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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 145 records · Page 8

Using machine learning and artificial intelligence to improve model-data integrated earth system model predictions of water and carbon cycle extremes

The research proposed here focuses on improving the predictive power of the land component of earth system models (ESMs) using (1) model-data fusion enabled by machine learning (ML) and artificial intelligence (AI), (2) predictive modeling through the combination of ML, AI, and big-data (comprising both model output and observations), and (3) insight of ESM structure and process mechanisms gleaned from complex data using ML and AI.

54 ENVIRONMENTAL SCIENCES↗

Linking Asthma Exacerbation and Air Pollution Data: A Step Toward Public Health and Environmental Data Integration

Studies have shown that reducing exposure to triggers such as air pollutants can reduce symptoms and the need for medication in asthma patients. However, systems that track asthma are generally not integrated with those that track environmental hazards related to asthma. Tlvs lack of integration hinders public health awareness and responsiveness to these environmental triggers. The current study is a collaboration between health and environmental professionals to utilize NASA-derived environmental data to develop a decision support system (DSS) for asthma prediction, surveillance, and intervention. The investigators link asthma morbidity data from the University of Mississippi Medical Center (UMMC) and Mississippi Department of Health (MDH) with air quality data from the Mississippi Department of Environmental Quality (MDEQ) and remote sensing data from NASA. Daily ambient environmental hazard data for PM2.5 and ozone are obtained from the MDEQ air quality monitoring locations and are combined with remotely sensed data from NASA to develop a state-wide spatial and time series profile of environmental air quality. These data are then used to study the correlation of these measures of air quality variation with the asthma exacerbation incidence throughout the state over time. The goal is to utilize these readily available measures to allow real-time risk assessment for asthma exacerbations. GeoMedStat, a DSS previously developed for biosurveillance, will integrate these measures to monitor, analyze and report the real-time risk assessment for asthma exacerbation throughout the state.

Faruque, Fazlay↗

GeneLab: Current and Future Omics Data Integration Between Space Biology and HRP

For the past five years, the Biological and Physical Sciences Division has pioneered Open Science in Space Biology by funding the NASA GeneLab project. Along with the Ames Life Sciences Data Archive, GeneLab has quickly become the world leader in archiving and scientifically curating spaceflight and spaceflight relevant multi-omics data. Specifically, the GeneLab Data System has become a full enterprise solution providing advanced mining capabilities, several application programming interfaces for data federation and machine learning approaches, and delivering to the world an analytical and visualization platform which has enabled collaboration within the scientific community. Over the past three years, large meta-analysis and modeling studies have been published by the GeneLab Analysis Working Groups (AWGs), which are comprised of ~200 volunteer scientists. One natural extension of GeneLab data reuse has recently turned towards linking animal data with human data, which is the next necessary step to further validate animal models for inferring biological risks to humans conducting LEO, lunar or Martian missions. As such, data from the Human Research Program are an essential component of GeneLab and ALSDA. At the moment, simulated space radiation experiments conducted at Brookhaven National Laboratory make the most of HRP GeneLab data, and the scientific community has been eager to also link their animal spaceflight results to actual Astronaut data and human analog data. We will discuss further the current status of knowledge and future approaches to accelerate our basics understanding of the impact of space stressors on humans using latest omics technology.

omics↗

Design specification for a general purpose Data Integration and Display System (DIDS)

The capability for any program written in FORTRAN or XSYMBOL to display its output is provided. Displays are presented on the Biomed Console CRT, the COMPLOT X-Y plotter or both. The display of data stored on magnetic tape is accomplished without the necessity of coding a program. The keyboard on the Biomed Console or the teletype was designed to be the user's interface with DIDS to call displays stored on magnetic tape.

