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At least 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Developing High-Throughput Organ-on-a-Chip Models to Investigate the Effects of Ionizing Radiation on the Central Nervous System

One of the main health risks in human space exploration is central nervous system (CNS) damage by ionizing radiation due to exposure to the galactic cosmic rays (GCRs). In animal models, irradiation with simulated GCRs or their components has been shown to cause neuronal damage and neuroinflammation associated with cognitive and behavioral dysfunction. In general, the extent of CNS damage is partially regulated by the blood-brain barrier (BBB), which enables immune cells to enter the CNS. The main cellular regulators of BBB permeability are astrocytes, which also modulate neuronal death, immune responses and oxidative stress, and thus could serve as a robust CNS-specific target for countermeasure development. However, studies on BBB permeability and astrocyte functions in regulating CNS responses to ionizing radiation have been limited, especially in human tissue/organ analogs. Therefore, we established a high-throughput 3D organ-on-a-chip system to study human CNS and BBB impairments in response to ionizing radiation, based on commercially available OrganoPlates (Mimetas, Inc.) seeded with primary or induced pluripotent stem cell-derived human cells. We investigated both immediate and delayed CNS responses to major GCR components: 0.15-0.5 Gy 250MeV/n 4-He, and 0.3-0.8 Gy 600 MeV/n 56-Fe; as well as to 0.5-1 Gy X-rays. We observed ionizing radiation-mediated increases in BBB permeability that was exacerbated by astrocyte presence and accompanied by morphological changes in endothelial cells and tight junctions, altered cytokine profile including TNFa upregulation, and increased oxidative stress. We also quantified irradiation-mediated changes in astrocyte activation and neuronal functions, revealing major astrocyte damage mediated by 600MeV/n 56-Fe particles. Thus, we demonstrate that deep space radiation may contribute to CNS damage by disrupting both astrocyte and endothelial cell components of the blood-brain barrier. Our next steps include mapping and validating the transcriptomic changes induced by simulated GCRs and their components in human CNS models. Ultimately, we aim to uncover potential novel targets for countermeasure developments to mitigate CNS damage in long duration spaceflight.

Radiation↗
DOE OSTI2024

Structural Characterization of Disulfide-Linked p53-Derived Peptide Dimers

Disulfide bonds provide a convenient method for chemoselective alteration of peptide and protein structure and function. We previously reported that mild oxidation of a p53-derived bisthiol peptide (CTFANLWRLLAQNC) under dilute non-denaturing conditions led to unexpected disulfide-linked dimers as the exclusive product. The dimers were antiparallel, significantly α-helical, resistant to protease degradation, and easily reduced back to the original bisthiol peptide. Here, in this work, we examine the intrinsic factors influencing peptide dimerization using a combination of amino acid substitution, circular dichroism (CD) spectroscopy, and X-ray crystallography. CD analysis of peptide variants suggests critical roles for Leu6 and Leu10 in the formation of stable disulfide-linked dimers. The 1.0 Å resolution crystal structure of the peptide dimer supports these data, revealing a leucine-rich LxxLL dimer interface with canonical knobs-into-holes packing. Two levels of higher-order oligomerization are also observed in the crystal: an antiparallel “dimer of dimers” mediated by Phe3 and Trp7 residues in the asymmetric unit and a tetramer of dimers mediated by Trp7 and Leu10. In CD spectra of Trp-containing peptide variants, minima at 227 nm provide evidence for the dimer of dimers in dilute aqueous solution. Importantly, and in contrast to the original dimer model, the canonical leucine-rich core and robust dimerization of most peptide variants suggests a tunable molecular architecture to target various proteins and evaluate how folding and oligomerization impact various properties, such as cell permeability.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Electrochemical Measurement of Water Transport Numbers in Anion-Exchange Membranes

