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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

GEOPHIRES Simulations for Deep Direct Use (DDU) Projects

This folder contains the GEOPHIRES codes and input files for running the base case scenarios for the six deep direct-use (DDU) projects. The six DDU projects took place during 2017-2020 and were funded by the U.S. Department of Energy Geothermal Technologies Office. They investigated the potential of geothermal deep direct-use at six locations across the country. The projects were conducted by Cornell University, West Virginia University (WVU), University of Illinois (U of IL), Sandia National Laboratory (SNL), Portland State University (PSU), and National Renewable Energy Laboratory (NREL). Four projects (Cornell, WVU, U of IL, SNL) investigated geothermal for direct heating of a local campus or community, the project by PSU considered seasonal subsurface storage of solar heating, and the NREL project investigated geothermal heating for turbine inlet cooling using absorption chillers. To allow comparison of techno-economic results across the six DDU projects, GEOPHIRES simulations were set up and conducted for each project. The GEOPHIRES code was modified for each project to simulate the local application and incorporate project-specific assumptions and results such as reservoir production temperature or financing conditions. The base case input file is included which simulates the base case conditions assumed by each project team. The levelized cost of heat (LCOH) is calculated and matches the base case LCOH reported by the project teams.

15 GEOTHERMAL ENERGY↗
DOE OSTI2026

Uinta Basin CarbonSAFE II: Storage Complex Feasibility (Final Report)

The primary objective of this CarbonSAFE Phase II project was to establish the technical and commercial feasibility of a commercial-scale CO 2 geological storage complex for Deseret Power Electric Cooperative Bonanza Power Plant and other CO 2 sources in the northeast Uinta Basin, Utah, with the goal to securely store at least 50 million metric tons of captured CO 2 and accelerate CO 2 capture, utilization, and storage (CCUS) deployment. The project team established high-potential technical and commercial feasibility for a storage site within the east Uinta Basin (Utah), in the Cretaceous sandstones (Frontier, Dakota, and Buckhorn), Entrada Sandstone, Nugget Sandstone, and/or Weber Sandstone southwest of the Bonanza coal-fired power plant. This project collected and analyzed state-of-the-art data to characterize the storage complex consistent with Environmental Protection Agency (EPA) permitting standards. The team conducted extensive analog studies, outcrop mapping, and data sampling, which largely contributed to understanding the subsurface lithology and facies. Existing data were obtained and assessed from Utah Division of Oil, Gas, and Mining (DOGM), Utah Geological Survey (UGS), Colorado Geological Survey (CGS), U.S. Geological Survey (USGS), and EPA. These data were analyzed using state-of-the-art CCUS technologies for Societal Considerations, Site Characterization, Modeling and Simulations, Risk Assessment, Management and Monitoring, potential Underground Injection Control (UIC) Class VI Well Permitting, and Technical/Economic Feasibility. Through these high-resolution data collection and feasibility studies, this project was expected to provide a reference for initiating Underground Injection Control (UIC) and other commercial-scale geological storage permitting processes in the Western United States, ultimately contributing to the nation's decarbonization goals through low-risk, cost-effective commercial-scale carbon capture, utilization, and storage (CCUS) projects.

42 ENGINEERING↗
DOE OSTI2025

Coupled Hydrological-Thermal-Biogeochemical Modeling for Predicting Arctic Carbon Emissions (CH4PACE)

