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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Active Seismoelectric Monitoring of CO 2 Injection

Conference presentation at Carbon Capture, Utilization, and Storage (CCUS) Conference 2024, Houston, Texas, March 11–13, 2024. We investigated the use of active seismoelectric monitoring (ASE) to determine its effectiveness in detecting CO 2 injected deep underground and as an additional monitoring option for carbon storage projects. The EERC performed an ASE survey in February of 2023 at Pennel oil field near Baker, Montana, as part of the U.S. Department of Energy-sponsored Williston Basin CO 2 Field Laboratory in conjunction with operating partner Denbury Inc. The field site is part of the Cedar Creek Anticline geologic structure, with CO 2 planned for injection into a stacked storage complex (SSC) in the Interlake Formation containing both a residual oil zone and a conventional reservoir. The objective was to test the ASE method’s ability to characterize baseline fluid distribution in both the near surface and the SSC prior to CO 2 injection.

04 OIL SHALES AND TAR SANDS↗
DOE OSTI2026

Two-component dynamics in supercritical $\text {CO}_2$ from inelastic X-ray scattering

Supercritical fluids are characterized by unique thermodynamic properties. One of these properties is the existence of two-component dynamics that is associated with distinct low-frequency and high-frequency vibrational responses of the fluid. However, the origin of this behavior remains unknown. By combining inelastic X-ray scattering and molecular dynamics simulations, we show that this behavior can be connected to density heterogeneities arising from molecular clusters. Analyses of measurements and molecular trajectories suggest that the two-component dynamics emerges due to distinct momentum fluctuations of clustered and unbound molecules. This connection between clusters and two-component dynamics highlights the importance of molecular-structural heterogeneities in supercritical fluids, colloids, and condensed-matter systems.

biophysics↗
DOE OSTI2021

Nanopore networks in colloidal silica assemblies characterized by XCT for confined fluid flow modeling

Fluid flow through nanopore structures has exhibited different behavior than that described by Darcy's law, derived from pore networks of micrometer scale. Here, pressure assemblies of colloidal silica spheres of specified diameters from 94 to 620 nanometers were prepared as model nano-porous media. The smaller silica spheres tended to form random packing, but some substantial ordering was found in the packing of the larger silica spheres. X-ray computed tomography (XCT), with a voxel resolution of 16 nm, was used to characterize the nanopore networks. The porosity of the Nano-XCT pore network (34%) was less than the total porosity of the assemblies as determined by X-ray attenuation (52%), possibly due to the limits of voxel resolution during segmentation. Fluid flow in the nanopore networks was simulated using the single-phase Lattice Boltzmann Method, and the simulated permeability was compared with the empirical and experimental values. Based on our characterization, although a well-ordered packing of silica spheres was not achieved, it was found that the nanopore networks in the colloidal silica assemblies had pore size distributions corresponding to the particle sizes. The simulated permeability was less than the experimental measurement for water flow, but the complex packing of silica spheres and surface chemistry issues need to be considered in future research.

02 PETROLEUM↗
DOE OSTI2023

Embedding hard physical constraints in neural network coarse-graining of three-dimensional turbulence

In recent years, deep learning approaches have shown much promise in modeling complex systems in the physical sciences. A major challenge in deep learning of partial differential equations is enforcing physical constraints and boundary conditions. In this work, we propose a general framework to directly embed the notion of an incompressible fluid into convolutional neural networks, and apply this to coarse-graining of turbulent flow. These physics-embedded neural networks leverage interpretable strategies from numerical methods and computational fluid dynamics to enforce physical laws and boundary conditions by taking advantage the mathematical properties of the underlying equations. Here, we demonstrate results on three-dimensional fully developed turbulence, showing that this technique drastically improves local conservation of mass, without sacrificing performance according to several other metrics characterizing the fluid flow.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Potential Challenges of HyBlend Storage in a Methane Reservoir Located in Southwestern United States

