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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

Establishing A Geologic Baseline of Cape Canaveral''s Natural Landscape: Black Point Drive

The goal of this project is to identify the process responsible for the formation of geomorphic features in the Black Point Drive area of Merritt Island National Wildlife Refuge/Kennedy Space Center (MINWR/KSC), northwest Cape Canaveral. This study confirms the principal landscape components (geomorphology) of Black Point Drive reflect interaction between surficial sediments deposited in association with late-Quaternary sea-level highstands and the chemical evolution of late-Cenozoic sub-surface limestone formations. The Black Point Drive landscape consists of an undulatory mesic terrain which dips westward into myriad circular and channel-like depression marshes and lakes. This geomorphic gradient may reflect: (1) spatial distinctions in the elevation, character or age of buried (pre-Miocene) limestone formations, (2) dissolution history of late-Quaternary coquina and/or (3) thickness of unconsolidated surface sediment. More detailed evaluation of subsurface data will be necessary before this uncertain0 can be resolved.

Parkinson, Randall W.↗
NASA NTRS2019

Saildrone Baja Field Campaign: A Comparison of Surface Meteorology with GEOS Products

The Saildrone Baja field campaign was an international effort to collect measurements across the air-sea interface for a 62-day period between April 11-June 11, 2018. The field campaign was executed using a saildrone, an unmanned surface vehicle (USV) carrying a comprehensive suite of instruments to measure meteorological, ocean surface, and subsurface data. We use these data to validate near-surface meteorology and ocean surface temperature fields in theGlobal Earth Observing System (GEOS). This is the first study using Saildrone data to validate GEOS products. As these USV platforms become more prevalent, they could be used to improve model representation of the air-sea interface variables.

Akella, Santha↗
DOE OSTI2024

EGS Reservoir Modeling for Developing Geothermal District Heating at Cornell University: Preprint

Cornell University is pursuing development of an enhanced geothermal system (EGS) for providing heating to its main campus in Upstate New York. A ~10,000 ft (~3 km) deep vertical observation well ("CUBO") was drilled in 2022 to characterize the subsurface using wellbore logging, borehole imaging, fluid sampling, mini-frac tests, coring and drill cutting analysis. Down-hole temperatures measured at 3 km depth are about 80 degrees C, sufficiently high for direct-use heating. The well drilled through generally low porosity and low permeability Paleozoic sedimentary formations and into metamorphic basement rock, encountered at about 9,400 ft depth. Leveraging subsurface data obtained through CUBO, we investigated technical feasibility and design requirements of a doublet well system with horizontal laterals connected to a fracture network created through hydraulic fracturing. The EGS reservoir is sized to provide a nominal heat output in the range 5 to 10 MWth of continuous heating over a 15 year-lifetime with limited thermal drawdown. We applied the Gringarten Multiple parallel fracture model, the Cornell Discrete Fracture Simulator FOXFEM and the commercial simulator ResFrac to estimate required heat transfer area and design a potential hydraulic stimulation treatment. Reservoir simulations indicate that, depending on fluid flow rate and injection temperature, 2 to 3 km2 of effective fracture heat transfer area is required to supply the target heat output of 5 to 10 MWth over 15 years.

district heating↗
DOE OSTI2025

EGS Reservoir Modeling for Developing Geothermal District Heating at Cornell University

Cornell University is pursuing development of an enhanced geothermal system (EGS) for providing heating to its main campus in Upstate New York. A ~10,000 ft (~3 km) deep vertical observation well ('CUBO') was drilled in 2022 to characterize the subsurface using wellbore logging, borehole imaging, fluid sampling, mini-frac tests, coring and drill cutting analysis. Down-hole temperatures measured at 3 km depth are about 80 degrees C, sufficiently high for direct-use heating. The well drilled through generally low porosity and low permeability Paleozoic sedimentary formations and into metamorphic basement rock, encountered at about 9,400 ft depth. Leveraging subsurface data obtained through CUBO, we investigated technical feasibility and design requirements of a doublet well system with horizontal laterals connected to a fracture network created through hydraulic fracturing. The EGS reservoir is sized to provide a nominal heat output in the range 5 to 10 MWth of continuous heating over a 15 year-lifetime with limited thermal drawdown. We applied the Gringarten Multiple parallel fracture model, the Cornell Discrete Fracture Simulator FOXFEM and the commercial simulator ResFrac to estimate required heat transfer area and design a potential hydraulic stimulation treatment. Reservoir simulations indicate that, depending on fluid flow rate and injection temperature, 2 to 3 km2 of effective fracture heat transfer area is required to supply the target heat output of 5 to 10 MWth over 15 years.

