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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 1,315 records · Page 73
All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

Applied Meteorology Unit (AMU) Quarterly Report Third Quarter FY · 13

The AMU team worked on seven tasks for their customers: (1) Ms. Crawford completed the objective lightning forecast tool for east -central Florida airports and delivered the tool and the final report to the customers. (2) Ms. Shafer continued work for Vandenberg Air Force Base on an automated tool to relate pressure gradients to peak winds. (3) Dr. Huddleston updated and delivered the tool that shows statistics on the timing of the first lightning strike of the day in the Kennedy Space Center (KSC)/Cape Canaveral Air Force Station (CCAFS) area. (4) Dr. Bauman continued work on a severe weather forecast tool focused on the Eastern Range (ER). (5) Ms. Crawford acquired the software and radar data needed to create a dual-Doppler analysis over the east-central Florida and KSC/CCAFS areas. (6) Mr. Decker continued developing a wind pairs database for the Launch Services Program to use when evaluating upper-level winds for launch vehicles. (7) Dr. Watson continued work to assimilate observational data into the high-resolution model configurations she created for Wallops Flight Facility and the ER.

Bauman, William↗
NASA NTRS2013

IT Security Support for Spaceport Command and Control System

During the fall 2013 semester, I worked at the Kennedy Space Center as an IT Security Intern in support of the Spaceport Command and Control System under the guidance of the IT Security Lead Engineer. Some of my responsibilities included assisting with security plan documentation collection, system hardware and software inventory, and malicious code and malware scanning. Throughout the semester, I had the opportunity to work on a wide range of security related projects. However, there are three projects in particular that stand out. The first project I completed was updating a large interactive spreadsheet that details the SANS Institutes Top 20 Critical Security Controls. My task was to add in all of the new commercial of the shelf (COTS) software listed on the SANS website that can be used to meet their Top 20 controls. In total, there are 153 unique security tools listed by SANS that meet one or more of their 20 controls. My second project was the creation of a database that will allow my mentor to keep track of the work done by the contractors that report to him in a more efficient manner by recording events as they occur throughout the quarter. Lastly, I expanded upon a security assessment of the Linux machines being used on center that I began last semester. To do this, I used a vulnerability and configuration tool that scans hosts remotely through the network and presents the user with an abundance of information detailing each machines configuration. The experience I gained from working on each of these projects has been invaluable, and I look forward to returning in the spring semester to continue working with the IT Security team.

computer security↗
NASA NTRS2018

Biocene 2018 - Welcome to the Period of New Life

Biocene is the period of new life. When our descendants look back at this period in time, they will see evidence, in the geologic and electronic record, of anthropic climate change, growing population, and scarcity of resources. But they will also see the rebirth of human ingenuity as we overcame the challenges that faced us through nature-inspired exploration. The Periodic Table of Life (PeTaL) is a proposed tool and open source framework that uses artificial intelligence to aid in the systematic inquiry of biology for its application to human systems. This presentation defines the PeTaL concept and workflow. Biomimicry, biophysics, biomimetics, bionics and numerous other terms refer to the use of biology and biological principles to inform practices in other disciplines. For the most part, the domain of inquiry in these fields have been confined to extant biological models with the proponents of biomimicry often citing the evolutionary success of extant organisms relative to extinct ones. The primary objective of this paper is to expand the domain of inquiry for human processes that seek to model those that are, were or could be found in nature with examples that relate to the field of aerospace and to spur development of tools that can work together to accelerate the use of artificial intelligence in problem solving. Specifically specialized fields such as paleomimesis, anthropomimesis and physioteleology are proposed in conjunction with artificial evolution. Blockchain technology may be vital in allowing open source design tools such as PeTaL to democratize design and yet protect intellectual property. The overarching philosophy outlined here can be thought of as physiomimetics, a holistic and systematic way of learning from natural history. The backbone of PeTaL integrates an unstructured database with an ontological model consisting of function, morphology, environment, state of matter and ecosystem. Tools include text classification, thesaurus, data visualization, and analysis. Applications of PeTaL include guiding human space exploration, understanding human and geological history, and discovering new or extinct life.

