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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
NASA NTRS2022

Rapid Radiolytic Degradation of Amino Acids in the Martian Shallow Subsurface: Implications for the Search for Extinct Life

Amino acids are fundamental to life as we know them as the monomers of proteins and enzymes. They are also readily synthesized under a variety of plausible prebiotic conditions and are common in carbon-rich meteorites. Thus, they represent a reasonable class of organics to target in the search for prebiotic chemistry or chemical evidence of life on Mars. However, regardless of their origin, amino acids and other organic molecules present in near-surface regolith and rocks on Mars can be degraded by exposure to cosmic rays that can penetrate to a depth of a few meters. We exposed several pure amino acids in dry and hydrated silicate mixtures and in mixtures of silicates with perchlorate salts to gamma radiation at various temperatures and radiation doses representative of the martian near-subsurface. We found that irradiation of amino acids mixed with dry silica powder increased the rate of amino acid radiolysis, with the radiolysis constants of amino acids in silicate mixtures at least a factor of 10 larger compared with the radiolysis constants of amino acids alone. The addition of perchlorate salts to the silicate samples or hydration of silicate samples further accelerated the rate of amino acid destruction during irradiation and increased the radiolysis constants by a factor of *1.5. Our results suggest that even low-molecular-weight amino acids could degrade in just *20 million years in the top 10 cm of the martian surface regolith and rock, and even faster if the material contains elevated abundances of hydrated silicate minerals or perchlorates. We did not detect evidence of amino acid racemization after gamma radiation exposure of the samples, which indicates that the chirality of some surviving amino acids may still be preserved. Our experimental results suggest serious challenges for the search of ancient amino acids and other potential organic biosignatures in the top 2 m of the martian surface.

Alexander A. Pavlov↗
NASA NTRSDate not supplied

Impact Of Rotation on the Sun’s Subsurface Structure

It is well known that the dynamical evolution of subsurface flows of the Sun and magnetic fields is strongly linked to rotation. Observational investigation of sub surface structuring and dynamics can be performed only with relatively low resolution using helioseismic inversion techniques. To confidently model the coupling of turbulent convection, magnetic fields, and rotation in the solar interior, we perform advanced radiative hydrodynamic and MHD modeling of local scales. To explore the coupling effects in the upper layers of the convection zone, we present results of analysis from a series of hydrodynamic simulations performed for a 25-Mm-deep computational domain at different latitudes obtained for 1) the Carrington rotation rate at all latitudes and 2) the realistic rotation rate from the global helioseismic inversions during the solar minimum. Using additional 3D radiative hydrodynamic models, we reveal how physical properties of the solar convection are affected by rotation.

Heliophysics↗
DOE OSTI2020

Microbial sensor system for the assessment of subsurface environments

A microbial sensor, system, and method that can be used to determine a chemical environment and/or substrate concentrations in anaerobic or aerobic environments, such as soils, sediments and ground waters, are disclosed. An exemplary system uses one or more (e.g., inert) measurement electrodes and a reference electrode. The reference electrode can include an electrode exposed to atmospheric oxygen (e.g., a cathode) or an electrode exposed to stable anaerobic or aerobic conditions. The exemplary microbial sensor system measures open-circuit voltage to characterize the chemical (oxidizing or reducing) environment and/or recovery voltage to measure substrate concentrations in the subsurface.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Apparatus and method for dynamic acousto-elasticity technique measurements at simulated subsurface pressures

An apparatus (10) and method for performing nonlinear elasticity measurements using the dynamic acousto-elasticity technique (DAET) at simulated subsurface conditions in the laboratory, are described. The current state-of-the-art for measuring nonlinear elasticity parameters using DAET is limited to ambient pressure conditions on the bench-top. The present invention permits nonlinear parameter measurements at controlled sample internal fluid pore pressures (52) and external confining stress (44), (50) conditions.

Roberts, Peter M.↗
DOE OSTI2020

Initial Field Testing in the Deep Subsurface for the Thermal Breakout Project for Measuring In Situ Stress