district heating↗
DOE OSTI2024

Exploring the Feasibility of a Carbon Dioxide Storage Hub in Western North Dakota

The University of North Dakota Energy & Environmental Research Center (EERC) and project partner ONEOK, Inc. (ONEOK) are investigating the feasibility of establishing a CO2 (carbon dioxide) storage hub in western North Dakota—in the heart of the Williston Basin. The conceived Roughrider Carbon Storage Hub would store CO2 captured from six gas-processing plants owned and operated by project partner ONEOK and a planned gas-to-liquids plant. This 2-year U.S. Department of Energy-sponsored Carbon Storage Assurance Facility Enterprise (CarbonSAFE) Phase II feasibility study is evaluating the aggregation of the CO2 captured from these seven sources for injection into stacked geologic storage complexes. The proposed hub includes several aspects that make it a highly qualified candidate for a feasibility study with a notably reduced project risk profile. These include 1) a project partner (ONEOK) with a committed goal to reduce greenhouse gas emissions; 2) prior subsurface data analysis supporting a potential stacked storage configuration with adequate CO2 storage resource; 3) commitment from local, regional, and state-level stakeholders; and 4) a state with U.S. Environmental Protection Agency underground injection control Class VI primacy. ONEOK’s assets in the Williston Basin provide significant environmental benefits by capturing and processing natural gas that may otherwise be flared or vented. Storing CO2 from these gas-processing facilities will reduce overall CO2 emissions in the basin while providing essential services to producers there and contributing to continued energy independence in the domestic markets.

03 NATURAL GAS↗
DOE OSTI2024

Filling in Subsurface Storage Open Data Gaps - Updates to CCS Data Availability on EDX and EDX Spatial (FWP-1022465)

There is a need to preserve and efficiently access data resources to drive the next generation of research and development while ensuring compliance with DOE regulations. Over the last 10+ years, there has been ongoing efforts by the DOE Carbon Storage Program to ensure that there is effective data curation and preservation of DOE funded research leveraging the NETL-FECM data repository, the Energy Data eXchange (EDX). This talk presents updates about ongoing efforts to continue to support the mission of ensuring that carbon storage data is findable, accessible, interoperable, and reusable to the carbon storage stakeholder community through EDX and EDX Spatial. Presented at the NETL Carbon Management Review Meeting, Pittsburgh, 2024.

Morkner, Paige↗
NASA NTRS2005

A Tower-based Prototype VHF/UHF Radar for Subsurface Sensing: System Description and Data Inversion Results

Knowledge of subsurface characteristics such as permittivity variations and layering structure could provide a breakthrough in many terrestrial and planetary science disciplines. For Earth science, knowledge of subsurface and subcanopy soil moisture layers can enable the estimation of vertical flow in the soil column linking surface hydrologic processes with that in the subsurface. For planetary science, determining the existence of subsurface water and ice is regarded as one of the most critical information needs for the study of the origins of the solar system. The subsurface in general can be described as several near-parallel layers with rough interfaces. Each homogenous rough layer can be defined by its average thickness, permittivity, and rms interface roughness assuming a known surface spectral distribution. As the number and depth of layers increase, the number of measurements needed to invert for the layer unknowns also increases, and deeper penetration capability would be required. To nondestructively calculate the characteristics of the rough layers, a multifrequency polarimetric radar backscattering approach can be used. One such system is that we have developed for data prototyping of the Microwave Observatory of Subcanopy and Subsurface (MOSS) mission concept. A tower-mounted radar makes backscattering measurements at VHF, UHF, and L-band frequencies. The radar is a pulsed CW system, which uses the same wideband antenna to transmit and receive the signals at all three frequencies. To focus the beam at various incidence angles within the beamwidth of the antenna, the tower is moved vertically and measurements made at each position. The signals are coherently summed to achieve focusing and image formation in the subsurface. This requires an estimate of wave velocity profiles. To solve the inverse scattering problem for subsurface velocity profile simultaneously with radar focusing, we use an iterative technique based on a forward numerical solution of the layered rough surface problem. The layers are each defined in terms of a small number of unknown distributions as given above. An a priori estimate of the solution is first assumed, based on which the forward problem is solved for the backscattered measurements. This is compared with the measured data and using iterative techniques an update to the solution for the unknowns is calculated. The process continues until convergence is achieved. Numerical results will be shown using actual radar data acquired with the MOSS tower radar system in Arizona in Fall 2003, and compared with in-situ measurements.