Biocene↗
DOE OSTI2021

Ultra-compact system for characterization of physical, chemical and ignition properties of fuels

The present disclosure relates to a miniaturized fuel laboratory system that makes use of a housing, a processor housed within the housing, and a fuel inlet port supported from the housing for receiving a quantity of fuel to be used as a fuel test sample. The system may also have at least one fuel sensor housed in the housing in communication with the fuel inlet port for receiving the fuel test sample and carrying out combustion thereof. An electronic component may be housed in the housing, which enables communication with an external remote subsystem. A database may be incorporated which contains at least one of stored fuel characteristics or stored fuel analysis models, accessible by the processor. The processor may use fuel oxidation information generated by the fuel sensor, and at least one of the stored fuel characteristics or stored combustion models, to determine at least one fuel characteristic of the fuel test sample.

McNenly, Matthew J.↗
DOE OSTI2024

Ab initio property predictions of quinary solid solutions using small binary cells

The Set of Small Ordered Structures (SSOS) approach is an ab initio technique for modelling random solid solutions in which many small structures are averaged so that their correlation functions match those of a desired composition. SSOS has been shown to be effective in reducing the cost of density functional theory calculations relative to other well-known techniques such as cluster expansions and special quasirandom structures for modelling solid solutions. Here in this work, we demonstrate that SSOS’s can be constructed using cells with only a subset of elements while still accurately modelling multi-component systems. Specifically, we show that small binary cells can effectively model two quinary high entropy alloys – NbTaTiHfZr and MoNbTaVW – accurately capturing properties such as formation energy, lattice parameters, elastic constants, and root-mean-square atomic displacements. Overall, this insight is useful for those looking to construct databases of such small structures for predicting the properties of multi-component solid solutions, as it greatly decreases the number of structures that needs to be considered.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Structured information extraction from scientific text with large language models

Extracting structured knowledge from scientific text remains a challenging task for machine learning models. Here, we present a simple approach to joint named entity recognition and relation extraction and demonstrate how pretrained large language models (GPT-3, Llama-2) can be fine-tuned to extract useful records of complex scientific knowledge. We test three representative tasks in materials chemistry: linking dopants and host materials, cataloging metal-organic frameworks, and general composition/phase/morphology/application information extraction. Records are extracted from single sentences or entire paragraphs, and the output can be returned as simple English sentences or a more structured format such as a list of JSON objects. This approach represents a simple, accessible, and highly flexible route to obtaining large databases of structured specialized scientific knowledge extracted from research papers.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2024

Isotope effects and Alfvén eigenmode stability in JET H, D, T, DT, and He plasmas

While much about Alfvén eigenmode (AE) stability has been explored in previous and current tokamaks, open questions remain for future burning plasma experiments, especially regarding exact stability threshold conditions and related isotope effects; the latter, of course, requiring good knowledge of the plasma ion composition. In the JET tokamak, eight in-vessel antennas actively excite stable AEs, from which their frequencies, toroidal mode numbers, and net damping rates are assessed. The effective ion mass can also be inferred using measurements of the plasma density and magnetic geometry. Thousands of AE stability measurements have been collected by the Alfvén Eigenmode Active Diagnostic in hundreds of JET plasmas during the recent Hydrogen, Deuterium, Tritium, DT, and Helium-4 campaigns. In this novel AE stability database, spanning all four main ion species, damping is observed to decrease with increasing Hydrogenic mass, but increase for Helium, a trend consistent with radiative damping as the dominant damping mechanism. These data are important for confident predictions of AE stability in both non-nuclear (H/He) and nuclear (D/T) operations in future devices. In particular, if radiative damping plays a significant role in overall stability, some AEs could be more easily destabilized in D/T plasmas than their H/He reference pulses, even before considering fast ion and alpha particle drive. Active MHD spectroscopy is also employed on select HD, HT, and DT plasmas to infer the effective ion mass, thereby closing the loop on isotope analysis and demonstrating a complementary method to typical diagnosis of the isotope ratio.

