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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Local spring effect in titanium-based layered oxides

Titanium-based layered oxides (TLOs) are one of the most promising electrode material families for sodium-ion batteries (NIBs) due to their smooth charge/discharge profiles and excellent cycle performance. However, the reaction mechanism of these materials, especially the reason for the disappearance of multiple voltage plateaus, is still not clear. Herein, two representative TLOs (Na 2/3 Ni 1/3 Ti 2/3 O 2 and Na 2/3 Co 1/3 Ti 2/3 O 2 ) with the same P2 crystal structure have been studied to scrutinize those unexplained issues. In situ synchrotron high-energy X-ray diffraction revealed a solid solution reaction mechanism for both, suggesting the absence of rigid phase transitions upon electrochemical cycling. An interesting “spring effect” of the TiO 6 octahedron, i.e., the reversible vibration of the central Ti atom inside the local octahedron upon electrochemical redox, was demonstrated by advanced X-ray absorption spectroscopy and theoretical calculations. Such an effect could suppress the rigid phase transitions, and result in smooth charge/discharge profiles and enhanced cycle stability. Finally, this work not only accounts for the disappearance of multiple voltage plateaus of TLOs for NIBs, but also provides an effective local-structure viewpoint to increase the cycle stability of electrode materials for other advanced battery systems.

25 ENERGY STORAGE↗
DOE OSTI2021

Ecological Dichotomies Arise in Microbial Communities Due to Mixing of Deep Hydrothermal Waters and Atmospheric Gas in a Circumneutral Hot Spring

Understanding the source and availability of energy capable of supporting life in hydrothermal environments is central to predicting the ecology of microbial life on early Earth when volcanic activity was more widespread. Little is known of the substrates supporting microbial life in circumneutral to alkaline springs, despite their relevance to early Earth habitats.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Training dataset and results for geothermal exploration artificial intelligence, applied to Brady Hot Springs and Desert Peak

The submission includes the labeled datasets, as ESRI Grid files (.gri, .grd) used for training and classification results for our machine leaning model: - brady_som_output.gri, brady_som_output.grd, brady_som_output.* - desert_som_output.gri, desert_som_output.grd, desert_som_output.* The data corresponds to two sites: Brady Hot Springs and Desert Peak, both located near Fallon, NV. Input layers include: - Geothermal: Labeled data (0: Non-geothermal; 1: Geothermal) - Minerals: Hydrothermal mineral alterations, as a result of spectral analysis using Chalcedony, Kaolinite, Gypsum, Hematite and Epsomite - Temperature: Land surface temperature (% of times a pixel was classified as "Hot" by K-Means) - Faults: Fault density with a 300mradius - Subsidence: PSInSAR results showing subsidence displacement of more than 5mm - Uplift: PSInSAR results showing subsidence displacement of more than 5mm Also, the results of the classification using Brady and Desert Peak to build 2 Convolutional Neural Networks. These were applied to the training site as well as the other site, the results are in GeoTiff format. - brady_classification: Results of classification of the Brady-trained model - desert_classification: Results of classification of the Desert Peak-trained model - b2d_classification: Results of classification of Desert Peak using the Brady-trained model - d2b_classification: Results of classification of Brady using the Desert Peak-trained model

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Pilgrim Hot Springs: GEOPHIRES Inputs and Outputs for Direct-Use Geothermal District Heating and Cooling

This dataset includes files for a techno-economic analysis conducted using the GEOPHIRES simulator to examine the feasibility of expanding a larger district heating site in a remote location: Pilgrim Hot Springs, Alaska. Files included here are GEOPHIRES inputs and outputs for five different scenarios with varying demand, cycle, and system design characteristics to analyze. Also included is the link to the GEOPHIRES GitHub, as well as a link to the dataset that contains the energy modelling used to determine the heating demand for the district. For a list of the differences between scenarios, see the included "Input Overview.txt" file. Fields included in the input files are: subsurface technical parameters, surface technical parameters, financial parameters, capital and O&M parameters, as well as simulation parameters. The output files are case reports that summarize all equipment, reservoir characteristics, costs, and heating profiles.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

