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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 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Impacts of Pore Network-Scale Wettability Heterogeneity on Immiscible Fluid Displacement: A Micromodel Study

The mixed-wet nature of reservoir formations imposes a wide range of rock wettability from strong resident-fluid wetting to strong invading-fluid wetting. The characteristics of two-phase flow in porous media composed of mixed-wetting surfaces remain poorly understood. In this study, we investigated the displacement of resident ethylene glycol (EG) by hexane in two mixed-wet micromodels of identical 2.5-D geometry heterogeneity, with uniformly or heterogeneously distributed patches strongly wetting to hexane. These patches are mixed among pores with unaltered EG-wetting surfaces. Along with control tests in the originally EG-wet micromodel, here we show the classic fingering and transitions in flow regimes at $logCa$ (capillary number) from -7.2 to -3.9. Moreover, pore-scale distributions of wettability and their spatial correlation influence displacement efficiency. In the two mixed-wet micromodels, we found (a) an increase of steady-state hexane saturation at the end of experiments by up to 0.12 in the capillary fingering regime and a decrease of at most by 0.06 in the viscous fingering regime, compared to the EG-wet micromodel, and (b) dispersed and fragmented hexane distribution after displacement. Brine drainage during supercritical CO 2 (scCO 2 ) injections in these micromodels occurs with lower wettability contrasts, and under similar viscosity ratios and interfacial tensions resulted in higher displacement efficiency relative to displacement of EG by hexane. While mixed-wettability can enhance displacement efficiency compared to uniform wettability, the dynamics of immiscible fluids in strong mixed-wet reservoirs are expected to be less pronounced in contributing to the efficiency of geological CO 2 sequestration, oil recovery, and remediation of hydrocarbon-contaminated aquifers.

2.5-D micromodel↗
DOE OSTI2025

Eocene-Oligocene Metamorphism, Fluid Flow and Deformation in the Ruby Mountains-East Humboldt Range Metamorphic Core Complex

Metamorphic core complexes are ubiquitous in collapsed orogens globally and play a primary role in crustal exhumation. Here, we investigate the metamorphic history of the Ruby Mountains-East Humboldt Range metamorphic core complex, Nevada, using petrochronology to understand how magmatism, metamorphism and deformation interact to modulate crustal rheology, and the timing of exhumation within the Sevier orogenic belt. Field study, microstructural analysis, thermobarometry and laser ablation split-stream monazite, titanite and allanite petrochronology of the mylonitic footwall were integrated to elucidate the pressure-temperature-time (P-T-t) evolution. Major-, trace-element and quartz-in-garnet thermobarometry show peak metamorphism occurred at 5.5–6 kbar and 600–650°C across the study area. Monazite and titanite U-(Th)-Pb petrochronology constrain this episode of metamorphism to 88–81 Ma with the structurally deepest samples yielding dates down to ca. 71 Ma. The preservation of peak metamorphic mineral assemblages indicates these rocks remained at near-peak temperature conditions into the Cenozoic. Cenozoic metamorphism occurred during a punctuated episode contemporaneous with the Great Basin ignimbrite flare up. All samples show a distinct 39–37 Ma population of monazite, titanite and allanite dates that correlate with the emplacement of quartz diorite and gabbro intrusions throughout the footwall. Accessory phases contain zoning textures in backscattered electron images that are consistent with fluid-mediated dissolution-reprecipitation reactions. The U-(Th)-Pb analyses from these zones yield 39–27 Ma dates interpreted as the timing of fluid flow. The results of this study elucidate the integrated importance of magmatism, melting and fluid flow in driving the coupled evolution of Late Cretaceous metamorphism within the Sevier hinterland and the subsequent Cenozoic metamorphic core complex development that exhumed the middle crust.

