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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS1987

Advanced techniques for the storage and use of very large, heterogeneous spatial databases. The representation of geographic knowledge: Toward a universal framework

A new approach to building geographic data models that is based on the fundamental characteristics of the data is presented. An overall theoretical framework for representing geographic data is proposed. An example of utilizing this framework in a Geographic Information System (GIS) context by combining artificial intelligence techniques with recent developments in spatial data processing techniques is given. Elements of data representation discussed include hierarchical structure, separation of locational and conceptual views, and the ability to store knowledge at variable levels of completeness and precision.

Peuquet, Donna J.↗
NASA NTRS2020

Spatial Heterogeneity in CO2, CH4, and Energy Fluxes: Insights from Airborne Eddy Covariance Measurements Over the Mid-Atlantic Region

The exchange of carbon between the Earth’s atmosphere and biosphere influences the atmospheric abundances of carbon dioxide (CO2) and methane (CH4). Airborne eddy covariance can quantify surface-atmosphere exchange from landscape-to-regional scales, offering a unique perspective on carbon cycle dynamics. We use extensive airborne measurements to quantify fluxes of sensible heat, latent heat, CO2, and CH4across multiple ecosystems in the Mid-Atlantic region during September 2016 and May 2017. In conjunction with footprint analysis and land cover information, we use the airborne dataset to explore the effects of landscape heterogeneity on measured fluxes. Our results demonstrate large variability in CO2 uptake over mixed agricultural and forested sites, with fluxes ranging from -3.4 ± 0.7 to -11.5 ± 1.6μmol m-2s-1 for croplands and -9.1 ± 1.5 to -22.7 ± 3.2μmol m-2s-1for forests. We also report substantial CH4emissions of 32.3 ± 17.0to 76.1 ± 29.4nmol m-2s-1 from a brackish herbaceous wetland and 58.4± 12.0 to 181.2 ± 36.8nmol m-2s-1 from a freshwater forested wetland. Comparison of ecosystem-specific aircraft observations with measurements from eddy covariance flux towers along the flight path demonstrate that towers capture ~30–75% of the regional variability in ecosystem fluxes. Diel patterns measured at the tower sites suggest that peak, midday flux measurements from aircraft accurately predicts net daily CO2exchange. We discuss next steps in applying airborne observations to evaluate bottom-up flux models and improve understanding of the biophysical processes that drive carbon exchange from landscape-to-regional scales.

airborne measurements to quantify fluxes of sensib↗
DOE OSTI2020

Revisiting the first Sandia Fracture Challenge with transient deformation heating and strain localization considerations

In this study, we present a systematic experimental study and accompanying theoretical analysis of the dependence of ductile fracture on strain localization, strain hardening rates, deformation-induced thermal softening, and transient heat conduction under spatially uniform as well as spatially heterogeneous deformation. Spatially uniform cases are studied via standard dogbone shaped specimens subject to uniaxial tension. Spatially heterogeneous deformation is studied via the so-called Sandia Fracture Challenge (SFC) specimen, which is a standard compact tension specimen modified with three machined holes in front of a blunt notch. We utilize the same precipitation hardened martensitic stainless steel used in the first SFC experiments, i.e. 15-5 PH with an H1075 heat treatment. We also study 15-5 PH in Condition A and with the H900 heat treatment, each of which has a different hardening behavior and ductility. We find that the ductility does not correlate with the deformation to first crack initiation in the SFC specimen. Instead, hardening rates are better correlated. Moreover, a re-examination finds that an accurate calibration of the hardening rates is strongly correlated with accurate blind predictions of ductile fracture in the SFC specimens. Given that thermal softening can greatly affect hardening rates, we provided a thermographic analysis of deformation-induced heating and transient heat transfer in both the dogbone shaped samples and the SFC specimens. Transient heating in stainless steels is found to have first-order effects on the strain at the onset of necking, strain to fracture, as well as strain localization and ductile fracture in complex geometries even under so-called quasi-static loading rates.

