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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Resolution Enhancement of MODIS-Derived Water Indices for Studying Persistent Flooding

Monitoring coastal marshes for persistent flooding and salinity stress is a high priority issue in Louisiana. Remote sensing can identify environmental variables that can be indicators of marsh habitat conditions, and offer timely and relatively accurate information for aiding wetland vegetation management. Monitoring activity accuracy is often limited by mixed pixels which occur when areas represented by the pixel encompasses more than one cover type. Mixtures of marsh grasses and open water in 250m Moderate Resolution Imaging Spectroradiometer (MODIS) data can impede flood area estimation. Flood mapping of such mixtures requires finer spatial resolution data to better represent the cover type composition within 250m MODIS pixel. Fusion of MODIS and Landsat can improve both spectral and temporal resolution of time series products to resolve rapid changes from forcing mechanisms like hurricane winds and storm surge. For this study, using a method for estimating sub-pixel values from a MODIS time series of a Normalized Difference Water Index (NDWI), using temporal weighting, was implemented to map persistent flooding in Louisiana coastal marshes. Ordinarily NDWI computed from daily 250m MODIS pixels represents a mixture of fragmented marshes and water. Here, sub-pixel NDWI values were derived for MODIS data using Landsat 30-m data. Each MODIS pixel was disaggregated into a mixture of the eight cover types according to the classified image pixels falling inside the MODIS pixel. The Landsat pixel means for each cover type inside a MODIS pixel were computed for the Landsat data preceding the MODIS image in time and for the Landsat data succeeding the MODIS image. The Landsat data were then weighted exponentially according to closeness in date to the MODIS data. The reconstructed MODIS data were produced by summing the product of fractional cover type with estimated NDWI values within each cover type. A new daily time series was produced using both the reconstructed 250-m MODIS, with enhanced features, and the approximated daily 30-m high-resolution image based on Landsat data. The algorithm was developed and tested over the Calcasieu-Sabine Basin, which was heavily inundated by storm surge from Hurricane Ike to study the extent and duration of flooding following the storm. Time series for 2000-2009, covering flooding events by Hurricane Rita in 2005 and Hurricane Ike in 2008, were derived. High resolution images were formed for all days in 2008 between the first cloud free Landsat scene and the last cloud-free Landsat scene. To refine and validate flooding maps, each time series was compared to Louisiana Coastwide Reference Monitoring System (CRMS) station water levels adjusted to marsh to optimize thresholds for MODIS-derived time series of NDWI. Seasonal fluctuations were adjusted by subtracting ten year average NDWI for marshes, excluding the hurricane events. Results from different NDWI indices and a combination of indices were compared. Flooding persistence that was mapped with higher-resolution data showed some improvement over the original MODIS time series estimates. The advantage of this novel technique is that improved mapping of extent and duration of inundation can be provided.

Underwood, L. W.↗
NASA NTRS2023

Tree Growth Enhancement Drives a Persistent Biomass Gain in Unmanaged Temperate Forests

While enhanced tree growth over the last decades has been reported in forests across the globe, it remains unclear whether it drives persistent biomass increases of forest stands, particularly in mature forests. Enhanced tree growth and stand-level biomass are often linked with a simultaneous increase in density-driven mortality and a reduction in tree longevity. Identifying empirical evidence regarding the balance between these processes is challenging due to the confounding effects of stand history, management, and environmental changes. Here, we investigate the link between growth and biomass via the negative relationship between average tree size and stand density (tree number per area). We find increasing stand density for a given mean tree size in unmanaged closed-canopy forests in Switzerland over the past six decades and a positive relationship between tree growth and stand density across forest plots—qualitatively consistent with our simulations using a mechanistic, cohort-resolving ecosystem model (BiomeE). Model simulations show that, in the absence of other disturbances, enhanced tree growth persistently increases biomass stocks despite simultaneous decreases in carbon residence time and tree longevity. However, the magnitude of simulated biomass changes for a given growth enhancement critically depends on the shape of the mortality functions. Our analyses reconcile reports of growth-induced reductions of tree longevity with model predictions of persistent biomass increases, and with our finding of trends toward denser forests in response to growth—also in mature stands.

