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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Cumulative Spatial Impact Layers: A Novel Multivariate Spatio-Temporal Analytical Summarization Tool

Scientific inquiry often requires analysis of multiple spatio-temporal datasets, ranging in type and size, using complex multi-step processes demanding an understanding of GIS theory and software. Cumulative Spatial Impact Layers (CSIL) is a GIS-based tool that summarizes spatio-temporal datasets based on overlapping features and attributes. Leveraging a recursive quadtree method, and applying multiple additive frameworks, the CSIL tool allows users to analyze raster and vector datasets by calculating data, record, or attribute density. Providing an efficient and robust method for summarizing disparate, multi-format, multi-source geospatial data, CSIL addresses the need for a new integration approach and resulting geospatial product. The built-in flexibility of the CSIL tool allows users to answer a range of spatially-driven questions. Example applications are provided in this paper to illustrate the versatility and variety of uses for this CSIL tool and method. Use cases include addressing regulatory decision-making needs, economic modeling, and resource management. Performance reviews for each use case are also presented, demonstrating how CSILs provides a more efficient and robust approach to assess a range of multivariate spatial data for a variety of uses.

58 GEOSCIENCES↗
DOE OSTI2025

Geospatial analysis of preterm and small-for-gestational age births in Washington D.C.

Background: This study is based on the recognition that adverse pregnancy outcomes significantly affect maternal and infant health, leading to increased morbidity and mortality. These outcomes are shaped by a complex interplay of individual-level factors—like maternal age and education—and community-level influences, including socio-economic status and access to healthcare. Understanding these determinants is crucial for developing effective public health strategies, especially for marginalized populations, by identifying high-risk areas and informing targeted interventions that address both individual and structural barriers. Methods: We utilized geospatial analysis to explore the association between individual- and community-level factors and adverse pregnancy outcomes, specifically preterm birth (PTB) and small-for-gestational-age (SGA) birthweight in Washington, D.C. We used Empirical Bayes smoothing methods to calculate rates of adverse birth outcomes from 2010 to 2018 at the U.S. Census tract–level. Spatial scan statistics were used to investigate if adverse birth outcomes clustered in specific areas. ANOVA tests were conducted for individual- and community-level factors within identified clusters. Results: Spatial analysis identified significant high-risk clusters for PTB and SGA infants primarily in southeastern Washington, D.C., particularly in Wards 7 and 8. Individuals residing within these clusters experienced a 47% increased risk of PTB (RR = 1.467) and a 56% increased risk of SGA (RR = 1.560) compared to those outside clusters. Space–time analysis revealed temporal variation, with PTB clusters persisting from 2011 to 2014 and SGA clusters extending through 2017. Compared to low-risk clusters, high-risk clusters had younger birthing individuals (mean age ~26.5 vs. ~33 years), lower maternal college degree attainment (~20% vs. ~80%), higher rates of late or no prenatal care (~16% vs. 11%), and increased prevalence of smoking and hypertension (all P < 0.001). Community-level indicators showed lower median household incomes ($\$40,000$ vs. ~$\$105,000$), greater poverty (~16% vs. ~7% below $\$10,000$/year), higher public assistance use (~32% vs. ~5%), and reduced healthcare access (greater distances to emergency and specialty care) in high-risk areas (all P < 0.001). Neighborhood deprivation indices were significantly elevated, commutes were longer, and population density was lower in these clusters. These findings highlight that adverse birth outcomes cluster in neighborhoods with pronounced socioeconomic and health disparities. Conclusion: High-risk birth clusters highlight intertwined factors: individual, socio-economic, and geographic. Addressing these requires comprehensive interventions focusing on social and structural determinants of health.

Birth outcomes↗
DOE OSTI2016

Chapter 10: Experimental Methods for the Determination of Parameters. In the book Multiphase Catalytic Reactors: Theory, Design, Manufacturing, and Applications.

The determination of kinetic parameters is a key element in catalyst research and multiphase catalytic process development. In this chapter, the experimental methods used to determine kinetic parameters, the nature of the parameters, and the areas of application and advantages of the different experimental approaches are discussed. Emphasis is placed on transient techniques and methods that provide intrinsic kinetic parameters, i.e., parameters that can be directly linked to the surface composition/structure of a heterogeneous catalyst.