Alfvén eigenmodes↗
DOE OSTI2026

Optical Vibrational Spectroscopic Investigation of Natural and Synthetic Analogs of Uranyl Oxyhydroxyhydrate Minerals

Uranyl oxy-hydroxy-hydrate minerals are common alteration products of uraninite (UO2+x) which is chemically and structurally analogous to uranium dioxide nuclear fuel. Therefore, structural and spectroscopic investigations of these alteration minerals and their analogous anthropogenic counterparts can provide insight into the environmental behavior of nuclear fuel cycle materials. Previously, we compiled available vibrational spectroscopic data for uranyl minerals in the Compendium of Uranium Raman and Infrared Experimental Spectra (CURIES) and found that only 37% of known uranyl oxy-hydroxy-hydrate minerals had spectra readily available in the literature and existing databases for inclusion therein. Furthermore, no available infrared spectra for this mineral group were included in CURIES. To expand our understanding of the spectroscopic features of uranyl oxy-hydroxy-hydrates and the structural origins thereof, we collected, and now include in CURIES, Raman and infrared spectra for an additional 12 uranyl hydroxide phases. To better understand the impact of structural and compositional variations of these phases on their spectroscopic features, we compare Raman spectra of different anion sheet topological groups and of analogous phases hosting different counter cations. We identify spectroscopic variations related to differences in equatorial bonding and structural changes as a result of cation substitution. We also prepare a uranyl hydroxide phase via hydrolysis of uranyl fluoride (UO2F2) as an analog of hydrolysis reactions that occur in nuclear fuel cycle materials; and we find that the alteration product of UO2F2, despite chemical and structural similarities to uranyl oxy-hydroxy-hydrate minerals, is readily distinguishable from related mineral phases using Raman spectroscopy. In this work, we provide new insights into the structural origins of spectroscopic features in uranyl oxy-hydroxy-hydrate minerals, improve the average Raman spectrum for this group of minerals, and thereby improve capabilities for identifying these mineral species and related anthropogenic phases using Raman spectroscopy.

Barth, Brodie [ORNL] (ORCID:0000000256142601)↗
NASA NTRS2003

Measurement of Charged Particle Interactions in Spacecraft and Planetary Habitat Shielding Materials

Accurate models of health risks to astronauts on long-duration missions outside the geomagnetosphere will require a full understanding of the radiation environment inside a spacecraft or planetary habitat. This in turn requires detailed knowledge of the flux of incident particles and their propagation through matter, including the nuclear interactions of heavy ions that are a part of the Galactic Cosmic Radiation (GCR). The most important ions are likely to be iron, silicon, oxygen, and carbon. Transport of heavy ions through complex shielding materials including self-shielding of tissue modifies the radiation field at points of interest (e.g., at the blood-forming organs). The incident flux is changed by two types of interactions: (1) ionization energy loss, which results in reduced particle velocity and higher LET (Linear Energy Transfer); and (2) nuclear interactions that fragment the incident nuclei into less massive ions. Ionization energy loss is well understood, nuclear interactions less so. Thus studies of nuclear fragmentation at GCR-like energies are needed to fill the large gaps that currently exist in the database. These can be done at only a few accelerator facilities where appropriate beams are available. Here we report results from experiments performed at the Brookhaven National Laboratory s Alternating Gradient Synchrotron (AGS) and the Heavy Ion Medical Accelerator in Chiba, Japan (HIMAC). Recent efforts have focused on extracting charge-changing and fragment production cross sections from silicon beams at 400, 600, and 1200 MeV/nucleon. Some energy dependence is observed in the fragment production cross sections, and as in other data sets the production of fragments with even charge numbers is enhanced relative to those with odd charge numbers. These data are compared to the NASA-LaRC model NUCFRG2. The charge-changing cross section data are compared to recent calculations using an improved model due to Tripathi, which accurately predicts the observed (slight) energy dependence. An additional set of data will be presented from an analysis of shielding material performance in the 1 GeV/nucleon iron beam at the AGS. A wide variety of candidate materials for spacecraft construction, as well as elemental targets, have been placed in this beam and their effects on transmitted dose and dose equivalent measured. The results support a prediction by J. Wilson et al. that hydrogen-loaded materials give the greatest dose reduction per unit mass.

