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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 829 records · Page 46
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Fluid and hybrid simulations of the ionization instabilities in Hall thruster

Low-frequency axial oscillations in the range of 5–50 kHz stand out as a pervasive feature observed in many types of Hall thrusters. While it is widely recognized that the ionization effects play the central role in this mode, as manifested via the large-scale oscillations of neutral and plasma density, the exact mechanism(s) of the instabilities remain unclear. To gain further insight into the physics of the breathing mode and evaluate the role of kinetic effects, a one-dimensional time-dependent full nonlinear low-frequency model describing neutral atoms, ions, and electrons is developed in full fluid formulation and compared to the hybrid model in which the ions and neutrals are kinetic. Both models are quasi-neutral and share the same electron fluid equations that include the electron diffusion, mobility across the magnetic field, and the electron energy evolution. The ionization models are also similar in both approaches. Further, the predictions of fluid and hybrid simulations are compared for different test cases. Two main regimes are identified in both models: one with pure low-frequency behavior and the other one, where the low-frequency oscillations coexist with high-frequency oscillations in the range of 100–200 kHz, with the characteristic time scale of the ion channel fly-by time, 100–200 kHz. The other test case demonstrates the effect of a finite temperature of injected neutral atoms, which has a substantial suppression effect on the oscillation amplitude.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Geomechanics of CO 2 Reservoir Seals

Chemically-assisted subcritical fracture growth within overlying shale caprock can threaten seal integrity of CO 2 sequestration reservoirs. Here, we integrate laboratory fracture mechanics testing conducted under a wide range of environmental conditions including dry and wet supercritical CO 2 , dry CO 2 gas, ambient air, deionized water, and aqueous solutions of varying pH and salinity, with numerical simulations of fracture network growth and caprock degradation calculations, to investigate the coupled chemo-mechanical processes associated with potential fracture-controlled leakage from subsurface CO 2 storage. Double torsion tests quantify in detail the influence of aqueous fluid chemistry and temperature on subcritical fracture growth of caprock at atmospheric pressure, while short rod tests derive fracture toughness of caprock under pressurized supercritical CO 2 environments. We find that lowered pH as expected after brine acidification enhances subcritical fracture growth properties in carbonate-rich shale. An increase in salinity that may result from scCO 2 -brine interaction would potentially suppress fracture growth in clay-rich shales. Dehydration by dry supercritical CO 2 significantly strengthens shale lithologies. Through boundary element fracture network models that account for subcritical fracture growth we demonstrate that changes in aqueous fluid composition can affect fracture network geometry and connectivity, and thus potentially degrading caprock efficiency at preventing upward migration of CO 2 . Calculations based on boundary element simulation suggest that caprock degradation rates may increase by 58% following acidification of formation water in contact with carbonate-rich caprock. With spatially and temporally variable CO 2 -brine interaction in storage reservoirs, chemo-mechanical interactions may control the location of potential leakage pathway evolution, with preexisting faults and reservoir heterogeneities providing the preferred locus for environmentally assisted fracture growth and subsequent caprock failure.

58 GEOSCIENCES↗
DOE OSTI2021

Measurement of Deformation Heterogeneity During Shale Swelling Using Digital Image Correlation

Abstract Rock-fluid interactions in shale formations are one of the main sources of wellbore instability issues and inadequate stimulation performance. For better planning of fracturing operations and optimizing production from these reservoirs, it is important to understand the mechanisms behind these interactions. These issues are especially prevalent in clay-rich shales, such as Tuscaloosa Marine Shale, which is the subject of this study. Conventional techniques to quantify these shale-fluid interactions comprise of measuring swelling in powdered rock grains or measurement of deformation in the whole pieces of the core using a linear variable differential transformer and strain gages. However, the contribution from individual laminae to overall deformation cannot be evaluated using these methods. In this study, we developed an experimental setup to evaluate the spatial deformation in shale during interaction with water using digital image correlation (DIC). Deformation of two shale samples, with 34 wt% to 51 wt% clay content, was studied. White paint was used to generate a random speckle pattern on the specimen and then immersed in deionized water. The deformation process was captured using a digital camera and images were analyzed using DIC to quantify the deformation. The implementation of the DIC technique enables the visualization and quantification of spatial deformation in the specimen during interacting with water. The results show the localization of large strains in select laminations. The results provide a better understanding of shale deformation when interacting with water in comparison to traditional measurements that can provide only an average strain value.