Hydrogen has been identified as a flexible energy carrier with zero or negative emissions across multiple energy systems. It is possible to utilize hydrogen by storing Hyblend, or hydrogen gas blended with methane, in existing natural gas infrastructure. However, the compatibility of adapting the current CH4 storage strategies to include H2 injection has not been fully demonstrated. It is essential that we understand the impact of H2 gas on the naturally occurring microbial community of subsurface storage reservoirs before deploying large-scale H2-CH4 storage. We designed a series of experiments that allowed us to identify potential geochemical and microbial challenges of HyBlend Storage in existing methane reservoirs. First, we collected and characterized field fluid samples from a methane reservoir located in southwestern United States. Next, we used these field fluid samples to complete a series of short-term reactor experiments at reservoir conditions (80 °C and ~1,000 psi) for a natural gas (100% CH4) and HyBlend(80% CH4/20% H2) storage environment to measure the transformation of gas content. We conducted both biotic and abiotic (sterilized) measurements to accurately understand and decouple abiotic and microbially driven processes. Overall, we found that our field sample was characterized by a diverse microbial community with the metabolic capacity for sulfur reduction, iron reduction, and acetogenesis. Across our reactors, there was minimal change in geochemistry.

hydrogen storage↗
DOE OSTI2023

Theory and simulations of linear and nonlinear two-dimensional Rayleigh–Taylor dynamics with variable acceleration

Interfacial Rayleigh–Taylor mixing is crucial to describing important natural and engineering processes, such as exploding supernovae, laser micromachining, hot spots in inertial confinement fusion, and optical telecommunications. These require the characterization of the time dependence of the driving acceleration. We compare our theoretical formulation based on group theory foundations with interface-capturing numerical simulations for linear and nonlinear two-dimensional Rayleigh–Taylor instabilities in a finite-sized domain with time-varying acceleration over broad ranges of Atwood numbers and acceleration exponents. Detailed corroboration between theory and simulations is provided for this foundational case. Both demonstrate the strong interfacial nature of Rayleigh–Taylor instabilities, which suggests that practical flow fields can be reconstructed from the derived fluid potential using the proposed theory. A robust agreement is also obtained for the early and late-time evolution of the amplitudes of the bubble and spike, which demonstrate that the Rayleigh–Taylor flow can transition to the mixing regime even for a single-mode initial perturbation. Corroboration with experiments of high energy density plasmas motivated by studies of supernovae is also achieved. In addition, a long-standing puzzle in Rayleigh–Taylor dynamics on the interplay between the acceleration, the shear, and the interface morphology in the theory and simulations is resolved by accounting for finite viscosity of the fluids. The characterization of Rayleigh–Taylor instabilities as a highly interfacial phenomenon provides valuable insight into its multiscale nature, which enhances the design and understanding of numerous processes of practical interest.

42 ENGINEERING↗
DOE OSTI2024

PYSIMFRAC: A Python library for synthetic fracture generation and analysis

In this paper, we introduce PYSIMFRAC, an open-source python library for generating 3-D synthetic fracture realizations, integrating with fluid simulators, and performing analysis. PYSIMFRAC allows the user to specify one of three fracture generation techniques (Box, Gaussian, or Spectral) and perform statistical analysis including the autocorrelation, moments, and probability density functions of the fracture surfaces and aperture. This analysis and accessibility of a python library allows the user to create realistic fracture realizations and vary properties of interest. In addition, PYSIMFRAC includes integration examples to two different pore-scale simulators and the discrete fracture network simulator, dfnWorks. The capabilities developed in this work provides opportunity for quick and smooth adoption and implementation by the wider scientific community for accurate characterization of fluid transport in geologic media. We present PYSIMFRAC along with integration examples and discuss the ability to extend PYSIMFRAC from a single complex fracture to complex fracture networks.