Zeitlin, Cary J.↗
NASA NTRS2020

A Flexible Parameterization for Shortwave and Longwave Optical Properties of Ice Crystals and Derived Bulk Optical Properties for Climate Models

We provide a parameterization of the extinction efficiency, single scattering albedo and asymmetry parameter of single ice crystals with any combination of particle volume, projected area, component aspect ratio and crystal distortion at any wavelength between 0.2 and 100 mm. The paramerization is an extension of the one previously published by van Diedenhoven et al. (2014, https://doi.org/10.1175/JAS-D-13-0205.1). In addition, the parameterized optical properties are integrated over size distributions yielding bulk extinction efficiencies, single scattering albedos and asymmetry parameters for large ranges of effective radii, particle component aspect ratios and crystal distortion values. The parameterization of single particle optical properties is evaluated with a reference database. The bulk optical properties are evaluated against the ice model selected for the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6 products, for which accurate optical properties are available. Mean absolute errors in parameterized extinction efficiency, asymmetry parameter and single scattering albedo are shown to be 0.0272, 0.00890 and 0.00468, respectively for shortwave wavelengths, while they are 0.0641, 0.0368 and 0.0200 in the longwave. Shortwave and longwave asymmetry parameter and single scattering albedos are shown to vary strongly with particle component aspect ratio and distortion, resulting in substantial variation in shortwave fluxes, but relatively small variations in longwave cloud emissivity. The parameterization and bulk optical properties are made publicly available.

Bastiaan Van Diedenhoven↗
DOE OSTI2020

How Wrong Can the Operational AEP Uncertainty Estimate Be When We Ignore the Correlations Between the Uncertainty Components?

Calculations of wind farm annual energy production (AEP) on operational data are essential for a variety of financial transactions during the life of wind plants. The AEP estimate is associated with an uncertainty value, which is calculated by combining contributions connected to on-site measurements, long-term reference measurements, losses, regression, windiness adjustment, and wind resource interannual variability. Although very limited documentation on the topic exists, the conventional approach currently used by the wind energy community to assess the uncertainty connected to the operational AEP estimate assume that the different uncertainty components are uncorrelated and therefore calculates the overall uncertainty with a sum of squares approach. In this analysis, we contrast the traditional technique to estimate the overall AEP uncertainty by ignoring the correlation between its different components with a novel Monte Carlo based approach, which can instead take into account the correlation between different uncertainty categories. We consider monthly operational data from 472 wind farms from the Energy Information Administration (EIA) 923 database to assess the difference between the two approaches. Long-term wind speed data needed for the AEP assessment are taken from three reanalysis products: the Modern-Era Retrospective analysis for Research and Applications v2 (MERRA-2), the European Reanalysis Interim (ERA-interim), and the National Centers for Environmental Prediction v2 (NCEP-2). The results of the Monte Carlo approach show that three pairs of AEP uncertainty components do show a statistically significant correlation: the uncertainty connected with wind resource inter-annual variability is positively correlated with the one related to the windiness correction and negatively correlated with the one due to the regression, and the wind measurement uncertainty is positively correlated with the regression uncertainty. All these correlations, which are found between uncertainty components which are not only part of an operational analysis, but also of a wind resource assessment, are currently ignored in the conventional techniques used as industry standard. We further investigate the causes of these correlations, in terms of common dependencies of different uncertainty components on wind resource variability, number of data points, and quality of the regression between wind speed and energy production data. Next, we quantify the error in the current industry standard technique, in terms of the percentage difference in total uncertainty calculated with the two considered approaches, for all the analyzed wind farms. We find a mean absolute percentage difference of about 6%, with the largest differences being greater than 20%. The data clearly confirm that ignoring the actual correlation between the uncertainty components can lead to large errors in the assessment of the operational AEP uncertainty, and the proposed Monte Carlo approach should be preferred.