biomass stocks↗
DOE OSTI2017

Persistence behavior of metamifop and its metabolite in rice ecosystem

In this study, a field experiment was conducted to determine the persistence of metamifop in transplanted rice crop for two seasons. Metamifop 10% EC was applied at two doses: 100 g a.i. ha -1 and 200 g a.i. ha -1 at 2–3 leaf stage of Echinochloa crusgalli. The residues of metamifop along with its major metabolite, N-(2-fluorophenyl)-2-hydroxy-N-methylpropionamide (HFMPA), were estimated in rice plant, field water and soil using Liquid Chromatography Mass Spectrometry. Limit of detection and limit of quantification of the method for both the compounds were set at 0.003 μg g -1 and 0.010 μg g -1 respectively. Metamifop showed less persistence in field water and rice plant as compared to soil samples. Presence of HFMPA was recorded in rice plant and soil. Both the compounds were found below level of quantification in harvest samples of straw, grains, husk and soil. Lastly, a safe waiting period of 52 d was suggested for harvesting of rice when metamifop was applied at 100 g a.i. ha -1 (recommended dose).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Use of Physics to Improve Solar Forecast: Physics-Informed Persistence Models for Simultaneously Forecasting GHI, DNI, and DHI

Observation-based statistical models have been widely used in forecasting solar energy; however, existing models often lack a clear relation to physics and are limited largely to global horizontal irradiance (GHI) forecasts over relatively short time horizons (< 1 hour). Incorporating physics into observation-based models, increasing forecast time horizons and developing a model system for forecasting not only GHI but also direct normal irradiance (DNI) and diffuse horizontal irradiance (DHI) remain challenging, especially under cloudy conditions because of complex cloud-radiation interactions. This work attempts to address these challenges by developing a hierarchy of four new physics-informed persistence models that can be used to simultaneously forecast GHI, DNI and DHI. The decade-long measurements (1998 to 2014) at the U.S. Department of Energy's Atmospheric Radiation Measurement (ARM)'s Southern Great Plains (SGP) Central Facility site are used to evaluate the performance of the new models. Overall, the results show that the new physics-informed forecast models generally outperform the simple and smart persistence models, and improve the forecast accuracy at lead times from 1.25 hours up to 6 hours. Further analysis reveals that the forecast error is highly related to the error and temporal variability of the assumed cloud predictor. The best model for forecasting different radiative components can be explained by the relationship between solar irradiances and cloud properties.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Shape-Persistent, Thermoresponsive Polypeptide Brushes Prepared by Vapor Deposition Surface-Initiated Ring-Opening Polymerization of α-Amino Acid N -Carboxyanhydrides

We report that surface-grafting thermoresponsive polymers allows the preparation of thin polymer brush coatings with surface properties that can be manipulated by variation of temperature. In most instances, thermoresponsive polymer brushes are produced using polymers that dehydrate and collapse above a certain temperature. This report presents the preparation and properties of polymer brushes that show thermoresponsive surface properties, yet are shape-persistent in that they do not undergo main chain collapse. The polymer brushes presented here are obtained via vapor deposition surface-initiated ring-opening polymerization (SI-ROP) of γ-di- or tri(ethylene glycol)-modified glutamic acid N-carboxyanhydrides. Vapor deposition SI-ROP of γ-di- or tri(ethylene glycol)-modified L- or D-glutamic acid N-carboxyanhydrides affords helical surface-tethered polymer chains that do not show any changes in secondary structure between 10 and 70 °C. QCM-D experiments, however, revealed significant dehydration of poly(γ-(2-(2-methoxyethoxy)ethyl)-l-glutamate) (poly(L-EG 2 -Glu)) brushes upon heating from 10 to 40 °C. At the same time, AFM and ellipsometry studies did not reveal significant variations in film thickness over this temperature range, which is consistent with the shape-persistent nature of these polypeptide brushes and indicates that the thermoresponsiveness of the films is primarily due to hydration and dehydration of the oligo(ethylene glycol) side chains. The results we present here illustrate the potential of surface-initiated NCA ring-opening polymerization to generate densely grafted assemblies of polymer chains that possess well-defined secondary structures and tunable surface properties. These polypeptide brushes complement their conformationally unordered counterparts that can be generated via surface-initiated polymerization of vinyl-type monomers and represent another step forward to biomimetic surfaces and interfaces.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Spatially Resolved Persistent Photoconductivity in MoS2–WS2 Lateral Heterostructures

The optical and electronic properties of 2D semiconductors are intrinsically linked via the strong interactions between optically excited bound species and free carriers. Here we use near-field scanning microwave microscopy (SMM) to image spatial variations in photoconductivity in MoS 2 –WS 2 lateral multijunction heterostructures using photon energy-resolved narrowband illumination. We find that the onset of photoconductivity in individual domains corresponds to the optical absorption onset, confirming that the tightly bound excitons in transition metal dichalcogenides can nonetheless dissociate into free carriers. These photogenerated carriers are most likely n-type and are seen to persist for up to days. Informed by finite element modeling we reveal that they can increase the carrier density by up to 200 times. This persistent photoconductivity appears to be dominated by contributions from the multilayer MoS 2 domains, and we attribute the flake-wide response in part to charge transfer across the heterointerface. Spatial correlation of our SMM imaging with photoluminescence (PL) mapping confirms the strong link between PL peak emission photon energy, PL intensity, and the local accumulated charge. This work reveals the spatially and temporally complex optoelectronic response of these systems and cautions that properties measured during or after illumination may not reflect the true dark state of these materials but rather a metastable charged state.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Population models reveal unexpected patterns of local persistence despite widespread larval dispersal in a highly exploited species

