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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Decovalex-2019 (Task A Final Report)

The DECOVALEX Project is an on-going international research collaboration, established in 1992, to advance the understanding and modeling of coupled Thermal (T), Hydrological (H), Mechanical (M) and Chemical (C) processes in geological in geological systems. This document is the final report of Task A which was proposed by the DECOVALEX Project and coordinated by the British Geological Survey (BGS), presenting the technical definitions of the problems studied, approaches applied, achievements made and outstanding issues for future research. The purpose of Task A under DECOVALEX-2019 is to better understand the processes governing the advective movement of gas in both low-permeability argillaceous repository host rocks and clay-based engineered barriers. Special attention is given to the mechanisms controlling gas entry, flow and pathway sealing and their impact on the performance of the engineered clay barrier. Previous work suggests gas flow may be accompanied by the creation of dilatant pathways whose properties change temporally and spatially within the medium. Thus, new numerical representations for the quantitative prediction of gas migration fluxes through argillaceous rock formations have been developed. These provide an invaluable tool with which to assess the impact of gas flow on repository layout and therefore design of any future facility. In addition, experience gained through this task is of direct relevance to other clay-based engineering issues where immiscible gas flow is a consideration including shale gas, hydrocarbon migration, carbon capture and storage and landfill design.

58 GEOSCIENCES↗
DOE OSTI2021

AI Scaling Laws for Extremes (AISLE)

Focal Area(s) Using artificial intelligence to understand the physics of hydrologic events across temporal and spatial scales, to assess their representation in climate models, and to predict their response to climate warming. This covers both the prescribed foci of (2) predictive modeling using a hierarchy of models and (3) insight gleaned from complex data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Spatiotemporal Downscaling Model for Solar Irradiance Forecast Using Nearest-Neighbor Random Forest and Gaussian Process

Accurate solar photovoltaic (PV) capacity estimation requires high-resolution, site-specific solar irradiance data to account for localized variability. However, global datasets, such as the National Solar Radiation Database (NSRDB), provide regional averages that fail to capture the fine-scale fluctuations critical for large-scale grid integration. This limitation is particularly relevant in the context of increasing distributed energy resources (DERs) penetration, such as rooftop PV. Additionally, it is critical to the implementation of the U.S. Federal Energy Regulatory Commission (FERC) Order 2222, which facilitates DER participation in U.S. bulk power markets. To address this challenge, this study evaluates Nearest-Neighbor Random Forest (NNRF) and Nearest-Neighbor Gaussian Process (NNGP) models for spatiotemporal downscaling of global solar irradiance data. By leveraging historical irradiance and meteorological data, these models incorporate spatial, temporal, and feature-based correlations to enhance local irradiance predictions. The NNRF model, a machine-learning approach, prioritizes computational efficiency and predictive accuracy, while the NNGP model offers a level of interpretability and prediction uncertainty by numerically quantifying correlations and dependencies in the data. Model validation was conducted using day-ahead predictions. The results showed that the average Goodness of Fit (GoF) of the NNRF model of 90.61% across all eight sites outperformed the GoF of the NNGP of 85.88%. Additionally, the computational speed of NNRF was 2.5 times faster than the NNGP. Finally, the NNGP displayed polynomial scaling while the NNRF scaled linearly with increasing number of nearest neighbors. Additional validation of the model on five sites in Puerto Rico further confirmed the superiority of the NNRF model over the NNGP model. These findings highlight the robustness and computational efficiency of NNRF for large-scale solar irradiance downscaling, making it a strong candidate for improving PV capacity estimation and real-time electricity market integration for DERs.

Asiedu, Shadrack (ORCID:0009000646004826)↗
DOE OSTI2021

The Portable Ice Nucleation Experiment (PINE): a new online instrument for laboratory studies and automated long-term field observations of ice-nucleating particles

