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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 1,009 records · Page 56
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Examining Tropical Convection Features at Storm-Resolving Scales Over the Maritime Continent Region

Global Storm Resolving Models (GSRMs) provide a way to understand weather and climate events across scales for better-informed climate impacts. In this work, we apply the recently developed and validated CAM (Community Atmosphere Model)—MPAS (Model for Prediction Across Scales) modeling framework, based on the open-source Community Earth System Model (CESM2), to examine the tropical convection features at the storm resolving scale over the Maritime Continent region at 3 km horizontal spacing. We target two global numerical experiments during the winter season of 2018 for comparison with observation in the region. Here we focus on the investigation of the representations of the convective systems, precipitation statistics, and tropical cyclone behaviors. We found that regional-refined experiments show more accurate precipitation distributions, diurnal cycles, and better agreement with observations for tropical cyclone features in terms of intensity and strength statistics. We expect the exploration of this work will further advance the development and use of the storm-resolving model in precipitation predictions across scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

xCDAT: A Python Package for Simple and Robust Analysis of Climate Data

xCDAT (Xarray Climate Data Analysis Tools) is an open-source Python package that extends Xarray (Hoyer & Hamman, 2017) for climate data analysis on structured grids. xCDAT streamlines analysis of climate data by exposing common climate analysis operations through a set of straightforward APIs. Some of xCDAT’s key features include spatial averaging, temporal averaging, and regridding. These features are inspired by the Community Data Analysis Tools (CDAT) library (Dean N. Williams et al., 2009) (D. N. Williams, 2014) (Doutriaux et al., 2019) and leverage powerful packages in the Xarray ecosystem including xESMF (Zhuang et al., 2023), xgcm (Abernathey et al., 2022), and CF xarray (Cherian et al., 2023). To ensure general compatibility across various climate models, xCDAT operates on datasets that are compliant with the Climate and Forecast (CF) metadata conventions (Hassell et al., 2017).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Energy Modeling in Urban Districts: Forecast of Multi-Sector Energy Use and GHG Emissions

This document reports the findings of the energy use and greenhouse gases (GHG) emissions model loosely based on three districts in the San Francisco Bay Area, District A, District B, and District C. Modeling platforms exist for city energy benchmarking, inventorying, and GHG emissions forecasting and planning. However, the wide variety and features of today’s tools, their focus on a sub-set or snapshot data from various energy generation and consumption sectors, and the fact that many of them are not open data models, create sub-optimal environments for the energy analysis districts are seeking to conduct. Hence, we have developed a new software tool with customized data and dynamic visualization; DEPICT (Decision-support and Emissions Prediction Interactive Cities Tool) to obtain energy and emissions forecasts at different stages of the districts’ build-out by varying selected design parameters. This report presents the methodology and framework we have developed to estimate whole district emissions and details the results by district, with the objective of finding insights into the main sources of emissions, and the available levers to reduce them efficiently. This document details the impact of each emissions mitigation measure investigated, along with the assumption and models that were used to reach these values

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Sub-millimeter resolution SiPM-based neutron anger camera

Thermal and cold neutron beamlines require detector systems that have a high neutron efficiency, large active area, and good spatial resolution. One type of detector that has been implemented at beamlines at the Spallation Neutron Source (SNS) is a scintillator-based Anger camera that utilizes photomultiplier tubes (PMTs) as photodetectors. In this work, we present a new Anger camera design that replaces PMTs with silicon photomultipliers (SiPMs). This new design offers better resolution, less distortion, and more compactness than the previous cameras. A camera with active area of ~100 cm 2 was shown to have a spatial resolution better than 0.5 mm. Additionally, the use of SiPMs allows for use in strong magnetic fields, opening the possibility of additional experimental capabilities. In conclusion, prototype has been built that demonstrates vacuum-compatibility, as required for a proposed beamline for the Second Target Station at SNS.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

Provenance–aware workflow for data quality management and improvement for large continuous scientific data streams