Source record↗

High-frequency Data Integration for Landscape Model Calibration of Carbon Fluxes Across Diverse Tidal Marshes

Terrestrial Aquatic Interfaces (TAIs), and tidal wetlands in particular, store large amounts of carbon yet are not well represented in Earth System Models (ESMs). Predictions of carbon cycling and greenhouse gas (GHG) emissions in tidal wetlands are highly uncertain. Eddy covariance (EC) towers provide ecosystem-scale GHG flux data at a temporal resolution (every 30min) that is helpful for parameterizing and improving mechanistic realism in ESMs. We propose to use a network of eddy covariance towers and standardized ancillary data streams, along with mesocosm experiments and statistical analyses, across diverse tidal wetlands of North America to develop and improve biogeochemical modeling at the TAI. Our overarching objective is to improve understanding and process-based modeling of gross primary productivity (GPP) and CH4 emission responses, both non-linear and asynchronous, to stressors including plant inundation, disturbance, salinity and nitrogen loading.

54 ENVIRONMENTAL SCIENCES↗

The Monarch Initiative in 2019: an integrative data and analytic platform connecting phenotypes to genotypes across species

In biology and biomedicine, relating phenotypic outcomes with genetic variation and environmental factors remains a challenge: patient phenotypes may not match known diseases, candidate variants may be in genes that haven’t been characterized, research organisms may not recapitulate human or veterinary diseases, environmental factors affecting disease outcomes are unknown or undocumented, and many resources must be queried to find potentially significant phenotypic associations. The Monarch Initiative (https://monarchinitiative.org) integrates information on genes, variants, genotypes, phenotypes and diseases in a variety of species, and allows powerful ontology-based search. We develop many widely adopted ontologies that together enable sophisticated computational analysis, mechanistic discovery and diagnostics of Mendelian diseases. Our algorithms and tools are widely used to identify animal models of human disease through phenotypic similarity, for differential diagnostics and to facilitate translational research. Launched in 2015, Monarch has grown with regards to data (new organisms, more sources, better modeling); new API and standards; ontologies (new Mondo unified disease ontology, improvements to ontologies such as HPO and uPheno); user interface (a redesigned website); and community development. Monarch data, algorithms and tools are being used and extended by resources such as GA4GH and NCATS Translator, among others, to aid mechanistic discovery and diagnostics.

59 BASIC BIOLOGICAL SCIENCES↗

Integrated Data Modeling and Simulation on the Joint Polar Satellite System Program

The Joint Polar Satellite System is a modern, large-scale, complex, multi-mission aerospace program, and presents a variety of design, testing and operational challenges due to: (1) System Scope: multi-mission coordination, role, responsibility and accountability challenges stemming from porous/ill-defined system and organizational boundaries (including foreign policy interactions) (2) Degree of Concurrency: design, implementation, integration, verification and operation occurring simultaneously, at multiple scales in the system hierarchy (3) Multi-Decadal Lifecycle: technical obsolesce, reliability and sustainment concerns, including those related to organizational and industrial base. Additionally, these systems tend to become embedded in the broader societal infrastructure, resulting in new system stakeholders with perhaps different preferences (4) Barriers to Effective Communications: process and cultural issues that emerge due to geographic dispersion and as one spans boundaries including gov./contractor, NASA/Other USG, and international relationships.

Roberts, Christopher J.↗

Bayesian tomography and integrated data analysis in fusion diagnostics

In this article, a Bayesian tomography method using non-stationary Gaussian process for a prior has been introduced. The Bayesian formalism allows quantities which bear uncertainty to be expressed in the probabilistic form so that the uncertainty of a final solution can be fully resolved from the confidence interval of a posterior probability. Moreover, a consistency check of that solution can be performed by checking whether the misfits between predicted and measured data are reasonably within an assumed data error. In particular, the accuracy of reconstructions is significantly improved by using the non-stationary Gaussian process that can adapt to the varying smoothness of emission distribution. The implementation of this method to a soft X-ray diagnostics on HL-2A has been used to explore relevant physics in equilibrium and MHD instability modes. This project is carried out within a large size inference framework, aiming at an integrated analysis of heterogeneous diagnostics.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Development of an integrated data base for land use and water quality planning

