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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS1982

An inventory of undiscovered Canadian mineral resources

Unit regional value (URV) and unit regional weight are area standardized measures of the expected value and quantity, respectively, of the mineral resources of a region. Estimation and manipulation of the URV statistic is the basis of an approach to mineral resource evaluation. Estimates of the kind and value of exploitable mineral resources yet to be discovered in the provinces of Canada are used as an illustration of the procedure. The URV statistic is set within a previously developed model wherein geology, as measured by point counting geologic maps, is related to the historical record of mineral resource production of well-developed regions of the world, such as the 50 states of the U.S.A.; these may be considered the training set. The Canadian provinces are related to this training set using geological information obtained in the same way from geologic maps of the provinces. The desired predictions of yet to be discovered mineral resources in the Canadian provinces arise as a consequence. The implicit assumption is that regions of similar geology, if equally well developed, will produce similar weights and values of mineral resources.

Labovitz, M. L.↗
NASA NTRS1984

Ice-covered volcanic water flows on Ganymede

The most geologically reasonable model for the origin of grooved terrain on Ganymede involves flooding of a planetary graben system by water or water-ice magmas that rose to the surface along normal faults in the rift zones. To investigate this process further, the thermal evolution of a water flow on Ganymede's surface was examined. The model is a variation of earlier work on ice-covered water flows. It is based on the simplifying assumptions that laminar flow and a concomitant solid ice cover are achieved relatively soon after eruption; and that the amount of energy lost to the substratum is negligible.

Allison, M. L.↗
NASA NTRS1987

Digital cartography of the planets - New methods, its status, and its future

A system has been developed that establishes a standardized cartographic database for each of the 19 planets and major satellites that have been explored to date. Compilation of the databases involves both traditional and newly developed digital image processing and mosaicking techniques, including radiometric and geometric corrections of the images. Each database, or digital image model (DIM), is a digital mosaic of spacecraft images that have been radiometrically and geometrically corrected and photometrically modeled. During compilation, ancillary data files such as radiometric calibrations and refined photometric values for all camera lens and filter combinations and refined camera-orientation matrices for all images used in the mapping are produced. The system is designed to aid in the following: access to and utilization of spatial data returned by planetary spacecraft; coregistration of cartographic image and topographic elevation models with geological, geophysical, and geochemical databases; and the design and preparation of both standard and custom map products. A major goal of the project is to publish the DIMs on compact computer-compatible media such as digital-optical (CD-ROM) disks.

Batson, R. M.↗
NASA NTRS1991

ELAS: A powerful, general purpose image processing package

ELAS is a software package which has been utilized as an image processing tool for more than a decade. It has been the source of several commercial packages. Now available on UNIX workstations it is a very powerful, flexible set of software. Applications at Stennis Space Center have included a very wide range of areas including medicine, forestry, geology, ecological modeling, and sonar imagery. It remains one of the most powerful image processing packages available, either commercially or in the public domain.

Walters, David↗
NASA NTRS1991

The role of thermal vapor diffusion in the subsurface hydrologic evolution of Mars

The hydrologic response of groundwater to the thermal evolution of the early martian crust is considered. When a temperature gradient is present in a moist porous medium, it gives rise to a vapor-pressure gradient that drives the diffusion of water vapor from regions of high to low temperature. By this process, a geothermal gradient as small as 15 K/km could drive the vertical transport of 1 km of water to the freezing front at the base of the martian crysophere every 10 exp 6-10 exp 7 years, or the equivalent of about 100-1000 km of water over the course of martian geologic history. Models of the thermal history of Mars suggest that this thermally-driven vapor flux may have been as much as 3-5 times greater in the past. The magnitude of this transport suggests that the process of geothermally-induced vapor diffusion may have played a critical role in the initial emplacement of ground ice and the subsequent geomorphic and geochemical evolution of the martian crust.