Moghaddam, Mahta↗
NASA NTRS1985

Geophysical Interpretation of Venus Gravity Data

The subsurface distribution of Venus was investigated through the analysis of the data from Pioneer Venus Orbiter (PVO). In particular, the Doppler tracking data were used to map the gravitational potential. These were compared to the topographic data from the PVO radar (ORAD). In order to obtain an unbiased comparison, the topography data obtained from the PVO-ORAD were filtered to introduce distortions which are the same as those of the gravity models. Both the gravity and filtered topography maps are derived by two stage processes with a common second stage. In the first stage, the topography was used to calculate a corresponding spacecraft acceleration under the assumptions that the topography has a uniform given density and no compensation. In the second stage, the acceleration measures found in the first stage were passed through a linear inverter to yield maps of gravity and topography. Because these maps are the result of the same inversion process, they contain the same distortion; a comparison between them is unbiased to first order.

Reasenberg, R. D.↗
DOE OSTI2026

A ModEx Framework for Watershed Subsurface Investigation With Limited Geophysical Data Using Machine Learning and Hydrologic Modeling

Abstract Subsurface heterogeneity influences watershed hydrology strongly but remains difficult to characterize at catchment scales with sparse and costly field data. Geophysical surveys such as electromagnetic induction (EMI) provide local spatial subsurface images yet scaling them to watershed scales and converting EMI‐derived resistivity into hydraulic properties remains a challenge. We present a Model–Experiment (ModEx) framework that integrates limited EMI data with machine learning (ML) and hydrologic modeling to improve process representation and guide field investigations. Sparse EMI surveys were scaled to the catchment scale using a Random Forest model, and the resulting resistivity fields were combined with nearby borehole constraints to parameterize a hydrologic model. The EMI‐informed hydrological simulations improved predictions of streamflow sustained by subsurface flow and shallow saturation patterns. By combining EMI data and ML with hydrologic modeling, the ModEx framework guides future subsurface surveys, providing a transferable and efficient strategy for data–model integration across diverse watersheds. Plain Language Summary Mapping the underground network of soil and rock that controls water is essential for predicting floods and droughts, but seeing underground is difficult and expensive. We cannot drill everywhere, so scientists use geophysical tools to scan broad areas. There are two key challenges: these geophysical scans are often sparse across the whole watershed, and the geophysical data is hard to translate into water‐related properties. We used artificial intelligence to solve these problems. We taught a computer to find patterns linking the limited geophysical data to the land surface properties. This allowed it to fill in the gaps and create a complete, useful subsurface map for the entire watershed. This new map improves hydrologic simulations, leading to more accurate predictions of water movement in the watershed. It also helps scientists build better models with less data and generates a priority map showing where to measure next, making future investigations more efficient. Key Points Limited EMI scaled with ML improves catchment‐scale subsurface parameterization for hydrologic models The framework integrates hydrologic modeling with limited geophysical data to support subsurface investigation design ModEx framework offers a transferable data–model integration strategy that quantifies and reduces uncertainty guiding watershed studies

Chen, Hang↗
DOE OSTI2024

Opportunities for Earth Observation to Inform Risk Management for Ocean Tipping Points

Abstract As climate change continues, the likelihood of passing critical thresholds or tipping points increases. Hence, there is a need to advance the science for detecting such thresholds. In this paper, we assess the needs and opportunities for Earth Observation (EO, here understood to refer to satellite observations) to inform society in responding to the risks associated with ten potential large-scale ocean tipping elements: Atlantic Meridional Overturning Circulation; Atlantic Subpolar Gyre; Beaufort Gyre; Arctic halocline; Kuroshio Large Meander; deoxygenation; phytoplankton; zooplankton; higher level ecosystems (including fisheries); and marine biodiversity. We review current scientific understanding and identify specific EO and related modelling needs for each of these tipping elements. We draw out some generic points that apply across several of the elements. These common points include the importance of maintaining long-term, consistent time series; the need to combine EO data consistently with in situ data types (including subsurface), for example through data assimilation; and the need to reduce or work with current mismatches in resolution (in both directions) between climate models and EO datasets. Our analysis shows that developing EO, modelling and prediction systems together, with understanding of the strengths and limitations of each, provides many promising paths towards monitoring and early warning systems for tipping, and towards the development of the next generation of climate models.