Nearshore marine populations are structured in metapopulations that are connected through larval dispersal across national boundaries. One of the main challenges for effective management of these metapopulations is the need for partnerships between nations that share the same resource. By coupling large-scale connectivity information to a dynamic population model, we analyzed the patterns of connectivity and population persistence for the Caribbean spiny lobster ( Panulirus argus ) metapopulation both within and across national boundaries. Although spiny lobster subpopulations are highly connected at the basin scale, several nations located in the northern Caribbean and ecoregional networks could persist independently of the larger basinwide metapopulation. Based on these results, we propose transnational neighborhoods for spiny lobster management. Our analysis suggests that the dynamics and management of those subpopulations neighborhoods are not intrinsically dependent on “upstream” connectivity even though current rates of upstream larval supply are very high.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Robustness of topological persistence in knowledge distillation for wearable sensor data

Topological data analysis (TDA) has shown great success in various applications involving wearable sensor data. However, there are difficulties in leveraging topological features in machine learning and wearable sensors because of the large time consumption and computational resources required to extract the features. To address this problem, knowledge distillation (KD) is utilized to generate a small model and accommodate topological features with persistence image (PI) representations from the raw time series data. Deploying topological knowledge in KD enables the student to achieve better performance compared to the one trained solely on raw time series data. However, it is not yet known if there are coherent characteristics for topological features in PI, which can aid in improving the performance during KD. In this paper, we investigate the suitability and challenges of utilizing topological features in KD for wearable sensor data, thereby contributing to the advancement of the field. Our study explores the impact of transferred topological features by comparing the Teacher-to-Student framework with Multiple Teachers-to-Student where teachers utilize both time series data and persistence images obtained by TDA as inputs. Additionally, we conduct a rigorous examination of topological knowledge effects by testing under various corruptions, knowledge types, and learning strategies in the context of human activity recognition tasks. Our analysis of topological features in KD presents the optimal strategy for incorporating these features. This study includes datasets of varying scales, window lengths, and activity classes, providing a comprehensive evaluation. Our results demonstrate that leveraging topological features in KD to enhance performance across databases.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

Work Stealing and Persistence-based Load Balancers for Iterative Overdecomposed Applications

Applications often involve iterative execution of identical or slowly evolving calculations. Such applications require good initial load balance coupled with efficient periodic rebalancing. In this paper, we consider the design and evaluation of two distinct approaches to addressing this challenge: persistence-based load balancing and work stealing. The work to be performed is overdecomposed into tasks, enabling automatic rebalancing by the middleware. We present a hierarchical persistence-based rebalancing algorithm that performs localized incremental rebalancing. We also present an active-message-based retentive work stealing algorithm optimized for iterative applications on distributed memory machines. These are shown to incur low overheads and achieve over 90% efficiency on 76,800 cores.

persistence-based load balancing↗
DOE OSTI2019

Implementing efficient data compression and encryption in a persistent key-value store for HPC

Recently, persistent data structures, like key-value stores (KVSs), which are stored in a high-performance computing (HPC) system’s nonvolatile memory, provide an attractive solution for a number of emerging challenges like limited I/O performance. Data compression and encryption are two well-known techniques for improving several properties of such data-oriented systems. This article investigates how to efficiently integrate data compression and encryption into persistent KVSs for HPC with the ultimate goal of hiding their costs and complexity in terms of performance and ease of use. Our compression technique exploits deep memory hierarchy in an HPC system to achieve both storage reduction and performance improvement. Our encryption technique provides a practical level of security and enables sharing of sensitive data securely in complex scientific workflows with nearly imperceptible cost. We implement the proposed techniques on top of a distributed embedded KVS to evaluate the benefits and costs of incorporating these capabilities along different points in the dataflow path, illustrating differences in effective bandwidth, latency, and additional computational expense on Swiss National Supercomputing Centre’s Grand Tavé and National Energy Research Scientific Computing Center’s Cori.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Chapter 13: Assessing Persistence and Other Evaluation Issues Cross-Cutting Protocol. The Uniform Methods Project: Methods for Determining Energy Efficiency Savings for Specific Measures