To help understand the role played by different land resources in water quality management a computer based data system was created. The Land Resource Information System (LRIS) allows data to be readily retrieved or statistically analyzed for a variety of purposes. It is specifically formatted to perform coordination of water quality data with logy, etc. New understanding of the region gained through the use of LRIS has gone well beyond the initial purpose of assessing water quality conditions. The land use and natural features information has provided a well defined starting point for a systematic evaluation of proposed land uses, transportation, housing, and other public investments. It has laid the foundation for a comprehensive and integrated approach to many different planning and investment programs presently underway.

Adams, J.↗

Summary of Thermodynamic Data Integration (M4SF-23LL010301052)

This progress report (Level 4 Milestone Number M4SF-23LL010301052) summarizes research conducted at Lawrence Livermore National Laboratory (LLNL) within the Argillite Activity Number M4SF-23LL010301052. SUPCRTNE is being developed as the primary engine for thermodynamic database development in support of geologic disposal of high-level nuclear waste. As used here, “SUPCRT” refers to both a computer program and its supporting database. Additional letters or numbers refer to specific variants (SUPCRT92, Johnson et al., 1992; SUPCRTBL, Zimmer et al., 2016; and SUPCRTNE). A SUPCRT database contains the data required to calculate the thermodynamic properties of solid, gas, and aqueous species over a wide range of temperature and pressure. Normally SUPCRT is used to create a higher-level data base that directly supports modeling and simulation codes such as EQ3/6, GWB, PHREEQC, and PFLOTRAN.

58 GEOSCIENCES↗

Ocean of Data: Integrating First-Principles Calculations and CALPHAD Modeling with Machine Learning

Thermodynamics is a science concerning the state of a system, whether it is stable, metastable or unstable, when interacting with the surroundings. Computational thermodynamics enables quantitative calculations of thermodynamic properties as a function of both external conditions and internal configurations, in terms of first and second derivatives of energy with respect to either potentials or molar quantities. Thermodynamic modeling based on the CALPHAD method enables the thermodynamics beyond stable states and is the foundation of Materials Genome and materials design. In last several decades, first-principles calculations based on density functional theory have provided invaluable thermochemical data to improve the robustness of CALPHAD modeling. Today with ever increasing computing power and large amount of data repositories online, it calls for a new paradigm for CALPHAD modeling approach incorporating machine learning to create a sustainable ecosystem for the ocean of data and for emergent behaviors.

Chemistry↗

Million-scale data integrated deep neural network for phonon properties of heuslers spanning the periodic table

Existing machine learning potentials for predicting phonon properties of crystals are typically limited on a material-to-material basis, primarily due to the exponential scaling of model complexity with the number of atomic species. We address this bottleneck with the developed Elemental Spatial Density Neural Network Force Field, namely Elemental-SDNNFF. The effectiveness and precision of our Elemental-SDNNFF approach are demonstrated on 11,866 full, half, and quaternary Heusler structures spanning 55 elements in the periodic table by prediction of complete phonon properties. Self-improvement schemes including active learning and data augmentation techniques provide an abundant 9.4 million atomic data for training. Deep insight into predicted ultralow lattice thermal conductivity (<1 Wm –1 K –1 ) of 774 Heusler structures is gained by p–d orbital hybridization analysis. Additionally, a class of two-band charge-2 Weyl points, referred to as “double Weyl points”, are found in 68% and 87% of 1662 half and 1550 quaternary Heuslers, respectively.