02 PETROLEUM↗
DOE OSTI2017

Computing and visualizing time-varying merge trees for high-dimensional data

We introduce a new method that identifies and tracks features in arbitrary dimensions using the merge tree -- a structure for identifying topological features based on thresholding in scalar fields. This method analyzes the evolution of features of the function by tracking changes in the merge tree and relates features by matching subtrees between consecutive time steps. Using the time-varying merge tree, we present a structural visualization of the changing function that illustrates both features and their temporal evolution. We demonstrate the utility of our approach by applying it to temporal cluster analysis of high-dimensional point clouds.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Alkali-silica reaction products and cracks: X-ray micro-tomography-based analysis of their spatial-temporal evolution at a mesoscale

In this study, we propose a laboratory-scale methodology, based on X-ray micro-tomography and caesium (Cs) as a contrast agent, to advance the understanding of cracking due to alkali-silica reaction (ASR) in concrete. The methodology allows achieving a completely non-destructive and time-lapse characterization of the spatial-temporal patterns of both the cracks and the ASR products. While Cs addition slightly accelerated the ASR kinetics, the crack patterns, with and without Cs addition, were statistically equivalent. Cracks with ASR products appeared first in the aggregates, close to the interface with the cement paste. They propagated afterwards towards the aggregates interior. Some products were then extruded for several mm into air voids and cracks in the cement paste. This process suggests that, in the early stage, the ASR products may be a low-viscosity gel that can flow away from the source aggregate and may settle later elsewhere as a rigid phase, upon calcium uptake.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Lowering the barrier to access information-rich transient kinetic data for machine learning methods

Transient kinetic data contain a wealth of information about intrinsic features of a catalyst as well as the reaction mechanism. Currently, high volume transient data is underutilized, and data science methods could both increase the value of information that can be extracted from this data, integrate experimental with theoretical data sources, and accelerate the pace of catalyst technology advancement. Transient kinetic characterizations with simple probe molecules exhibiting reversible adsorption, irreversible adsorption and bulk-surface diffusion are presented as training components for similar experiments with more complex surface reactions. In conclusion, by increasing the availability and accessibility of transient kinetic data through details of its structure and acquisition, we aim to decrease the barrier for data scientists to apply machine learning methods to this valuable data source.

Catalysis↗
DOE OSTI2025

High entropy alloys as catalysts: A focused review

A brief literature review of recent experimental and computational efforts on the use of high entropy alloys (HEAs) as catalysts is presented, while also sharing some perspectives and future insights. To fully broach the vast compositional possibilities of HEA materials, integrating computational modeling with high-throughput experimental synthesis and validation is necessary to accelerate their design and development. Once identified, specific HEAs can be a class of materials for the next generation of catalysts when addressing global challenges related to energy independence, commodity chemical production, environmental remediation, abating emissions, and modernized domestic supply chain resilience.