Clifford, Stephen M.↗
NASA NTRS2007

Post-glacial Sediment Load and Subsidence in Coastal Louisiana

Sea level rise in the Gulf of Mexico has occurred at a rate of 1.8-2.2 mm/yr during the 20th century, or nearly the same as observed globally due to combined steric and water mass changes. Tide gauges in coastal Louisiana, however, record a substantially larger rate of rise and while a number of causal mechanisms may be responsible, their specific contribution is poorly understood. Using a realistic viscoelastic Earth model, detailed geologic parameters for south Louisiana and new GPS data, we demonstrate that Holocene sedimentary loading in the Gulf and Mississippi River delta is capable of contributing to 1-8 mm/yr of subsidence over areas of 30-0.75 x 10(exp 3) km(exp 2).

rheology mantle↗
DOE OSTI2020

Geologic Study in Central North Dakota

Fact sheet explaining the process of drilling a test hole to collect data for the North Dakota CarbonSAFE project. North Dakota CarbonSAFE is an Energy & Environmental Research Center project, conducted in partnership with the U.S. Department of Energy.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2022

NRAP-Open-IAM: NRAP Open Source Integrated Assessment Model

Note: This is the last version (a2.6.1) of NRAP-Open-IAM released during NRAP Phase II in 2022. The latest version of NRAP-Open-IAM is available here: https://edx.netl.doe.gov/dataset/phase-iii-nrap-open-iam NRAP-Open-IAM is an open-source software product that enables quantification of containment effectiveness and leakage risk at storage sites in the context of system uncertainties and variability. NRAP-Open-IAM represents the next-generation in a line of systems-based computational models developed for quantitative geological carbon storage (GCS) risk assessment. The model comprises a set of reduced-order and analytical models of various components of the GCS system, potential leakage pathways, receptors of concern including impact to groundwater resources and the atmosphere, a framework to support stochastic simulation, time stepping, uncertainty quantification, other analytical functionality for scenario and risk-performance evaluation, and a basic graphical user interface to support scenario development, data input simulation definition, and basic post-processing and results display. As the NRAP Open-IAM functionality continues to evolve, we continue to add to its capability to develop quantitative, probabilistic, and time-dependent profiles of the evolution of risk at a GCS site and evaluate the influence of uncertain parameters on uncertainty in predicted risk. It can be used to quantify the dynamics of reservoir saturation plume and pressure-affected area, for evaluation of the area of potential groundwater impact (i.e., Area of Review) and monitoring requirements to support cost and regulatory analysis, and for consideration of different post-injection site care and closure scenarios. This submission contains the current version of NRAP-Open-IAM available for evaluation and testing. To use the NRAP-Open-IAM, download the source code (https://edx.netl.doe.gov/dataset/08f396c8-bc5f-44ad-a028-6e98a6ea6d70/resource/4c24a3da-3b40-4ffe-9892-c807ae9f8760) then open the NRAP-Open-IAM user's guide (https://edx.netl.doe.gov/dataset/08f396c8-bc5f-44ad-a028-6e98a6ea6d70/resource/8b27335a-343c-4836-b8a3-3ad0bdc9e669) to read more about the tool. Installation instructions for Windows, Mac, and Linux can be found in the "installers" folder of the extracted NRAP-Open-IAM folder and describe setup of environment (e.g., Python libraries) needed for proper work of the tool. Test of installation can be done by running "python openiam_setup_tests.py" in the "setup" folder. The installation test also runs a test suite to see if the NRAP-Open-IAM has been installed correctly. To run the test suite separately, run "python iam_test.py" in the "test" folder. User's guide: https://edx.netl.doe.gov/dataset/08f396c8-bc5f-44ad-a028-6e98a6ea6d70/resource/8b27335a-343c-4836-b8a3-3ad0bdc9e669 Developer's guide: https://edx.netl.doe.gov/dataset/08f396c8-bc5f-44ad-a028-6e98a6ea6d70/resource/3bc6ee7d-609d-4eb6-80ba-fa6130ee0313 Reservoir simulation data used in some examples distributed with NRAP-Open-IAM: - Kimberlina: https://edx.netl.doe.gov/dataset/08f396c8-bc5f-44ad-a028-6e98a6ea6d70/resource/eb62cece-61b2-4037-9b6d-32407dde2ab8 - Kimberlina (compartmentalized): https://edx.netl.doe.gov/dataset/08f396c8-bc5f-44ad-a028-6e98a6ea6d70/resource/366f9530-3b32-4b84-affe-ab2df1d9a8b5 - FutureGen 2.0: https://edx.netl.doe.gov/dataset/futuregen-2-0-1008-simulation-reservoir-lookup-table NRAP-Open-IAM GitLab repository: https://gitlab.com/NRAP/OpenIAM Related publications: - Bacon, D., Yonkofski, C., Brown, C., Demirkanli, D. and Whiting, J., 2019. Risk-based post injection site care and monitoring for commercial-scale carbon storage: Reevaluation of the FutureGen 2.0 site using NRAP-Open-IAM and DREAM. International Journal of Greenhouse Gas Control 90: 102784. - Bacon, D. Demirkanli, D., and White, S., 2020. Probabilistic risk-based Area of Review (AoR) determination for a deep-saline carbon storage site. International Journal of Greenhouse Gas Control 102: 103153. - Harp, D., Oldenburg, C., and Pawar, R., 2019. A metric for evaluating conformance robustness during geologic CO2 sequestration operations. International Journal of Greenhouse Gas Control 85: 100-108. - Lackey, G., Vasylkivska, V., Huerta, N., King, S., and Dilmore, R., 2019. Managing well leakage risks at a geologic carbon storage site with many wells, International Journal of Greenhouse Gas Control, 88 :182-194. - Vasylkivska, V., Dilmore, R., Lackey, G., Zhang, Y., King, S., Bacon, D., Chen, B., Mansoor, K., and Harp, D., 2021. NRAP-Open-IAM: A flexible open-source integrated assessment model for geologic carbon storage risk assessment and management, Environmental Modelling & Software, 143: 105114. Presentations: - Chen, B., Harp, D., and Pawar, R., A data assimilation approach (ES-MDA) coupling with NRAP-Open-IAM for quantifying uncertainty reduction in geological CO2 sequestration. AGUFM 2019: T44A-02. - Chen, B., and Harp, D., Improving risk analysis precision for geologic CO2 sequestration by quantifying the uncertainty reduction before and after acquiring monitoring data. 14th Greenhouse Gas Control Technologies Conference, Melbourne, Australia, 2018, pp. 21-26. - Harp, D., National Risk Assessment Partnership Task 2: Containment Assurance. No. LA-UR-19-28654, Los Alamos National Laboratory (LANL), Los Alamos, NM (United States), 2019. - Vasylkivska, V., King, S., Bacon, D., Harp, D., Chen, B., Mansoor, K., Onishi, T., Yang, Y., Zhang, Y., and Keating, E., NRAP-Open-IAM: An open-source integrated assessment model, poster, Mastering the Subsurface Through Technology Innovation, Partnerships and Collaboration: Carbon Storage and Oil and Natural Gas Technologies Review Meeting, Pittsburgh, PA, August 13-16, 2018. - Vasylkivska, V., Lackey, G., King, S., Wentworth, A., Huerta, N., Creason, C., DiGiulio, J., Yang, Y., and Dilmore, R., Long-term risk analysis of a geologic CO2 storage project during the post-injection period, SIAM Conference on Computational Science and Engineering, Spokane, WA, February 25-March 1, 2019. - Vasylkivska, V., Overview of the NRAP-Open-IAM tool for carbon storage (beta release), 2019 Annual NRAP Tool Users Meeting, Pittsburgh, PA, August 27, 2019. - Vasylkivska, V., Bacon, D., Chen, B., Dilmore, R., Harp, D., King, S., Lackey, G., Lindner, E., Liu, G., Mansoor, K. and Zhang, Y., NRAP-Open-IAM: A new, open-source code for integrated assessment of geologic carbon storage containment effectiveness and leakage risk, poster, American Geophysical Union Fall Meeting 2020 (virtual meeting), December 2020. - Vasylkivska, V., NRAP open-source integrated assessment model and relevant application, oral presentation, NRAP workshop "NRAP Tools for Geologic Carbon Storage Risk-Based Decision Making" held in conjunction with Groundwater Protection Council (GWPC) 2021 Annual Forum (virtual meeting), Salt Lake City, UT, September 2021. - Vasylkivska, V., NRAP-Open-IAM: open-source integrated assessment model, digital poster/demonstration, software demonstration session, 2022 Carbon Management Project Review Meeting, August 16, 2022