Energy & Fuels↗
DOE OSTI2021

A Physics-Constrained Deep Learning Model for Simulating Multiphase Flow in 3D Heterogeneous Porous Media

Physics-based simulators for multiphase flow in porous media emulate nonlinear processes with coupled physics, and usually require extensive computational resources for software development, maintenance and simulation execution. As a result, a huge demand exists for fast modeling of coupled processes in a wide range of subsurface applications including geological sequestration, hydrocarbon recovery and geothermal energy extraction. In this work, an efficient physics-constrained deep learning model is developed for solving multiphase flow in 3-Dimensional (3D) heterogeneous porous media. The model fully leverages the spatial topology predictive capability of convolutional neural networks, specifically U-Net with successive contracting and expansive steps, and is coupled with an efficient continuity-based smoother to predict flow responses that need spatial continuity. Furthermore, the transient regions are penalized to steer the training process such that the model can accurately capture flow in these regions. The model takes inputs including properties of porous media, fluid properties and well controls, and predicts the temporal-spatial evolution of the state variables (pressure and saturation). While maintaining the continuity of fluid flow, the 3D spatial domain is decomposed into 2D images for reducing training cost, and the decomposition results in an increased number of training data samples and better training efficiency. Additionally, a surrogate model is separately constructed as a postprocessor to calculate well flow rate based on the predictions of state variables from the deep learning model. We use the example of CO 2 injection into saline aquifers, and apply the physics-constrained deep learning model that is trained from physics-based simulation data and emulates the physics process. The model performs prediction with a speedup of ~ 1400 times compared to physics-based simulations, and the average temporal errors of predicted pressure and saturation plumes are 0.27% and 0.099% respectively. Furthermore, water production rate is efficiently predicted by a surrogate model for well flow rate, with a mean error less than 5%. Therefore, with its unique scheme to cope with the fidelity in fluid flow in porous media, the physics-constrained deep learning model can become an efficient predictive model for computationally demanding inverse problems or other coupled processes.

58 GEOSCIENCES↗
DOE OSTI2020

Drive-pressure optimization in ramp-wave compression experiments through differential evolution

Ramp-wave dynamic-compression experiments are used to examine quasi-isentropic loading paths in materials. The gradual and continuous increase in pressure created by ramp waves make these types of experiments ideal for studying nonequilibrium material behavior, such as solidification kinetics. In ramp-wave compression experiments, the input drive pressure to the experimental setup may be exerted through one of a number of different mechanisms (e.g., magnetic fields, gas-gun-driven impactors, or high-energy lasers) and is generally required for simulating such experiments. Yet, regardless of the specific mechanism, this drive pressure cannot be measured directly (measurements are generally taken at a location near the back of the experimental setup through a transparent window), leading to an inverse problem where one must determine the drive pressure at the front of the experimental setup (i.e., the input) that corresponds to the particle velocity (the output) measured near the back of the experimental setup. Furthermore, we solve this inverse problem using a heuristic optimization algorithm, known as differential evolution, coupled with a multiphysics, hydrodynamics code that simulates the compression of the experimental setup. By running many rounds of forward simulations of the experimental setup, our optimization process iteratively searches for a drive pressure that is optimized to closely reproduce the experimentally measured particle velocity near the back of the experimental setup. While our optimization methodology requires a significant number of hydrodynamics simulations to be conducted, many of these can be performed in parallel, which greatly reduces the time cost of our methodology. One novel aspect of our method for determining the drive pressure is that it does not require physical modeling of the drive mechanism and can thus be broadly applied to many types of ramp-compression experiments, regardless of the drive mechanism.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