58 GEOSCIENCES↗
DOE OSTI2026

WellPINN: Accurate Well Representation for Transient Fluid Pressure Diffusion in Subsurface Reservoirs With Physics‐Informed Neural Networks

Accurate representation of pumping wells is essential for reliable reservoir characterization and simulation of operational scenarios in subsurface flow models. Physics-informed neural networks (PINNs) are emerging as a promising alternative to numerical models for reservoir modeling, offering seamless integration of monitoring data and governing physical equations. However, existing PINN-based studies face major challenges in capturing fluid pressure near wells when using a source/sink term, particularly during the early stages after pumping begins. We address this problem by introducing WellPINN, a workflow in which an initially trained PINN infers fluid pressure across the entire reservoir domain using a large equivalent well radius. This initial PINN solution is then locally refined around the well by a set of subdomain PINNs that are trained for smaller equivalent well radii. Continuity across these subdomain interfaces as well as at the initial condition is ensured by hard-constraining each PINN on its subdomain boundary. Our results demonstrate WellPINN as the first workflow of its kind to focus on accurate inference of fluid pressure from pumping rates throughout the entire injection period, significantly advancing the potential of PINNs for inverse modeling and operational scenario simulations. All data and code for this paper are openly available at https://doi.org/10.20350/DIGITALCSIC/17260.

58 GEOSCIENCES↗
DOE OSTI2022

Transient evolution of permeability and friction in a slowly slipping fault activated by fluid pressurization

The mechanisms of permeability and friction evolution in a natural fault are investigated in situ. During three fluid injection experiments at different places in a fault zone, we measured simultaneously the fluid pressure, fault displacements and seismic activity. Changes in fault permeability and friction are then estimated concurrently. Results show that fault permeability increases up to 1.58 order of magnitude as a result of reducing effective normal stress and cumulative dilatant slip, and 19-to-60.8% of the enhancement occurs without seismic emissions. When modeling the fault displacement, we found that a rate-and-state friction and a permeability dependent on both slip and slip velocity together reasonably fit the fault-parallel and fault-normal displacements. This leads to the conclusion that the transient evolution of fault permeability and friction caused by a pressure perturbation exerts a potentially dominant control on fault stability during fluid flow.

58 GEOSCIENCES↗
DOE OSTI2023

Supercritical fluids behave as complex networks

Abstract Supercritical fluids play a key role in environmental, geological, and celestial processes, and are of great importance to many scientific and engineering applications. They exhibit strong variations in thermodynamic response functions, which has been hypothesized to stem from the microstructural behavior. However, a direct connection between thermodynamic conditions and the microstructural behavior, as described by molecular clusters, remains an outstanding issue. By utilizing a first-principles-based criterion and self-similarity analysis, we identify energetically localized molecular clusters whose size distribution and connectivity exhibit self-similarity in the extended supercritical phase space. We show that the structural response of these clusters follows a complex network behavior whose dynamics arises from the energetics of isotropic molecular interactions. Furthermore, we demonstrate that a hidden variable network model can accurately describe the structural and dynamical response of supercritical fluids. These results highlight the need for constitutive models and provide a basis to relate the fluid microstructure to thermodynamic response functions.

42 ENGINEERING↗
DOE OSTI2020

Large-scale proteomic analysis of Alzheimer’s disease brain and cerebrospinal fluid reveals early changes in energy metabolism associated with microglia and astrocyte activation

Our understanding of Alzheimer’s disease (AD) pathophysiology remains incomplete. Here, for this work, we used quantitative mass spectrometry and coexpression network analysis to conduct the largest proteomic study thus far on AD. A protein network module linked to sugar metabolism emerged as one of the modules most significantly associated with AD pathology and cognitive impairment. This module was enriched in AD genetic risk factors and in microglia and astrocyte protein markers associated with an anti-inflammatory state, suggesting that the biological functions it represents serve a protective role in AD. Proteins from this module were elevated in cerebrospinal fluid in early stages of the disease. In this study of >2,000 brains and nearly 400 cerebrospinal fluid samples by quantitative proteomics, we identify proteins and biological processes in AD brains that may serve as therapeutic targets and fluid biomarkers for the disease.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Shape-anisotropy inverses the behavior of emergent vortices in active chiral fluids

Active colloidal fluids exhibit spontaneous emergence of correlated states, characterized by complex collective dynamics and self-organization. In geometrically confined systems, activity modulations trigger robust polar state reversals of a macroscopic vortex formed by colloidal rollers. Here, we reveal that the shape anisotropy of dielectric rollers transforms the system into a chiral active fluid comprised of rollers of arbitrary handedness. The chiral rollers self-assemble into multiple freestanding vortices with a spontaneously selected sense of rotation. We demonstrate that upon reactivation of the system after a complete cessation of activity beyond all relevant timescales, the vortices simultaneously restore their previous chiral states in striking contrast to the chiral state reversals demonstrated by spherical rollers. The analysis reveals that shape-anisotropy modifies the collective state memory of the ensemble. The findings provide insights into the emergence of complex collective behavior in chiral colloidal fluids governed by an interplay between shape anisotropy, chiral motion, and activity modulations.