Anion-exchange membranes (AEMs) are a possible replacement for perfluorosulfonic-acid membranes in energy-conversion devices, primarily due to the hydroxide mobile ion allowing the devices to operate in alkaline conditions with less expensive electrocatalysts. However, the transport properties of AEMs remain understudied, especially electro-osmosis. In this work, an electrochemical technique, where the open-circuit voltage is measured between two ends of a membrane maintained at different relative humidities, is used to determine the water transport number of various ionomers, including Versogen and Sustainion AEMs and Nafion cation-exchange membrane (CEM), as a function of water content and temperature. In addition, the CEMs and AEMs are examined in differing single-ion forms, specifically proton and sodium (CEM) and hydroxide and carbonate (AEM). Carbonate-form AEMs have the highest transport number (∼11), followed by sodium-form CEMs (∼8), hydroxide-form AEMs (∼6), and proton-form CEMs (∼3). Finally, a multicomponent transport model based on the Stefan-Maxwell-Onsager framework of binary interactions is used to develop a link between water transport number and water-transport properties, extracting a range for the unmeasured membrane water permeability of Versogen as a function of water content.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2024

Jurassic deserts and CO2 sequestration: the Glen Canyon Group in Utah, western USA

The Early Jurassic in the Western Interior of USA consisted of an extensive desert environment, including one of the largest ergs in geologic history. The Navajo erg has been estimated to extend as much as 2.2 million square kilometers, though the preserved extent is somewhat smaller. The Mesozoic was a global greenhouse phase, and during the Jurassic this region experienced fluctuations in climate aridity, reflected in the depositional environment. In addition to extensive dunefields, interdune deposits (lakes and oases) and fluvial systems are also documented within formations of the Glen Canyon Group. The Navajo Sandstone has received much attention as a potential CO2 injection target in recent years. It consists of thick, aeolian sandstones with high porosity and permeability, occurs in both outcrop and subcrop, and has industry data. Mapping of stratigraphic and sedimentologic changes within the Navajo Sandstone has been undertaken in localized areas, however piecing together these studies and developing regional models for CO2 potential has not received as much attention. There is significant industry data across Utah, and utilizing this data to pivot from a focus on hydrocarbon extraction to CO2 injection is an effective way to move forward with green energy, and to meet carbon neutral emission goals. Using legacy well data, we are developing a more comprehensive study of the Navajo Sandstone as a potential CO2 reservoir, in addition to identifying other zones of interest within the Glen Canyon Group, and improving understanding of stratigraphic complexity within one of the most significant aeolian systems in the world.

Mahon, Elizabeth↗
NASA NTRSDate not supplied

Updates to PATO’s Thermo-Mechanical Model

The solid mechanics module within the Porous material Analysis Toolbox (PATO) material response code was updated to model the stress contribution from both internal pressure and pyrolysis shrinkage as function of material’s decomposition. Incorporating these physical phenomena, alongside the previously included temperature dependent mechanical properties, thermal expansion, and aerodynamic loads, allows for a more accurate thermo-mechanical behavior modeling of Thermal Protection System (TPS) materials, which is critical to assess spallation risks during atmospheric entry. This poster outlines the workflow for obtaining the necessary PATO inputs, derived from dilatometry experiments, which are used to model the stress field in TPS materials due to thermal expansion and pyrolysis shrinkage. Furthermore, to analyze the relevance of the stress contribution from the internal pressure, a study was conducted using TACOT with different permeability values.