58 GEOSCIENCES↗
DOE OSTI2020

Geologic Characterization for CO 2 Storage with Enhanced Oil Recovery in Northern Michigan

The Midwest Regional Carbon Sequestration Partnership (MRCSP) was founded in 2003 as part of the U.S. Department of Energy’s (DOE’s) Regional Carbon Sequestration Partnership initiative. Since its founding, MRCSP has made significant strides toward making CCUS a viable option for states in the region. The public/private consortium, funded through the DOE Regional Carbon Sequestration Initiative, brings together nearly 40 industry partners and 10 states. Battelle, as the project lead, oversees research, development and operations and coordinates activities among the partners. The incremental, phased approach has built a valuable knowledge base for the industry and paved the way for commercial-scale adoption of CCUS technologies. From 2008 to 2020, MRCSP Phase III focused on the development of large-scale injection projects. This report is part of a series of reports prepared under the Midwestern Regional Carbon Sequestration Partnership (MRCSP) Phase III (Development Phase). These reports summarize and detail the findings of the work conducted under the Phase III project. This report compiles the results of geologic characterization of late-stage reefs, active EOR reefs, and new EOR reefs in the Northern Niagaran Pinnacle Reef Trend (NNPRT) in Michigan to demonstrate developed methodologies, geologic variability, and reservoir potential for CO 2 storage. Conducting CO 2 injection and monitoring in these settings provide significant insights for addressing the project objectives: assessment of injectivity in complex carbonate reef deposits; assessing CO 2 trapping mechanisms in a closed reservoir system; assessing any final oil recovery from transitional or residual oil zones in a field where CO 2 flooding is nearing completion; evaluating the transition from EOR to storage of CO 2 ; assessing regional commercialization; assessing new technologies for tracking CO 2 , brine, and oil movements underground; and monitoring options in a closed reservoir with oil, residual oil, and water zones.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2020

Quantitative Protein Corona Composition and Dynamics on Carbon Nanotubes in Biological Environments

When nanoparticles enter biological environments, proteins adsorb to form the "protein corona" which alters nanoparticle biodistribution and toxicity. Herein, we measure protein corona formation on DNA-functionalized single-walled carbon nanotubes (ssDNA-SWCNTs), a nanoparticle used widely for sensing and delivery, in blood plasma and cerebrospinal fluid. We characterize corona composition by mass spectrometry, revealing high-abundance corona proteins involved in lipid binding, complement activation, and coagulation. We investigate roles of electrostatic and entropic interactions driving selective corona formation. Lastly, we study real-time protein binding on ssDNA-SWCNTs, obtaining agreement between enriched proteins binding strongly and depleted proteins binding marginally, while highlighting cooperative adsorption mechanisms. Knowledge of protein corona composition, formation mechanisms, and dynamics informs nanoparticle translation from in vitro design to in vivo application.

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

Spatial heterogeneity analyses of pore structure and mineral composition of Barnett Shale using X-ray scattering techniques

The spatial heterogeneity of pore structure and mineral composition at mu m to mm scales in mm to cm-sized shale samples complicates the laboratory measurements of porosity & pore size distribution and consequently reservoir quality evaluation. Traditional fluid invasion characterization methods typically take hours to days to get data and can only test relatively small samples (usually 2.54 cm diameter core plugs and mm-sized rock chips). Furthermore, the Xray scattering techniques at the Advanced Photon Source of the Argonne National Laboratory have the capability to non-destructively determine the pore structure and mineral composition of mm x mm area in a short time of seconds and to hold several to hundreds of mm 2 sized sample to conduct large area heterogeneity analysis in the short duration of hours. With the use of ultra-small angle X-ray scattering (USAXS), small-angle X-ray scattering (SAXS), and wide-angle X-ray scattering (WAXS), the porosity, surface area and pore size distribution of two Barnett Shale samples have been mapped out and the mineral compositions are determined qualitatively. Overall, the porosity and pore surface area of the Barnett Shale Sample A over a 36 cm2 area ranges from 1.70 % to 8.13 % and 8.87 m 2 /g to 40.2 m 2 /g respectively. The porosity and surface area of Sample B over a 24 cm 2 area varies from 3.15 % to 11.7 % and 18.3 m 2 /g to 60.2 m 2 /g. In Sample A, the mineral composition shows a shift from carbonate-rich to siliciclastic-rich over a distance of several millimeters. For Sample B, the mineral compositions are mainly siliciclastic and do not show an obvious lithological change. The direct observations of high spatial heterogeneity of pore structure and mineral composition in shale illustrate the utility of integrated X-ray scattering techniques to provide valuable insights into shale studies and reservoir evaluation.