42 ENGINEERING↗
NASA NTRS2026

Characterizing the subglacial environment of lower Thwaites Glacier using radar modeling

Understanding the spatial heterogeneity beneath Thwaites Glacier, West Antarctica, is vital to projecting its impact on future sea levels. Radar-echo sounding (RES) is commonly used to infer subglacial conditions, but these data can be challenging to interpret. We assess basal heterogeneity across Thwaites Glacier by comparing RES returns to a radar backscattering simulator for over 400 km of RES data. The modeled variations in bed returned power exhibited a strong correlation with actual RES data in 40% of our simulated flight segments, which we consider evidence for a relatively homogeneous glacier bed. Other sites (40%) demonstrated improved fit quality when hydrology or substrate transitions were introduced in the bed material model. The remaining simulated segments (20%) were diagnosed as having more complex basal heterogeneity. The spatial distribution of complex heterogeneity appears to coincide with asymmetric patterns in the RES specularity content, which has been interpreted in previous studies as a signature for channelized hydrology. Conversely, the homogeneous substrate locations coincide with areas of fast-moving ice in western Thwaites. Our simulation method can isolate power variations induced by material heterogeneity vs topography, which is an important limitation of existing RES analysis methods.

Antarctic glaciology↗
DOE OSTI2020

Temporal flow variations interact with spatial physical heterogeneity to impact solute transport in managed river corridors

The interactions between surface water and groundwater in river corridors lead to temporal fluctuations in subsurface water fluxes which have a critical role on solute transport dynamics. Here, we develop a framework to analyze the relative impacts of different temporal frequencies of the flow field in a spatially heterogeneous aquifer on solute transport. Our analysis indicates that the advection-dispersion equation behaves as a low-pass filter by wiping out the effect of high-frequency velocity fluctuations on the first two spatial moments of the solute plume, namely its center of mass and spreading. The concepts discussed in the theoretical analysis are then applied to understand solute transport dynamics at the 300 Area of the Hanford site (USA) adjacent to the Columbia River. We examine the temporal behavior of the solute plume's spatial moments for different temporal frequencies utilizing geostatistical parameters estimated in the 300 Area. Due to the proximity to the Columbia river, groundwater fluxes at the Hanford site are highly dynamic resulting in a large range of characteristic temporal frequencies. Nonetheless, similar to the theoretical analysis, our results show that the effect of high-frequency fluctuations is filtered, with most of the solute transport dynamics being controlled by fluctuations characterized by a large characteristic period.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2016

Observational Constraints on the Identification of Shallow Lunar Magmatism: Insights from Floor-Fractured Craters

Floor-fractured craters are a class of lunar crater hypothesized to form in response to the emplacement of a shallow magmatic intrusion beneath the crater floor. The emplacement of a shallow magmatic body should result in a positive Bouguer anomaly relative to unaltered complex craters, a signal which is observed for the average Bouguer anomaly interior to the crater walls. We observe the Bouguer anomaly of floor-fractured craters on an individual basis using the unfiltered Bouguer gravity solution from GRAIL and also a degree 100-600 band-filtered Bouguer gravity solution. The low-magnitude of anomalies arising from shallow magmatic intrusions makes identification using unfiltered Bouguer gravity solutions inconclusive. The observed anomalies in the degree 100-600 Bouguer gravity solution are spatially heterogeneous, although there is spatial correlation between volcanic surface morphologies and positive Bouguer anomalies. We interpret these observations to mean that the spatial heterogeneity observed in the Bouguer signal is the result of variable degrees of magmatic degassing within the intrusions.

