories for Nuclear Material Measurement that is qualified to provide Uranium and Plutonium isotopic analysis of nuclear materials by Thermal Ionization Mass Spectrometry. As part of the membership, SRNL participated in the 2019 Nuclear Material Round Robin to maintain the qualification to provide isotopic analysis. SRNL also participated with the additional intent to qualify Uranium Assay by Potentiometric Titration (Davies and Gray method) and Uranium and Plutonium Isotope Dilution by Thermal Ionization Mass Spectrometry as part of the International Atomic Energy Agency’s Network of Analytical Laboratories. The proficiency test exercise was conducted by the Office of Safeguards Analytical Services, Department of Safeguards.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Specification of FIPD Fission Gas Chemistry Data

The current FIPD library contains two main sets of fission gas chemistry data. The first set is data collected during the Integral Fast Reactor (IFR) program from 1984 to 1994, using a gas mass spectrometry system located in the Analytical Laboratory (AL) at Argonne National Laboratory-West (Argonne-West). Throughout this period, numerous fission gas release and chemistry datasets were gathered from a variety of metallic fuel pins. The fission gas was sampled by the Gas Assay, Sample and Recharge (GASR) System in the Hot Fuel Examination Facility (HFEF) and transferred to the AL to perform gas composition and isotopic abundance analysis. The second set is data collected after the IFR program. The fission gas samples were also collected by the GASR system at the HFEF, but analyzed using a similar gas mass spectrometer located in Pacific Northwest National Laboratory (PNNL). Many fuel pins irradiated in Experimental Breeder Reactor II (EBR-II) and the Fast Flux Test Facility (FFTF) were measured, including the fuel pins for the MFF series of experiments, designed to qualify metal fuel for use as driver fuel in the FFTF and X496 experiment. For either set of data, fission gas was sampled with the gas sampling line in GASR using sample bottles after the capsule/element volume has been determined and the system is still full of radioactive gas. The sample bottles were then transferred to the sample packaging cylinder or an approved storage location pending transfer to the AL or prepared for shipment to another laboratory (such as PNNL) for analysis of the collected gas as directed on the GASR data form, other approved form. The receiving laboratories (AL or PNNL) required their Analytical Service Request form to be completed prior to sample transfer. Typical sample transfer processes were initiated at HFEF by the principal or process engineer. The laboratories performing the analyses (AL or PNNL) use the sample bottle numbers as well as a sample number produced by the respective laboratory. HFEF and the responsible experimenter tracked the sample using the analysis number, the gas bottle number, and the fuel pin number.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
NASA NTRS1977

Study of palladium plating components

Palladium deposits were prepared by electrolysis for evaluation as catalytic materials. Electrolysis was carried out in acidic solutions consisting of either 1.0 M in NaCl and 0.01 M PdCl2 or 1.0 M NaCl and 0.04 M PdCl2. It was during the preparation of the palladium deposits that unexpected observations were made that led to the request for analytical services. The analyses did not, nor were they intended to, answer all of the questions. They did, however, shed light on the nature and magnitude of some of the contaminants in the solutions and in the palladium electrodes, as well as characterize the forms of the palladium deposits. Results of analyses are grouped into solution, deposit, and electrode categories for comparison purposes.

Source record↗
NASA NTRS1999

First NASA/Industry High-Speed Research Configuration Aerodynamics Workshop

This publication is a compilation of documents presented at the First NASA/Industry High Speed Research Configuration Aerodynamics Workshop held on February 27-29, 1996 at NASA Langley Research Center. The purpose of the workshop was to bring together the broad spectrum of aerodynamicists, engineers, and scientists working within the Configuration Aerodynamics element of the HSR Program to collectively evaluate the technology status and to define the needs within Computational Fluid Dynamics (CFD) Analysis Methodology, Aerodynamic Shape Design, Propulsion/Airframe Integration (PAI), Aerodynamic Performance, and Stability and Control (S&C) to support the development of an economically viable High Speed Civil Transport (HSCT) aircraft. To meet these objectives, papers were presented by representative from NASA Langley, Ames, and Lewis Research Centers; Boeing, McDonnell Douglas, Northrop-Grumman, Lockheed-Martin, Vigyan, Analytical Services, Dynacs, and RIACS.

Wood, Richard M.↗
NASA NTRS1999

First NASA/Industry High-Speed Research Configuration Aerodynamics Workshop

This publication is a compilation of documents presented at the First NASA/Industry High Speed Research Configuration Aerodynamics Workshop held on February 27-29, 1996 at NASA Langley Research Center. The purpose of the workshop was to bring together the broad spectrum of aerodynamicists, engineers, and scientists working within the Configuration Aerodynamics element of the HSR Program to collectively evaluate the technology status and to define the needs within Computational Fluid Dynamics (CFD) Analysis Methodology, Aerodynamic Shape Design, Propulsion/Airframe Integration (PAI), Aerodynamic Performance, and Stability and Control (S&C) to support the development of an economically viable High Speed Civil Transport (HSCT) aircraft. To meet these objectives, papers were presented by representative from NASA Langley, Ames, and Lewis Research Centers; Boeing, McDonnell Douglas, Northrop-Grumman, Lockheed-Martin, Vigyan, Analytical Services, Dynacs, and RIACS.