Bead–Spring Simulation of Ionomer Melts—Studying the Effects of Chain-Length and Associating Group Fraction on Equilibrium Structure and Extensional Flow Behavior

Ionomers are associative polymers with diverse applications ranging from selective membranes and high-performance adhesives to abrasion- and chemical-resistant coatings, insulation layers, vacuum packaging, and foamed sheets. Within equilibrium melt, the ionic or associating groups are known to form thermally reversible, associative clusters whose presence can significantly affect the system’s mechanical, viscoelastic, and transport properties. It is, thus, of great interest to understand how to control such clusters’ size distribution, shape, and stability through the designed choice of polymer architecture and the ionic groups’ fraction, arrangement, and interaction strength. In this work, we represent linear associating polymers using a Kremer–Grest type bead–spring model and perform large-scale MD simulations to explore the effect of polymer chain-length (l) and fraction (f s ) of randomly placed associating groups on the size distribution and stability of formed clusters. We consider different chain-lengths (below and above entanglement), varying fractions of associating groups (represented by ‘sticky’ beads) between 5 and 20%, and a fixed sticky–sticky nonbond interaction strength of four times that between regular non-associating beads. For all melts containing associating groups the equilibrium structure factor S(q) displays a signature ionomer peak at low wave vector q whose intensity increases with increasing f s and l. The average cluster size Nc increases with f s . However, the effect of chain-length on Nc appears to be pronounced only at higher values of f s . Under extensional flows, the computed stress (and viscosity) is higher at higher f s and l regardless of strain rate. Beyond a critical strain rate, we observe fragmentation of the associative clusters, which has interesting effects on the stress/viscous response.

36 MATERIALS SCIENCE↗
NASA NTRS1963

Spring separation of spacecraft

IBM 7090 digital computer program for solving equations of motion for spacecraft separating from final rocket stage or another spacecraft by means of precision helical compression springs

SPACECRAFT CONFIGURATION↗
NASA NTRS2015

Design and Testing of a Dynamically-Tuned Magnetostrictive Spring with Electrically-Controlled Stiffness

This paper details the development of an electrically-controlled, variable-stiffness spring based on magnetostrictive materials. The device, termed a magnetostrictive Varispring, can be applied as a semi-active vibration isolator or switched stiffness vibration controller for reducing transmitted vibrations. The Varispring is designed using 1D linear models that consider the coupled electrical response, mechanically-induced magnetic diffusion, and the effect of internal mass on dynamic stiffness. Modeling results illustrate that a Terfenol-D-based Varispring has a rise time almost an order of magnitude smaller and a magnetic diffusion cut-off frequency over two orders of magnitude greater than a Galfenol-based Varispring. The results motivate the use of laminated Terfenol-D rods for a greater stiffness tuning range and increased bandwidth. The behavior of a prototype Varispring is examined under vibratory excitation up to 6 MPa and 25 Hz using a dynamic load frame. For this prototype, stiffness is indirectly varied by controlling the excitation current. Preliminary measurements of continuous stiffness tuning via sinusoidal currents up to 1 kHz are presented. The measurements demonstrate that the Young's modulus of the Terfenol-D rod inside the Varispring can be continuously varied by up to 21.9 GPa. The observed stiffness tuning range is relatively constant up to 500 Hz, but significantly decreases thereafter. The stiffness tuning range can be greatly increased by improving the current and force control such that a more consistent current can be applied and the Varispring can be accurately tested at a more optimal bias stress.

Vibration control↗
NASA NTRS2015

A Comet Engulfs Mars: MAVEN Observations of Comet Siding Spring's Influence on the Martian Magnetosphere

The nucleus of comet C/2013 A1 (Siding Spring) passed within 141,000 km of Mars on 19 October 2014. Thus, the cometary coma and the plasma it produces washed over Mars for several hours producing significant effects in the Martian magnetosphere and upper atmosphere. We present observations from Mars Atmosphere and Volatile EvolutioN's (MAVEN's) particles and field's instruments that show the Martian magnetosphere was severely distorted during the comet's passage. We note four specific major effects: (1) a variable induced magnetospheric boundary, (2) a strong rotation of the magnetic field as the comet approached, (3) severely distorted and disordered ionospheric magnetic fields during the comet's closest approach, and (4) unusually strong magnetosheath turbulence lasting hours after the comet left. We argue that the comet produced effects comparable to that of a large solar storm (in terms of incident energy) and that our results are therefore important for future studies of atmospheric escape, MAVEN's primary science objective.