AoR↗
DOE OSTI2022

DPC Direct Disposal Postclosure Thermal Modeling

Performance of geologic radioactive waste repositories depends on near-field and far-field processes, including km-scale flow and transport in engineered and natural barriers, that may require simulations of up to 1 M years of regulatory period. For a relatively short time span (less than 1000 years), the thermohydro-mechanical-chemical (THMC) coupled processes caused by heat from the waste package will influence near-field multiphase flow, chemical/reactive transport, and mechanical behaviors in the repository system. This study integrates the heat-driven perturbations in thermo-hydro-mechanical characteristics into thermo-hydro-chemical simulations using PFLOTRAN to reduce dimensionality and improve computational efficiency by implementing functions of stress-dependent permeability and saturation-temperature-dependent thermal conductivity. These process couplings are developed for spent nuclear fuel in dual-purpose canisters in two different hypothetical repositories: a shale repository and a salt repository.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1985

Carbon and sulfur cycling through geologic time

Mathematical models of the coupled global systems of sedimentary reservoirs and fluxes are used to infer variations in reservoir sizes and rates of sedimentation over periods of hundreds of millions of years. Perhaps most interesting is the coupled sulfide/sulfate carbon/carbonate system that controls global oxygen and carbon dioxide production and consumption is discussed.