58 GEOSCIENCES↗
DOE OSTI2021

Quantification of Dissolved O 2 in Bulk Aqueous Solutions and Porous Media Using NMR Relaxometry

Effects of dissolved paramagnetic oxygen (O 2 ) in water on 1 H nuclear magnetic resonance (NMR) Carr-Purcell-Meiboom-Gill (CPMG) experiments is evaluated at a 1 H Larmor frequency of 2 MHz. Dissolution of O 2 into water significantly reduces the 1 H transverse relaxation coefficient (T 2 ). For deoxygenated water, T 2 is 3388 ms, water at ambient atmospheric conditions (7.4 mg/L O2) exhibits a T2 of 2465 ms, and dissolution of 2710 mg/L O 2 further reduces T 2 to 36 ms. The results were fit with an empirical model to facilitate prediction of T 2 times for bulk water as a function of paramagnetic oxygen concentrations in solution. Dissolved O 2 also greatly influences 1 H NMR CPMG experiments of confined water in a model system composed of Berea sandstone. For this system, 90 mg/L O 2 in H 2 O enhances T 2 relaxation of bulk water such that the relaxation time is comparable to physically confined water in the sandstone pores. Given the sensitivity of NMR T 2 coefficients to paramagnetic oxygen, low-field NMR-based characterization of fluid and porous media structure requires control of dissolved oxygen, as geospatial variation in the partial pressure of O 2 alone is expected to perturb fluid and pore relaxation times by up to 60 and 36%, respectively.

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

Active liquid crystals powered by force-sensing DNA-motor clusters

Significance Single-molecule techniques have elucidated how isolated molecular motors generate piconewton forces with unprecedented detail. However, in diverse biological and synthetic settings, force-generating proteins collectively power nonequilibrium dynamics, including continuous large-scale rearrangements and persistent fluid flows. Characterizing motor-generated forces in these dense and dynamical environments remains a challenge. We assembled a reversible DNA-based force-sensing probe that, by an optical readout, reveals the molecular arrangements and the force loads experienced by kinesin motors. These probes provide insight into motor-generated forces that collectively power the unique dynamics of microtubule-based active nematics, a noteworthy example of an internally driven active matter system. DNA-based force probes can be extended to study forces and stresses in various synthetic systems as well as diverse cellular environments.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Space Nuclear Power Autonomous Control Algorithm and Control Element Test Bed

Nuclear thermal rockets are currently NASA’s preferred option for use in a manned mission to Mars in the 2040s. The communication delay between an Earth ground station and a spacecraft heading toward Mars can be up to 20 min. Therefore, controlling the nuclear rocket engine would require either a full-time reactor operator on the mission or an autonomous control system for the reactor. The latter idea of making space nuclear reactors fully autonomous has drawn more interest from stakeholders, but such an autonomous control system must be rigorously tested and validated before it is certified for human use. The cost of a full ground test for a space nuclear reactor is tremendous, so a nonnuclear mock reactor test bed was created to test and validate control elements and control algorithms for space nuclear reactors. The test bed consists of control element hardware that inputs physical measurement data into a reactor emulator to produce the reactor’s performance under steady-state, transient, and fault conditions. The control element hardware consists of six full-sized control drums equipped with servo drives and motors and is instrumented with optical encoders, resolvers, and torque sensors for drum movement characterization. In addition to the drums, a two-phase flow loop was designed and built to mimic the valves and turbomachinery associated with the propellant flow through a nuclear thermal rocket engine; components such as pressure sensors, flow meters, thermocouples, and tachometers are instrumented throughout the loop to characterize the fluid flow, valve, and turbomachinery behavior of the system. The data from the physical hardware (e.g., drum position, propellant flow rates) are input to a nuclear reactor simulator to determine the actual nuclear reactor parameters, and the data are sent back to a control algorithm to complete the control loop. The ability to conduct numerous tests of the control systems and autonomous algorithms can help validate the instrumentation and control aspects for a space nuclear reactor for every possible fault situation.