Addressing other evaluation issues that have been raised in the context of energy efficiency programs, this chapter focuses on methods used to address the persistence of energy savings, which is an important input to the benefit/cost analysis of energy efficiency programs and portfolios. In addition to discussing 'persistence' (which refers to the stream of benefits over time from an energy efficiency measure or program), this chapter provides a summary treatment of these issues -Synergies across programs -Rebound -Dual baselines -Errors in variables (the measurement and/or accuracy of input variables to the evaluation).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS2016

Persistent Identifiers Implementation in EOSDIS

This presentation provides the motivation for and status of implementation of persistent identifiers in NASA's Earth Observation System Data and Information System (EOSDIS). The motivation is provided from the point of view of long-term preservation of datasets such that a number of questions raised by current and future users can be answered easily and precisely. A number of artifacts need to be preserved along with datasets to make this possible, especially when the authors of datasets are no longer available to address users questions. The artifacts and datasets need to be uniquely and persistently identified and linked with each other for full traceability, understandability and scientific reproducibility. Current work in the Earth Science Data and Information System (ESDIS) Project and the Distributed Active Archive Centers (DAACs) in assigning Digital Object Identifiers (DOI) is discussed as well as challenges that remain to be addressed in the future.

persistent identifiers↗
NASA NTRS2017

Performance Enhancement of a Computational Persistent Homology Package

In recent years, persistent homology has become an attractive method for data analysis. It captures topological features, such as connected components, holes, voids, etc., from a point cloud by finding out when these features appear and disappear in the filtration sequence. In this project, we focus on improving the performance of Eirene, a fancy computational persistent homology package. Eirene is a 5000-line opensource software implemented by using the dynamic programming language Julia. We use the Julia profiling tools to identify the performance bottlenecks and develop different methods to manage the bottlenecks, including the parallelization of some time-consuming functions on the multicore/manycore hardware. The empirical results show that the performance can be greatly improved.

Profiling↗
NASA NTRS2019

Tuning the Performance of a Computational Persistent Homology Package

In recent years, persistent homology has become an attractive method for data analysis. It captures topological features, such as connected components, holes, and voids from point cloud data and summarizes the way in which these features appear and disappear in a filtration sequence. In this project, we focus on improving the performanceof Eirene, a computational package for persistent homology. Eirene is a 5000-line open-source software library implemented in the dynamic programming language Julia. We use the Julia profiling tools to identify performance bottlenecks and develop novel methods to manage them, including the parallelization of some time-consuming functions on multicore/manycore hardware. Empirical results show that performance can be greatly improved.

Persistent Homology↗
DOE OSTI2021

Shape Persistent, Highly Conductive Ionogels from Ionic Liquids Reinforced with Cellulose Nanocrystal Network

Abstract Shape‐persistent, conductive ionogels where both mechanical strength and ionic conductivity are enhanced are developed using multiphase materials composed of cellulose nanocrystals and hyperbranched polymeric ionic liquids (PILs) as a mechanically strong supporting network matrix for ionic liquids with an interrupted ion‐conducting pathway. The integration of needlelike nanocrystals and PIL promotes the formation of multiple hydrogen bonding and electrostatic ionic interaction capacitance, resulting in the formation of interconnected networks capable of confining a high amount of ionic liquid (≈95 wt%) without losing its self‐sustained shape. The resulting nanoporous and robust ionogels possess outstanding mechanical strength with a high compressive elastic modulus (≈5.6 MPa), comparable to that of tough, rubbery materials. Surprisingly, these rigid materials preserve the high ionic conductivity of original ionic liquids (≈7.8 mS cm −1 ), which are distributed within and supported by the nanocrystal network‐like rigid frame. On the one hand, such stable materials possess superior ionic conductivities in comparison to traditional solid electrolytes; on the other hand, the high compression resistance and shape‐persistence allow for easy handling in comparison to traditional fluidic electrolytes. The synergistic enhancement in ion transport and solid‐like mechanical properties afforded by these ionogel materials make them intriguing candidates for sustainable electrodeless energy storage and harvesting matrices.