42 - ENGINEERING↗
DOE OSTI2019

Response of deep aquifers to climate variability

There is a general agreement that deep aquifers experience significant lag time in their response to climatic variations. Analysis of Temporal Gravity Recovery and Climate Experiment (GRACE), Soil Moisture and Ocean Salinity mission (SMOS), satellite altimetry, stable isotopic composition of groundwater, and precipitation and static global geopotential models over the Nubian Sandstone Aquifer System (NSAS) revealed rapid aquifer response to climate variability. Findings include: (1) The recharge areas of the NSAS (Northern Sudan Platform subbasin) witnessed a dry period (2002-2012), where average annual precipitation (AAP) was modest (85 mm) followed by a wet period (2013-2016; AAP: 107 mm), and during both periods the APP remained negligible (<10 mm) over the northern parts of the NSAS (Dakhla subbasin); (2) the secular trends in terrestrial water storage (TWS) over the Dakhla subbasin were estimated at -3.8 ± 1.3 mm/yr and + 7.8 ± 1 mm/yr for the dry and wet periods, respectively; (3) spatial variations in TWS values and phase are consistent with rapid groundwater flow from the Northern Sudan Platform subbasin and Lake Nasser towards the Dakhla subbasin during the wet period and from the lake during the dry period; and (4) networks of densely fractured and karstified bedrocks provide preferential pathways for groundwater flow. The proposed model is supported by (1) rapid response in groundwater levels in distant wells (>280 km from source areas) and in soil moisture content in areas with shallow (<2 m) groundwater levels to fluctuations in Lake Nasser surface water, and (2) the isotopic composition (O, H) of groundwater along the preferred pathways, consistent with mixing of enriched (Lake Nasser water or precipitation over Sudan) and depleted (NSAS fossil water) end-members. Here, findings provide new insights into the response of large, deep aquifers to climate variability and address the sustainability of the NSAS and similar fossil aquifers worldwide.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Fermi-Based Kinetic Model for the Sabatier Reaction: Sabatier Principle and Beyond It

The CO 2 methanation reaction (aka the Sabatier reaction) is one of the important carbon utilization technologies to reduce atmospheric greenhouse gases. In this study, kinetic modeling of the Sabatier reaction proceeding via the CO route has been presented by considering weak and strong chemisorption concepts rooted in electronic theory. Based on the single-route mechanism of the Sabatier reaction, the dependence of the reaction rate on the position of the catalyst Fermi level with respect to the antibonding states of the reagent (CO 2 ) and the product (CH 4 ), is demonstrated with the classic Sabatier volcano-shape. Furthermore, the model was applied to explain experimental results of reaction rates for Ni- and Ru-based catalytic systems and to understand origin of enhancement of turnover frequencies established for dynamic catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

CRAGE-RB-PI-seq reveals transcriptional dynamics of plant-associated bacteria during root colonization

Plant roots release a wide array of metabolites into the rhizosphere, shaping microbial communities and their functions. While metagenomics has expanded our understanding of these communities, little is known about the physiology of their members in host environments. Transcriptome analysis via RNA sequencing is a common approach to learning more, but its use has been challenging because of low bacterial biomass and interference from plant RNA. To overcome this, we developed a randomly-barcoded promoter-library insertion sequencing (RB-PI-seq) combined with chassis-independent recombinase-assisted genome engineering (CRAGE). Using Pseudomonas simiae WCS417 as a model rhizobacterium, this method enabled targeted amplification of barcoded transcripts, bypassing plant RNA interference and allowing measurement of thousands of promoter activities during Arabidopsis root colonization. Our analysis revealed temporally resolved transcriptional regulation, including those associated with cell growth, chemotaxis, plant immune suppression, biofilm formation, and stress responses, reflecting the coordinated physiological adaptation to the root environment. Additionally, we discovered that transcriptional activation of xanthine dehydrogenase and a lysozyme inhibitor is crucial for evading plant immune systems. This framework is scalable to other bacterial species and provides new opportunities for understanding rhizobacterial gene regulation in native environments.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Kinetic theory of the filamentation instability in a collisional current-driven plasma with nonextensive distribution

The evolution of filamentation instability in a weakly ionized current-carrying plasma with nonextensive distribution was studied in the diffusion frequency region, taking into account the effects of electron-neutral collisions. Using the kinetic theory, Lorentz transformation formulas, and Bhatnagar-Gross-Krook collision model, the generalized dielectric permittivity functions of this plasma system were achieved. By obtaining the dispersion relation of low-frequency waves, the possibility of filamentation instability and its growth rate were investigated. It was shown that collisions can increase the maximum growth rate of instability. The analysis of temporal evolution of filamentation instability revealed that the growth rate of instability increased by increasing the q-parameter and electron drift velocity. Finally, the results of Maxwellian and q-nonextensive velocity distributions were compared and discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Gallium oxide (Ga 2 O 3 ) energy dependent scintillation response to fast neutrons and flash gamma-rays