Wood, Richard M.↗
NASA NTRS1999

First NASA/Industry High-Speed Research Configuration Aerodynamics Workshop

This publication is a compilation of documents presented at the First NASA Industry High Speed Research Configuration Aerodynamics Workshop held on February 27-29, 1996 at NASA Langley Research Center. The purpose of the workshop was to bring together the broad spectrum of aerodynamicists, engineers, and scientists working within the Configuration Aerodynamics element of the HSR Program to collectively evaluate the technology status and to define the needs within Computational Fluid Dynamics (CFD) Analysis Methodology, Aerodynamic Shape Design, Propulsion/Airframe Integration (PAI), Aerodynamic Performance, and Stability and Control (S&C) to support the development of an economically viable High Speed Civil Transport (HSCT) aircraft. To meet these objectives, papers were presented by representatives from NASA Langley, Ames, and Lewis Research Centers; Boeing, McDonnell Douglas, Northrop-Grumman, Lockheed-Martin, Vigyan, Analytical Services, Dynacs, and RIACS.

Wood, Richard M.↗
NASA NTRS1993

Laser Analyzer

Dopant level analysis is important to the laser system designer because it allows him to model the laser's performance. It also allows the end user to determine what went wrong when a laser fails to perform as expected. Under a Small Business Innovation Research (SBIR) contract, Scientific Materials Corporation has developed a process for producing uniform laser rods in which the amount of water trapped in the crystal during growth is reduced. This research led to the formation of a subsidiary company, Montana Analytical Services, which conducts analysis of laser rods for dopant ion concentrations. This is a significant advance in laser technology.

Source record↗
NASA NTRS1992

The Ribosomal Database Project

The Ribosomal Database Project (RDP) complies ribosomal sequences and related data, and redistributes them in aligned and phylogenetically ordered form to its user community. It also offers various software packages for handling, analyzing and displaying sequences. In addition, the RDP offers (or will offer) certain analytic services. At present the project is in an intermediate stage of development.

Non-NASA Center↗
NASA NTRS2011

Capabilities of the Impact Testing Facility at Marshall Space Flight Center

The test and analysis capabilities of the Impact Testing Facility at NASA's Marshall Space Flight Center are described. Nine different gun systems accommodate a wide range of projectile and target sizes and shapes at velocities from subsonic through hypersonic, to accomplish a broad range of ballistic and hypervelocity impact tests. These gun systems include ballistic and microballistic gas and powder guns, a two-stage light gas gun, and specialty guns for weather encounter studies. The ITF "rain gun" is the only hydrometeor impact gun known to be in existence in the United States that can provide single impact performance data with known raindrop sizes. Simulation of high velocity impact is available using the Smooth Particle Hydrodynamic Code. The Impact Testing Facility provides testing, custom test configuration design and fabrication, and analytical services for NASA, the Department of Defense, academic institutions, international space agencies, and private industry in a secure facility located at Marshall Space Flight Center, on the US Army's Redstone Arsenal in Huntsville, Alabama. This facility performs tests that are subject to International Traffic in Arms Regulations (ITAR) and DoD secret classified restrictions as well as proprietary and unrestricted tests for civil space agencies, academic institutions, and commercial aerospace and defense companies and their suppliers.

Finchum, Andy↗
NASA NTRS2015

High Resolution Nature Runs and the Big Data Challenge

NASA's Global Modeling and Assimilation Office at Goddard Space Flight Center is undertaking a series of very computationally intensive Nature Runs and a downscaled reanalysis. The nature runs use the GEOS-5 as an Atmospheric General Circulation Model (AGCM) while the reanalysis uses the GEOS-5 in Data Assimilation mode. This paper will present computational challenges from three runs, two of which are AGCM and one is downscaled reanalysis using the full DAS. The nature runs will be completed at two surface grid resolutions, 7 and 3 kilometers and 72 vertical levels. The 7 km run spanned 2 years (2005-2006) and produced 4 PB of data while the 3 km run will span one year and generate 4 BP of data. The downscaled reanalysis (MERRA-II Modern-Era Reanalysis for Research and Applications) will cover 15 years and generate 1 PB of data. Our efforts to address the big data challenges of climate science, we are moving toward a notion of Climate Analytics-as-a-Service (CAaaS), a specialization of the concept of business process-as-a-service that is an evolving extension of IaaS, PaaS, and SaaS enabled by cloud computing. In this presentation, we will describe two projects that demonstrate this shift. MERRA Analytic Services (MERRA/AS) is an example of cloud-enabled CAaaS. MERRA/AS enables MapReduce analytics over MERRA reanalysis data collection by bringing together the high-performance computing, scalable data management, and a domain-specific climate data services API. NASA's High-Performance Science Cloud (HPSC) is an example of the type of compute-storage fabric required to support CAaaS. The HPSC comprises a high speed Infinib and network, high performance file systems and object storage, and a virtual system environments specific for data intensive, science applications. These technologies are providing a new tier in the data and analytic services stack that helps connect earthbound, enterprise-level data and computational resources to new customers and new mobility-driven applications and modes of work. In our experience, CAaaS lowers the barriers and risk to organizational change, fosters innovation and experimentation, and provides the agility required to meet our customers' increasing and changing needs

big data analysis↗