TPS↗
DOE OSTI2021

Computationally Efficient Multiscale Neural Networks Applied to Fluid Flow in Complex 3D Porous Media

Abstract The permeability of complex porous materials is of interest to many engineering disciplines. This quantity can be obtained via direct flow simulation, which provides the most accurate results, but is very computationally expensive. In particular, the simulation convergence time scales poorly as the simulation domains become less porous or more heterogeneous. Semi-analytical models that rely on averaged structural properties (i.e., porosity and tortuosity) have been proposed, but these features only partly summarize the domain, resulting in limited applicability. On the other hand, data-driven machine learning approaches have shown great promise for building more general models by virtue of accounting for the spatial arrangement of the domains’ solid boundaries. However, prior approaches building on the convolutional neural network (ConvNet) literature concerning 2D image recognition problems do not scale well to the large 3D domains required to obtain a representative elementary volume (REV). As such, most prior work focused on homogeneous samples, where a small REV entails that the global nature of fluid flow could be mostly neglected, and accordingly, the memory bottleneck of addressing 3D domains with ConvNets was side-stepped. Therefore, important geometries such as fractures and vuggy domains could not be modeled properly. In this work, we address this limitation with a general multiscale deep learning model that is able to learn from porous media simulation data. By using a coupled set of neural networks that view the domain on different scales, we enable the evaluation of large ( $$>512^3$$ > 512 3 ) images in approximately one second on a single graphics processing unit. This model architecture opens up the possibility of modeling domain sizes that would not be feasible using traditional direct simulation tools on a desktop computer. We validate our method with a laminar fluid flow case using vuggy samples and fractures. As a result of viewing the entire domain at once, our model is able to perform accurate prediction on domains exhibiting a large degree of heterogeneity. We expect the methodology to be applicable to many other transport problems where complex geometries play a central role.

36 MATERIALS SCIENCE↗
NASA NTRS2002

Formation of ferrihydrite and associated iron corrosion products in permeable reactive barriers of zero-valent iron

Ferrihydrite, which is known to form in the presence of oxygen and to be stabilized by the adsorption of Si, PO4 and SO4, is ubiquitous in the fine-grained fractions of permeable reactive barrier (PRB) samples from the U.S. Coast Guard Support Center (Elizabeth City, NC) and the Denver Federal Center (Lakewood, CO) studied by high-resolution transmission electron microscopy and selected area electron diffraction. The concurrent energy-dispersive X-ray data indicate a strong association between ferrihydrite and metals such as Si, Ca, and Cr. Magnetite, green rust 1, aragonite, calcite, mackinawite, greigite and lepidocrocite were also present, indicative of a geochemical environment that is temporally and spatially heterogeneous. Whereas magnetite, which is known to form due to anaerobic Fe0 corrosion, passivates the Fe0 surface, ferrihydrite precipitation occurs away from the immediate Fe0 surface, forming small (<0.1 microm) discrete clusters. Consequently, Fe0-PRBs may remain effective for a longer period of time in slightly oxidized groundwater systems where ferrihydrite formation occurs compared to oxygen-depleted systems where magnetite passivation occurs. The ubiquitous presence of ferrihydrite suggests that the use of Fe0-PRBs may be extended to applications that require contaminant adsorption rather than, or in addition to, redox-promoted contaminant degradation.

Metals/chemistry↗
DOE OSTI2023

High-Performance Hemofiltration via Molecular Sieving and Ultra-Low Friction in Carbon Nanotube Capillary Membranes

Conventional dialyzer membranes typically comprise of unevenly distributed polydisperse, tortuous, rough pores, embedded in relatively thick ≈20–50 µm polymer layers wherein separation occurs via size exclusion as well as differences in diffusivity of the permeating species. However, transport in such polymeric pores is increasingly hindered as the molecule size approaches the pore dimension, resulting in significant retention of undesirable middle molecules (≥15–60 kDa) and uremic toxins. Enhanced removal of middle molecules is usually accompanied by high albumin loss (≈66 kDa) causing hypoalbuminemia. Here, the scalable bottom-up fabrication of wafer-scale carbon nanotube (CNT) membranes with highly aligned, low-friction, straight-channels/capillaries and narrow pore-diameter distributions (≈0.5–4.5 nm) is demonstrated, to overcome persistent challenges in hemofiltration/hemodialysis. Using fluorescein isothiocyanate (FITC)-Ficoll 70 and albumin in phosphate buffered saline (PBS) as well as in bovine blood plasma, it is shown that CNT membranes can allow for significantly higher hydraulic permeability (more than an order of magnitude when normalized to pore area) than commercial high-flux hemofiltration/hemodialysis membranes (HF 400), as well as greatly enhance removal of middle molecules while maintaining comparable albumin retention. These findings are rationalized via an N-pore transport model that highlights the critical role of molecular flexing and deformation during size-selective transport within nanoscale confinements of the CNTs. In conclusion, the unique transport characteristics of CNTs coupled with size-exclusion and wafer-scale fabrication offer transformative advances for hemofiltration, and the obtained insight into molecular transport can aid advancements in several other bio-systems/applications beyond hemofiltration/hemodialysis.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Geologic hydrogen: From natural occurrences to anthropogenic generation – A review of fundamentals, potential, challenges and prospects