Garrels, R. M.↗
DOE OSTI2026

A Boundary Element Model for Assessing Large‐Scale Pressurization in Faulted Geological Storage Systems

Assessing large-scale pressurization at the regional scale—a possible outcome of large subsurface storage applications such as wastewater injection and geological carbon sequestration—presents significant computational challenges. These challenges are particularly pronounced when accounting for complex geologic structures with multiple reservoir and caprock layers, fault zones, and wells. This study introduces a computationally efficient model that integrates single-phase semi-analytical solutions with a boundary element (BE) approach. The model simulates pressure propagation in multilayered 3D systems, including vertical faults, caprock, basement, and confining units. We apply this new model to a representative scenario involving CO 2 injection near a partially sealing fault with verification against an independent two-phase flow model. Results demonstrate that our model accurately captures far-field pressure responses and that, outside the CO 2 plume zone, pressure predictions from single-phase and two-phase models are nearly identical. This supports the use of single-phase models like ours for efficient estimation of far-field pressure changes. Additionally, we demonstrate its effectiveness at a large scale, incorporating multiple wells and faults. With its ability to represent multiple wells, fault zones, and geological heterogeneity, our model is well suited for assessments of basin-scale pressurization. Its computational efficiency also makes it a promising tool for integration with optimization frameworks aimed at designing and managing injection strategies in faulted storage systems.

Cihan, A. [Lawrence Berkeley National Laboratory (↗
DOE OSTI2026

Quantifying mean, variability, and uncertainty in indoor radon exposure in Pennsylvania using random forest and quantile regression forest models

Radon is a naturally occurring radioactive gas that poses a serious health risk as the primary cause of lung cancer in non-smokers. Despite the well-known adverse association with health outcomes, current radon exposure assessments are limited to county-level or average-level estimates, which fail to capture regional variability. This study uses Machine Learning models, including Random Forest (RF) and Quantile Regression Forest (QRF), to estimate the indoor radon concentrations at the ZCTA (Zip code tabulation area)-level and characterize uncertainties in model estimates. Incorporating geological, meteorological, and building-specific data, the models aim to improve radon risk assessment by capturing mean exposure, variability, and extreme concentration levels. Processed radon test data (n = 718,111) were analyzed using average, variability, and quantile prediction methods. Models that estimate the average radon exposure at the ZCTA-level can yield promising model-fit results, but they do not capture the underlying variability of indoor radon exposure within a ZCTA. We utilize volatility analyses to identify characteristics indicative of high variability of indoor radon exposure. We also show that a QRF model can be used to estimate upper quantiles of residential radon exposure, thereby uncovering localized areas of elevated exposure that were not apparent in mean estimates. The results highlighted the need for a deep characterization of exposure risk and show that regions with moderate average exposure levels could still harbor extreme outliers with implications for evaluating health risks. Utilizing multiple radon exposure models allows for a deeper characterization of radon risk within a geographic area and can better identify high-risk areas. The results from this study provide a foundation for developing mitigation strategies and examining associations between radon exposure and health outcomes at fine scales. Future research should extend the geographic scope and incorporate additional environmental risk factors to establish a comprehensive framework for risk assessment.

Lee, Heechan [ORNL]↗
NASA NTRS2001

Mapping Arid Vegetation Species Distributions in the White Mountains, Eastern California, Using AVIRIS, Topography, and Geology