Jozwiak, L. M.↗
NASA NTRS2017

Daily Ambient Air Pollution Metrics for Five Cities: Evaluation of Data Fusion-Based Estimates and Uncertainties

Spatiotemporal characterization of ambient air pollutant concentrations is increasingly relying on the combination of observations and air quality models to provide well-constrained, spatially and temporally complete pollutant concentration fields. Air quality models, in particular, are attractive, as they characterize the emissions, meteorological, and physiochemical process linkages explicitly while providing continuous spatial structure. However, such modeling is computationally intensive and has biases. The limitations of spatially sparse and temporally incomplete observations can be overcome by blending the data with estimates from a physically and chemically coherent model, driven by emissions and meteorological inputs. We recently developed a data fusion method that blends ambient ground observations and chemical transport-modeled (CTM) data to estimate daily, spatially resolved pollutant concentrations and associatedcorrelations. In this study, we assess the ability of the data fusion method to produce daily metrics (i.e., 1-hr max, 8-hr max, and 24-hr average) of ambient air pollution that capture spatiotemporal air pollution trends for 12 pollutants (CO, NO2, NOx, O3, SO2, PM (sub10), PM (sub 2.5), and five PM (sub 2.5) components) across five metropolitan areas (Atlanta, Birmingham, Dallas, Pittsburgh, and St. Louis), from 2002 to 2008. Three sets of comparisons are performed: (1) the CTM concentrations are evaluated for each pollutant and metropolitan domain, (2) the data fusion concentrations are compared with the monitor data, (3) a comprehensive cross-validation analysis against observed data evaluates the quality of the data fusion model simulations across multiple metropolitan domains. The resulting daily spatial field estimates of air pollutant concentrations and uncertainties are not only consistent with observations, emissions, andmeteorology, but substantially improve CTM-derived results for nearly all pollutants and all cities, with the exception of NO2 for Birmingham. The greatest improvements occur for O3 and PM (sub 2.5). Squared spatiotemporal correlation coefficients range between simulations and observations determined using cross-validation across all cities for air pollutants of secondary and mixed origins are R-squared equal to 0.88-0.93 (O3), 0.81-0.89 (SO4), 0.67-0.83 (PM (sub 2.5)), 0.52-0.72 (NO3), 0.43-0.80 (NH4), 0.32-0.51 (OC), and 0.14-0.71 (PM (sub 10)). Results for relatively homogeneous pollutants of secondary origin, tend to be better than those for more spatially heterogeneous (larger spatial gradients) pollutants of primary origin (NOx, CO, SO2 and EC). Generally, background concentrations and spatial concentration gradients reflect interurban airshed complexity and the effects of regional transport, whereas daily spatial pattern variability shows intra urban consistency in the fused data. With sufficiently high CTM spatial resolution, traffic-related pollutants exhibit gradual concentration gradients that peak toward the urban centers. Ambient pollutant concentration uncertainty estimates for the fused data are both more accurate and smaller than those for either the observations or the model simulations alone.

spatiotemporal fusion↗
NASA NTRS2017

Evaluation of Satellite Remote Sensing Albedo Retrievals over the Ablation Area of the Southwestern Greenland Ice Sheet