Study of Non-Newtonian Behavior of CaO-SiO{sub 2}-Based Mold Slag and Its Effect on Lubrication in Continuous Casting of Steel

To understand the effect of the non-Newtonian behavior of mold slag on lubrication during continuous casting of steel, the current study investigated the rheology of CaO-SiO{sub 2}-based mold slag using a rotational viscometer with variable rotating speed. The constitutive equations at different temperatures were determined. Subsequently, the obtained viscosity as a function of temperature and shear rate was incorporated into a validated mathematical model. The main results demonstrated that slag viscosity decreased dramatically with increased shear rate as the experimental temperature approached the break temperature of mold slag, meaning that the mold slag had a property of shear thinning. The predicted evolution of slag viscosity during mold oscillation was consistent with the shear thinning as the shear rate exerted on the slag channel varied. The calculated slag consumption was higher than that for slag treated as a Newtonian fluid, which agreed well with measurements using a miniature continuous caster. This study finds that the consideration of the non-Newtonian behavior of mold slag is significant to understand the lubrication mechanism and optimize related parameters via simulation.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Solution-Based Adaptivity as a Paradigm for Computational Fluid Dynamics

This is the final report for the DOE Early Career award. Through innovation in error estimation and solution-based adaptation methods we strive to dramatically improve the efficiency and robustness of computational science and engineering simulations. By solution-based error estimation and adaptation we refer to techniques for estimating numerical error and efficiently reducing it through targeted discretization changes. In such a setting, high-order methods play a key role, though they are just one mechanism for efficient accuracy improvement. Other mechanisms include well known mesh size and stretching optimization, as well as less-practiced mesh motion and basis optimization. With additional work on the latter, we are integrating these techniques into one adaptive suite that maximizes efficiency and robustness of Computational Fluid Dynamics (CFD) calculations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Experimental evidence for chemo-mechanical coupling during carbon mineralization in ultramafic rocks

It is known that storing carbon dioxide in the subsurface as carbonate minerals has the benefit of long-term stability and immobility. Ultramafic rock formations have been suggested as a potential reservoir for this type of storage due to the availability of cations to react with dissolved carbon dioxide and the fast reaction rates associated with minerals common in ultramafic formations; however, the rapid reactions have the potential to couple with the mechanical and hydraulic behavior of the rocks and little is known about the extent and mechanisms of this coupling. In this study, we argue that the dissolution of primary minerals and the precipitation of secondary minerals along pre-existing fractures in samples lead to reductions in both the apparent Young's modulus and shear strength of aggregates, accompanied by reduction in permeability. Hydrostatic and triaxial deformation experiments were run on dunite samples saturated with de-ionized water and carbon dioxide-rich solutions while stress, strain, permeability and pore fluid chemistry were monitored. Sample microstructures were examined after reaction and deformation using scanning electron microscopy (SEM). The results show that channelized dissolution and carbonate mineral precipitation in the samples saturated with carbon dioxide-rich solutions modify the structure of grain boundaries, leading to the observed reductions in stiffness, strength and permeability. A geochemical model was run to help interpret fluid chemical data, and we find that the apparent reaction rates in our experiments are faster than rates calculated from powder reactors, suggesting mechanically enhanced reaction rates. In conclusion, we find that chemo-mechanical coupling during carbon mineralization in dunites leads to substantial modification of mechanical and hydraulic behavior that needs to be accounted for in future modeling efforts of in situ carbon mineralization projects.