Monte Carlo↗
DOE OSTI2023

Group additivity values for entropy and heat capacities of C 2 –C 8 alkanes, alkyl hydroperoxides, and their radicals

Group additivity values for the thermodynamic properties of oxygenated radicals are poorly determined due to the absence of high quality reference data. Here, a set of 58 group additive values (GAV) for the standard entropy and heat capacity of relevance to alkane oxidation is derived from fits to an extensive and accurate database of standard entropies (298.15 K) and heat capacities (300–3000 K) recently calculated with the “STAR-1D” formalism. The 192 species in this database represent the alkanes (RH), alkyl radicals ($\dot{R}$), alkyl hydroperoxides (RO 2 H), alkyl-peroxy (R$\dot{O}$ 2 ) and hydroperoxy-alkyl ($\dot{Q}$OOH) radicals for all of the isomers of C 2 –C 5 alkane fuels and a select number of isomers of C 6 –C 9 species. The STAR-1D thermochemical data for this set of species was previously obtained from a coupling of scaled B2PLYPD3/cc-pVTZ vibrational analyses with scaled ωB97X-D/cc-pVTZ one-dimensional hindered rotor corrections. The 2σ uncertainties in the GAV results relative to the STAR-1D data set are 2.4 cal K –1 mol –1 for the entropies and at most 2.0 cal K –1 mol –1 for the heat capacities in the temperature range 500–800 K. The 2σ fitting uncertainties in the heat capacity gradually reduce at higher temperatures reaching a value of 0.8 cal K –1 mol –1 at 2000 K decreasing to only 0.5 cal K –1 mol –1 at 3000 K. The high degree of accuracy for the GAV representations is obtained through the introduction of various new group terms, together with the re-optimization of existing group terms. Among the full set of 58 GAV terms, 25 include non-next-nearest neighbor interactions (NNI) and β-corrections. The updated GAVs can be applied in the prediction of entropies and heat capacities for a wide range of hydrocarbons and hydroperoxide species and their radicals, which is important to the accurate prediction of fuel reactivity at low-temperatures in the range 600–1000 K.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Wildfire‐induced increases in photosynthesis in boreal forest ecosystems of North America

Abstract Observations of the annual cycle of atmospheric CO 2 in high northern latitudes provide evidence for an increase in terrestrial metabolism in Arctic tundra and boreal forest ecosystems. However, the mechanisms driving these changes are not yet fully understood. One proposed hypothesis is that ecological change from disturbance, such as wildfire, could increase the magnitude and change the phase of net ecosystem exchange through shifts in plant community composition. Yet, little quantitative work has evaluated this potential mechanism at a regional scale. Here we investigate how fire disturbance influences landscape‐level patterns of photosynthesis across western boreal North America. We use Alaska and Canadian large fire databases to identify the perimeters of wildfires, a Landsat‐derived land cover time series to characterize plant functional types (PFTs), and solar‐induced fluorescence (SIF) from the Orbiting Carbon Observatory‐2 (OCO‐2) as a proxy for photosynthesis. We analyze these datasets to characterize post‐fire changes in plant succession and photosynthetic activity using a space‐for‐time approach. We find that increases in herbaceous and sparse vegetation, shrub, and deciduous broadleaf forest PFTs during mid‐succession yield enhancements in SIF by 8–40% during June and July for 2‐ to 59‐year stands relative to pre‐fire controls. From the analysis of post‐fire land cover changes within individual ecoregions and modeling, we identify two mechanisms by which fires contribute to long‐term trends in SIF. First, increases in annual burning are shifting the stand age distribution, leading to increases in the abundance of shrubs and deciduous broadleaf forests that have considerably higher SIF during early‐ and mid‐summer. Second, fire appears to facilitate a long‐term shift from evergreen conifer to broadleaf deciduous forest in the Boreal Plain ecoregion. These findings suggest that increasing fire can contribute substantially to positive trends in seasonal CO 2 exchange without a close coupling to long‐term increases in carbon storage.