The Arctic, with nearly 1,700 billion metric tons of carbon stored in its soils, is experiencing significant warming trends that raise concerns about the potential release of greenhouse gases, particularly methane. This report investigates the conversion of carbon stored in Arctic soils and permafrost into methane and its subsequent atmospheric release over the coming decades. Recent data indicate a rise in global methane concentrations, highlighting the importance of understanding the mechanisms of methane generation under anaerobic conditions prevalent in thawing permafrost. Our study employs a multi-faceted approach that integrates fieldwork, benchtop experiments, and numerical simulations to explore the subsurface hydrological-thermal-biogeochemical systems influencing methane emissions. We focus on the relationship between microbial activity in decomposing organic matter under oxygen-limited conditions and the transport of methane out of these saturated wetland soils. Key hydrological parameters, including permeability, porosity, and thermal conductivity, were measured on soil samples from Fairbanks, Alaska, and used to parameterize PFLOTRAN, a coupled hydrological-thermal-reactive transport simulator. Our model enables prediction of the evolution of the active layer and its impact on methane production and release. Our findings underscore the critical need for a mechanistic understanding of methane dynamics in permafrost environments to improve predictions of methane emissions in Earth systems models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Inverse Modeling of Hydrologic Parameters in CLM4 via Generalized Polynomial Chaos in the Bayesian Framework

In this work, generalized polynomial chaos (gPC) expansion for land surface model parameter estimation is evaluated. We perform inverse modeling and compute the posterior distribution of the critical hydrological parameters that are subject to great uncertainty in the Community Land Model (CLM) for a given value of the output LH. The unknown parameters include those that have been identified as the most influential factors on the simulations of surface and subsurface runoff, latent and sensible heat fluxes, and soil moisture in CLM4.0. We set up the inversion problem in the Bayesian framework in two steps: (i) building a surrogate model expressing the input–output mapping, and (ii) performing inverse modeling and computing the posterior distributions of the input parameters using observation data for a given value of the output LH. The development of the surrogate model is carried out with a Bayesian procedure based on the variable selection methods that use gPC expansions. Our approach accounts for bases selection uncertainty and quantifies the importance of the gPC terms, and, hence, all of the input parameters, via the associated posterior probabilities.

97 MATHEMATICS AND COMPUTING↗
NASA NTRSDate not supplied

Celestial Mapping System for Lunar Surface Mapping and Analytics

Celestial Mapping System (CMS) is a software platform to generate virtual 3D globe for celestial bodies within our solar system. Various layers are built on top of the virtual globe to provide visualization of high resolution imagery, enable precise measurements, build analytical capabilities and broad range of functionalities to assist planetary scientists and mission planners. CMS is built using OpenJDK 11 and will run on a wide variety of platforms such as Linux, Windows, OSX, etc. It has a thick client with less overhead to access hardware resources. This allows features such as terrain profiling and distance calculations to be performed on the client and on the fly. The present focus of CMS is on developing lunar mapping tool kits to provide features such as - 3D first person view with zoom and navigational capabilities, realistic terrain visualization based on LRO data, measurement tools, Apollo landing site annotations, stereoscopic view, elevation profiles, line of sight analysis and many more. The application is developed to provide situational and domain awareness on Lunar surface, planning capabilities for equipment placements and traverse path optimization. As data becomes available, CMS has the capabilities to integrate data sets that change dynamically in real-time, which will be useful for monitoring satellites and remotely-sensed data on Lunar surface. CMS utilizes NASA WorldWind Java library and OpenGL to achieve high-performance rendering of data and measurements, and also adheres to OGC standards. CMS supports importing synthetic features in a variety of 3D, 2D, vector and raster formats. Nomenclature is pulled from USGS Moon IAU2000 database, and lunar parameters are based of the standardized IAU2000 Moon ellipsoid. GDAL (Geospatial Data Abstraction Library) was used to modify and test the accuracy of datasets before integrating into the application. Our high-resolution global elevation model was compared with the LRO LOLA DEM elevation values and tested to ensure accuracy. Celestial Mapping System has several potential use cases for NASA including subsurface lava tubes visualization and analysis, soil analysis, resource visualization and representation on 3D globe.