58 GEOSCIENCES↗
DOE OSTI2019

Deformation Mechanisms at Grain Boundaries in Polycrystals

Grain boundaries (GBs) are important sources of deformation accommodation and strengthening in polycrystalline materials. Grain boundary sliding is a deformation mechanism that is known to activate at high temperatures, low strain rates, and for materials with small grain sizes. While crystalline slip has been extensively studied, investigations of grain boundary sliding has been mostly restricted to nanocrystalline materials, symmetric or synthetic GBs, and loading in high-temperature environments. This study is aimed at improving our understanding of the coupling between deformation mechanism relationships, namely between slip-GB interaction and grain boundary sliding, by means of a combined high-resolution experimental characterization in conjunction with multiscale modeling. The material of choice in the present study is high-purity aluminum with a through-the-specimen-thickness grain structure. Digital image correlation experiments are performed to measure 2D strains relative to the microstructural features. These experiments, performed at various load steps, can resolve individual slip bands and the onset of grain boundary sliding. Onset of grain boundary sliding is observed in the first loadstep (the first loadstep was collected just after macroscopic yield), which suggests that the mechanism is driven by high stress as opposed to only being active to accommodate large values of plastic strain. Further, grain boundary sliding is observed in cases where slip impingement is present, as well as at boundaries that do not interact with obvious slip events. A temperature-dependent crystal plasticity model is used to study the constitutive response, which is then compared to full-field strain response experimentally obtained at the microscale-level. From this analysis, it is determined that a combination of the resolved shear stress at the grain boundary plane and boundary straightness form a set of criteria for predicting sliding propensity. Further, the GBs characterized from the experiments are exactly reproduced in a molecular dynamics framework as bicrystal systems, and the underlying atomistic scale mechanisms for pure sliding are studied. It is seen that GBs in the present study undergo sliding similar to a fluid-like flow. To study slip and sliding interaction, notches are introduced to facilitate dislocation emission and eventual interaction with the sliding GB. It was seen that slipGB interaction causes local increases in stress concentration, and a subsequent increase in the local sliding rate. These atomistic scale insights are used to inform a modified 3 crystal plasticity model with explicit GB elements and additional degrees of freedom to include GB sliding. The modified model results in improved predictions of deformation near the GBs than a conventional crystal plasticity model. These results improve the sophistication and accuracy of deformation modeling by establishing a set of criteria to describe the grain boundary sliding mechanism and help better predict micromechanical quantities near the grain boundaries.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Laboratory evidence of dynamo amplification of magnetic fields in a turbulent plasma

Magnetic fields are ubiquitous in the Universe. The energy density of these fields is typically comparable to the energy density of the fluid motions of the plasma in which they are embedded, making magnetic fields essential players in the dynamics of the luminous matter. The standard theoretical model for the origin of these strong magnetic fields is through the amplification of tiny seed fields via turbulent dynamo to the level consistent with current observations. However, experimental demonstration of the turbulent dynamo mechanism has remained elusive, since it requires plasma conditions that are extremely hard to re-create in terrestrial laboratories. Here in this paper, we demonstrate, using laser-produced colliding plasma flows, that turbulence is indeed capable of rapidly amplifying seed fields to near equipartition with the turbulent fluid motions. These results support the notion that turbulent dynamo is a viable mechanism responsible for the observed present-day magnetization.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

Micromechanical processes in consolidated granular salt

Here, granular salt is likely to be used as backfill material and a seal system component within geologic salt formations serving as a repository for long-term isolation of nuclear waste. Pressure from closure of the surrounding salt formation will promote consolidation of granular salt, eventually resulting in properties comparable to native salt. Understanding dependence of consolidation processes on stress state, moisture availability, temperature, and time is important for demonstrating sealing functions and long-term repository performance. This study characterizes laboratory-consolidated granular salt by means of microstructural observations. Granular salt material from mining operations was obtained from the bedded Salado Formation hosting the Waste Isolation Pilot Plant and the Avery Island salt dome. Laboratory test conditions included hydrostatic consolidation of jacketed granular salt with varying conditions of confining isochoric stress to 38 MPa, temperature to 250 °C, moisture additions of 1% by weight, time duration, and vented and non-vented states. Resultant porosities ranged between 1% and 22%. Optical and scanning electron microscopic techniques were used to ascertain consolidation mechanisms. From these investigations, samples with 1% added moisture or unvented during consolidation, exhibit clear pressure solution processes with tightly cohered grain boundaries and occluded fluid pores. Samples with only natural moisture content consolidated by a combination of brittle, cataclastic, and crystal plastic deformation. Recrystallization at 250 °C irrespective of moisture conditions was also observed. The range and variability of conditions applied in this study, combined with the techniques used to display microstructural features, are unique, and provide insight into an important area of governing deformation mechanism(s) occurring within salt repository applications.