MODerate resolution Imaging Spectroradiometer (MODIS) albedo products have been validated over spatially uniform, snow-covered areas of the Greenland ice sheet (GrIS) using the so-called single 'point-to-pixel' method. This study expands on this methodology by applying a 'multiple-point-to-pixel' method and examination of spatial autocorrelation (here using semivariogram analysis) by using in situ observations, high-resolution World- View-2 (WV-2) surface reflectances, and MODIS Collection V006 daily blue-sky albedo over a spatially heterogeneous surfaces in the lower ablation zone in southwest Greenland. Our results using 232 ground-based samples within two MODIS pixels, one being more spatial heterogeneous than the other, show little difference in accuracy among narrow and broad band albedos (except for Band 2). Within the more homogenous pixel area, in situ and MODIS albedos were very close (error varied from −4% to +7%) and within the range of ASD standard errors. The semivariogram analysis revealed that the minimum observational footprint needed for a spatially representative sample is 30 m. In contrast, over the more spatially heterogeneous surface pixel, a minimum footprint size was not quantifiable due to spatial autocorrelation, and far exceeds the effective resolution of the MODIS retrievals. Over the high spatial heterogeneity surface pixel, MODIS is lower than ground measurements by 4-7%, partly due to a known in situ undersampling of darker surfaces that often are impassable by foot (e.g., meltwater features and shadowing effects over crevasses). Despite the sampling issue, our analysis errors are very close to the stated general accuracy of the MODIS product of 5%. Thus, our study suggests that the MODIS albedo product performs well in a very heterogeneous, low-albedo, area of the ice sheet ablation zone. Furthermore, we demonstrate that single 'point-to-pixel' methods alone are insufficient in characterizing and validating the variation of surface albedo displayed in the lower ablation area. This is true because the distribution of in situ data deviations from MODIS albedo show a substantial range, with the average values for the 10th and 90th percentiles being −0.30 and 0.43 across all bands. Thus, if only single point is taken for ground validation, and is randomly selected from either distribution tails, the error would appear to be considerable. Given the need for multiple in-situ points, concurrent albedo measurements derived from existing AWSs, (low-flying vehicles (airborne or unmanned) and high-resolution imagery (WV-2)) are needed to resolve high sub-pixel variability in the ablation zone, and thus, further improve our characterization of Greenland's surface albedo.

Ablation zone↗
DOE OSTI2022

Unstable turbulent channel flow response to spanwise-heterogeneous heat fluxes: Prandtl's secondary flow of the third kind

Turbulent secondary flows are defined as Prandtl's secondary flow of the first or second kind, the former produced by stretching and/or tilting of vorticity, the latter produced via spatial heterogeneity of Reynolds stresses. Both mechanisms are instantaneously active within inertia-dominated wall turbulence; Reynolds stress spatial heterogeneity is required for Reynolds-averaged secondary flows. Spanwise-variable surface roughness can induce turbulent stress spatial heterogeneity in the spanwise–wall-normal plane and provide sustenance for streamwise-aligned mean secondary flows. Herein, we demonstrate that turbulent secondary flows can also be sustained by spanwise variability in the surface heat flux in unstably stratified turbulent channels, defined hereafter as Prandtl's secondary flow of the third kind. Support for this mechanism is established with scaling arguments, while large-eddy simulation is used to model inertia-dominated channel turbulence responding to a lower boundary with uniform aerodynamic/hydrodynamic roughness but spanwise-variable surface heat flux. Transport equations for streamwise vorticity and turbulent kinetic energy, k, outline the conditions needed for third-kind production: shear and buoyancy production over the elevated heat flux regions necessitates lateral entrainment of low- k fluid, inducing mean counter-rotating secondary cells aligned such that upwelling and downwelling occur over the high and low heat flux regions, respectively. Buoyancy-driven production of k alters aggregate flow response and thus is a distinctly different mechanism responsible for sustenance of secondary flows.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Probing the Influence of Multiscale Heterogeneity on Effective Properties of Graphite Electrodes

Graphite electrodes in the lithium-ion battery exhibit various particle shapes, including spherical and platelet morphologies, which influence structural and electrochemical characteristics. It is well established that porous structures exhibit spatial heterogeneity, and the particle morphology can influence transport properties. The impact of the particle morphology on the heterogeneity and anisotropy of geometric and transport properties has not been previously studied. Herein, this study characterizes the spatial heterogeneities of 18 graphite electrodes at multiple length scales by calculating and comparing the structural anisotropy, geometric quantities, and transport properties (pore-scale tortuosity and electrical conductivity). We found that the particle morphology and structural anisotropy play an integral role in determining the spatial heterogeneity of directional tortuosity and its dependency on pore-scale heterogeneity. Our analysis reveals that the magnitude of in-plane and through-plane tortuosity difference influences the multiscale heterogeneity in graphite electrodes.

