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At least 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Fracture Network Quantification during CO2 Injection

This is the conference paper accompanying an oral presentation at the ARMA 2025 (59th US Rock Mechanics/Geomechanics Symposium) Conference held in Santa Fe, New Mexico, June 8-11, 2025. Accurate mapping and quantification of these networks are essential to ensure the integrity of CO2 storage reservoirs, understand and reduce potential leakage, and maintain long-term environmental safety. This study presents a novel machine learning-driven approach, integrated with geomechanical analysis, to quantify fracture networks and assess their spatial distribution during CO2 injection. This paper combines microseismic monitoring data with principles of hydraulic diffusivity and geomechanical analysis to characterize reservoir scale fracture network. The novelty of our approach lies in its capacity to assimilate time-dependent pressure data and microseismicity into a cohesive framework, which not only identifies microseismic triggering fronts but also tracks fracture distribution during active injection. Besides, leveraging image log data and analysis our approach also provides another angle of the insights to solidate the fracture networks understanding and geomechanical impacts. Key results from our study include the detection of over 100 distinct fracture clusters across the injection site, with fracture orientations strongly correlated with the prevailing in-situ stress field.

CO2 storage and sequestration↗
DOE OSTI2026

Dynamical Downscaling of Earth System Model Data for Energy System Analysis

Assessing energy resources (e.g., solar, wind, and hydro) under future scenarios requires datasets with sufficient spatial and temporal detail to capture variability and extreme events. While global-scale Earth System Model (ESM) projections are widely used, their coarse resolution limits direct application to regional energy system analyses. Dynamical downscaling offers a robust approach to generate physically consistent, fine-scale datasets that better represent local atmospheric processes impacting energy resources. In this work, we present a two-stage approach for producing high-resolution historical and future projections over the contiguous United States (CONUS). First, we optimize the Weather Research and Forecasting (WRF) model configuration for energy-relevant variables - solar irradiance, wind speed, and precipitation - by conducting ERA5-driven simulations at 8-km and 28-km resolution. Multiple physics schemes and model configurations within the WRF are evaluated against observational datasets including the National Solar Radiation Database (NSRDB), the Parameter-elevation Regressions on Independent Slopes Model (PRISM), and the Stage IV multi-radar/multi-sensor precipitation product for the CONUS domain. Using the best-performing configuration, we dynamically downscale MPI-ESM1-2-HR simulations for 2000-2060 under SSP2-4.5 and SSP5-8.5 scenarios at 4-km spatial and hourly temporal resolution. This presentation will provide a comprehensive analysis of the results from multiple numerical experiments and high-resolution ESM projections. In addition, we will discuss potential applications of our high-resolution datasets within the energy sector and outline future research avenues dedicated to evaluating how extreme weather events influence system performance and resilience.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Using spatio-temporal graph neural networks to estimate fleet-wide photovoltaic performance degradation patterns

Accurate estimation of photovoltaic (PV) system performance is crucial for determining its feasibility as a power generation technology and financial asset. PV-based energy solutions offer a viable alternative to traditional energy resources due to their superior Levelized Cost of Energy (LCOE). A significant challenge in assessing the LCOE of PV systems lies in understanding the Performance Loss Rate (PLR) for large fleets of PV systems. Estimating the PLR of PV systems becomes increasingly important in the rapidly growing PV industry. Precise PLR estimation benefits PV users by providing real-time monitoring of PV module performance, while explainable PLR estimation assists PV manufacturers in studying and enhancing the performance of their products. However, traditional PLR estimation methods based on statistical models have notable drawbacks. Firstly, they require user knowledge and decision-making. Secondly, they fail to leverage spatial coherence for fleet-level analysis. Additionally, these methods inherently assume the linearity of degradation, which is not representative of real world degradation. To overcome these challenges, we propose a novel graph deep learning-based decomposition method called the Spatio-Temporal Graph Neural Network for fleet-level PLR estimation (PV-stGNN-PLR). PV-stGNN-PLR decomposes the power timeseries data into aging and fluctuation components, utilizing the aging component to estimate PLR. PV-stGNN-PLR exploits spatial and temporal coherence to derive PLR estimation for all systems in a fleet and imposes flatness and smoothness regularization in loss function to ensure the successful disentanglement between aging and fluctuation. We have evaluated PV-stGNN-PLR on three simulated PV datasets consisting of 100 inverters from 5 sites. Experimental results show that PV-stGNN-PLR obtains a reduction of 33.9% and 35.1% on average in Mean Absolute Percent Error (MAPE) and Euclidean Distance (ED) in PLR degradation pattern estimation compared to the state-of-the-art PLR estimation methods.