Growing demand for hydrogen is exposing the environmental and economic limits of reforming-based and carbon-managed supply chains, while the scale-up of electrolytic capacity remains capital-constrained. Geologic hydrogen, defined as molecular H₂ generated and stored within the Earth's crust offers a complementary, potentially lower-cost resource, yet exploration is still ad hoc. This review (1) revisits a global inventory of confirmed hydrogen seeps and subsurface occurrences; (2) analyzes the controlling reactions, migration pathways, and trapping conditions governing these occurrences; (3) proposes a process-based geologic hydrogen system concept analogous to, yet distinct from, the petroleum system; and (4) evaluates potential geologic hydrogen systems within the United States as a representative case study. Here, we contrast natural systems powered by serpentinization, mantle degassing or radiolysis with anthropogenic systems that stimulate the same reactions or convert in-situ hydrocarbons. Stable hydrogen accumulations require generation rates that outpace combined physical, chemical and microbial losses; the Bourakébougou field (Mali) exemplifies a self-recharging, free-gas reservoir sustained by meteoric-water serpentinization beneath an efficient caprock. Prospective geologic hydrogen resources are likely to occur in regions where iron-rich lithologies, deep-seated faults, and low-permeability sealing formations coexist. Applying this principle, we highlight three promising hydrogen play types in U.S. geological terrains: ophiolite belts (Appalachian and Californian regions), the Midcontinent Rift and the Lake Superior banded‑iron formations. Multiphysics numerical models and positive-unlabeled machine-learning workflows help to accelerate play screening and de-risk future production; yet, reaction kinetics, stimulation strategies, and full techno-economic and life-cycle assessments remain pivotal knowledge gaps.

Anthropogenic hydrogen generation↗
DOE OSTI2024

Modeling with uncertainty quantification reveals the essentials of a non-canonical algal carbon-concentrating mechanism

The thermoacidophilic red alga Cyanidioschyzon merolae survives its challenging environment likely in part by operating a carbon-concentrating mechanism (CCM). Here, we demonstrated that C. merolae 's cellular affinity for CO 2 is stronger than the affinity of its rubisco for CO 2 . This finding provided additional evidence that C. merolae operates a CCM while lacking the structures and functions characteristic of CCMs in other organisms. To test how such a CCM could function, we created a mathematical compartmental model of a simple CCM, distinct from those we have seen previously described in detail. The results of our modeling supported the feasibility of this proposed minimal and non-canonical CCM in C. merolae . To facilitate the robust modeling of this process, we measured and incorporated physiological and enzymatic parameters into the model. Additionally, we trained a surrogate machine-learning model to emulate the mechanistic model and characterized the effects of model parameters on key outputs. This parameter exploration enabled us to identify model features that influenced whether the model met the experimentally derived criteria for functional carbon concentration and efficient energy usage. Such parameters included cytosolic pH, bicarbonate pumping cost and kinetics, cell radius, carboxylation velocity, number of thylakoid membranes, and CO 2 membrane permeability. Our exploration thus suggested that a non-canonical CCM could exist in C. merolae and illuminated the essential features generally necessary for CCMs to function.