25 ENERGY STORAGE↗
DOE OSTI2023

Stability of Kuramoto networks subject to large and small fluctuations from heterogeneous and spatially correlated noise

Oscillatory networks subjected to noise are broadly used to model physical and technological systems. Due to their nonlinear coupling, such networks typically have multiple stable and unstable states that a network might visit due to noise. In this article, we focus on the assessment of fluctuations resulting from heterogeneous and spatially correlated noise inputs on Kuramoto model networks. We evaluate the typical, small fluctuations near synchronized states and connect the network variance to the overlap between stable modes of synchronization and the input noise covariance. Going beyond small to large fluctuations, we introduce the indicator mode approximation that projects the dynamics onto a single amplitude dimension. Such an approximation allows for estimating rates of fluctuations to saddle instabilities, resulting in phase slips between connected oscillators. Statistics for both regimes are quantified in terms of effective noise amplitudes that are compared and contrasted for several noise models. In conclusion, bridging the gap between small and large fluctuations, we show that a larger network variance does not necessarily lead to higher rates of large fluctuations.

42 ENGINEERING↗
DOE OSTI2022

Detecting Hot Spots of Methane Flux Using Footprint‐Weighted Flux Maps

Abstract In this study, we propose a new technique for mapping the spatial heterogeneity in gas exchange around flux towers using flux footprint modeling and focusing on detecting hot spots of methane (CH 4 ) flux. In the first part of the study, we used a CH 4 release experiment to evaluate three common flux footprint models: the Hsieh model (Hsieh et al., 2000), the Kljun model (Kljun et al., 2015), and the K & M model (Kormann and Meixner, 2001), finding that the K & M model was the most accurate under these conditions. In the second part of the study, we introduce the Footprint‐Weighted Flux Map, a new technique to map spatial heterogeneity in fluxes. Using artificial CH 4 release experiments, natural tracer approaches and flux chambers we mapped the spatial flux heterogeneity, and detected and validated a hot spot of CH 4 flux in a oligohaline restored marsh. Through chamber measurements during the months of April and May, we found that fluxes at the hot spot were on average as high as 6589 ± 7889 nmol m −2 s −1 whereas background flux from the open water were on average 15.2 ± 7.5 nmol m −2 s −1 . This study provides a novel tool to evaluate the spatial heterogeneity of fluxes around eddy‐covariance towers and creates important insights for the interpretation of hot spots of CH 4 flux, paving the way for future studies aiming to understand subsurface biogeochemical processes and the microbiological conditions that lead to the occurrence of hot spots and hot moments of CH 4 flux.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Ebullition dominates methane fluxes from the water surface across different ecohydrological patches in a temperate freshwater marsh at the end of the growing season

Measurements of the spatial heterogeneity of methane fluxes in wetlands are critical to better understand and predict methane emissions at the ecosystem scale. However, the within-wetland spatial heterogeneity of fluxes is rarely assessed. Here, we use a spatially balanced rapid chamber-based survey of methane at different ecohydrological patches within a temperate freshwater marsh. We measured fluxes exclusively from the water surface without including vegetation. We further used the data from chamber measurements to partition diffusive and ebullitive fluxes. Three ecohydrological patches were distinguishable in the marsh, defined by the type and presence/absence of vegetation. Here, these patches were emergent vegetation, floating-leaved, and open water. Net methane fluxes from the water surface (diffusion plus ebullition) in emergent vegetation patches were larger than in the floating-leaved vegetation and open water patches (p < 0.05). Diffusive fluxes, representing a sizable smaller fraction of net fluxes, were larger in vegetated than in unvegetated patches (p < 0.05), while ebullitive fluxes mirrored the magnitude and differences observed in the net fluxes.Moreover, pooled net and ebullitive fluxes across patches (but not diffusive fluxes) were negatively correlated with water levels, the primary variable affecting patch distribution. Altogether, our results indicate that the differences among ecohydrological patches are driven by ebullition, ultimately highlighting challenges faced by scientists and practitioners in the field and modelers seeking to improve the predictability and resolution of wetland biogeochemical models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Learning heterogeneous reaction kinetics from X-ray videos pixel by pixel