GIS system↗
DOE OSTI2021

Increasing freshwater and dissolved organic carbon flows to Northwest Alaska’s Elson lagoon

Manifestations of climate change in the Arctic are numerous and include hydrological cycle intensification and permafrost thaw, both expected as a result of atmospheric and surface warming. Across the terrestrial Arctic dissolved organic carbon (DOC) entrained in arctic rivers may be providing a carbon subsidy to coastal food webs. Yet, data from field sampling is too often of limited duration to confidently ascertain impacts of climate change on freshwater and DOC flows to coastal waters. This study applies numerical modeling to investigate trends in freshwater and DOC exports from land to Elson Lagoon in Northwest Alaska over the period 1981-2020. While the modeling approach has limitations, the results point to significant increases in freshwater and DOC exports to the lagoon over the past four decades. The model simulation reveals significant increases in surface, subsurface (suprapermafrost), and total freshwater exports. Significant increases are also noted in surface and subsurface DOC production and export, influenced by warming soils and associated active-layer thickening. The largest changes in subsurface components are noted in September, which has experienced a ~50% increase in DOC export emanating from suprapermafrost flow. Direct coastal suprapermafrost freshwater and DOC exports in late summer more than doubled between the first and last five years of the simulation period, with a large anomaly in September 2019 representing a more than fourfold increase over September direct coastal export during the early 1980s. These trends highlight the need for dedicated measurement programs that will enable improved understanding of climate change impacts on coastal zone processes in this data sparse region of Northwest Alaska.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1976

Development of specifications for surface and subsurface oceanic environmental data

The existing need for synoptic subsurface observations was demonstrated giving special attention to the requirements of meteorology. The current state of synoptic oceanographic observations was assessed; a preliminary design for the Basic Observational Network needed to fulfill the minimum needs of synoptic meteorology and oceanography was presented. There is an existing critical need for such a network in the support of atmospheric modeling and operational meteorological prediction, and through utilization of the regional water mass concept an adequate observational system can be designed which is realistic in terms of cost and effort.

Wolff, P. M.↗
NASA NTRS1996

Radar Interferometric and Penetration Investigations using SIR-C Data

Progress, significant results, publications and future plans are discussed in relation to the following objectives: (1) To model, experimentally characterize, and verify penetration phenomena in hyperarid and vegetated regions using the SIR-C/X-SAR multiparameter radar system and groundbased receivers; (2) To invert measured radar backscatter as a function of frequency and polarization in terms of geophysical parameters of the surface, subsurface and vegetation canopy such as surface roughness, subsurface geomorphology, or tree height and density; and (3) To display subsurface and within-canopy features in an image format, thus easing the interpretability of the results.

Zebker, Howard A.↗
DOE OSTI2024

Subsurface electrical conductivity across the BEO site inferred using a capacitively coupled resistivity survey in May 2013, Utqiagvik, Alaska

Multiple transects across and around the Barrow Environmental Observatory (BEO) site were surveyed using a capacitively coupled resistivity tool to infer the subsurface electrical conductivity in the top ~6 m in order to improve the understanding of heterogeneity in ice and salinity content. This work was led by the environmental geophysics team from Lawrence Berkeley National Laboratory as part of the Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic). The acquisition was performed in May 2013 using a capacitively coupled resistivity tool (OhmMapper from Geometrics, Inc) mounted behind a sled hooked to a snowmobile. Twenty-eight ~750 m long transects cover the NGEE intensive site (polygon areas A, B, C, D) in the BEO with a measurement (apparent resistivity for 5 different geometries) taken every 1.5 to 2 m. The survey also includes other transects that have been acquired along Electrical Resistivity Tomography (ERT) transects previously acquired at the site (Site 0, AB, and BD), and several long transects (up to 7 km each) around the BEO site crossing several Drained Thawed Lake Basins (DTLB). The various transects acquired during this survey cover a distance of about 100 km. All the datasets are provided with the acquisition geometry and the associated subsurface apparent electrical conductivity. In addition, the 28 transects at the BEO intensive site were inverted to infer the subsurface electrical conductivity. Unprocessed and processed data products are included in this package. This metadata document contains a description of the survey and processing steps and the inferred products.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic) was a 15-year research effort (2012-2027) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy’s Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska, and 2) multiple areas in the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy’s Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Acoustic Research under the Source Physics Experiment