14 SOLAR ENERGY↗
NASA NTRS2000

The 3-Dimensional Inner and Outer Structure of Ejecta Around Eta Carinae as Detected by the STIS

The HST/STIS instrument was used successfully to perform a complete mapping of the Homunculus nebula at two wavelength ranges including H-alpha and H-beta with a spectral resolving power of about 5000 and a spatial resolution of 0.1". The individual spectra were merged to synthesize three-dimensional data cubes that contain a set of images of Eta Car with spatial resolution of 0.10 to 0.251, sliced at velocity increment of 10 -- 30 km/s. For the first time this unique method allows us to diagnose the origin of intrinsic narrow emission structure of the nebula with high spatial and velocity resolution. Our initial analysis revealed the inner emission structure appeared to trace an elongated bipolar shell (possibly other shells as well) with a scale size of an arcsecond (i.e., "little homunculus in the Homunculus"). Furthermore, the mapping data cube revealed that the "fan" or "paddle" -- often referred as the source of peculiar blue-shifted intrinsic emissions including the Strontium cloud -- is not the source of intrinsic emissions. The fan is not even a part of the equatorial disk, but is spatially separated from the peculiar emission structure. Indeed we suggest that the fan is a surface of the Northwest lobe, possibly revealed by a blowout of the equatorial disk. We will use a number of visualization techniques (tomographic animations and simple 3-D models) to show these structures. These new results have strong impact upon future numerical modelings of the Homunculus nebula and of understanding of the evolution of the ejecta powered by the central source(s).

Ishibashi, Kazunori↗
NASA NTRS1984

Thermal infrared analysis of volcanic surfaces: Mars and Hawaii

High spatial resolution data from the Viking infrared thermal mapper (IRTM) are used to examine the Tharsis volcanoes which are situated within a vast area of low thermal inertia material very fine particle size or very high porosity, with the volcanoes having the lowest thermal inertias. Thermal infrared images of the 1823 flow on Kilauea's southwest rift zone show lower thermal inertias near the vent area where shelly pahoehoe is common while individual channelized aa flows with abundant broken pahoehoe slabs are higher thermal inertia. The increase in aa flows to the southeast leads to a general trend of increasing thermal inertias from near vent to distal areas. Martian shield volcanoes have thermal inertias equal to or higher than their surrounding plans when atmospheric effects are removed from the data. The general increase in thermal inertias away from the summit calderas is consistent with the trend of the Hawaiian 1823 flow and may be related to changing lava properties away from the summit.

Zimbelman, J. R.↗
NASA NTRS1987

On the spatial structure of the Perseids meteor stream

The analysis of radar observations of the Perseid meteor stream conducted in an ionospherical laboratory in the period from 1964 to 1981 is presented. The Perseids meteor rates were determined by the fluctuation method. Analysis of their hourly distributions showed that the stream maximum position is different for different years, i.e., the stream nodal position is constantly changing. The results of the analysis are presented and discussed.

Andreev, G. V.↗
NASA NTRS2019

Global analysis and forecasts of carbon monoxide on Mars

Spatial and temporal variations in the Martian carbon monoxide (CO) cycle have been investigated through combining Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) retrievals of carbon monoxide mixing ratio and Mars Climate Sounder (MCS) temperature profiles with a Martian global circulation model (GCM) to produce the first global reanalysis of the Martian CO cycle. The reanalysis reduces the root mean square error between the forecast and CRISM CO retrievals by a factor of 2–4, dependent on the time of year. Forecasts initiated from the reanalysis show an improved match to standalone CRISM CO retrievals from northern winter solstice to northern summer solstice, indicating the benefit of data assimilation in simulating the CO abundance. The northern summer solstice CO minimum between 10°S – 50°S in the CRISM CO retrievals is found to be caused by a suppression of CO-enriched air leaking from the Hellas and Argyre basins, and is also strongly influenced by the amount of carbon dioxide condensing at the time. The GCM is the first reported to simulate the local CO minimum however it is weaker in strength, as CO-enriched air is also released northward in the area of Argyre basin in the GCM because of a shifted boundary between the southern polar vortex and mid-latitudes. The reanalysis, as a result of the assimilation of MCS temperature profiles, indicates that the polar vortex boundary is northward of Argyre basin and hence no northerly transport of CO-enriched air should be present over this location. Differences in local CO abundance between the reanalysis and GCM are also evident in spatio-temporal regions where no nearby CRISM CO retrievals are available as a result of alterations in local circulation and the sublimation/condensation of carbon dioxide through the combined assimilation of CRISM CO retrievals alongside MCS temperature profiles, illustrating how constraints can be imposed indirectly on the CO cycle through the powerful technique of data assimilation.