Atmospheric ice-nucleating particles (INPs) play an important role in determining the phase of clouds, which affects their albedo and lifetime. A lack of data on the spatial and temporal variation of INPs around the globe limits our predictive capacity and understanding of clouds containing ice. Automated instrumentation that can robustly measure INP concentrations across the full range of tropospheric temperatures is needed in order to address this knowledge gap. In this study, we demonstrate the functionality and capacity of the new Portable Ice Nucleation Experiment (PINE) to study ice nucleation processes and to measure INP concentrations under conditions pertinent for mixed-phase clouds, with temperatures from about -10 to about -40°C. PINE is a cloud expansion chamber which avoids frost formation on the cold walls and thereby omits frost fragmentation and related background ice signals during the operation. The development, working principle and treatment of data for the PINE instrument is discussed in detail. We present laboratory-based tests where PINE measurements were compared with those from the established AIDA (Aerosol Interaction and Dynamics in the Atmosphere) cloud chamber. Within experimental uncertainties, PINE agreed with AIDA for homogeneous freezing of pure water droplets and the immersion freezing activity of mineral aerosols. Results from a first field campaign conducted at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) observatory in Oklahoma, USA, from 1 October to 14 November 2019 with the latest PINE design (a commercially available PINE chamber) are also shown, demonstrating PINE's ability to make automated field measurements of INP concentrations at a time resolution of about 8 min with continuous temperature scans for INP measurements between -10 and -30°C. During this field campaign, PINE was continuously operated for 45 d in a fully automated and semi-autonomous way, demonstrating the capability of this new instrument to also be used for longer-term field measurements and INP monitoring activities in observatories.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

The Water Table Model (WTM) (v2.0.1): coupled groundwater and dynamic lake modelling

Abstract. Ice-free land comprises 26 % of the Earth's surface and holds liquid water that delineates ecosystems, affects global geochemical cycling, and modulates sea levels. However, we currently lack the capacity to simulate and predict these terrestrial water changes across the full range of relevant spatial (watershed to global) and temporal (monthly to millennial) scales. To address this knowledge gap, we present the Water Table Model (WTM), which integrates coupled components to compute dynamic lake and groundwater levels. The groundwater component solves the 2D horizontal groundwater flow equation using non-linear equation solvers from the C++ PETSc (Portable, Extensible Toolkit for Scientific Computation) library. The dynamic lake component makes use of the Fill–Spill–Merge (FSM) algorithm to move surface water into lakes, where it may evaporate or affect groundwater flow. In a proof-of-concept application, we demonstrate the continental-scale capabilities of the WTM by simulating the steady-state climate-driven water table for the present day and the Last Glacial Maximum (LGM; 21 000 calendar years before present) across the North American continent. During the LGM, North America stored an additional 14.98 cm of sea-level equivalent (SLE) in lakes and groundwater compared to the climate-driven present-day scenario. We compare the present-day result to other simulations and real-world data. Open-source code for the WTM is available on GitHub and Zenodo.

Callaghan, Kerry L. (ORCID:0000000226740838)↗
NASA NTRS1989

X-ray constraints on large scale clustering

HEAO-1 A2 all-sky survey data are analyzed to investigate the autocorrelation function of the surface brightness fluctuations of the extra-galactic 2-10-keV X-ray background on angular scales ranging from 3 to 27 deg. No significant signal has been detected on any scale. The derived upper limits set important bounds on correlated emission on scales of 10 Mpc or greater. X-ray data are found to be compatible with optical estimates of the two-point spatial correlation function of rich clusters of galaxies and with recent predictions for their cosmological evolution. Constraints on clustering of active galactic nuclei and on its dependence on cosmic time are analyzed in the light of results of recent optical studies.

De Zotti, G.↗
NASA NTRS1990

Trace element and isotopic effects arising from magma migration beneath mid-ocean ridges

The trace element concentrations and isotopic ratios in the magma erupted on mid-ocean ridges may differ from those in the source material due to physical effects such as porous flow dispersion, exchange of trace elements between the fluid and solid phases during magma migration, and convective mixing in magma chambers. These differences are in addition to those produced by better known processes such as fractional crystallization and partial melting. The effects of the three former processes are described. It is predicted that magma typically reaches the subridge magma chambers with a spatial heterogeneity only slightly reduced from that of the source material, but with a subdued variation in time. Convective mixing then further reduces the spatial heterogeneity. Application of the results for convective mixing to a recent Fourier analysis of Sr-87/Sr-86 variations along the Mid-Atlantic Ridge suggests that the falloff in amplitude of variation observed with decreasing wavelength in the Mid-Atlantic Ridge data cannot be explained by convective mixing in magma chambers. Instead, it is postulated that this falloff is due to the mechanics of the production and/or the solid-state convective mixing of chemical and isotopic heterogeneities in the solid mantle.

Kenyon, Patricia M.↗
NASA NTRS1993

A remote sensing research agenda for mapping and monitoring biodiversity

A remote sensing research agenda designed to expand the knowledge of the spatial distribution of species richness and its ecological determinants and to predict its response to global change is proposed. Emphasis is placed on current methods of mapping species richness of both plants and animals, hypotheses concerning the biophysical factors believed to determine patterns of species richness, and anthropogenic processes causing the accelerating rate of extinctions. It is concluded that biodiversity should be incorporated more prominently into the global change and earth system science paradigms.