Data quality assessment, management and improvement is integral part of any big data intensive scientific research to ensure accurate, reliable and reproducible science discoveries. The task of maintaining the quality of data, however, is non-trivial and pose a challenge for a program like Department of Energy’s Atmospheric Radiation Measurement (ARM) that collects data from hundreds of instruments across the world,and distributes thousands of streaming data products that are continuously growing in near-real-time in an archive 1.7 Petabyte in size and growing. We present a computational data processing workflow to collect the data quality issue via an easy and intuitive web-based portal that allows reporting of any quality issues for any site, facility or instruments at a granularity down to individual variable in the data files. Portal allows instrument specialists and scientists to provide corrective actions in form of symbolic equation. A parallel processing framework applies the data improvement to large volume of data in efficient parallel environment, while optimizing data transfer and file I/O operations. Corrected files are systematically versioned and archived. A provenance tracking module tracks and records any change made to the data during its entire life cycle which are communicated transparently to the scientific users. Developed in Python using open source technologies, software architecture enables efficient and fast management and improvement of data in an operational data center environment.

Kumar, Jitendra↗
NASA NTRS2018

NeMO-Net - The Neural Multi-Modal Observation & Training Network for Global Coral Reef Assessment

In the past decade, coral reefs worldwide have experienced unprecedented stresses due to climate change, ocean acidification, and anthropomorphic pressures, instigating massive bleaching and die-off of these fragile and diverse ecosystems. Furthermore, remote sensing of these shallow marine habitats is hindered by ocean wave distortion, refraction and optical attenuation, leading invariably to data products that are often of low resolution and signal-to-noise (SNR) ratio. However, recent advances in UAV and Fluid Lensing technology have allowed us to capture multispectral 3D imagery of these systems at sub-cm scales from above the water surface, giving us an unprecedented view of their growth and decay. By combining spatial and spectral information from varying resolutions, we seek to augment and improve the classification accuracy of previously low-resolution datasets at large temporal scales.NeMO-Net, the first open-source deep convolutional neural network (CNN) and interactive learning and training software, currently being developed at NASA Ames, is aimed at assessing the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology. The latest iteration uses fully convolutional networks to segment and identify coral imagery taken by UAVs and satellites, including WorldView-2 and Sentinel. We present results taken from the Indian Ocean where classification accuracy has exceeded 91% for 24 geomorphological classes given ample training data. In addition, we utilize deep Laplacian Pyramid Super-Resolution Networks (LapSRN) to reconstruct high resolution information from low resolution imagery, trained from various UAV and satellite datasets. Finally, in the case of insufficient training data, we have developed an interactive online platform that allows users to easily segment and submit their classifications, which has been integrated with the current NeMO-Net workflow. Specifically, we present results from the Fiji islands in which preliminary user data has allowed for the accurate identification of 9 separate classes, despite issues such as cloud shadowing and spectral variation. The project is being supported by NASA's Earth Science Technology Office (ESTO) Advanced Information Systems Technology (AIST-16) Program.

Neural↗
NASA NTRSDate not supplied

Spaceflight Environmental-Telemetry Data for Biological Science

There is a critical need for better access and visualization of spaceflight environmental telemetry and mission hardware data from sensors including relative humidity, carbon dioxide, oxygen, radiation, airflow, temperature, acceleration, and acoustics. Under the stewardship of the Ames Life Sciences Data Archive (ALSDA) and GeneLab, an effort is underway to consolidate, normalize and provide accessibility of archived mission environmental data and hardware information, with the purpose of providing important context to biological data. This effort is necessary to provide scientific context of its impact upon biological and biomedical data from spaceflight missions and experiments (genomic, metagenomic, gene expression, proteomic, metabolomic, physiological, phenomics, behavioral; tabular, imaging, video). Environmental spaceflight data is derived from dozens of sources, with various formats, and in the past year a pipeline is in development to collect, curate and present this data efficiently. In the upcoming year, a new Data Visualization Portal will utilize the standardized pipeline data to provide easy user access to compare parameters and environmental conditions between missions, locations, subjects, and durations. Environmental and hardware data enables broad accessibility and analytics, without the need for advanced data informatic expertise. Familiarity with the capabilities and limitations of a variety of existing hardware/tools is a strength that could be applied to creation of improved hardware for future ecosystems on the Moon and Mars. The intention is to make biological and environmental telemetry data maximally open-access and FAIR (findable, accessible, interoperable, reusable) for data mining-informatic approaches to support knowledge discovery necessary for low Earth orbit, cis-Lunar, Mars transit, and Mars surface missions.