James A. Holmes↗
DOE OSTI2022

Apparatus and amendment of wind turbine blade impact detection and analysis

A multisensory system provides both temporal and spatial coverage capacities for auto-detection of bird collision events. The system includes an apparatus having a first circuitry to capture and store a series of images or video of a blade of a wind turbine; and a memory to store the images from the first circuitry. The apparatus also has one or more sensors to continuously sense vibration of the blade or for acoustic recordings; and a second circuitry to analyze the sensor data stream and/or the series of images or video to identify a cause of the vibration and to trigger the camera(s). A communication interface transmits data from the second circuitry to another device, wherein the second circuitry applies artificial intelligence or machine learning to control sensitivity of the one or more sensors.

Johnston, Matthew↗
DOE OSTI2024

Rapid subsurface analysis of frequency-domain thermoreflectance images with K-means clustering

K-means clustering analysis is applied to frequency-domain thermoreflectance (FDTR) hyperspectral image data to rapidly screen the spatial distribution of thermophysical properties at material interfaces. Performing FDTR while raster scanning a sample consisting of 8.6 μm of doped-silicon (Si) bonded to a doped-Si substrate identifies spatial variation in the subsurface bond quality. Routine thermal analysis at select pixels quantifies this variation in bond quality and allows assignment of bonded, partially bonded, and unbonded regions. Performing this same routine thermal analysis across the entire map, however, becomes too computationally demanding for rapid screening of bond quality. To address this, K-means clustering was used to reduce the dimensionality of the dataset from more than 20 000 pixel spectra to just K = 3 component spectra. The three component spectra were then used to express every pixel in the image through a least-squares minimized linear combination providing continuous interpolation between the components across spatially varying features, e.g., bonded to unbonded transition regions. Fitting the component spectra to the thermal model, thermal properties for each K cluster are extracted and then distributed according to the weighting established by the regressed linear combination. Thermophysical property maps are then constructed and capture significant variation in bond quality over 25 μm length scales. The use of K-means clustering to achieve these thermal property maps results in a 74-fold speed improvement over explicit fitting of every pixel.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Uncertain Spatial Pattern of Future Land Use and Land Cover Change and Its Impacts on Terrestrial Carbon Cycle Over the Arctic–Boreal Region of North America

Land use and land cover change (LULCC) represents a key process of human-Earth system interaction and has profound impacts on terrestrial ecosystem carbon cycling. As a key input for ecosystem models, future gridded LULCC data is typically spatially downscaled from regional LULCC projections by integrated assessment models, such as the Global Change Analysis Model (GCAM). The uncertainty associated with the different spatial downscaling methods and its impacts on the subsequent model projections have been historically ignored and rarely examined. This study investigated this problem using two representative spatial downscaling methods and focused on their impacts on the carbon cycle over the Arctic-Boreal Vulnerability Experiment (ABoVE) domain, where extensive LULCC is expected. Specifically, we used the Future Land Use Simulation model (FLUS) and the Demeter model to generate 0.25° gridded LULCC data (i.e., LULCC FLUS and LULCC Demeter , respectively) with the same input of regional LULCC projections from GCAM, under both the low (i.e., SSP126) and high (i.e., SSP585) greenhouse gas emission scenarios. The two sets of downscaled LULCC were used to drive the Community Land Model version 5 and prognostically simulate the terrestrial carbon cycle dynamics over the 21st century. The results suggest large spatial-temporal differences between LULCC FLUS and LULCC Demeter , and the spatial distributions of the needleleaf evergreen boreal tree, broadleaf deciduous boreal tree, broadleaf deciduous boreal shrub, and C3 arctic grass are particularly different under both SSP126 and SSP585. Additionally, the spatiotemporal differences are larger under SSP126 than SSP585, due to more intensive LULCC under SSP126 than SSP585 from GCAM projection. The differences in LULCC further lead to large discrepancies in the spatial patterns of projected gross primary productivity, ecosystem respiration, and net ecosystem exchange, which represent more than 79% of the contributions of future LULCC in 2100. Additionally, the difference in carbon flux under SSP126 is generally larger than those under SSP585. This study highlights the importance of considering the uncertainties induced by the spatial downscaling process in future LULCC projections and carbon cycle simulations.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1988

Enhanced image products by limb-correction and smoothing of VAS radiance measurements

Limb darkening and brightening affect the GOES satellite's VISSR Atmospheric Sounder instrument's imagery with varying satellite viewing angles and instrument noise; limb effects are also associated with a vertical shift of a wavelength's characteristic weighting function. The radiances in an image can be normalized to a reference zenith angle by limb-correcting the image. An additional undesirable effect is that of instrument noise, which varies as a function of channel characteristics and is greatest for channels sensitive to the upper atmosphere. The statistical structure function analysis method of Hillger et al. (1987) is used to obtain noise levels and optimal spatial averaging distances; the averaging domain size from the analysis is used to produce smoothed images, via a running average technique.