Biodiversity & Conservation↗
NASA NTRS1995

Trainable Cataloging for Digital Image Libraries with Applications to Volcano Detection

Users of digital image libraries are often not interested in image data per se but in derived products such as catalogs of objects of interest. Converting an image database into a usable catalog is typically carried out manually at present. For many larger image databases the purely manual approach is completely impractical. In this paper we describe the development of a trainable cataloging system: the user indicates the location of the objects of interest for a number of training images and the system learns to detect and catalog these objects in the rest of the database. In particular we describe the application of this system to the cataloging of small volcanoes in radar images of Venus. The volcano problem is of interest because of the scale (30,000 images, order of 1 million detectable volcanoes), technical difficulty (the variability of the volcanoes in appearance) and the scientific importance of the problem. The problem of uncertain or subjective ground truth is of fundamental importance in cataloging problems of this nature and is discussed in some detail. Experimental results are presented which quantify and compare the detection performance of the system relative to human detection performance. The paper concludes by discussing the limitations of the proposed system and the lessons learned of general relevance to the development of digital image libraries.

digital image libraries, trainable cataloging↗
NASA NTRS2019

Extreme-Temperature Carbon- and Ceramic-Matrix Composite Nozzle Extensions for Liquid Rocket Engines

The United States (US) National Aeronautics and Space Administration (NASA) and its US industry partners are developing extreme-temperature composite nozzle extensions for a variety of cryogenic liquid rocket engine propulsion systems. Applications under consideration at the NASA Marshall Space Flight Center (MSFC) include launch vehicle (upper stage), in-space, and lunar lander descent/ascent propulsion systems. Composite material systems of interest include carbon-carbon (C-C) and carbon/silicon-carbide (C-SiC) composites, as well as modified versions of such composites (coatings, mixed matrices, oxidation inhibitors, etc.). Missions addressed include access to low Earth orbit, the lunar surface, and more distant destinations. Cryogenic upper-stage and in-space liquid rocket engines are optimized for performance through the use of high area ratio nozzles to fully expand combustion gases to low exit pressures, increasing exhaust velocities. As a result of the large size of such nozzles, and the related engine performance requirements, composite nozzle extensions are being considered to reduce mass impacts. Currently, metallic and foreign composite nozzle extensions used on the Atlas V, Delta IV, Falcon 9, and Ariane 5 launch vehicles represent the state-of-the-art. Such extensions are limited to use at or slightly above 2000°F (1093°C). Materials under development by MSFC and its industry partners have the potential to operate at temperatures up to (or above) 4250°F (2343°C). Marshall Space Flight Center efforts are aimed at (a) further developing the technology and databases needed to enable the use of composite nozzle extensions on cryogenic liquid rocket engines, (b) developing and demonstrating low-cost capabilities for testing and qualifying such nozzle extensions, and (c) advancing the US domestic supply chain for nozzle extensions. Through the Small Business Innovation Research (SBIR) and Small Business Technology Transfer (STTR) Programs, low-level internal MSFC research projects, and teaming arrangements with domestic industry partners, composite material design, development, hot-fire test, and evaluation efforts are progressing. Hot- fire engine tests of subscale hardware have been conducted using oxygen/hydrogen (LOX/H2), oxygen/methane (LOX/CH4), and oxygen/kerosene (LOX/RP-1) propellants. These engine tests at MSFC have enabled the evaluation of both heritage and state-of-the-art material systems, demonstrating the initial capabilities of the extreme temperature materials and their fabrication methods. Recent, ongoing, and potential future work supporting cryogenic propulsion systems development will be presented. The composite nozzle extension technology and test capabilities being developed are intended to support both NASA and US Department of Defense requirements, as well as those of the broader Commercial Space industry.