The current state-of-the-art technology for in situ stress measurements involves an integrated approach that combines borehole breakout observations, drilling-induced tensile fractures, and hydraulic fracturing tests (i.e., mini-fracs); however, this methodology has several limitations that often prevent successful in situ stress measurements. One major limitation is that breakouts do not appear in every borehole and are generally a natural occurrence that cannot easily be controlled. Because borehole breakouts are used to measure the maximum horizontal in situ stress magnitude, the absence of borehole breakouts presents a major data gap for in situ stress measurements. As a response to this data gap a new thermal breakout technology is being developed that will provide a method for thermally inducing borehole breakouts and obtaining consistent measurements of the maximum horizontal stress magnitude. This thermal breakout technology involves heating the borehole and increasing the thermoelastic compressive stress in the rock until a breakout develops, which is directly correlated to the maximum horizontal stress magnitude. An initial component of the thermal breakout project involves developing a prototype downhole tool and performing field testing in the deep subsurface. The primary objective of the initial tool development and field testing is to provide a physical proof of concept for the thermal breakout technology. Three thermal breakout field tests were performed at approximately 4850 feet deep in the Sanford Underground Research Facility. Each test was performed in a borehole that had been previously used for overcoring stress measurements. The third and final test successfully created two diametrically opposed breakouts after deploying the thermal breakout tool for approximately 3 hours of continuous heating. Post-analysis of the thermally induced breakouts confirmed that the thermal breakout orientation directly corresponds to the known in situ stress orientation and magnitude.

Voegeli, Sam↗
DOE OSTI2022

Machine learning-enabled model-data integration for predicting subsurface water storage

Subsurface water storage (SWS) is a key variable of the climate system and a storage component for precipitation and radiation anomalies, inducing persistence in the climate system. It plays a critical role in climate-change projections and can mitigate the impacts of climate change on ecosystems. However, because of the difficult accessibility of the underground, hydrologic properties and dynamics of SWS are poorly known. Direct observations of SWS are limited, and accurate incorporation of SWS dynamics into Earth system land models remains challenging. We propose a machine learning-enabled model-data integration framework to improve the SWS prediction at local to conus scales in a changing climate by leveraging all the available observation and simulation resources, as well as to inform the model development and guide the observation collection. The accurate prediction will enable an optimal decision of water management and land use and improve the ecosystem's resilience to the climate change.

Lu, Dan↗
DOE OSTI2022

Coupling subsurface and above-surface models for optimizing the design of borefields and district heating and cooling systems in the presence of varying water-table depth. In: Proceedings, 46th Workshop on Geothermal Reservoir Engineering

Dynamic energy simulation is important for the design and sizing of district heating and cooling systems with geothermal heat exchange. Current modeling approaches in building and district energy simulation tools typically consider heat conduction through the ground between boreholes, without flow of groundwater. On the other hand, detailed simulation tools for subsurface heat and mass transfer exist, but these fall short in simulating above-surface energy systems. To support the design and operation of such systems, we have developed a coupled model including a software package for building and district energy simulation, and software for detailed heat and mass transfer in the ground. For the first, we use the open-source Modelica Buildings Library, which includes dynamic simulation models for building and district energy and control systems. For the heat and mass transfer in the soil, we use the TOUGH simulator. TOUGH can model heat and multi-phase, multi-component mass transport for a variety of fluid systems, as well as chemical reactions, in fractured porous media. In previous work, we described the coupling of these software packages, including how time-dependent boundary conditions for the borehole walls are synchronized for use in Modelica and TOUGH. We verified that the coupled Modelica/TOUGH code produced consistent results with the original Modelica code for an idealized problem in which heat transfer was purely by conduction in a uniform geologic medium. Here, we examine less idealized problems for which TOUGH’s advanced capabilities for modeling fluid flow are required. The first problem has a shallow vadose zone, and the second problem has a thicker vadose zone with a water-table depth that varies in time, which requires a fine vertical grid discretization for the TOUGH model.

Doughtry, Christine↗
DOE OSTI2021

System and method for optimizing hydrocarbon production from subsurface reservoirs

A method is described for subsurface hydrocarbon reservoir characterization including receiving a time-lapse electromagnetic (EM) dataset and a flow dataset; inverting the time-lapse EM dataset using a parametric inversion that models steel well casings to determine a volume of fluid-changed reservoir; inverting the time-lapse EM dataset and the flow dataset using a joint inversion that honors the volume of the fluid-changed reservoir to determine relative permeability and capillary pressure; and characterizing flow characteristics in the volume of the fluid-changed reservoir. The method may be executed by a computer system.

Hoversten, Gary Michael↗
DOE OSTI2022

System and method thermopile energy harvesting for subsurface well bore sensors

A system and method for powering a borehole sensor with thermal energy is disclosed. The system includes a tubular pipe inserted into a subsurface borehole. A borehole casing is coaxially disposed with the tubular pipe. An annular space between the casing and the tubular pipe has a power source placed in the borehole to power a sensor in response to a temperature gradient between a surface of the casing and a surface of the tubular pipe. The method includes attaching thermopiles on the borehole casing or tubing; placing the thermopile in the annulus between the casing and the tubing; inducing a thermal gradient across the thermopile; generating an electrical energy in response to the temperature gradient; powering the sensor from the generated energy; and monitoring vertical expansion of a CO2 plume.