Lee, Hansol↗
DOE OSTI2022

Tailored Persistent Radical‐containing Heterotrimetal‐Organic Framework for Boosting Efficiency of Visible/NIR Light‐driven Photocatalytic CO 2 Reduction

Abstract Promoting light absorption range of photocatalysts is of great significance to improve solar light‐driven photocatalytic CO 2 reduction efficiency. Herein, a new viologen‐based multicomponent heterotrimetallic metal–organic framework (MOF) [Cu 3 Th 6 ( µ 3 ‐O) 4 ( µ 3 ‐OH) 4 (cpb) 12 ][Fe III (CN) 6 ] 6 (IHEP‐14) with an unprecedented (6, 18)‐connected she ‐ d topology is presented. Upon UV irradiation, this MOF undergoes ligand and iron photoreduction, and a single‐crystal‐to‐single‐crystal transformation to generate persistent radical‐containing MOF [Cu 3 Th 6 ( µ 3 ‐O) 4 ( µ 3 ‐OH) 4 (cpb • ) 12 ][Fe II (CN) 6 ] 6 (IHEP‐15). This radical‐containing MOF shows excellent stability without fading after at least 2 months in air. Besides extending the photoabsorption to a wider wavelength range covering from 200 to 2,500 nm, the generation of persistent radical in IHEP‐15 also largely enhances its CO 2 adsorption capacity by a factor of three due to the strong affinity between π orbital of the radical and the π system of CO 2 . These attributes endow IHEP‐15 with excellent visible/NIR light‐driven CO 2 photoreduction activity, with CO production rates under visible and NIR irradiation of 570.3 and 209.3 µmol h −1 g −1 , respectively. Notably, the latter is a record high for NIR‐induced CO production among all MOFs reported so far.

Hu, Kong‐Qiu↗
DOE OSTI2018

Grazing disturbance increases transient but decreases persistent soil seed bank

Abstract Very few studies have examined whether the impacts of grazing disturbance on soil seed banks occur directly or indirectly through aboveground vegetation and soil properties. The potential role of the seed bank in alpine wetland restoration is also unknown. We used SEM (structural equation modeling) to explore the direct effect of grazing disturbance on the seed bank and the indirect effect through aboveground vegetation and soil properties. We also studied the role of the seed bank on the restoration potential in wetlands with various grazing intensities: low (fenced, winter grazed only), medium (seasonally grazed), and high (whole‐year grazed). For the seed bank, species richness and density per plot showed no difference among grazing intensities for each depth (0–5, 5–10, 10–15 cm) and for the whole depth (0–15 cm) in spring and summer. There was no direct effect of grazing disturbance on seed bank richness and density both in spring and summer, and also no indirect effect on the seed bank through its direct effect on vegetation richness and abundance. Grazing disturbance indirectly increased spring seed bank density but decreased summer seed bank density through its direct effect (negative correlation) on soil moisture and total nitrogen and its indirect effect on vegetation abundance. Species composition of the vegetation changed with grazing regime, but that of the seed bank did not. An increased trend of similarity between the seed bank and aboveground vegetation with increased grazing disturbance was found in the shallow depth and in the whole depth only in spring. Although there was almost no change in seed bank size with grazing intensities, grazing disturbance increased the quantity of transient seeds but decreased persistent seeds. Persistent seeds stored in the soil could play a crucial role in vegetation regeneration and in restoration of degraded wetland ecosystems. The seed bank should be an integral part of alpine wetland restoration programs.

Ma, Miaojun↗
DOE OSTI2021

Climate warming threatens the persistence of a community of disturbance-adapted native annual plants

With ongoing climate change, populations are expected to exhibit shifts in demographic performance that will alter where a species can persist. This presents unique challenges for managing plant populations and may require ongoing interventions, including in situ management or introduction into new locations. However, few studies have examined how climate change may affect plant demographic performance for a suite of species, or how effective management actions could be in mitigating climate change effects. Over the course of two experiments spanning 6 yr and four sites across a latitudinal gradient in the Pacific Northwest, United States, here we manipulated temperature, precipitation, and disturbance intensity, and quantified effects on the demography of eight native annual prairie species. Each year we planted seeds and monitored germination, survival, and reproduction. We found that disturbance strongly influenced demographic performance and that seven of the eight species had increasingly poor performance with warmer conditions. Across species and sites, we observed 11% recruitment (the proportion of seeds planted that survived to reproduction) following high disturbance, but just 3.9% and 2.3% under intermediate and low disturbance, respectively. Moreover, mean seed production following high disturbance was often more than tenfold greater than under intermediate and low disturbance. Importantly, most species exhibited precipitous declines in their population growth rates (λ) under warmer-than-ambient experimental conditions and may require more frequent disturbance intervention to sustain populations. Aristida oligantha, a C4 grass, was the only species to have λ increase with warmer conditions. These results suggest that rising temperatures may cause many native annual plant species to decline, highlighting the urgency for adaptive management practices that facilitate their restoration or introduction to newly suitable locations. Frequent and intense disturbances are critical to reduce competitors and promote native annuals’ persistence, but even such efforts may prove futile under future climate regimes.

54 ENVIRONMENTAL SCIENCES↗