Reaction rates at spatially heterogeneous, unstable interfaces are notoriously difficult to quantify, yet are essential in engineering many chemical systems, such as batteries and electrocatalysts. Experimental characterizations of such materials by operando microscopy produce rich image datasets, but data-driven methods to learn physics from these images are still lacking because of the complex coupling of reaction kinetics, surface chemistry and phase separation. Here we show that heterogeneous reaction kinetics can be learned from in situ scanning transmission X-ray microscopy (STXM) images of carbon-coated lithium iron phosphate (LFP) nanoparticles. Combining a large dataset of STXM images with a thermodynamically consistent electrochemical phase-field model, partial differential equation (PDE)-constrained optimization and uncertainty quantification, we extract the free-energy landscape and reaction kinetics and verify their consistency with theoretical models. We also simultaneously learn the spatial heterogeneity of the reaction rate, which closely matches the carbon-coating thickness profiles obtained through Auger electron microscopy (AEM). Across 180,000 image pixels, the mean discrepancy with the learned model is remarkably small (<7%) and comparable with experimental noise. Our results open the possibility of learning nonequilibrium material properties beyond the reach of traditional experimental methods and offer a new non-destructive technique for characterizing and optimizing heterogeneous reactive surfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Learning heterogeneous reaction kinetics from X-ray movies pixel-by-pixel

Reaction rates at spatially heterogeneous, unstable interfaces are notoriously difficult to quantify, yet are essential in engineering many chemical systems, such as batteries 1 and electrocatalysts 2. Experimental characterizations of such materials by operando microscopy produce rich image datasets 3–6, but data-driven methods to learn physics from these images are still lacking because of the complex coupling of reaction kinetics, surface chemistry and phase separation 7. Here we show that heterogeneous reaction kinetics can be learned from in situ scanning transmission X-ray microscopy (STXM) images of carbon-coated lithium iron phosphate (LFP) nanoparticles. Combining a large dataset of STXM images with a thermodynamically consistent electrochemical phase-field model, partial differential equation (PDE)-constrained optimization and uncertainty quantification, we extract the free-energy landscape and reaction kinetics and verify their consistency with theoretical models. We also simultaneously learn the spatial heterogeneity of the reaction rate, which closely matches the carbon-coating thickness profiles obtained through Auger electron microscopy (AEM). Across 180,000 image pixels, the mean discrepancy with the learned model is remarkably small (<7%) and comparable with experimental noise. Our results open the possibility of learning nonequilibrium material properties beyond the reach of traditional experimental methods and offer a new non-destructive technique for characterizing and optimizing heterogeneous reactive surfaces.

Chueh, William↗
DOE OSTI2025

Spatial‐Uniformity–Driven Bayesian Optimization for Rapid Development of Printed Perovskite Solar Cells

Printed metal halide perovskites can enable rapid, roll-to-roll manufacturing of a broad class of optoelectronics—flexible solar cells and imagers among them—while promising cost and speed advantages over incumbent silicon. However, though current methods offer high throughput and patterning capabilities, perovskite films’ spatial heterogeneity remains a challenge for large-area devices. Here, a spatial-uniformity-driven Bayesian optimization (BO) approach is leveraged to accelerate the development of printed perovskite solar cells and improve large-area device performance. Using a BO surrogate model, a 6D design space of ink chemistry and printing physics is explored via extensive iterative experimentation (≈100) informed by an objective function capturing spatial photoluminescence (PL) variance. It is discovered that optimizing for uniformity drives rapid advances in photovoltaic performance, yielding ≈20% power conversion efficiency (PCE) for small area (0.134 cm 2 ) devices and > 16% for large area (1 cm 2 ) devices. This machine-learning approach simultaneously enables rheological comparison of ink formulations that accelerate the leveling of Saffman-Taylor artifacts and improve film uniformity. Here, this showcases uniformity-driven BO as an efficient approach for uncovering the key printing physics and mitigating spatial heterogeneity to enable device scaling beyond small cell areas.

14 SOLAR ENERGY↗