Stoms, D. M.↗
NASA NTRS1999

Global Simulation of Atmospheric Mercury Concentrations and Deposition Fluxes

Results from a numerical model of the global emissions, transport, chemistry, and deposition of mercury (Hg) in the atmosphere are presented. Hg (in the form of Hg(O) and Hg(II)) is emitted into the atmosphere from natural and anthropogenic sources (estimated to be 4000 and 2100 Mg/ yr, respectively). It is distributed between gaseous, aqueous and particulate phases. Removal of Hg from the atmosphere occurs via dry deposition and wet deposition, which are calculated by the model to be 3300 and 2800 Mg/ yr, respectively. Deposition on land surfaces accounts for 47% of total global deposition. The simulated Hg ambient surface concentrations and deposition fluxes to the Earth's surface are consistent with available observations. Observed spatial and seasonal trends are reproduced by the model, although larger spatial variations are observed in Hg(O) surface concentrations than are predicted by the model. The calculated atmospheric residence time of Hg is -1.7 years. Chemical transformations between Hg(O) and HG(II) have a strong influence on Hg deposition patterns because HG(II) is removed faster than Hg(O). Oxidation of Hg(O) to HG(II) occurs primarily in the gas phase, whereas HG(II) reduction to Hg(O) occurs solely in the aqueous phase. Our model results indicated that in the absence of the aqueous reactions the atmospheric residence time of Hg is reduced to 1.2 from 1.7 years and the Hg surface concentration is -25% lower because of the absence of the HG(II) reduction pathway. This result suggests that aqueous chemistry is an essential component of the atmospheric cycling of Hg.

Shia, Run-Lie↗
NASA NTRS2000

Hydrological Balance in Tropical Cyclones with Scatterometer and TRMM Data

Precipitation over oceans can be estimated from the radar and the microwave radiometer of the Tropical Rain Measuring Mission (TRMM). It can also be estimated from the divergence of the vertically integrated water vapor transport, through the conservation principle, assuming evaporation is relatively small. In tropical cyclones, the divergence of vertically integrated water vapor is highly dependent on the vertical transport and, therefore, on the wind divergence. Spaceborne scatterometers provide surface wind velocity and, therefore, surface wind divergence at spatial resolutions that are much higher than products of numerical weather prediction (NWP). In this study, ocean surface winds derived from the observations of space-based scatterometers and surface precipitation measured by TRMM were objectively interpolated to the same time and location during the passage of a tropical cyclone. Surface precipitation distribution was derived from wind and humidity profiles provided by NWP. When the surface level winds of NWP were replaced by the scatterometer winds, the surface precipitation patterns computed with the conservation method were found to be significantly changed and the new patterns are much closer in agreement with the patterns observed by TRMM.

Liu, W. Timothy↗
NASA NTRS1991

Space adaptation syndrome: multiple etiological factors and individual differences

Space motion sickness is a significant operational concern in the American and Soviet space programs. Nearly 70% of all astronauts and cosmonauts are affected to some degree during their first several days of flight. It is now beginning to appear that space motion sickness like terrestrial motion sickness is the consequence of multiple etiological factors. As we come to understand basic mechanisms of spatial orientation and sensory-motor adaptation we can begin to predict etiological factors in different motion environments. Individuals vary greatly in the extent to which they are susceptible to these different factors. However, individuals seem to be relatively self-consistent in terms of their rates of adaptation to provocative stimulation and their retention of adaptation. Attempts to relate susceptibility to motion sickness during the microgravity phases of parabolic flight maneuvers to vestibular function under 1G and 0G test conditions are described.

short duration↗
NASA NTRS1998

Climate Ocean Modeling on Parallel Computers

Ocean modeling plays an important role in both understanding the current climatic conditions and predicting future climate change. However, modeling the ocean circulation at various spatial and temporal scales is a very challenging computational task.