Nucleus↗
NASA NTRS2021

Spring Dust in Western North America and its Interannual Variability – Understanding the Role of Local and Transported Dust

Mineral dust over western North America is an important aerosol type contributing up to one half of surface aerosol concentrations in spring. In the present study, we use data from in-situ and remote-sensing observations and the NASA Unified WRF (NU-WRF) model to investigate the sources and interannual variations of the springtime fine-mode dust over western North America. The horizontal distribution, seasonality, and interannual variability of the springtime dust over the region are characterized with observations of fine dust concentrations at the Interagency Monitoring of Protected Visual Environments (IMPROVE) sites and dust optical depth (DOD) from the Aerosol Robotic Network (AERONET) measurements. We have conducted detailed modeling and analysis for April in selected years of 2005, 2008, and 2009, to understand the causes of interannual variabilities of the springtime dust with model experiments that separate the dust generated from local deserts with that transported across the Pacific Ocean. The results suggest that although several permanent deserts and semi-arid regions in the western North America are the major source of surface fine dust concentrations in the immediate vicinity, long-range transpacific transported dust is a dominant dust source in springtime, especially over the coastal regions and areas remote from the local deserts. Interannual variability of fine dust over western North America is explained with both local dust emission and long-range transported dust.

North America spring dust↗
DOE OSTI2021

Subsurface Characterization and Machine Learning Predictions at Brady Hot Springs: Preprint

Subsurface data analysis, reservoir modeling, and machine learning (ML) techniques have been applied to the Brady Hot Springs (BHS) geothermal field in Nevada, USA to further characterize the subsurface and assist with optimizing reservoir management. Hundreds of reservoir simulations have been conducted in TETRAD-G and CMG STARS to explore different injection and production fluid flow rates and allocations and to develop a training data set for ML. This process included simulating the historical injection and production since 1979 and prediction of future performance through 2040. ML networks were created and trained using TensorFlow based on multilayer perceptron (MLP), long short-term memory (LSTM), and convolutional neural network (CNN) architectures. These networks took as input selected flow rates, injection temperatures, and historical field operation data and produced estimates of future production temperatures. This approach was first successfully tested on a simplified single fracture doublet system, followed by the application to the BHS reservoir. Using an initial BHS dataset with 37 simulated scenarios, the trained and validated network predicted the production temperature for 6 production wells with the mean absolute percentage error of less than 8%. In a complementary analysis effort, the principal component analysis applied to 13 BHS geological parameters revealed that vertical fracture permeability shows the strongest correlation with fault density and fault intersection density. A new BHS reservoir model was developed considering the fault intersection density as proxy for permeability. This new reservoir model helps to explore under-exploited zones in the reservoir. A data gathering plan to obtain additional subsurface data was developed; it includes temperature surveying for three idle injection wells, at which the reservoir simulations indicate high bottom-hole temperatures. The collected data assist with calibrating the reservoir model and may lead to converting these wells to producers to access under-exploited zones in the reservoir. Data gathering activities are planned for the first quarter of 2021.

40 EE - Geothermal Technologies Office (EE-4G)↗
DOE OSTI2024

Hot Springs and Geysers: Exploring Historical and Modern Impacts of Geothermal Energy Production on Associated Natural Surface Systems and Standardizing Management Practices