Gallium oxide is a newly emerged ultrawide bandgap (4.9 eV) semiconductor that is suitable as a combined electronics and radiation detection platform. We have experimentally demonstrated fast neutron and gamma-ray scintillation from Czochralski-grown β-Ga 2 O 3 in a recent series (October 2023) of experiments at the unmoderated pulsed neutron spallation source located at the Los Alamos Neutron Science Center. Using the neutron time-of-flight (TOF) technique and a fast-gated intensified CCD camera, we observed energy-dependent neutron scintillation for neutron energies ranging from 1 to 400 MeV, including the 14.1 MeV neutron energy relevant to D–T fusion. Neutron flux is quantified and calibrated by cascading the scintillator after the fission chamber, enabling a detailed analysis of temporal and energy-dependent characteristics of the scintillation events. Further, a pronounced scintillation signal from the spallation gamma flash with a temporal full width of half maximum of ~4 ns is indicative of the material’s rapid response. Neutron energy dependent scintillation is observed using the TOF method at a 22.6-m distance from the neutron source. These results highlight the possibility of developing a Ga 2 O 3 based fusion neutron diagnostic platform integrated with both scintillation and electronics functions on the integrated chip scale.

47 OTHER INSTRUMENTATION↗
DOE OSTI2018

Comparative analysis of 2D spatio-temporal visualisation techniques for the pulsed THz-radiation field using an electro-optic crystal

Two 2D techniques for visualising the field of pulsed THz radiation (‘shadow’ and ‘interferometric’), which are based on the linear electro-optical effect with application of a ZnTe detector crystal 1 × 1 cm in size, are compared. The noise level and dynamic range for the aforementioned techniques are analysed and their applicability limits are discussed. (thz radiation)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

THE OPTICAL WIND LINE VARIABILITY OF η CARINAE DURING THE 2009.0 EVENT

We report on high-resolution spectroscopy of the 2009.0 spectroscopic event of η Carinae collected via SMARTS observations using the CTIO 1.5 m telescope and echelle spectrograph. Our observations were made almost every night over a two-month interval around the photometric minimum of η Car associated with the periastron passage of a hot companion. The photoionizing flux of the companion and heating related to colliding winds causes large changes in the wind properties of the massive primary star. Here we present an analysis of temporal variations in a sample of spectral lines that are clearly formed in the wind of the primary star. These lines are affected by a changing illumination of the flux of the secondary star during the periastron passage. We document the sudden onset of blueshifted absorption that occurred in most of the lines near or slightly after periastron, and we argue that these absorption components are seen when we view the relatively undisturbed wind of the foreground primary star. We present time series measurements of the net equivalent width of the wind lines and of the radial velocities of the absorption trough minima and the emission peak midpoints. Most lines decrease in emission strength around periastron, and those high excitation lines formed close to the primary exhibit a red-ward velocity excursion. We show how these trends can be explained using an illuminated hemisphere model that is based on the idea that the emission originates primarily from the side of the primary facing the hot companion.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Wireless Sensor Networks for Improved Snow Water Equivalent and Runoff Estimates

We leverage the frontiers of the Internet of Things technology in a recently developed end-to-end wireless sensor network (WSN) system that samples, collects, stores, and displays mountain hydrology measurements in near real-time. At the core of the system lies an ultra-low power, radio channel-hoping, and self-organizing mesh that allows for remote autonomous sampling of snow. Such properties, combined with a rugged weather-sealed design of the devices and multi-level data replication, provides reliable real-time data at spatial and temporal scales previously impractical to achieve in mountain environments. The system was deployed at three 1 km 2 sites across the North Fork of the Feather River basin with a cluster of 12 sensor nodes for each location. Measurements show that existing operational autonomous systems are non-representative spatially, with biases that can reach up to 50%. A comparison between a wet and dry year showed that snow depths exhibit strong multi-scale inter-year spatial stationarity with major rank conservation. Temporally dense analysis using elastic net regression shows that dominant features at the sub-km 2 scale are site-dependent and differ from the watershed scale. Newly introduced explanatory variables, based on the nearest neighbor with a Landsat assimilated historical product, consistently explained up to 90% of the variance in the watershed-scale SWE for both years. At two WSN sites, lagged cross-correlation of snowmelt with stream flow measurements showed a significant improvement of up to 100% compared with existing systems, suggesting that WSNs can be instrumental in improving runoff forecasting and water management.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Connect the Dots: In Situ 4-D Seismic Monitoring of CO 2 Storage With Spatio-Temporal CNNs