The Source Physics Experiment series is a long-term research and development (R&D) effort under the U.S. Department of Energy’s National Nuclear Security Administration focused on improving the physical understanding of how chemical explosions generate seismoacoustic signals. Beginning in 2011, a series of subsurface chemical explosions in two different and highly contrasting geologies were conducted at the Nevada National Security Site in Nevada, USA with the objective of improving simulation and modeling approaches to explosion identification, yield estimation and other monitoring applications. The two executed phases of the series provide new explosion signature source data from a wide range of geophysical diagnostic equipment; recorded data from the test series is now openly available to the broader seismoacoustic community. This manuscript details the executed test series, deployed seismoacoustic networks, and summarizes major scientific achievements utilizing recorded signatures from the explosive tests.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
NASA NTRS1994

Evidence for active hotspots on Venus from analysis of Magellan gravity data

The 500-Myr average crater retention age for Venus has raised questions about the present-day level of tectonic activity. In this study we examine the relationship between the gravity and topography of four large volcanic swells, Beta, Atla, Bell, and Western Eistla Regiones, for clues about their stage evolution. The Magellan line-of-sight gravity data are inverted using a point mass model of the anomalous mass to solve for the local vertical gravity field. Spectral admittance calculated from both the local gravity inversions and a spherical harmonic model is compared to three models of compensation: local compensation, a 'flexural' model with local and regional compensation of surface and subsurface loads, and a 'hotspot' model of compensation that includes top loading by volcanoes and subsurface loading due to a deep, low density mass anomaly. The coherence is also calculated in each region, but yields an elastic thickness estimate only at Bell Regio. In all models, the long wavelengths are compensated locally. Our results may indicate a relatively old, possibly inactive plume.

Smrekar, Suzanne E.↗
NASA NTRS2005

Application of an Orbital GPR Model to Detecting Martian Polar Subsurface Features

There are numerous challenges in successfully implementing and interpreting planetary ground penetrating radar (GPR) measurements. Many are due to substantial uncertainties in the target ground parameters and the intervening medium (i.e., the ionosphere). These uncertainties generate a compelling need for meaningful quantitative simulation of the planetary GPR problem. An accurate numerical model would enable realistic numerical GPR simulations using parameter regimes much broader than are possible in laboratory or field experiments. Parameters such as source bandwidth and power, surface and subsurface features, and ionospheric profiles could be rapidly iterated to understand their impact on GPR performance and the reliable interpretation of GPR data.

Xu, Y.↗
DOE OSTI2022

Model files for estimating snow dynamics and stable water isotopes across the East River, CO.

A coupled hydrologic and snowpack stable water isotope model is used to assesses controls on isotopic inputs across the East River, Colorado, a large, mountainous basin. The hydrologic model uses the semi-empirical, spatially distributed and publicly available U.S. Geological Survey numerical code Precipitation-Modelling Runoff System (PRMS). Water and energy are tracked daily through the atmosphere, canopy and subsurface at a 100-m grid resolution. The isotope mass balance model follows previous work by Ala-aho et al. (2017) to track stable isotopes entering the soil system as snowmelt or rain. Water stores and fluxes needed for the isotope model use hydrologic model output for each timestep and model modeled grid location. This data package provides all files related to the hydrologic model (executable, input and output files), the isotopic model calibration and the historic isotopic model (water years 2015-2020). The isotope model source code and executable are provided. The file "readme.txt" includes information on the file structure, steps to run the model, and description of included folders.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Rock Physics-Based Data Assimilation of Integrated Continuous Active-Source Seismic and Pressure Monitoring Data during Geological Carbon Storage