Danielle K. Lopez↗
DOE OSTI2022

Recycling rare earths: Perspectives and recent advances

Abstract Rare-earth element (REE) demand is expected to increase by a factor of up to 7 by 2040. Recycling avoids the significant hurdles associated with opening new mines, but collection and disassembly of REE-containing devices are barriers. Absolute and relative abundances of REEs and co-occurring constituents differ significantly in secondary compared to primary sources, presenting challenges and opportunities. REE concentrations are typically low, but manufactured devices include only the desired REE, avoiding the “REE balance problem” that besets natural ores. Fewer REEs need to be separated, as compared to separation of the entire lanthanide series. Co-recovery of precious (e.g., Au, Ag, Pt) or base metals (e.g., Cu, Sn, Zn) from e-wastes can offset recycling costs. Some examples of recently developed approaches for REE extraction and separation are presented here, with an emphasis on methods offering environmental benefits such as lower toxic chemical usage and reduced energy costs. Graphical abstract

36 MATERIALS SCIENCE↗
DOE OSTI2020

Molecular Optoelectronics (Final Technical Report)

The project developed new theoretical tools for analysis of nanodevices subjected to external optical and bias driving. Traditional theoretical techniques for molecular optoelectronics are either based on kinetic schemes or utilize quasiparticle description. The former fails to account for quantum mechanics of the system-bath interface and may fail qualitatively when used in open interacting systems. The latter is inconvenient in (usual for molecular optical spectroscopy) many body states description of the system. We developed a new technique - the Hubbard nonequilibrium Green's functions method - which allows to avoid shortcomings of standard theoretical approaches. The Hubbard NEGF was applied to analysis of experimental measurements of photoinduced current and bias-induced electroluminescence in STM molecular junctions. We also demonstrated practical usefulness of the Hubbard NEGF within newly proposed universal theory of current-induced forces for nonadiabatic molecular dynamics which generalizes celebrated Head-Gordon and Tully expression for electronic friction. Finally, following latest trends in laser techniques we studied local responses (local fluxes and local noise spectroscopy) of biased junctions as a source of information not accessible by total responses (total fluxes and noises) of the system.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2022

Modeling the small-scale deposition of snow onto structured Arctic sea ice during a MOSAiC storm using snowBedFoam 1.0.

The remoteness and extreme conditions of the Arctic make it a very difficult environment to investigate. In these polar regions covered by sea ice, the wind is relatively strong due to the absence of obstructions and redistributes a large part of the deposited snow mass, which complicates estimates for precipitation hardly distinguishable from blowing or drifting snow. Moreover, the snow mass balance in the sea ice system is still poorly understood, notably due to the complex structure of its surface. Quantitatively assessing the snow distribution on sea ice and its connection to the sea ice surface features is an important step to remove the snow mass balance uncertainties (i.e., snow transport contribution) in the Arctic environment. In this work we introduce snowBedFoam 1.0., a physics-based snow transport model implemented in the open-source fluid dynamics software OpenFOAM. We combine the numerical simulations with terrestrial laser scan observations of surface dynamics to simulate snow deposition in a MOSAiC (Multidisciplinary Drifting Observatory for the Study of Arctic Climate) sea ice domain with a complicated structure typical for pressure ridges. The results demonstrate that a large fraction of snow accumulates in their vicinity, which compares favorably against scanner measurements. However, the approximations imposed by the numerical framework, together with potential measurement errors (precipitation), give rise to quantitative inaccuracies, which should be addressed in future work. The modeling of snow distribution on sea ice should help to better constrain precipitation estimates and more generally assess and predict snow and ice dynamics in the Arctic.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Assessing residential PM 2.5 concentrations and infiltration factors with high spatiotemporal resolution using crowdsourced sensors