4-D seismic imaging has been widely used in CO 2 sequestration projects to monitor the fluid flow in the volumetric subsurface region that is not sampled by wells. Ideally, real-time monitoring and near-future forecasting would provide site operators with great insights to understand the dynamics of the subsurface reservoir and assess any potential risks. However, due to obstacles such as high deployment cost, availability of acquisition equipment, exclusion zones around surface structures, only very sparse seismic imaging data can be obtained during monitoring. That leads to an unavoidable and growing knowledge gap over time. The operator needs to understand the fluid flow throughout the project lifetime and the seismic data are only available at a limited number of times. This is insufficient for understanding reservoir behavior. To overcome those challenges, we have developed spatio-temporal neural-network-based models that can produce high-fidelity interpolated or extrapolated images effectively and efficiently. Specifically, our models are built on an autoencoder, and incorporate the long short-term memory (LSTM) structure with a new loss function regularized by optical flow. We validate the performance of our models using real 4-D post-stack seismic imaging data acquired at the Sleipner CO 2 sequestration field. We employ two different strategies in evaluating our models. Numerically, we compare our models with different baseline approaches using classic pixel-based metrics. We also conduct a blind survey and collect a total of 20 responses from domain experts to evaluate the quality of data generated by our models. Finally, via both numerical and expert evaluation, we conclude that our models can produce high-quality 2-D/3-D seismic imaging data at a reasonable cost, offering the possibility of real-time monitoring or even near-future forecasting of the CO 2 storage reservoir.

4-D seismic imaging↗
DOE OSTI2015

TU-AB-BRA-12: Impact of Image Registration Algorithms On the Prediction of Pathological Response with Radiomic Textures

Purpose: Tumor regions-of-interest (ROI) can be propagated from the pre-onto the post-treatment PET/CT images using image registration of their CT counterparts, providing an automatic way to compute texture features on longitudinal scans. This exploratory study assessed the impact of image registration algorithms on textures to predict pathological response. Methods: Forty-six esophageal cancer patients (1 tumor/patient) underwent PET/CT scans before and after chemoradiotherapy. Patients were classified into responders and non-responders after the surgery. Physician-defined tumor ROIs on pre-treatment PET were propagated onto the post-treatment PET using rigid and ten deformable registration algorithms. One co-occurrence, two run-length and size zone matrix textures were computed within all ROIs. The relative difference of each texture at different treatment time-points was used to predict the pathologic responders. Their predictive value was assessed using the area under the receiver-operating-characteristic curve (AUC). Propagated ROIs and texture quantification resulting from different algorithms were compared using overlap volume (OV) and coefficient of variation (CoV), respectively. Results: Tumor volumes were better captured by ROIs propagated by deformable rather than the rigid registration. The OV between rigidly and deformably propagated ROIs were 69%. The deformably propagated ROIs were found to be similar (OV∼80%) except for fast-demons (OV∼60%). Rigidly propagated ROIs with run-length matrix textures failed to significantly differentiate between responders and non-responders (AUC=0.65, p=0.07), while the differentiation was significant with other textures (AUC=0.69–0.72, p<0.03). Among the deformable algorithms, fast-demons was the least predictive (AUC=0.68–0.71, p<0.04). ROIs propagated by all other deformable algorithms with any texture significantly predicted pathologic responders (AUC=0.71–0.78, p<0.01) despite substantial variation in texture quantification (CoV>70%). Conclusion: Propagated ROIs using deformable registration for all textures can lead to accurate prediction of pathologic response, potentially expediting the temporal texture analysis process. However, rigid and fast-demons deformable algorithms are not recommended due to their inferior performance compared to other algorithms. The project was supported in part by a Kaye Scholar Award.

60 APPLIED LIFE SCIENCES↗