Steensma, Anne K. [Michigan State Univ., East Lans↗
DOE OSTI2020

Numerical Simulations of Gas Production from Gas Hydrate Reservoirs at the Prudhoe Bay Unit 7-11-12 Pad on Alaska North Slope

In December 2018, a partnership between the U.S. Department of Energy National Energy Technology Laboratory (DOE NETL), the Japan Oil, Gas and Metals National Corporation (JOGMEC), and the U.S. Geological Survey (USGS) successfully drilled and logged the Hydrate-01 Stratigraphic Test Well (STW) in the greater Prudhoe Bay oil field on Alaska North Slope. The logging-while-drilling (LWD) data confirmed the presence of gas hydrate-bearing reservoirs within two sand reservoirs (Unit B and Unit D) that are suitable targets for future testing. The interpreted log data and core sample measurements were used to create reservoir models for the Prudhoe Bay Unit (PBU) Kuparuk 7-11-12 Site. The models combine both gas hydrate-bearing sections in Unit B and Unit D together with the intermediate Unit C and over- and underburden sands and shales. The vertical heterogeneity in porosity, gas hydrate saturation, and permeability distributions for reservoir and non-reservoir units was implemented using fine mesh discretization. The depressurization method was applied to Unit B to induce gas hydrate destabilization at constant bottom hole pressure (BHP) values. The results of the numerical simulations support the development of production scenarios, well design, surface facilities, and field test procedures with the main goal to perform efficient and safe scientific production testing. Project results contribute to the knowledge base of permafrost-associated gas hydrate accumulations as a future energy source.

Myshakin, Evgeniy↗
DOE OSTI2023

Electron tomography unravels new insights into fiber cell wall nanostructure; exploring 3D macromolecular biopolymeric nano-architecture of spruce fiber secondary walls

Lignocellulose biomass has a tremendous potential as renewable biomaterials for fostering the “bio-based society” and circular bioeconomy paradigm. It requires efficient use and breakdown of fiber cell walls containing mainly cellulose, hemicellulose and lignin biopolymers. Despite their great importance, there is an extensive debate on the true structure of fiber walls and knowledge on the macromolecular nano-organization is limited and remains elusive in 3D. We employed dual-axis electron tomography that allows visualization of previously unseen 3D macromolecular organization/biopolymeric nano-architecture of the secondary S2 layer of Norway spruce fiber wall. Unprecedented 3D nano-structural details with novel insights into cellulose microfibrils (~2 nm diameter), macrofibrils, nano-pore network and cell wall chemistry (volume %) across the S2 were explored and quantified including simulation of structure related permeability. Matrix polymer association with cellulose varied between microfibrils and macrofibrils with lignin directly associated with MFs. Simulated bio-nano-mechanical properties revealed stress distribution within the S2 and showed similar properties between the idealized 3D model and the native S2 (actual tomogram). Present work has great potential for significant advancements in lignocellulose research on nano-scale understanding of cell wall assembly/disassembly processes leading to more efficient industrial processes of functionalization, valorization and target modification technologies.

3-D reconstruction↗
DOE OSTI2023

Semi-Analytical Leakage Solutions for Aquifers (SALSA) v1

SALSA is a semi-analytical modeling tool that can provide assessments of pressure perturbations and brine leakage because of fluid injection and extraction activities in sedimentary basins. Sedimentary basins typically contain vertical sequences of near-horizontal aquifers separated by less-permeable aquitards. In the context of geologic carbon sequestration (GCS), while aquitards are relied upon to contain injected buoyant free-phase CO2 and limit inter-aquifer brine flow, the large number of leaky wells (e.g., unused/unsuccessful exploration wells, or improperly plugged water or oil/gas wells) that are present in sedimentary basins creates concerns for potential leakage and groundwater contamination. The mathematical theory and solution method included in SALSA is presented in our recent manuscript under review. SALSA is the first to account for the coupled leakage through aquitards and leaky wells, with geologic pressurization sources. SALSA based on semi-analytical solutions can be computationally very efficient for problems containing many injection and leaky wells in multilayered sedimentary systems, compared to any numerical simulation software requiring local mesh refinement around each well to obtain accurate results. Therefore, stakeholders (e.g., regulators, operators) for site screening, injection and post-injection pressure behavior and assessing leakage risks can use SALSA as a fast-predictive tool in GCS applications in multilayered aquifer systems.