Valentine, Peter G.↗
DOE OSTI2024

Update on Activities Related to the Library of Graphite Microstructures

This report provides an overview and update of the ongoing efforts to create a comprehensive library of microstructures for nuclear graphite and carbon-based materials under consideration for nuclear applications. The library includes data on microstructural characterization of unirradiated graphite materials, a guide to the techniques used to analyze graphite (which complements the ASME guidelines and ASTM standards), a summary of characterization data for neutron-irradiated or oxidized material, and a compendium of microstructural information for carbon-based materials. These efforts are being conducted at various length scales for the filler and binder phases in graphite to better understand graphite’s local structure and property relationships. This report is a follow-up to the previous milestone report titled Report on initial development of a database of nuclear graphite characteristics based on microstructural characterization, ORNL/TM/-2023/2992, published in July 2023.The effort to develop the library of microstructures supports the US Department of Energy Office of Advanced Reactor Technologies program objectives of aiding the material selection, licensing, management, and core assessments of a graphite core by documenting the unirradiated microstructure of relevant grades or characterizing the microstructure’s evolution under the reactor environment. Additionally, this project aims to provide (1) information and guidelines for the characterizing of graphite and (2) a protocol to assess a nuclear graphite grade.

36 MATERIALS SCIENCE↗
NASA NTRS1986

A database management capability for Ada

The data requirements of mission critical defense systems have been increasing dramatically. Command and control, intelligence, logistics, and even weapons systems are being required to integrate, process, and share ever increasing volumes of information. To meet this need, systems are now being specified that incorporate data base management subsystems for handling storage and retrieval of information. It is expected that a large number of the next generation of mission critical systems will contain embedded data base management systems. Since the use of Ada has been mandated for most of these systems, it is important to address the issues of providing data base management capabilities that can be closely coupled with Ada. A comprehensive distributed data base management project has been investigated. The key deliverables of this project are three closely related prototype systems implemented in Ada. These three systems are discussed.

Chan, Arvola↗
DOE OSTI2022

End-to-end optimization for battery materials and molecules by combining graph neural networks and reinforcement learning

The National Renewable Energy Laboratory (NREL), together with the Colorado School of Mines (CSM) and Colorado State University (CSU), has developed a machine learning-enhanced approach to design new battery materials. Currently, such materials are designed in part via numerous expensive high-fidelity computational simulations that predict the performance of a given composition. Even with computational screening tools, the vast landscape of possible molecular or crystal structures exceeds current and future computational capacity. Improving the efficiency by which new materials can be optimized will therefore disrupt the cost, risk, and time required to bring new energy solutions to the marketplace. Predicting the properties of an organic molecule or periodic crystalline material given its structure has grown increasingly common. These approaches leverage large-scale computational and experimental databases and ML approaches such as graph neural networks. The inverse design problem of finding a material that possesses desired properties is substantially more challenging, since enumerating all valid material structures is not feasible. In this project, we leveraged recent success in reinforcement learning to efficiently navigate this high-dimensional search space. Just as algorithms can find the optimal chess moves from nearly limitless options, we train an approach to evolve a simple starting structure into a complex structure that possess the desired properties. Our solution has been demonstrated by applying it to two related design application tasks for short- and long-term energy storage, respectively: (1) the design of solid-state ion conductors and (2) the design of organic redox-active materials. The project has resulted an open-source software library for material design, documented examples of applying the library to both organic and inorganic material optimization, and peer-reviewed publications detailing the data, computational models, and resulting candidate materials.

25 ENERGY STORAGE↗