Bryan, Charles R.↗
DOE OSTI2023

Microbial sensor system for the assessment of subsurface environments

A microbial sensor, system, and method that can be used to determine a chemical environment and/or substrate concentrations in anaerobic or aerobic environments, such as soils, sediments and ground waters, are disclosed. An exemplary system uses one or more (e.g., inert) measurement electrodes and a reference electrode. The reference electrode can include an electrode exposed to atmospheric oxygen (e.g., a cathode) or an electrode exposed to stable anaerobic or aerobic conditions. The exemplary microbial sensor system measures open-circuit voltage to characterize the chemical (oxidizing or reducing) environment and/or recovery voltage to measure substrate concentrations in the subsurface.

Burge, Scott R.↗
DOE OSTI2020

Hydrologic Modeling of Subsurface Brine Density Stratification for Deep Borehole Disposal - 20213

Density-dependent and topographically-driven subsurface brine flow was modeled in regional-scale and Deep Borehole Disposal-scale domains under varying conditions. These conditions included variable basement permeability, brine density, and hydraulic head. Findings revealed the possibility of hydraulic isolation of deep basement for at least 1 million years under appropriate conditions, which supports the viability of the Deep Borehole Disposal concept. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Calibration and Uncertainty Estimation Using the Ensemble Kalman Filter with a Large Subsurface Flow and Transport Model - 20321

At routinely monitored groundwater contamination sites, periodically measured environmental conditions such as groundwater levels and contaminant concentrations are used to inform and confirm a conceptual site model (CSM) and guide the development and calibration of a numerical groundwater flow and transport model. The calibration of groundwater flow and transport models after each measurement (sampling) event can illuminate deficiencies in a CSM, identify areas where additional monitoring is warranted, and predict the behavior of the system to guide decision making. However, manual and automated (e.g. PEST) model calibration tools can be time-consuming and computationally expensive to implement after each sampling event. Perhaps as a result, such calibration tools generally utilize all available monitoring data simultaneously rather than sequentially assimilating monitoring data one sampling event at a time as the results from sampling become available. A more real-time data assimilation approach may reduce parameter uncertainty, quantify the value of additional monitoring data, and produce a usable model more quickly and with less effort. To mitigate the potential time-consuming aspects of manual and widely applied automated calibration techniques, a data assimilation algorithm called the ensemble Kalman filter (EnKF) was evaluated as a relatively efficient method of model calibration and uncertainty assessment via the sequential integration of monitoring data into a model. The EnKF was able to successfully and efficiently assimilate monitoring and modeling data to calibrate a complex flow and transport model at a real-world site with significant subsurface heterogeneity, uncertainty, and 12 years of monitoring data (over 4,000 individual measurements of groundwater levels and over 2,500 measurements of contaminant concentrations). Starting with an uncalibrated model data from annual sampling events were sequentially assimilated, and the resultant predication errors and estimated parameter uncertainties were tracked. After all monitoring data were assimilated, both flow and transport residuals at the end of the EnKF process were comparable to those produced via a concurrent PEST calibration effort but required fewer model simulations. Both uncertainty and prediction errors decreased over time. In a real-time application, the adequacy of the model could be assessed after each sampling event. The benefits of such a real-time approach to utilizing monitoring data include reduced costs (in the form of model updates or site characterization efforts), early flagging of possible errors in the CSM, and a reduced risk of overfitting and corresponding increased confidence in model predictions. This tool may be particularly useful compared to other calibration techniques (e.g. manual, PEST) when model runtimes are long, calibration parameters are many, or parameter uncertainty is large. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

An assessment of controlled source EM for monitoring subsurface CO 2 injection at the wyoming carbonSAFE geologic carbon storage site

Here we evaluate if electromagnetic (EM) geophysical methods for monitoring geologic carbon storage (GCS) efforts at the Wyoming CarbonSAFE project adjacent to the Dry Fork Station power plant near Gillette, Wyoming. This first involved acquiring both electric and magnetic fields at eleven different locations ranging in distance from immediately adjacent to 4 km from the plant. Passive EM measurements were made to provide spectral EM noise measurements generated by electricity production at the plant and to determine if useful magnetotelluric (MT) data can be successfully collected in the region. The processed data indicate that useful MT data can be collected as long as the site is located more than 2km away from the power plant as well as active roads and rail lines. Controlled source EM data were collected using three different source configurations, two of which connected to steel casings used to complete the injection wells. Comparing the EM noise measurements to the CSEM data show measurable electric and magnetic field signals at all sites. Next a series of three-dimensional (3D) numerical models were built that simulate resistivity changes caused by the proposed CO2 injection at depths ranging from 2.4 to 3.0km. These models were used to simulate various EM measurement configurations. The modeling shows that casing-source CSEM monitoring can provide sensitivity to the injected CO 2 if source electrodes are connected to the bottom of one or both of the injection wells.