Wood, Richard A. (ORCID:0000000239609513)↗
NASA NTRSDate not supplied

Future Orbiting and In-Situ Exploration of Venus: Mount Etna as Terrestrial Analog

The exploration of Venus will soon experience a new golden era thanks to the recently selected NASA Deep Atmosphere of Venus Investigation of Noble gases, Chemistry and Imaging (DAVINCI) mission, NASA Venus Emissivity, Radio Science, InSAR, Topography & Spectroscopy (VERITAS) mission, and ESA EnVision mission. The DAVINCI mission will focus on the analysis of the the atmospheric vertical structure and composition of Earth’s twin planet and on the geologic structure of a tesserae terrain. The VERITAS mission will investigate the geologic features of its surface as well as geodynamic characteristics of the subsurface, providing high-resolution emissivity data, a global radar map at an approximate resolution of 30 meters/pixel, and estimation of the gravity anomaly of the shallow crust of the planet. The ESA EnVision mission will be complementary to the two NASA missions, providing high resolution 0.8-2.5 micron emissivity data, Synthetic Aperture Radar (SAR) data, and Subsurface Radar Sounder (SRS) data. Beyond those, the proposed Roscosmos-NASA Venera-D mission will also be equipped with an orbiter that will investigate the atmospheric composition and circulation, as well as a lander that will analize the in-situ chemical composition and the surface-atmosphere interactions.

P. D’Incecco↗
NASA NTRS1977

JPL field measurements at the Finney County, Kansas, test site, October 1976: Meteorological variables, surface reflectivity, surface and subsurface temperatures

Data collected at the Finney County, Kansas test site as part of the Joint Soil Moisture Experiment (JSME) are presented here, prior to analysis, to provide all JSME investigators with an immediate source of primary information. The ground-truth measurements were taken to verify and complement soil moisture data taken by microwave and infrared sensors during aircraft overflights. Measurements were made of meteorological variables (air speed, temperature, relative humidity, and rainfall), surface reflectivity, and temperatures at and below the surface.

Kahle, A. B.↗
NASA NTRS1983

Stratigraphy and structural evolution of southern Mare Serenitatis - A reinterpretation based on Apollo Lunar Sounder Experiment data

Two subsurface reflecting horizons have been detected by the Apollo Lunar Sounder Experiment (ALSE) in the southern Mare Serenitatis which appear to be regolith layers more than 2 m thick, and are correlated with major stratigraphic boundaries in the southeastern Mare Serenitatis. The present stratigraphic boundaries in the southeastern Mare Serenitatis. The present analysis implies that the lower horizon represents the interface between the earliest mare unit and the modified Serenitatis basin material below. The depth of volcanic fill within Serenitatis is highly variable, with an average thickness of mare basalts under the ALSE ground track of 1.6 km. Comparisons with the Orientale basin topography suggests that a major increaae in load thickness could occur a few km basinward of the innermost extent of the traverse. The history of volcanic infilling of Mare Serenitatis was characterized by three major episodes of volcanism.

Sharpton, V. L.↗
NASA NTRS1980

Temporal variations in regional models of the Sargasso Sea from GEOS-3 altimetry

The paper considers temporal variations in regional models of the Sargasso sea from GEOS-3 telemetry. The methods of regional models and the analysis of overlapping passes are utilized, and short-wave maxima and minima in the regional surface models are examined for correlations with surface and remote sensed infrared temperature data supplemented with subsurface expendable bathythermograph data (XBT). The analysis of overlapping passes provide a better picture of instanteneous sea surface height (SSH) variability through wavelengths greater than 30 km. Correlation studies with cyclonic and anticyclonic ocean eddies from infrared imagery and XBT data indicate satisfactory agreement with equivalent SSH features 98% of the time if the time varying factors are allowed for.

Mather, R. S.↗
DOE OSTI2024

Curating Carbon Storage Data for Reuse: Enabling Research and Modeling from Earth’s Surface to Subsurface

The volume of public geologic carbon storage (GCS) data resources has continued to increase in recent years as the result of an increase in funding from government, industry, and academia towards national, basin, regional and field scale studies to ensure carbon capture and storage becomes a commercially viable operation. Despite the increasing volume of data, GCS data applied towards analyses such as geologic, cost, and risk modeling continues to be multi-sourced and often disparate in nature, published across government agencies, websites, data repositories and buried in derivative reports and documents. Much of the time preparing for an analysis and derivative product development is spent collecting, aggregating, transforming and preparing input data. There have been significant efforts within the DOE National Energy Technology Laboratory’s Carbon Storage Program to optimize multi-source, multi-scale subsurface geologic data curation and aggregation to support data discovery, interoperability, and reuse. Methods include the use of artificial intelligence, machine learning, and data science techniques. This talk will discuss the workflows, best practices, and processes developed to support the aggregation and curation of data through the whole system – surface to subsurface data - that support multi-scale, multi-purpose analysis for carbon storage research.