Wilson, Brandon↗
DOE OSTI2021

Modeling Contact Angle vs. Temperature for the Quartz-Water-Decane System

Innovative approaches are needed to improve the efficiency of oil recovery technologies to meet the growing demands of fossil-fuel based energy consumption. Enhanced oil recovery (EOR) methods such as low-salinity waterflooding and chemically tuned waterflooding aim to optimize the reservoir’s wetting properties, detaching oil globules from rock surfaces and allowing easier oil flow through pore throats. This wetting behavior is commonly quantified by contact angle measurements of the rock-oil-brine interface, which have been thoroughly investigated and theorized for many systems at ambient temperatures and pressures. However, few studies exist for extending contact angle theories away from ambient conditions. In this paper, we model the contact angles of a quartz-water-decane system at elevated temperatures using the surface tension component (STC) approach. Temperature-dependent van der Waals [Lifshitz-van der Waals (LW)] interactions and hydrogen-bonding (acid-base) interactions were calculated and are incorporated into the model for the quartz-water-decane interface. Additionally, the Hough and White procedure was used to create temperature-dependent dielectric functions of quartz, water, and normal decane for calculations of Hamaker coefficients. Hamaker coefficients calculated this way are highly linear with temperature and agree well with Israelachvili’s approximation. The acid-base interactions likely contribute the most to system wettability changes. Resulting contact angles of the quartz-water-decane system shift from water-wet (16°) to slightly water-wet (57.4°) as temperature increases. The model was also successfully verified for the quartz-air-water system. Our results can be used in future studies to determine optimal injected water compositions for specific rock-oil-brine and other systems with consideration of reservoir temperature.

02 PETROLEUM↗
DOE OSTI2022

Combustion Kinetics Model Development & Fluid Property Experimental Investigation For Improved Design Of Supercritical CO 2 Power Cycle Components

Supercritical carbon dioxide (sCO 2 ) cycles are being investigated for the future of power generation and will contribute to a carbon-neutral future to combat the effects of climate change. These direct-fired closed cycles will produce power without adding significant pollutants to the atmosphere. For such cycles to be efficient, they will need to operate at significantly higher pressures (e.g., 300 atm for Allam Cycle) than existing systems (typically less than 40 atm). There is limited knowledge on combustion at these high pressures and with a high dilution of carbon dioxide. Also, various experimental and computational investigations and model developments have been performed by the University of Central Florida (UCF), Embry-Riddle Aeronautical University (ERAU), and Stanford University (S.U.) to improve the current knowledge base and support the design and development of sCO 2 combustors. This project's technical aspects include chemical kinetics development, fundamental sCO 2 combustion, combustion model and sub-model development, supercritical fluid injection characterization, and heat transfer characterization.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2022

Induced microearthquakes predict permeability creation in the brittle crust

Predicting the evolution of permeability accurately during stimulation at the reservoir scale and at the resolution of individual fractures is essential to characterize the fluid transport and the reactive/heat-transfer characteristics of reservoirs where stress exerts significant control. Here, we develop a hybrid machine learning (ML) model to visualize in situ permeability evolution for an intermediate-scale (~10 m) hydraulic stimulation experiment. This model includes an ML model that was trained using the well history of flow rate and wellhead pressure and MEQ data from the first three stimulation episodes to predict average permeability from the statistical features of the MEQs alone for later episodes. Moreover, a physics-inspired model is integrated to estimate in situ fracture permeability spatially. This method relates fracture permeability to fracture dilation and scales dilation to the equivalent MEQ magnitude, according to laboratory observations. The seismic data are then applied to define incremental changes in permeability in both space and time. Our results confirm the excellent agreement between the ground truth and model-predicted permeability evolution. The resulting permeability map defines and quantifies flow paths in the reservoir with the averaged permeability comparing favorably with the ground truth of permeability.

induced seismicity↗