58 GEOSCIENCES↗
DOE OSTI2024

Diverse and unconventional methanogens, methanotrophs, and methylotrophs in metagenome-assembled genomes from subsurface sediments of the Slate River floodplain, Crested Butte, CO, USA

We use metagenome-assembled genomes (MAGs) to understand single-carbon (C1) compound-cycling—particularly methane-cycling—microorganisms in montane riparian floodplain sediments. We generated 1,233 MAGs (>50% completeness and <10% contamination) from 50- to 150-cm depth below the sediment surface capturing the transition between oxic, unsaturated sediments and anoxic, saturated sediments in the Slate River (SR) floodplain (Crested Butte, CO, USA). We recovered genomes of putative methanogens, methanotrophs, and methylotrophs (n = 57). Methanogens, found only in deep, anoxic depths at SR, originate from three different clades (Methanoregulaceae, Methanotrichaceae, and Methanomassiliicoccales), each with a different methanogenesis pathway; putative methanotrophic MAGs originate from within the Archaea (Candidatus Methanoperedens) in anoxic depths and uncultured bacteria (Ca. Binatia) in oxic depths. Genomes for canonical aerobic methanotrophs were not recovered. Ca. Methanoperedens were exceptionally abundant (~1,400× coverage, >50% abundance in the MAG library) in one sample that also contained aceticlastic methanogens, indicating a potential C1/methane-cycling hotspot. Ca. Methylomirabilis MAGs from SR encode pathways for methylotrophy but do not harbor methane monooxygenase or nitrogen reduction genes. Comparative genomic analysis supports that one clade within the Ca. Methylomirabilis genus is not methanotrophic. The genetic potential for methylotrophy was widespread, with over 10% and 19% of SR MAGs encoding a methanol dehydrogenase or substrate-specific methyltransferase, respectively. MAGs from uncultured Thermoplasmata archaea in the Ca. Gimiplasmatales (UBA10834) contain pathways that may allow for anaerobic methylotrophic acetogenesis. Overall, MAGs from SR floodplain sediments reveal a potential for methane production and consumption in the system and a robust potential for methylotrophy.

58 GEOSCIENCES↗
DOE OSTI2023

Closed Loop Geothermal Working Group: GeoCLUSTER App, Subsurface Simulation Results, and Publications

To better understand the heat production, electricity generation performance, and economic viability of closed-loop geothermal systems in hot-dry rock, the Closed-Loop Geothermal Working Group -- a consortium of several national labs and academic institutions has tabulated time-dependent numerical solutions and levelized cost results of two popular closed-loop heat exchanger designs (u-tube and co-axial). The heat exchanger designs were evaluated for two working fluids (water and supercritical CO2) while varying seven continuous independent parameters of interest (mass flow rate, vertical depth, horizontal extent, borehole diameter, formation gradient, formation conductivity, and injection temperature). The corresponding numerical solutions (approximately 1.2 million per heat exchanger design) are stored as multi-dimensional HDF5 datasets and can be queried at off-grid points using multi-dimensional linear interpolation. A Python script was developed to query this database and estimate time-dependent electricity generation using an organic Rankine cycle (for water) or direct turbine expansion cycle (for CO2) and perform a cost assessment. This document aims to give an overview of the HDF5 database file and highlights how to read, visualize, and query quantities of interest (e.g., levelized cost of electricity, levelized cost of heat) using the accompanying Python scripts. Details regarding the capital, operation, and maintenance and levelized cost calculation using the techno-economic analysis script are provided. This data submission will contain results from the Closed Loop Geothermal Working Group study that are within the public domain, including publications, simulation results, databases, and computer codes. GeoCLUSTER is a Python-based web application created using Dash, an open-source framework built on top of Flask that streamlines the building of data dashboards. GeoCLUSTER provides users with a collection of interactive methods for streamlining the exploration and visualization of an HDF5 dataset. The GeoCluster app and database are contained in the compressed file geocluster_vx.zip, where the "x" refers to the version number. For example, geocluster_v1.zip is Version 1 of the app. This zip file also contains installation instructions. **To use the GeoCLUSTER app in the cloud, click the link to "GeoCLUSTER on AWS" in the Resources section below. To use the GeoCLUSTER app locally, download the geocluster_vx.zip to your computer and uncompress this file. When uncompressed this file comprises two directories and the geocluster_installation.pdf file. The geo-data app contains the HDF5 database in condensed format, and the GeoCLUSTER directory contains the GeoCLUSTER app in the subdirectory dash_app, as app.py. The geocluster_installation.pdf file provides instructions on installing Python, the needed Python modules, and then executing the app.

15 GEOTHERMAL ENERGY↗