Cihan, Abdullah↗
DOE OSTI2022

A Brief Overview of Reactive Transport Codes Used in CO 2 Applications

Reactive transport modelling consists of computational and numerical models that describe the coupled physical, chemical, mechanical, and biological processes interacting with each other over a broad range of spatial and temporal scales. This report reviews some of the reactive transport codes available in the literature for carbon dioxide (CO 2 ) applications and can assist the scientific community with the applicability of each code to solve a specific problem. Approaches implemented in these codes can be categorized in three groups: (i) continuum-scale, (ii) pore-scale, and (iii) hybrid-scale approaches. Theoretical foundations, numerical implementations, and application examples using the models are described. In the continuum approach, flow and transport are formulated in terms of a representative control volume of the medium and coupled with geochemical reactions. The medium is characterized by bulk parameters such as porosity, permeability, or reactive surface area. In the pore-scale approach, each point of space in the pore network is occupied by either a fluid or solid phase. The pore-scale approach requires an exact knowledge of the spatial and temporal phase distribution. In the hybrid-scale approach, media are described by multiple characteristic length-scales, with some regions using a pore-scale approach while others used a continuum approach.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2025

Roughrider Carbon Storage Hub (Final Report)

The Roughrider Carbon Storage Hub was a 2-year project (October 2023 – September 2025) conducted by the Energy & Environmental Research Center (EERC) focused on advancing the feasibility of a commercial-scale carbon dioxide (CO 2 ) geologic storage hub in McKenzie County, North Dakota. The project’s objective was to investigate the potential that stacked storage complexes (multiple deep saline formations) can safely and economically store at least 50 million tonnes of CO 2 within 30 years. The captured CO 2 would be sourced from industrial emitters including project partner ONEOK, Inc.’s gas-processing plants and a planned gas-to-liquids facility. Drilling of the Roughrider 1 stratigraphic test well (14,979-ft total depth) was completed in November 2024. The wellbore intersected four candidate storage formations: Inyan Kara, Broom Creek, Mission Canyon, and Black Island–Deadwood. Operational challenges, including a stuck drill string, were resolved without long-term impact. A comprehensive logging and coring program was conducted, followed by successful well abandonment and site reclamation. Over 660 ft of 4-in. whole core was retrieved. Core plug samples were processed and analyzed for petrophysical and geochemical properties. Results confirmed promising porosity and permeability in the Inyan Kara and Broom Creek Formations and removal of the Mission Canyon and Black Island–Deadwood horizons from further investigation. Data derived from the logging and coring program were used to improve initial geologic models built from legacy data. CO 2 injection simulations showed that the Inyan Kara alone can feasibly store the target mass of CO 2 . Because of subtle differences in geologic structure and porosity trends between the formations, a stacked storage scenario using the Broom Creek and Inyan Kara Formations resulted in a larger overall plume area than using the Inyan Kara alone. Preliminary CO 2 pipeline routes from the industrial sources were mapped utilizing existing rights of way and evaluated for capacity and cost using U.S. Department of Energy Office of Fossil Energy and Carbon Management/National Energy Technology Laboratory models and U.S. Environmental Protection Agency emissions data. Integrating capture, transport, and storage cost estimates with policy incentives (e.g., 45Q credits) provided a total cost-per-ton analysis. Results indicate that the small scale of the volumes to be transported over the cumulative large distances does not support the project’s financial viability. However, the groundwork laid during this project from geological, regulatory, and social perspectives positions the Roughrider hub site as a promising candidate for commercial carbon storage in North Dakota, especially if the economy of scale is introduced for CO 2 transportation to the hub site.