partition↗
NASA NTRS2007

Alaska at the Crossroads of Migration: Space Based Ornithology

Understanding bird migration on a global scale is one of the most compelling and challenging problems of modern biology with major implications for human health and conservation biology. Revolutionary advances in remote sensing now provide us with near real-time measurements of atmospheric and land surface conditions at high spatial resolution over entire continents. We use spatially-explicit, individual based bird migration models driven by numerical weather prediction models of atmospheric conditions, dynamic habitat suitability maps derived from remotely sensed land surface conditions, biophysiological models, and biological field data to simulate migration routes, timing, energy budgets, and survival of individual birds and populations. Long-distance migratory birds travel annually between breeding grounds in Alaska and wintering grounds in Latin Amierica. Approximately 25% of these species are potential vectors of Avian Influenza. Alaska is at the crossroads of Asian and New World migratory flyways and is likely to be a point of introduction of Asian H5N1 AI into the western hemisphere. If/when an infected bird is detected, a pressing question will be where was this bird several days ago, and where is it likely to go after it was released from the survey site? Answers to such questions will increase effectiveness of AI surveillance and mitigation measures. From a conservation perspective, Alaska's diverse landscape provides breeding sites for many migrants, and climatic and land surface changes along migratory flyways in the western hemisphere may reduce bird survival and physical condition upon arrival at Alaskan breeding territories, success and migrant populations.

Deppe, Jill↗
NASA NTRS2004

A Behavioral Model of Landscape Change in the Amazon Basin: The Colonist Case

This paper presents the prototype of a predictive model capable of describing both magnitudes of deforestation and its spatial articulation into patterns of forest fragmentation. In a departure from other landscape models, it establishes an explicit behavioral foundation for algorithm development, predicated on notions of the peasant economy and on household production theory. It takes a 'bottom-up' approach, generating the process of land-cover change occurring at lot level together with the geography of a transportation system to describe regional landscape change. In other words, it translates the decentralized decisions of individual households into a collective, spatial impact. In so doing, the model unites the richness of survey research on farm households with the analytical rigor of spatial analysis enabled by geographic information systems (GIs). The paper describes earlier efforts at spatial modeling, provides a critique of the so-called spatially explicit model, and elaborates a behavioral foundation by considering farm practices of colonists in the Amazon basin. It then uses, insight from the behavioral statement to motivate a GIs-based model architecture. The model is implemented for a long-standing colonization frontier in the eastern sector of the basin, along the Trans-Amazon Highway in the State of Para, Brazil. Results are subjected to both sensitivity analysis and error assessment, and suggestions are made about how the model could be improved.

Walker, R. A.↗
NASA NTRS2017

Fragmentation Increases Impact of Wind Disturbance on Forest Structure and Carbon Stocks in a Western Amazonian Landscape

Tropical second-growth forests could help mitigate climate change, but the degree to which their carbon potential is achieved will depend on exposure to disturbance. Wind disturbance is common in tropical forests, shaping structure, composition, and function, and influencing successional trajectories. However, little is known about the impacts of extreme winds in fragmented landscapes, though second-growth forests are often located in mosaics of forest, pasture, cropland, and other land cover types. Though indirect evidence suggests that fragmentation increases risk of wind damage, few studies have found such impacts following severe storms. In this study, we ask whether fragmentation and forest type (old vs. second growth) were associated with variation in wind damage after a severe convective storm in a fragmented production landscape in western Amazonia. We applied linear spectral unmixing to Landsat 8 imagery from before and after the storm, and combined it with field observations of damage to map wind effects on forest structure and biomass (Figure 4, 5). We also used Landsat 8 imagery to map land cover with the goals of identifying old- and second-growth forest and characterizing fragmentation. We used these data to assess variation in wind disturbance across 95,596 hectares of forest, distributed over 6,110 patches. We find that fragmentation is significantly associated with wind damage, with damage severity higher at forest edges and in edgier, more isolated patches (Figure 7). Damage was more severe in old-growth than in second-growth forests, but this effect was weaker than that of fragmentation (Figure 8). These results illustrate the importance of considering spatial configuration and landscape context in planning tropical forest restoration and predicting carbon sequestration in second-growth forests. Future research should address the mechanisms behind these results, to minimize wind damage risk in second-growth forests so their carbon potential can be maximally achieved.