Colloids↗
DOE OSTI2026

Geologic stress modulates fluid mixing at fracture intersections

Fracture intersections are critical links that enable flow and transport in subsurface fracture networks, and their behavior strongly influences fluid mixing in a network. Although all subsurface fractures are subjected to geological stress, we lack a fundamental understanding of how fracture intersection geometry evolves under stress and how these changes influence fluid mixing. Here, we combine 3D printing, 3D X-ray tomographic imaging, and 3D pore-scale numerical simulations to reveal stress-induced changes in intersection geometry and their impact on mixing. Mixing is found to be strongly affected by partial closure of an intersection under stress. As an intersection closes, the void area for fluid flow and diffusion decreases leading to substantial deviations between conventional mixing models and full pore-scale modeling. To address this, we propose a modified mixing model that accounts for intersection deformation, which is essential for accurate modeling of solute transport and mixing through fracture networks.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

Genomics discovery of giant fungal viruses from subsurface oceanic crustal fluids

Abstract The oceanic igneous crust is a vast reservoir for microbial life, dominated by diverse and active bacteria, archaea, and fungi. Archaeal and bacterial viruses were previously detected in oceanic crustal fluids at the Juan de Fuca Ridge (JdFR). Here we report the discovery of two eukaryotic Nucleocytoviricota genomes from the same crustal fluids by sorting and sequencing single virions. Both genomes have a tRNATyr gene with an intron (20 bps) at the canonical position between nucleotide 37 and 38, a common feature in eukaryotic and archaeal tRNA genes with short introns (<100 bps), and fungal genes acquired through horizontal gene transfer (HGT) events. The dominance of Ascomycota fungi as the main eukaryotes in crustal fluids and the evidence for HGT point to these fungi as the putative hosts, making these the first putative fungi-Nucleocytoviricota specific association. Our study suggests active host-viral dynamics for the only eukaryotic group found in the subsurface oceanic crust and raises important questions about the impact of viral infection on the productivity and biogeochemical cycling in this ecosystem.

Bhattacharjee, Ananda S.↗
DOE OSTI2022

Engineering stability, longevity, and miscibility of microtubule-based active fluids

Microtubule-based active matter provides insight into the self-organization of motile interacting constituents. In this work, we describe several formulations of microtubule-based 3D active isotropic fluids. Dynamics of these fluids is powered by three types of kinesin motors: a processive motor, a non-processive motor, and a motor which is permanently linked to a microtubule backbone. Another modification uses a specific microtubule crosslinker to induce bundle formation instead of a non-specific polymer depletant. In comparison to the already established system, each formulation exhibits distinct properties. These developments reveal the temporal stability of microtubule-based active fluids while extending their reach and the applicability.

36 MATERIALS SCIENCE↗
DOE OSTI2026

An implicit-explicit time splitting strategy for the far SOL plasma fluid model with DG-FEM discretization

We consider a far scrape-off layer (SOL) plasma fluid model of ions that is governed by a Braginskiitype model: a one-dimensional, nonlinear system of advection-diffusion equations coupled with a diffusion equation for neutral particles. Our motivation for studying this system arises from the coupling between the edge plasma and radio-frequency (RF) heating, where solving a far SOL plasma fluid model provides critical insights into edge plasma dynamics. Numerical simulations of plasma fluid models require advanced computational techniques to achieve both efficiency and accuracy, especially when resolving the boundary layer in magnetically confined plasmas. In this work, we propose an implicit-explicit time operator splitting strategy that allows for an efficient solution algorithm, where the diffusive terms are treated semi-implicitly requiring only a linear solve, while the advection part is handled explicitly using a strong-stability-preserving Runge-Kutta (SSP-RK3) scheme. This leads to a fully decoupled system in which the diffusion and advection sub-problems can be solved separately, simplifying the overall solution procedure and allowing for efficient parallelization, which is particularly relevant for exploring the impact of RF heating on the SOL plasma. The main challenge of the discretization is due to the strong coupling between diffusion and advection, particularly through the boundary conditions. This makes implementation of such a scheme in an accurate and stable manner nontrivial. We discuss in detail how to split the equations and manage boundary conditions to maintain stability and well-posedness for each subsystem. We also describe a spatial discretization approach, based on the discontinuous Galerkin finite element method (DG-FEM) and present numerical results for a one-dimensional system.