Our challenge is to model plant species distributions in complex montane environments using disparate sources of data, including topography, geology, and hyperspectral data. From an ecologist's point of view, species distributions are determined by local environment and disturbance history, while spectral data are 'ancillary.' However, a remote sensor's perspective says that spectral data provide picture of what vegetation is there, topographic and geologic data are ancillary. In order to bridge the gap, all available data should be used to get the best possible prediction of species distributions using complex multivariate techniques implemented on a GIS. Vegetation reflects local climatic and nutrient conditions, both of which can be modeled, allowing predictive mapping of vegetation distributions. Geologic substrate strongly affects chemical, thermal, and physical properties of soils, while climatic conditions are determined by local topography. As elevation increases, precipitation increases and temperature decreases. Aspect, slope, and surrounding topography determine potential insolation, so that south-facing slopes are warmer and north-facing slopes cooler at a given elevation. Topographic position (ridge, slope, canyon, or meadow) and slope angle affect sediment accumulation and soil depth. These factors combine as complex environmental gradients, and underlie many features of plant distributions. Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data, digital elevation models, digitized geologic maps, and 378 ground control points were used to predictively map species distributions in the central and southern White Mountains, along the western boundary of the Basin and Range province. Minimum Noise Fraction (MNF) bands were calculated from the visible and near-infrared AVIRIS bands, and combined with digitized geologic maps and topographic variables using Canonical Correspondence Analysis (CCA). CCA allows for modeling species 'envelopes' in multidimensional environmental space, which can then be projected across entire landscapes.

VandeVen, C.↗
NASA NTRS1993

A wet-geology and cold-climate Mars model: Punctuation of a slow dynamic approach to equilibrium

It was suggested that Mars may have possessed a relatively warm humid climate and a vigorous hydrological cycle involving meteoric precipitation, oceans, and continental ice sheets. Baker hypothesized that these geologically active conditions may have been repeated several times; each of these dynamic epochs was followed by a collapse of the climate and hydrologic cycle of Mars into essentially current conditions, completing what is termed a 'Baker cycle'. The purpose is to present an endmember possibility that Martian glacial landscapes, including some that were previously considered to have formed under warm climatic conditions, might be explained by processes compatible with an extremely cold surface. Two aspects of hypothesized Martian glacial terrains were cited as favoring a warm climate during Baker cycles: (1) the formation of some landscapes, including possible eskers, tunnel channels, drumlins, and outwash plains, appears to have required liquid water, and (2) a liquid-surfaced ocean was probably necessary to feed the glaciers. The requirement for liquid water, if these features were correctly interpreted, is difficult to avoid; it is entirely possible that a comparatively warm climate was involved, but it is not clear that formation of landforms by wet-based glaciers actually requires a warm climate. Even less certain is the supposed requirement for liquid oceans. Formation of glaciers only requires a source of water or ice to supply an amount of precipitation that exceeds losses due to melting and sublimation. At Martian temperatures precipitation is very low, but so are melting and sublimation, so a large body of ice that is unstable with respect to sublimation may take the role of Earth's oceans in feeding the glaciers. Recent models suggest that even current Martian polar caps, long thought to be static bodies of ice and dust, might actually be slow-moving, cryogenic continental glaciers. Is it possible that subglacial processes beneath cryogenic (but wetbased) ice sheets formed the hypothesized Martian glacial landscapes?

Kargel, J. S.↗
NASA NTRS1973

Optical modeling of agricultural fields and rough-textured rock and mineral surfaces

Review was made of past models for describing the reflectance and/or emittance properties of agricultural/forestry and geological targets in an effort to select the best theoretical models. An extension of the six parameter Allen-Gayle-Richardson model was chosen as the agricultural plant canopy model. The model is used to predict the bidirectional reflectance of a field crop from known laboratory spectra of crop components and approximate plant geometry. The selected geological model is based on Mie theory and radiative transfer equations, and will assess the effect of textural variations of the spectral emittance of natural rock surfaces.

Suits, G. H.↗
DOE OSTI2021

A screening model for predicting injection well pressure buildup and plume extent in CO 2 geologic storage projects

We present a new screening model for predicting injection well pressure buildup and CO 2 plume migration for CO 2 geologic sequestration projects. The model requires only limited information and is quite accurate when compared to detailed simulation results. Such models can assist project developers during the early days of project planning (e.g., for 45Q related projects), and also help regulators perform simple checks against detailed numerical models. The screening model consists of two correlations: one for injectivity index in terms of the slope of the CO 2 fractional flow curve, and the second for total storage efficiency within the footprint of plume as a function of gravity number and slope of the CO 2 fractional flow curve. Using these two correlations, as well as a knowledge of some basic reservoir characteristics and estimates of fluid properties from standard correlations, the injection-well pressure buildup and CO 2 plume extent in the formation can be readily estimated. Finally, the new correlations show a good match with the results of the underlying simulations, and also provide good agreement with independent calculations for two example problems.

42 ENGINEERING↗