Summary There has been substantial controversy concerning the role of geological carbon storage (GCS) in sequestering anthropogenic carbon emissions to mitigate climate change and global warming. Arguments center on the inability to monitor a geological storage site precisely and continuously, especially highlighting the associated costs and spatiotemporal trade-offs when using conventional subsurface monitoring techniques (well logs, core samples, chemical tracers, and 4D seismics). Active surveillance of GCS sites is essential for managing and mitigating potential leaks but is also required by regulation. With the goal of enhancing the monitoring capability at GCS sites, we present a rock physics-based joint data assimilation model to study a popular GCS site at Cranfield, Mississippi, USA. Synthetic continuous active-source seismic monitoring (CASSM) data (in the form of Vp and Qp measurements) and wellbore pressure monitoring data are assimilated with an ensemble of reservoir realizations to monitor gas saturation and reservoir pressure changes over a period of 100 years. Synthetic seismic attributes are generated using rock physics models (RPMs) and wellbore pressure monitoring data are extracted from the ground truth. Two assimilation methods, ensemble Kalman filter (EnKF) and ensemble Kalman smoother (EnKS), are tested in an observation system simulation experiment (OSSE) environment to assess the prediction accuracy of the individual and composite observation systems. The joint monitoring system achieves more accurate estimates of gas saturation and pressure, across the time span from start of injection to end of forecast, as compared to a single type of monitoring tool and irrespective of data assimilation algorithm choice. These results indicate that jointly assimilated data from two types of sensors (in this case, crosswell seismic and downhole pressure) may lead to a more risk-reducing monitoring design. One would expect that more data, vis-à-vis inclusion of a new sensor type, will improve the accuracy of any GCS monitoring system. However, from a practical standpoint, one important question is whether such a gain in accuracy is worth the additional cost associated with the new sensor. This paper focuses on quantifying the gain in accuracy, such that a practitioner can answer this question.

Engineering↗
DOE OSTI2023

Transient Pressure Interference During CO2 Injection in Saline Aquifers

Abstract CO2 injection in subsurface geological formations (e.g. deep saline aquifers) causes pressure perturbations over a large area surrounding the injection well. Observation wells are widely considered in geologic CO2 storage (GCS) projects where the pressure perturbation induced by CO2 injection is measured. In this work, we use analytical and numerical modeling tools along with field data to examine the pressure behavior in GCS projects before and after CO2 arrival at an observation well. Prior to CO2 arrival, a baseline pressure trend is established which corresponds to single-phase brine flow across the observation well (approximated by Theis solution). Therefore, analysis of early-time pressure data is straightforward, provides the single-phase flow characteristics (mobility and storativity), and helps establishing a baseline pressure change that can be extended beyond the single-phase flow period at the observation well. Upon CO2 arrival, a departure from this baseline trend is expected. For the pressure to detect the CO2 arrival at an observation well, the departure from baseline pressure behavior must be significant and well above the background noise levels. We use existing analytical models to determine the strength of the expected pressure departure signal from the baseline trend upon CO2 arrival. The strength of the expected pressure departure is found to be directly proportional to the mobility ratio. Accordingly, we establish a criterion to determine whether the pressure at an observation well can detect the CO2 arrival. We present an analysis approach through application to synthetic and field data and show the characteristic pressure behavior before and after CO2 arrival. We show that while generally the pressure can be either above or below the expected baseline pressure trend, it would be likely above the baseline upon CO2 arrival. This is because the mobility ratio becomes less than unity after CO2 arrival. We show that depending on the reservoir characteristics, changes in the pressure trend may or may not be sufficient to detect the CO2 arrival.