Schwartz, Naomi B.↗
NASA NTRSDate not supplied

Oculometric Detection and Characterization of Sub-Clinical Visual/Visuomotor Impairment

It has long been known that qualitative abnormalities in eye movements can be used to diagnose overt brain pathologies (Diefendorf & Dodge, 1908; Fox & Holmes, 1926; Leigh & Zee, 2015). Here, we will examine the use of a set of quantitative measures of the human behavioral response (oculometrics) in a 5-minute radial ocular tracking task (Krukowski & Stone, 2005) with sufficient temporal, spatial, and directional uncertainty to minimize the contribution of a priori prediction or anticipation, and to emphasize the use of a posteriori visual processing of the stimulus trajectory (Liston & Stone, 2014). The derived oculometrics provide a largely independent, reliable set of metrics that are sensitive enough to detect mild sub-clinical impairment across a range of possible neural loci (Stone et al., 2019) with the pattern of impairment across the set providing specificity as to its nature (Tyson et al., 2023). We will review our earlier findings where oculometrics have been used to detect mild impairment due to traumatic brain injury, sleep loss, and low-dose alcohol (Liston et al., 2017; Stone et al., 2019; Tyson et al., 2021). We will also report on a recent clinical study of asymptomatic patients at risk of retinal pathology (Leung et al., 2022) and show that oculometrics can detect and characterize substantive loss of visual function in the absence of clinical indicators of pathology. We conclude that oculometric testing could be used as a routine non-invasive ophthalmological or neurological tool to aid in the early detection and diagnosis of neural injury, toxicity, or disease.

eye movements↗
DOE OSTI2022

Spatiotemporal Modeling of Real World Backsheets Field Survey Data: Hierarchical (Multilevel) Generalized Additive Models: Preprint

Assessing photovoltaic module backsheet durability is critical to increasing module lifetime. Lab based accelerating testing has recently failed to predict large scale failures of widely adopted polymeric materials. Field surveyed data is critical to assess the performance of component lifetime. Using a documented field survey protocol, 13 field surveys where conducted. Each measurement is encoded with it's spatial location in respect to the other modules. By combining field survey data on degradation predictors with real time satellite weather data, data-driven predictive models of backsheet degradation were trained. LOESS models were constructed to investigate the spatial dependence of measurements. It was found that micro-climatic effects like treelines, ground surface changes, and elevation changes effected the magnitude and variance of the measurements. A GAM model was created to predict the value of degradation based on measured predictors. The model includes variables on the climate of the system and the location of each measurement in the PV mounting structure. The model performed well with an adj:R2 of 0:95 for yellowness index prediction. The model was cross-validated using k-folds.

backsheet↗
DOE OSTI2025

Diagenesis is key to unlocking outcrop fracture data suitable for quantitative extrapolation to geothermal targets

Exceptionally large, well-exposed sandstone outcrops in New York provide insights into folds, deformation bands, and fractures that could influence permeability, heat exchange, and stimulation outcomes of geothermal reservoir targets. Cambrian Potsdam Sandstone with <5% porosity contains decimeter-scale open, angular-limbed monoclines <0.5 km apart with associated low-porosity mm-wide cataclastic deformation bands. Crossing and abutting relationships among sub-vertical opening-mode fractures show four chronological Sets A–D, striking NNW, NE, NW, and ENE, respectively. Fracture lengths and heights range from millimeters to tens of meters. Sets A and C macro-fractures, and possibly B and D, contain quartz deposits. All sets have abundant associated quartz cemented microfractures that also record set orientations and crosscutting relations. Quartz cement deposits—evidence of diagenesis—are the key to identifying attributes of outcrop fractures suitable for extrapolation to geothermal targets in sandstones because they show which fractures formed in the subsurface. Set A fluid inclusion homogenization temperatures (120°C–129°C) are compatible with fracture at >3 km depth. Fractures are stiff and those ≥0.05 mm (Set C) and ≥0.1 mm (Set A) are open and potentially conducive to flow. Sets A and D are abundant in outcrops with close fracture spacing—0.18 m and 0.68 m, respectively—and define a rectangular connectivity network dominated by crossing and abutting X and Y nodes. Set A aperture distributions follow a power law with slope –0.8 up to 0.15 mm; other sets have lognormal distributions. Set A and D microfractures are weakly clustered, while macro-fractures commonly have 1D anticlustered (regular or periodic) arrangements at shorter length scales (<0.2 m). Sub-horizontal fractures are barren and may have formed near the surface. Fracture heights, lengths, and spatial arrangements show good trace connectivity but low open connectivity. For geothermal applications, outcrop results predict low initial well-test permeabilities owing to quartz disconnecting open fractures, but stimulation of closely spaced microfractures and partly open macro-fractures could yield high surface area for heat exchange. Quantitative extrapolation of key fracture attributes like abundance, orientation, spatial arrangement, length, and open fracture connectivity is possible from outcrops to fractured reservoirs if differing thermal histories and diagenesis are accounted for.

02 PETROLEUM↗