Building conditions, outdoor climate, and human behavior influence residential concentrations of fine particulate matter (PM 2.5 ). To study PM 2.5 spatiotemporal variability in residences, we acquired paired indoor and outdoor PM 2.5 measurements at 3,977 residences across the United States totaling >10,000 monitor-years of time-resolved data (10-min resolution) from the PurpleAir network. Time-series analysis and statistical modeling apportioned residential PM 2.5 concentrations to outdoor sources (median residential contribution = 52% of total, coefficient of variation = 69%), episodic indoor emission events such as cooking (28%, CV = 210%) and persistent indoor sources (20%, CV = 112%). Residences in the temperate marine climate zone experienced higher infiltration factors, consistent with expectations for more time with open windows in milder climates. Likewise, for all climate zones, infiltration factors were highest in summer and lowest in winter, decreasing by approximately half in most climate zones. Large outdoor–indoor temperature differences were associated with lower infiltration factors, suggesting particle losses from active filtration occurred during heating and cooling. Absolute contributions from both outdoor and indoor sources increased during wildfire events. Infiltration factors decreased during periods of high outdoor PM 2.5 , such as during wildfires, reducing potential exposures from outdoor-origin particles but increasing potential exposures to indoor-origin particles. Time-of-day analysis reveals that episodic emission events are most frequent during mealtimes as well as on holidays (Thanksgiving and Christmas), indicating that cooking-related activities are a strong episodic emission source of indoor PM 2.5 in monitored residences.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

IPEAT+: A Built-In Optimization and Automatic Calibration Tool of SWAT+

For almost 30 years, the Soil and Water Assessment Tool (SWAT) has been successfully implemented to address issues around various scientific subjects in the world. On the other hand, it has been reaching to the limit of potential flexibility in further development by the current structure. The new generation SWAT, dubbed SWAT+, was released recently with entirely new coding features. SWAT+ is designed to have far more advanced functions and capacities to handle challenging watershed modeling tasks for hydrologic and water quality processes. However, it is still inevitable to conduct model calibration before the SWAT+ model is applied to engineering projects and research programs. The primary goal of this study is to develop an open-source, easy-to-operate automatic calibration tool for SWAT+, dubbed IPEAT+ (Integrated Parameter Estimation and Uncertainty Analysis Tool Plus). There are four major advantages: (i) Open-source code to general users; (ii) compiled and integrated directly with SWAT+ source code as a single executable; (iii) supported by the SWAT developer group; and, (iv) built with efficient optimization technique. The coupling work between IPEAT+ and SWAT+ is fairly simple, which can be conducted by users with minor efforts. IPEAT+ will be regularly updated with the latest SWAT+ revision. If users would like to integrate IPEAT+ with various versions of SWAT+, only few lines in the SWAT+ source code are required to be updated. IPEAT+ is the first automatic calibration tool integrated with SWAT+ source code. Users can take advantage of the tool to pursue more cutting-edge and forward-thinking scientific questions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Modeling inter- and intra-granular dislocation transport using crystal plasticity

Here, this work presents the development of a crystal plasticity material model that incorporates both dislocation transport within grains and dislocation transfer across grain boundaries. This model has been implemented in the open-source finite element code MOOSE. In addition, a novel geometry-based criterion is developed to determine the direction of dislocation transfer across grain boundaries. The transfer criterion incorporates the geometric features of the grain boundary, such as the grain boundary plane normal, and its misorientation, which is accounted for through the orientation of the incoming and outgoing slip systems. The model is tested with several cases, including a copper single crystal, bi-crystal, and polycrystal. The development of the transfer criterion, implementation of the model, and its application to these test cases are discussed in detail.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Coherent X-ray spectroscopy reveals the persistence of island arrangements during layer-by-layer growth

Understanding surface dynamics during epitaxial film growth is key to growing high-quality materials with controllable properties. X-ray photon correlation spectroscopy (XPCS) using coherent X-rays opens new opportunities for in situ observation of atomic-scale fluctuation dynamics during crystal growth. Here in this paper, we present XPCS measurements of two-dimensional island dynamics during homoepitaxial growth in the layer-by-layer mode. Analysis of the results using two-time correlations reveals a new phenomenon-a memory effect in the arrangement of islands formed on successive crystal layers. Simulations indicate that this persistence in the island arrangements arises from communication between islands on different layers via adatoms. With the worldwide advent of new coherent X-ray sources, the experimental and analysis methods pioneered here will enable broad application of XPCS to observe atomic-scale processes on surfaces.