36 MATERIALS SCIENCE↗

Stability of Transactive Energy Market-Based Power Distribution System Under Data Integrity Attack

Future smart power distribution system with multiple active consumers and aggregators exchanging real-time electricity pricing and electricity consumption information over a communication network is prone to cyberattack. The goal of this paper is to understand the impact of attacks on pricing/load signals on the physical grid within a transactive energy market framework. First, this paper models the interaction between real-time electricity price and total energy demand in the form of a discrete time nonlinear autonomous dynamical system. Second, equilibrium electricity price and energy demand associated with this coupled dynamical system is derived and conditions for bounded input bounded output (BIBO) stability are identified. Third, a BIBO stable algorithm to design real-time electricity pricing scheme from a techno-economic perspective is developed. Finally, the impact of various levels of false data injection (FDI) attack on price of electricity, demand, and distribution system voltage is investigated. The proposed model is analyzed using simulations on the IEEE 69-bus test system and the impact of FDI attack on both electricity price/demand and distribution grid voltage is quantified. In conclusion, this paper shows that impact of FDI attack on electricity prices is more severe than an attack on electricity demand.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NRIC Asset Suite Engineering and Operations Data Integration Plan

The National Reactor Innovation Center (NRIC), established by the U.S. Department of Energy (DOE) in August 2019, accelerates the demonstration and deployment of advanced nuclear energy through its mission to inspire stakeholders and the public, empower innovators, and deliver successful outcomes through efficient coordination of partners and resources. NRIC is a national program led by Idaho National Laboratory (INL), enabling collaborators to harness the world-class capabilities of the U.S. National Laboratory System. Committed to demonstrating advanced reactors by the end of 2025, NRIC is designed to bridge the gap between research, development, and the marketplace to help convert some of the Nation’s most promising advanced nuclear reactors into commercial applications by 2030. To meet these needs, NRIC is developing two reactor demonstration test beds at Idaho National Laboratory (INL), the Laboratory for Operation and Testing in the United States (LOTUS) and the Demonstration and Operation of Microreactor Experiments (DOME) test bed. Each test bed involves the modification of existing facilities at INL’s Materials and Fuels Complex (MFC). Retrofitting these facilities to accommodate novel reactors, as well as subsequent but similar NRIC projects, is a non-trivial engineering task and is expected to generate a significant amount of new and revised documentation. Leveraging digital engineering practices, this documentation will be managed in a purpose-built data management tool to facilitate origination, review, and approval while coordinating with the design contractor. The subsequent upload and review of documentation to INL’s existing document control system comprises a long and unnecessarily manual task. An opportunity exists to automate this upload process and save job-hours while continuing to adhere to INL/MFC document management procedures.

99 GENERAL AND MISCELLANEOUS↗

New Views of the Moon: Improved Understanding Through Data Integration

Understanding the Moon is crucial to future exploration of the solar system.The Moon preserves a record of the first billion years of the Earth-Moon system's history, including evidence of the Moon's origin as accumulated debris from a giant impact into early Earth. Lunar rocks provide evidence of early differentiation and extraction of a crust. Lacking an atmospheric shield, the Moon's regolith retains a record of the activity of solar wind over the past 4 billion years. It also holds a complete record of impact cratering, and analysis of samples has allowed calibration of ages, and thus dating of other planetary surfaces. And because of its proximity to Earth, it's low gravity well, and stable surface, the Moon's resources will be useful both in establishing lunar habitations and as fuel for exploration beyond the Moon. Lunar science has advanced tremendously in the 30 years since the Apollo and Luna missions. We know that the Moon is strongly differentiated, and recent tungsten isotope studies indicate that this differentiation occurred soon after solar system formation. The Moon probably accreted rapidly from debris that formed as a large planetesimal struck the early Earth. Ancient highland rocks provide evidence of early lunar differentiation, and basalts formed by later melting within the mantle reveal it cumulus nature. However, the timing, extent, and depth of differentiation, variations within the mantle, and lateral and vertical variations within the crust can only be surmised from the limited sample suites,gravity studies,and surface geophysics of the Apollo era. Data from the recent Lunar Prospector and Clementine missions permit reassessment of the global characteristics of the Moon and a reexamination of the distribution of elemental components, rock and soil types, and resources, as well as remanent magnetism, gravity field, and global topography New research provides some answers, but also leads to new questions.

Jolliff, B. L.↗