Surface thermal features, most notably hot springs and geysers are increasingly being recognized for their importance to ecosystems, indigenous cultures, and in some cases agriculture, recreation, and tourism. Geothermal project development poses a potential risk to these natural features but current regulatory requirements for assessing and managing these risks during exploration, permitting and monitoring are somewhat inconsistent and unpredictable across different geothermal fields. This has resulted in uncertainty and increases in exploration risk for geothermal energy developers that have led to costly project delays, cancellations, or hesitation to commit. Varying regulatory requirements may also influence public perception, fostering confusion, distrust and ultimately opposition to geothermal projects, further contributing to project delays or cancellations. At a time when there is an increasing urgency for reliable baseload clean energy, geothermal is a net-zero, renewable solution that additionally provides access to more equitable and environmentally just clean power. Continued integration of geothermal energy into the national energy roadmap can be facilitated through consistent and predictable permitting, providing regulators the framework they need, developers a clear path forward, and transparency that the public deserves. This project, currently in its beginning phases, seeks to address this important issue by providing a technical basis from which to build a preliminary protocol for assessing and managing potential impacts from new or existing geothermal energy projects to surface thermal features and their associated ecosystems. Development of this preliminary protocol will be informed by (1) a literature review of well-documented case studies in the western U.S. and New Zealand to understand the range of conditions that exemplify geothermal-surface thermal systems; (2) development of generic illustrative conceptual-numerical models to quantify, understand, and predict the first-order controls (e.g., pressure and permeability) on surface flows; and (3) additional independent and scientifically rigorous evaluations of geothermal-surface thermal system case studies from the Basin and Range Province that incorporate publicly available data as well as data provided by industry through data-sharing agreements. Learning from the successes of the process used to develop the Induced Seismicity Management Protocol (ISMP), we ultimately aim to use these initial efforts as a springboard for establishing a surface thermal feature management working group that will work collaboratively to finalize the protocol as well as co-create recommended best practices for implementation. We envision that the working group will primarily be composed of representatives from regulatory entities, government agencies, Tribes, academia, national laboratories, and industry, and will include early and regular engagement with community organizations and environmental groups. This will help ensure broad acceptance and implementation of the protocol, which will facilitate a more consistent, predictable, and standardized regulatory process, and help to ensure that geothermal energy continues to provide a reliable source of clean energy, and a pathway to achieving greater energy equity in the U.S.

Best Practices↗
DOE OSTI2022

Efficacy of a Short-Term Captive Broodstock Program Compared with Hatchery-Origin Spring Chinook Salmon Derived from the Same Population

Abstract We examined the efficacy of a one-generation (five brood years: 1997–2001) captive broodstock program for spring Chinook Salmon Oncorhynchus tshawytscha by comparing survival rates of captive broodstock progeny (CBP; F2) with that of hatchery-origin fish (HOR) from a conservation hatchery supplementation program in which both groups were derived from the Tucannon River (Washington State) population for the 2000–2006 brood years. Survival rates compared were egg to fry, fry to smolt, egg to smolt, total (ages 3–5) and adult (ages 4+) smolt-to-adult-return (SAR) survival, and total (ages 3–5) and adult (ages 4+) progeny-to-parent (P:P) ratio. Total escapement and adult P:P ratios were also examined to determine if observed demographic benefits to the population continued after the captive broodstock program ended. The CBP group had lower within-hatchery survival than the HOR group, with significant differences in survival at the egg-to-fry and egg-to-smolt stages due to poor egg viability. Mean untransformed total and adult SARs for the CBP were half those of the HOR group; however, SARs did not differ significantly. The CBP also had significantly lower total and adult P:P ratios than the HOR group and were below replacement for six of the seven brood years. While the captive broodstock provided additional fish for release that would not have been available otherwise, overall the CBP performed poorly and below expectations compared with the HOR group, both within the hatchery and after release. The captive broodstock program provided a short-term demographic boost, most notable in the 2008–2010 return years, but the benefit did not carry over after the program ended.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Divergent responses of spring phenology to daytime and nighttime warming

Spring phenology (i.e., start of season, SOS) has shifted earlier in response to warmer temperatures. However, the respective influences of daytime and nighttime temperatures on SOS changes remain poorly understood. Here we characterized the responses of satellite-derived SOS to minimum temperature (Tmin) and maximum temperature (Tmax) across Appalachian Trail regions in the Eastern United States during 2000-2013. We found SOS responded differently to Tmin and Tmax at 81.5% of the study area. Furthermore, the SOS responses to Tmin and Tmax both changed across space, and specifically, these two responses showed significant divergent trends from cold to warm regions (P<0.001). We propose a new framework utilizing both Tmin and Tmax, instead of daily average temperature, in modeling phenology. This study, for the first time, disentangled phenological responses to daytime temperature from nighttime temperature across a wide range of temperatures. The findings suggest that model projections of future phenological changes should incorporate the divergent phenology responses to daytime and nighttime temperatures, in order to improve the representation of land-atmosphere interactions in Earth system models in light of asymmetric diurnal warming.