36 MATERIALS SCIENCE↗
DOE OSTI2025

PyLRO: A Python calculator for analyzing long-range structural order

We present PyLRO, an open-source Python calculator designed to detect, quantify, and display long-range order in periodic structures. The program’s design methodology, workflow, and approach to order quantification are described and demonstrated using a simple toy model. Additionally, we apply PyLRO to a series of metastable AlPO 4 structural intermediates from a prior high-pressure study, demonstrating how to compute and visualize structural order in all directions on a Miller sphere. We further highlight the program’s capabilities through a high-throughput analysis of structural patterns in the pressure-induced amorphization of AlPO 4 , revealing atomistic insights into specific energy regions of massive amorphous structures. These results suggest that PyLRO can be a valuable tool for investigating crystal–amorphous transition in materials research.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Magic high-order harmonics from a quasi-one-dimensional hexagonal solid

High-order harmonic generation (HHG) from atoms is a coherent light source that opens up attosecond physics, but it is the application of HHG to solids that has brought much excitement in the last decade. Here in this paper we report a special kind of harmonics in a quasi-one-dimensional and hexagonal barium titanium sulfide: Under circularly polarized laser excitation, harmonics are generated only at first, fifth, seventh, and eleventh orders. These magic harmonics appear only with circularly polarized light, not with linearly polarized light. Neither cubic nor tetragonal cells have magic harmonics even with circularly polarized light. Through a careful group-theory analysis, we find that two subgroups of symmetry operations unique to the hexagonal symmetry cancel out third and ninth harmonics. This feature presents a rare opportunity to develop HHG into a crystal-structure characterization tool for phase transitions between hexagonal and nonhexagonal structures.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Experimental characterization and modeling of optical tweezer particle handling dynamics [Modeling and Simulation of Optical Tweezer Particle Handling Dynamics]

Here, we report a new framework for a quantitative understanding of optical trapping (OT) particle handling dynamics. We present a novel three-dimensional particle-based model that includes optical, hydrodynamic, and inter-particle forces. This semi-empirical colloid model is based on an open-source simulation code known as LAMMPS (large-scale atomic/molecular massively parallel simulator) and properly recapitulates the full OT force profile beyond the typical linear approximations valid near the trap center. Simulations are carried out with typical system parameters relevant for our experimental holographic optical trapping (HOT) system, including varied particle sizes, trap movement speeds, and beam powers. Furthermore, we present a new experimental method for measuring both the stable and metastable boundaries of the optical force profile to inform or validate the model’s underlying force profile. We show that our framework is a powerful tool for accurately predicting particle behavior in a practical experimental OT setup and can be used to characterize and predict particle handling dynamics within any arbitrary OT force profile.

36 MATERIALS SCIENCE↗
DOE OSTI2026

High temperature stabilization of ultrafine grain tungsten alloys through synergistic compositional complexities

Thermally-stabilized fine-grained microstructures in tungsten provide a pathway to harnessing enhanced properties such as a reduced ductile-to-brittle transition temperature and improved strength while mitigating the adverse effects of grain growth and recrystallization. Here, in this study, we employ a material design strategy that relies on grain boundary segregation in the nanocrystalline state driven by alloy thermodynamics balanced with impurity scavenging through in situ formation of kinetically-stabilizing metal carbides. A W-Ti-Cr alloy is designed through lattice Monte Carlo methods and subsequently synthesized in a single-phase nanocrystalline state, which upon annealing, evolves into an ultrafine grained microstructure containing chromium grain boundary segregation collectively with a dispersed TiX (X=C,O) phase through the reaction of titanium with carbon and oxygen impurities. In situ synchrotron X-ray diffraction experiments demonstrate that increased Ti promotes stabilization across a larger temperature range but with diminishing returns above 10 at.% Ti. Long-term stability was confirmed through the retention of the ultrafine grained microstructure for a total of 8 days (192 h) at 1300 °C without grain/carbide growth and/or recrystallization. Our results demonstrate that, through strategic tailoring of composition and microstructure, one can harness the benefits of both thermodynamic and kinetic stabilization mechanisms, opening pathways for future alloy formulations that expand the window of stability.

36 MATERIALS SCIENCE↗