Burkovska, Olena [ORNL] (ORCID:0000000163101130)↗
DOE OSTI2020

Deep learning surrogate model for kinetic Landau-fluid closure with collision

In this work, the kinetic Landau-fluid (LF) closure with collision and periodic boundary condition is used in the development of the deep learning (DL) surrogate model. A classical neural network, namely, feedforward neural network or sometimes termed multilayer perceptron, is constructed and trained to learn the kinetic LF closure in the static limit and arbitrary mean free path in configuration space. The preliminary relation between best hyperparameters and critical parameters for data generation is found. Compared with the numerical approach (non-Fourier method) of the LF closure, the deep learning surrogate model shows an order of magnitude of improvement in terms of accuracy. Perhaps most importantly, the surrogate model closure has been integrated for the first time with fluid simulations. Our DL-enabled fluid simulations, for the first time, give the correct Landau damping rate for a wide range of wave vectors, while the Hammett–Perkins closure cannot produce the correct damping rate. We correctly connect the collisionless Hammett–Perkins closure and collisional Braginskii closure to reproduce the intrinsic nonlocal feature of the heat flux with DL techniques. We address the most concerning error accumulation problem and find that simulations with the deep learning surrogate model are as good as, if not better than, simulations with the analytic closure in terms of long-term numerical stability in the linear Landau damping test.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Fluid-like shock compression of dilute polymer nanocomposites

The shock Hugoniot of heterogenous mixtures of discrete particles has been experimentally investigated for porous agglomerates and fluids, while the study of full-density solids has been primarily limited to compressed powders and high-dimensional composites. By dispersing ceria nanoparticles in a polyethylene matrix, we are able to examine the hydrodynamic behavior of a nonporous, heterogenous solid in thermal equilibrium during weak shock compression. Phase-driven discontinuities in the Hugoniot particle velocity–shock velocity (u−D) relationship of pure polyethylene are replicated in the nanocomposites but are shifted to lower velocity and to higher pressure with higher particle concentration. The results are explained using an isothermal, two-velocity fluid model under the hydrodynamic approximation. The model, which assumes a theoretical equation-of-state for ceria and either a low-order or high-order fit to the measured polyethylene Hugoniot, reasonably predicts the Hugoniot for two different polyethylene/ceria nanocomposites. Using the model, the mixture Hugoniot is shown to be insensitive to the Hugoniot of the stiffer constituent when the moduli are sufficiently disparate, while dependence on particle density and volume fraction is preserved through fluid-like motion.

Moore, Nathan W. [Sandia National Laboratories (SN↗
DOE OSTI2025

Coupled 2D MHD and runaway electron fluid simulations of SPARC disruptions

Runaway electrons (REs) generated during disruption events in tokamaks can carry mega-Ampère level currents, potentially causing damage to plasma-facing components. Understanding RE evolution during disruption events is important for evaluating strategies to mitigate RE damage. Using two-dimensional toroidally symmetric magnetohydrodynamic (MHD) simulations in M3D-C1, which incorporates a fluid RE model evolved self-consistently with the bulk MHD fluid, we examine the seeding and avalanching of REs during disruptions in the SPARC tokamak – a compact, high-field, high-current device designed to achieve a fusion gain Q > 2 in deuterium–tritium plasmas. The M3D-C1 simulations of unmitigated disruptions demonstrate RE plateau formation and peaking of the final current density, which agree well with the results of lower-fidelity reduced RE fluid models. This work provides the first systematic comparison and benchmarking of different primary sources, including activated tritium beta decay and Compton scattering, in SPARC disruption simulations with self-consistent MHD and RE coupling.