asymmetric warming, temperature sensitivity, Appal↗
DOE OSTI2023

Predicting spring phenology in deciduous broadleaf forests: NEON phenology forecasting community challenge

Accurate models are important to predict how global climate change will continue to alter plant phenology and near-term ecological forecasts can be used to iteratively improve models and evaluate predictions that are made a priori. The Ecological Forecasting Initiative's National Ecological Observatory Network (NEON) Forecasting Challenge, is an open challenge to the community to forecast daily greenness values, measured through digital images collected by the PhenoCam Network at NEON sites before the data are collected. For the first round of the challenge, which is presented here, we forecasted canopy greenness throughout the spring at eight deciduous broadleaf sites to investigate when, where, and for what model type phenology forecast skill is highest. A total of 192,536 predictions were submitted, representing eighteen models, including a persistence and a day of year mean null models. We found that overall forecast skill was highest when forecasting earlier in the greenup curve compared to the end, for shorter lead times, for sites that greened up earlier, and when submitting forecasts during times other than near budburst. The models based on day of year historical mean had the highest predictive skill across the challenge period. In this first round of the challenge, by synthesizing across forecasts, we started to elucidate what factors affect the predictive skill of near-term phenology forecasts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Application of remote sensing precipitation data and the $\mathrm{CONNECT}$ algorithm to investigate spatiotemporal variations of heavy precipitation: Case study of major floods across Iran (Spring 2019)

In recent years, the number of floods following unprecedented rainfall events have increased in Iran during early spring (March 21st to April 20th, referred to in Iran as the month of “Farvadin”). While numerous studies have addressed changes in climate extremes and precipitation trends at different temporal scales from daily to annual across the country, analyses of short-duration and heavy precipitation, especially during recent years, are rarely considered. Furthermore, most studies investigate the variations in extremes and total precipitation using a limited number of synoptic weather stations across Iran. Here this study assesses the variations in heavy precipitation (precipitation with intensities greater than or equal to 3 mm/3 h) at 0.04° spatial and 3-hourly temporal resolution during the month of Farvardin. In addition, the effect of atmospheric river conditions over Iran and their possible link to intensifying heavy precipitation is explored. For this purpose, the CONNected-objECT (CONNECT) algorithm is applied on a precipitation dataset, Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS), and an Integrated Water Vapor Transport (IVT) dataset from the NASA Modern-Era Retrospective Analysis for Research and Applications Version-2 (MERRA-2). The results suggest that the increase in the number of floods in recent years is related to the increase in the intensity and volume of heavy precipitation events, although the frequency and duration of heavy precipitation events have not changed significantly. Furthermore, the results show that atmospheric river conditions over the country are present during the same window as each year’s most extreme events. It is found that 8 out of 13 of the largest ARs over Iran come from moisture plumes with pathways over the African and Red Sea.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Time–series Analysis of Volume Change at Brady Hot Springs, Nevada, USA using Geodetic Data from 2003 – 2018

Brady Hot Springs geothermal field has exhibited subsidence, as measured by interferometric synthetic aperture radar (InSAR). Previous studies have examined both the temporal evolution of the deformation from 2004 through 2016 and the spatial extent of the deformation, directly relating the observed subsidence to volumetric changes below the surface. We extend the modeling at Brady to analyze a data set of interferometric pairs spanning from the end of 2003 through 2018. We examine spatial and temporal trends in the observed deformation by time–series analysis of each of the 1656 cubic voxels in a parameterized elastic dislocation model to identify areas where the subsurface volume changes as a function of time. Joint time–series analysis of Global Positioning System and InSAR pairs confirm significant changes in rates of volume change during time intervals when well operations were varied. Here, the rate of subsidence increases with increased injection, consistent with the identification of thermal contraction of the rock matrix as the dominant driving mechanism. Conversely, the modeled volume increases when pumping ceases, suggesting thermal expansion of the rock matrix.

58 GEOSCIENCES↗