Jones, Andrew S.↗
NASA NTRS1990

Multispectral remote sensing contribution to land surface evaporation

The global water cycle is perhaps the most important of all the biogeochemical cycles and evaporation, which is a significant component of the water cycle, is also linked with the energy and carbon cycles. Long-term evaporation over large areas has generally been computed as the difference of precipitation and river runoff. Analysis of short-term evaporation rate and its spatial pattern, however, is extremely complex, and multispectral remotely sensed data could aid in such analysis. Multispectral data considered here are visible and near-infrared reflectances, infrared surface temperature and the 37 GHz brightness temperatures. These observations are found to be not totally independent of each other. A few of their relationships are established and discussed considering physically-based models.

Choudhury, B. J.↗
NASA NTRS1989

Recent developments in deployment analysis simulation using a multi-body computer code

Deployment is a candidate mode for construction of structural space systems components. By its very nature, deployment is a dynamic event, often involving large angle unfolding of flexible beam members. Validation of proposed designs and conceptual deployment mechanisms is enhanced through analysis. Analysis may be used to determine member loads thus helping to establish deployment rates and deployment control requirements for a given concept. Futhermore, member flexibility, joint free-play, manufacturing tolerances, and imperfections can affect the reliability of deployment. Analyses which include these effects can aid in reducing risks associated with a particular concept. Ground tests which can play a similar role to that of analyses are difficult and expensive to perform. Suspension systems just for vibration ground tests of large space structures in a 1 g environment present many challenges. Suspension of a structure which spatially expands is even more challenging. Analysis validation through experimental confirmation on relatively small simple models would permit analytical extrapolation to larger more complex space structures.

Housner, Jerrold M.↗
DOE OSTI2020

Integrated Biophysical Modeling and Image Analysis: Application to Neuro-Oncology

Central nervous system (CNS) tumors come with vastly heterogeneous histologic, molecular, and radiographic landscapes, rendering their precise characterization challenging. The rapidly growing fields of biophysical modeling and radiomics have shown promise in better characterizing the molecular, spatial, and temporal heterogeneity of tumors. Integrative analysis of CNS tumors, including clinically acquired multi-parametric magnetic resonance imaging (mpMRI) and the inverse problem of calibrating biophysical models to mpMRI data, assists in identifying macroscopic quantifiable tumor patterns of invasion and proliferation, potentially leading to improved (a) detection/segmentation of tumor subregions and (b) computer-aided diagnostic/prognostic/predictive modeling. This article presents a summary of (a) biophysical growth modeling and simulation,(b) inverse problems for model calibration, (c) these models' integration with imaging workflows, and (d) their application to clinically relevant studies. We anticipate that such quantitative integrative analysis may even be beneficial in a future revision of the World Health Organization (WHO) classification for CNS tumors, ultimately improving patient survival prospects.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1987

Cluster analysis of multiple planetary flow regimes

A modified cluster analysis method was developed to identify spatial patterns of planetary flow regimes, and to study transitions between them. This method was applied first to a simple deterministic model and second to Northern Hemisphere (NH) 500 mb data. The dynamical model is governed by the fully-nonlinear, equivalent-barotropic vorticity equation on the sphere. Clusters of point in the model's phase space are associated with either a few persistent or with many transient events. Two stationary clusters have patterns similar to unstable stationary model solutions, zonal, or blocked. Transient clusters of wave trains serve as way stations between the stationary ones. For the NH data, cluster analysis was performed in the subspace of the first seven empirical orthogonal functions (EOFs). Stationary clusters are found in the low-frequency band of more than 10 days, and transient clusters in the bandpass frequency window between 2.5 and 6 days. In the low-frequency band three pairs of clusters determine, respectively, EOFs 1, 2, and 3. They exhibit well-known regional features, such as blocking, the Pacific/North American (PNA) pattern and wave trains. Both model and low-pass data show strong bimodality. Clusters in the bandpass window show wave-train patterns in the two jet exit regions. They are related, as in the model, to transitions between stationary clusters.