01 COAL, LIGNITE, AND PEAT↗
NASA NTRS1986

Possible Mars brines - Equilibrium and kinetic considerations

To determine the fate of postulated near surface brines on Mars, the rate of H2O mass loss from subsurface brines was calculated as a function of latitude, depth, regolith porosity, eutectic temperature, and pore size. A model for a chemically reasonable brine that could reproduce Martian radar results was developed, and the escape rate of H2O molecules from such a brine was estimated. It is suggested that the presence of a low-permeability duricrust may be required to preserve such a brine for reasonable periods, and to prevent detection of an extensive subsurface system by the Viking MAWD instrument.

Zent, A. P.↗
DOE OSTI2026

Coupled Investigation of Fracture Permeability Impact on Reservoir Stress and Seismic Slip Behavior (Final Technical Report)

Enhanced Geothermal Systems (EGS) produce clean energy by circulating fluid through hot rock deep underground and bringing that heat to the surface to generate electricity. For this process to work reliably, fluids must be able to move efficiently through networks of natural or engineered fractures in the rock. Enhancing and maintaining subsurface permeability over time is essential for sustainable energy production. However, fluid injection changes the underground temperature, pressure, rock stress, and chemistry, which can alter permeability and sometimes trigger earthquakes. Predicting these interconnected processes remains a key challenge. To address this, we combined high-temperature laboratory experiments with high-fidelity simulations to better understand how fractures in geothermal reservoirs evolve over time. Our experiments measured how fractures respond to stress, slip, slip rate, and chemical reactions under geothermal conditions. These data were integrated into coupled thermal-hydrological-mechanical-chemical and earthquake (THMC+E) models tailored to the Utah FORGE site. The validated modeling framework improves predictions of reservoir performance and seismic response and helps guide operational decisions. This work reduces technical risk and strengthens the scientific foundation needed to make geothermal energy a reliable and scalable clean energy resource.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

Predictive Inverse Model for Advective Heat Transfer in a Short–Circuited Fracture: Dimensional Analysis, Machine Learning, and Field Demonstration

Identifying fluid flow maldistribution in planar geometries is a well–established problem in subsurface science/engineering. Of particular importance to the thermal performance of enhanced (or “engineered”) geothermal systems is identifying the existence of nonuniform (i.e., heterogeneous) permeability and subsequently predicting advective heat transfer. Here, machine learning via a genetic algorithm (GA) identifies the spatial distribution of an unknown permeability field in a two–dimensional Hele–Shaw geometry (i.e., parallel plates). The inverse problem is solved by minimizing the L2 norm between simulated residence time distribution (RTD) and measurements of an inert tracer breakthrough curve (BTC) (C–Dot nanoparticle). Principal component analysis (PCA) of spatially correlated permeability fields enabled reduction of the parameter space by more than a factor of 10 and restricted the inverse search to reservoir–scale permeability variations. Thermal experiments and tracer tests conducted at the mesoscale Altona Field Laboratory (AFL) demonstrate that the method accurately predicts the effects of extreme flow channeling on heat transfer in a single bedding–plane rock fracture. However, this is only true when the permeability distributions provide adequate matches to both tracer RTD and frictional pressure loss. Without good agreement to frictional pressure loss, it is still possible to match a simulated RTD to measurements, but subsequent predictions of heat transfer are grossly inaccurate. Here, the results of this study suggest that it is possible to anticipate the thermal effects of flow maldistribution, but only if both simulated RTDs and frictional pressure loss between fluid inlets and outlets are in good agreement with measurements.

42 ENGINEERING↗