Engineering↗
DOE OSTI2020

Sensor Recommendations for Long Term Monitoring of the F-Area Seepage Basins

In mid-2018, a new paradigm for long-term monitoring was developed after of decade of applied research projects funded by the Department of Energy’s office of Environmental Management Technology Development program. The program at SRNL was focused on transitioning complex environmental waste sites from active to passive remediations strategies. A key result of these studies was that the use of enhanced attenuation approaches at radiologically contaminated sites will result in the creation of secondary source areas in the subsurface that will require monitoring for decades. Alternative monitoring approaches are being developed and tested at the Savannah River Site’s F-Area Hazardous Waste Management Facility, the new paradigm provides innovative solutions that will significantly lower costs of monitoring through the coupling of data collection, machine learning and deterministic groundwater modeling. The foundation of this approach is a well-optimized network of sensors for measuring hydrogeochemical master variables that control, and therefore act as indicators of groundwater contaminant transport. By monitoring changes in the controlling master variables over time arising from geological and environmental shifts, predictive modelling can assist with identifying new strategies for ensuring regulatory requirements are met if trends toward conditions for potential remobilization of attenuated contaminants are detected. In this report, we evaluated commercially available single parameter sensor platforms (e.g., temperature/depth) and configurable multi-parameter sensor platforms (e.g., pH, oxidation-reduction potential, temperature, depth, dissolved oxygen, and conductivity). Each was scored using an optimization function based on how well the system supports the proposed long-term monitoring paradigm, in general, and the site-specific conditions at F-Area, in particular. Several viable sensor systems were identified. Of these, a combined platform including the In-Situ Aqua TROLL 500 multi-parameter sensor platform and the In-Situ temperature/depth sensor had the highest rating and was identified as the most suitable candidate for installation and monitoring of the master variables and potentiometric surface that control groundwater contaminant plumes emanating from the F-Area Seepage Basins. The discussion of recommended potential deployment locations builds upon recommendations made by Denham et al (2019).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Knowledge-informed deep learning for hydrological model calibration: an application to Coal Creek Watershed in Colorado

Abstract. Deep learning (DL)-assisted inverse mapping has shown promise in hydrological model calibration by directly estimating parameters from observations. However, the increasing computational demand for running the state-of-the-art hydrological model limits sufficient ensemble runs for its calibration. In this work, we present a novel knowledge-informed deep learning method that can efficiently conduct the calibration using a few hundred realizations. The method involves two steps. First, we determine decisive model parameters from a complete parameter set based on the mutual information (MI) between model responses and each parameter computed by a limited number of realizations (∼50). Second, we perform more ensemble runs (e.g., several hundred) to generate the training sets for the inverse mapping, which selects informative model responses for estimating each parameter using MI-based parameter sensitivity. We applied this new DL-based method to calibrate a process-based integrated hydrological model, the Advanced Terrestrial Simulator (ATS), at Coal Creek Watershed, CO. The calibration is performed against observed stream discharge (Q) and remotely sensed evapotranspiration (ET) from the water year 2017 to 2019. Preliminary MI analysis on 50 realizations resulted in a down-selection of 7 out of 14 ATS model parameters. Then, we performed a complete MI analysis on 396 realizations and constructed the inverse mapping from informative responses to each of the selected parameters using a deep neural network. Compared with calibration using observations covering all time steps, the new inverse mapping improves parameter estimations, thus enhancing the performance of ATS forward model runs. The Nash–Sutcliffe efficiency (NSE) of streamflow predictions increases from 0.53 to 0.8 when calibrating against Q alone. Using ET observations, on the other hand, does not show much improvement on the performance of ATS modeling mainly due to both the uncertainty of the remotely sensed product and the insufficient coverage of the model ET ensemble in capturing the observation. By using observed Q only, we further performed a multiyear analysis and show that Q is best simulated (NSE > 0.8) by including in the calibration the dry-year flow dynamics that show more sensitivity to subsurface characteristics than the other wet years. Moreover, when continuing the forward runs till the end of 2021, the calibrated models show similar simulation performances during this evaluation period as the calibration period, demonstrating the ability of the estimated parameters in capturing climate sensitivity. Our success highlights the importance of leveraging data-driven knowledge in DL-assisted hydrological model calibration.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1986

1985 International Geoscience and Remote Sensing Symposium (IGARSS '85), University of Massachusetts, Amherst, October 7-9, 1985, Proceedings

Papers are presented on an EM subsurface radar based on the transient field radiated by a wire antenna; the microwave dielectric, structural, and salinity properties of simulated sea ice; the extraction of sea-ice data from satellite SAR imagery, and the probing of thick vegetation canopies with a field microwave scatterometer. Also discussed are the bidirectional reflectance modeling of a conifer forest canopy, a microwave dielectric model for aggregated soils, and the estimation of soil hydraulic parameters with passive microwave data.

Carver, K. R.↗