Mo, Kingtse↗
NASA NTRS1991

Method for determining stable isotope ratios of dissolved organic carbon in interstitial and other natural marine waters

A procedure is described for the analysis of the stable carbon isotopic composition of dissolved organic carbon (DOC) in natural waters from marine and higher-salinity environments. Rapid (less than 5 min) and complete oxidation of DOC is achieved using a modification of previous photochemical oxidation techniques. The CO2 evolved from DOC oxidation can be collected in less than 10 min for isotopic analysis. The procedure is at present suitable for oxidation and collection of 1-5 micromoles of carbon and has an associated blank of 0.1-0.2 micromole of carbon. Complete photochemical oxidation of DOC standards was demonstrated by quantitative recovery of CO2 as measured manometrically. Isotopic analyses of standards by photochemical and high-temperature sealed-tube combustion methods agreed to within 0.3%. Photochemical oxidation of DOC in a representative sediment pore-water sample was also quantitative, as shown by the excellent agreement between the photochemical and sealed-tube methods. The delta 13C values obtained for pore-water DOC using the two methods of oxidation were identical, suggesting that the modified photochemical method is adequate for the isotopically non-fractionated oxidation of pore-water DOC. The procedure was evaluated through an analysis of DOC in pond and pore waters from a hypersaline microbial mat environment. Concentrations of DOC in the water column over the mat displayed a diel pattern, but the isotopic composition of this DOC remained relatively constant (average delta 13C = -12.4%). Pore-water DOC exhibited a distinct concentration maximum in the mat surface layer, and delta 13C of pore-water DOC was nearly 8% lighter at 1.5-2.0-cm depth than in the mat surface layer (0-0.5-cm depth). These results demonstrate the effectiveness of the method in elucidating differences in DOC concentration and delta 13C over biogeochemically relevant spatial and temporal scales. Carbon isotopic analysis of DOC in natural waters, especially pore waters, should be a useful probe of biogeochemical processes in recent environments.

NASA Discipline Exobiology↗
DOE OSTI2024

Efficient continuous Energy-Multigroup hybrid depletion scheme using the Shift Monte Carlo code. Part I: Energy condensation sensitivity analysis

Monte Carlo (MC) codes coupled to depletion solvers are increasingly used to provide high fidelity fuel cycle modeling capabilities. Here, these coupled depletion-MC tools produce accurate results in general but can experience nonphysical spatial oscillations when time steps are large or when a system’s dominance ratio approaches unity. Two substepping techniques have been developed previously to remedy and dampen these spatial oscillations without needing to reduce step sizes. The first approach relied on higher-order techniques to account for spectral changes within steps (extrapolation and interpolation techniques). The second approach used the first order perturbation (FOP) theory to account for the change in the one-group spatial flux distribution within steps. This paper develops a hybrid depletion methodology which, in a way, combines how the flux is handled in both substepping techniques. Specifically, the multigroup (MG) MC Shift code is used to update the flux distribution within steps rather than a one-group FOP solver. A fully reflected pincell is investigated, which is not spatially dependent in the MG representation. Thus, the analysis in this paper is an initial demonstration of hybrid depletion. An upcoming companion paper will focus on how the hybrid depletion dampens spatial oscillations. The hybrid depletion approach is verified to be consistent with previous constant extrapolation depletion (CED) methods. This paper finds that the hybrid CED exhibits some error in the eigenvalue and one group constants within macro steps. To address this discrepancy, a simple interpolation scheme (CELI) is investigated. This work found that CELI sufficiently addresses the discrepancy in spectrum for macro steps up to 100 days. Overall, this work demonstrates that the hybrid depletion method can significantly reduce the number of high fidelity MC executions in a MC-coupled depletion with an acceptable eigenvalue error.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Towards scanning nanostructure X-ray microscopy

This article demonstrates spatial mapping of the local and nanoscale structure of thin film objects using spatially resolved pair distribution function (PDF) analysis of synchrotron X-ray diffraction data. This is exemplified in a lab-on-chip combinatorial array of sample spots containing catalytically interesting nanoparticles deposited from liquid precursors using an ink-jet liquid-handling system. A software implementation is presented of the whole protocol, including an approach for automated data acquisition and analysis using the atomic PDF method. The protocol software can handle semi-automated data reduction, normalization and modeling, with user-defined recipes generating a comprehensive collection of metadata and analysis results. By slicing the collection using included functions, it is possible to build images of different contrast features chosen by the user, giving insights into different aspects of the local structure.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