Compton scattering↗
DOE OSTI2025

Conservative projection-based data-driven model order reduction of a fluid-kinetic spectral solver

Kinetic simulations are computationally intensive due to six-dimensional phase space discretization. Many kinetic spectral solvers use the asymmetrically weighted Hermite expansion due to its conservation and fluid-kinetic coupling properties, i.e., the lower-order Hermite moments capture and describe the macroscopic fluid dynamics, and higher-order Hermite moments describe the microscopic kinetic dynamics. We leverage this structure by developing a parametric data-driven reduced-order model based on the proper orthogonal decomposition, which projects the higher-order kinetic moments while retaining the fluid moments intact. We demonstrate analytically and numerically that the method ensures local and global mass, momentum, and energy conservation. The numerical results show that the proposed method effectively replicates the high-dimensional spectral simulations at a fraction of the computational cost and memory, as validated on the weak Landau damping and two-stream instability benchmark problems.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Implications of a two-fluid heat diffusion model for RF condensation effects in magnetic islands

Theoretical calculations have predicted an “RF condensation” effect through which the temperature perturbation and current drive may be nonlinearly enhanced in electron cyclotron (EC) heated magnetic islands. Previously, two-fluid effects had been neglected in the OCCAMI code used to model RF condensation. For realistic experimental conditions, we show that two-fluid effects in an EC heated plasma may have a major impact on RF condensation. Less collisional plasmas, where electron and ion temperatures are decoupled, exhibit an enhanced linear temperature perturbation in the island, and an even stronger nonlinear enhancement of the perturbed temperature. This can occur even when nonlinear effects are small in the single-fluid limit. We also calculate corresponding hysteresis effects. Finally, we demonstrate that other physical effects, including the rotation of the magnetic island and the Gaussian spread of the beam from a gyrotron, can significantly decrease the predicted observable RF condensation effect.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Complex subsurface hydrothermal fluid mixing at a submarine arc volcano supports distinct and highly diverse microbial communities

Hydrothermally active submarine volcanoes are mineral-rich biological oases contributing significantly to chemical fluxes in the deep sea, yet little is known about the microbial communities inhabiting these systems. Here we investigate the diversity of microbial life in hydrothermal deposits and their metagenomics-inferred physiology in light of the geological history and resulting hydrothermal fluid paths in the subsurface of Brothers submarine volcano north of New Zealand on the southern Kermadec arc. From metagenome-assembled genomes we identified over 90 putative bacterial and archaeal genomic families and nearly 300 previously unknown genera, many potentially endemic to this submarine volcanic environment. While magmatically influenced hydrothermal systems on the volcanic resurgent cones of Brothers volcano harbor communities of thermoacidophiles and diverse members of the superphylum “DPANN,” two distinct communities are associated with the caldera wall, likely shaped by two different types of hydrothermal circulation. The communities whose phylogenetic diversity primarily aligns with that of the cone sites and magmatically influenced hydrothermal systems elsewhere are characterized predominately by anaerobic metabolisms. These populations are probably maintained by fluids with greater magmatic inputs that have interacted with different (deeper) previously altered mineral assemblages. However, proximal (a few meters distant) communities with gene-inferred aerobic, microaerophilic, and anaerobic metabolisms are likely supported by shallower seawater-dominated circulation. Furthermore, mixing of fluids from these two distinct hydrothermal circulation systems may have an underlying imprint on the high microbial phylogenomic diversity. Collectively our results highlight the importance of considering geologic evolution and history of subsurface processes in studying microbial colonization and community dynamics in volcanic environments.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Fluid inertia controls mineral precipitation and clogging in pore to network-scale flows

Mineral precipitation caused by fluid mixing presents complex control and predictability challenges in a variety of natural and engineering processes, including carbon mineralization, geothermal energy, and microfluidics. Precipitation dynamics, particularly under the influence of fluid flow, remain poorly understood. Combining microfluidic experiments and three-dimensional reactive transport simulations, we demonstrate that fluid inertia controls mineral precipitation and clogging at flow intersections, even in laminar flows. We observe distinct precipitation regimes as a function of Reynolds number (Re). At low Reynolds numbers (Re < 10), precipitates form a thin, dense layer along the mixing interface, which shuts precipitation off, while at high Reynolds numbers (Re > 50), strong three-dimensional flows significantly enhance precipitation over the entire intersection, resulting in rapid clogging. When injection rates from two inlets are uneven, flow symmetry-breaking leads to unexpected flow bifurcation phenomena, which result in enhanced concurrent precipitation in both downstream channels. Finally, we extend our findings to rough channel networks and demonstrate that the identified inertial effects on precipitation at the intersection scale are also present and even more dramatic at the network scale. This study sheds light on the fundamental mechanisms underlying mixing-induced mineral precipitation and provides a framework for designing and optimizing processes involving mineral precipitation.

Science & Technology - Other Topics↗