Morkner, Paige↗
NASA NTRS2023

Subsurface Gravimetry Using Rover IMU Navigation Systems Data

Gravimetry is a valuable analytical tool for probing density distributions in the subsurface. Extraterrestrial data is currently limited to orbital collection, restricting spatial resolution to tens to hundreds of kilometers. Therefore, surface-based gravity surveys are necessary to study the gravity field and- lateral density variations at a finer scale. Traditional gravity sensors (gravimeters) are rare on science payloads owing to their relatively high mass, fragility, and cost. Inertial measurement units (IMU); however, are included on every rover platform to perform navigation and attitude determination. This project aims to solve this issue by demonstrating the utility in recalibrating the accelerometers contained within an IMU to measure the static acceleration of gravitational fields and, by extension, gravity anomalies induced by subsurface density variations.

Chandler Lawson↗
DOE OSTI2024

Subsurface Energy Systems Mapping Inquiry Tool (MapIT)

The Subsurface Energy Systems Mapping Inquiry Tool (MapIT) is an online web mapping tool designed to help users discover available public-sourced data to facilitate data exploration for subsurface energy exploration and characterization efforts for resource identification (e.g. critical minerals, hydrocarbons, geothermal) as well as injection of geologic sequestration of carbon dioxide (e.g. enhanced oil recovery, saline storage, etc.). Modules within the tool curate data related to geology, faults, fractures, injection and confining zones, hydrologic information, groundwater, groundwater wells, geomechanical and petrophysical data, and geochemical data. User documentation on how to use the tool is also provided. Data have been collected from authoritative national, state, and local sources and made available in this tool. The data is also available as a data catalog and Esri Geodatabase at: https://edx.netl.doe.gov/dataset/mapit-database Disclaimer: There is no guarantee of completeness or appropriateness for individual user’s requirements. Use of this tool is solely at the discretion of the user. See full Federal Disclaimer for further information (https://netl.doe.gov/home/disclaimer). This project was funded by the United States Department of Energy, National Energy Technology Laboratory, in part, through a site support contract. Neither the United States Government nor any agency thereof, nor any of their employees, nor the support contractor, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. https://www.netl.doe.gov/home/disclaimer

Carbon Sequestration↗
NASA NTRS2020

Hawai'i Water Resources: Utilizing NASA Earth Observations to Assess Ocean Conditions Leading to the Spread of the Nuisance Red Algae (Chondria tumulosa) in Papahānaumokuākea Marine National Monument, Hawai’i

Chondria tumulosa, a newly discovered red alga, was observed in low abundance in 2016 but has since proliferated and is now smothering and decimating vast expanse of coral reefs in Manawai, located in Papahānaumokuākea Marine National Monument (PMNM). If the spread persists, the outbreak of this cryptogenic species could potentially cause region-wide ecosystem degradation. In coordination with the U.S. Fish and Wildlife Service, Marine National Monuments of the Pacific and the National Oceanographic and Atmospheric Administration (NOAA) Office of National Marine Sanctuaries’ Papahānaumokuākea Marine National Monument, this project created a tool to analyze oceanographic conditions (sea surface temperature (SST), chlorophyll-a, water velocity, salinity, turbidity) across the Monument that could potentially be driving the algal spread. The Google Earth Engine tool enabled the partners to visualize oceanographic conditions and gather time-series graphs utilizing Aqua and Terra Moderate Resolution Imaging Spectroradiometer (MODIS), Suomi National Polar-orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS), Sentinel-3 Ocean and Land Colour Instrument (OLCI), Hybrid Coordinate Ocean Model (HYCOM) and NOAA's Climate Data Record in a user-friendly interface. The team used in situ SST data from subsurface temperature recorders provided by the partners to validate the tool's accuracy. Preliminary statistical analysis of MODIS data found warming trends in SST in Manawai as well as increased chlorophyll-a levels during the summer months in contrast to the control (non-infected) Lalo atoll. The tool did not aim to classify algal presence due to limited availability of higher resolution satellite imagery but instead enabled PMNM managers to monitor conditions that may be conducive to algal growth around the monument to make informed decisions and mitigation practices.

DEVELOP Project Summary↗