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

Coupled Thermo–Hydro–Mechanical Modeling of Hydro-Shearing Stimulation in an Enhanced Geothermal System in the Raft River Geothermal Field, USA

The Raft River Enhanced Geothermal System (EGS) demonstration project aims to improve the geothermal production by enhancing the reservoir permeability via shear stimulation in well RRG-9. In this paper, we performed a series of 3D thermo– hydro–mechanical (THM) simulations to investigate the influence of hydraulic and thermal effects on the development of this EGS. The model includes synthetic fracture populations based on borehole televiewer images and in-situ stress measurements from well RRG-9. Fracture permeability evolution is determined using an empirical permeability law developed from laboratory experiments. The model was calibrated by comparing the hydraulic response to field observations, including wellhead pressure, injection rate, and well injectivity. Particularly, we analyzed the enhancement of reservoir permeability and the spatial extent of the stimulation zone for the given injection schedule. Our results indicate that the permeability enhancement of fractured geothermal reservoir is caused by the combined effects of injection-induced cooling and fluid pressure increase. The decrease of temperature plays a dominant role in reactivation of natural fractures under the hydro-shearing mechanism, while the higher injection pressure promotes shear failure and enlarges the stimulation zone. Finally, for the specified extensional stress state, the model favors greatest permeability enhancement along the maximum horizontal principal stress, a moderate vertical enhancement, and a smaller gain along the minimum horizontal principal stress.

58 GEOSCIENCES↗
DOE OSTI2022

Validation and parameterization of a novel physics-constrained neural dynamics model applied to turbulent fluid flow

We report, in fluid physics, data-driven models to enhance or accelerate time to solution are becoming increasingly popular for many application domains, such as alternatives to turbulence closures, system surrogates, or for new physics discovery. In the context of reduced order models of high-dimensional time-dependent fluid systems, machine learning methods grant the benefit of automated learning from data, but the burden of a model lies on its reduced-order representation of both the fluid state and physical dynamics. In this work, we build a physics-constrained, data-driven reduced order model for Navier–Stokes equations to approximate spatiotemporal fluid dynamics in the canonical case of isotropic turbulence in a triply periodic box. The model design choices mimic numerical and physical constraints by, for example, implicitly enforcing the incompressibility constraint and utilizing continuous neural ordinary differential equations for tracking the evolution of the governing differential equation. We demonstrate this technique on a three-dimensional, moderate Reynolds number turbulent fluid flow. In assessing the statistical quality and characteristics of the machine-learned model through rigorous diagnostic tests, we find that our model is capable of reconstructing the dynamics of the flow over large integral timescales, favoring accuracy at the larger length scales. More significantly, comprehensive diagnostics suggest that physically interpretable model parameters, corresponding to the representations of the fluid state and dynamics, have attributable and quantifiable impact on the quality of the model predictions and computational complexity.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Mucus-Inspired Tribology, a Sticky Yet Flowing Hydrogel

The mucus blanket can trap foreign particles before they enter the lungs, while at the same time, it flows up to remove these particles. This manifests the dual nature of mucus: sticky, on one hand, and fluid, on the other. Inspired by this function of mucus in the lungs, we designed a mucus simulant which emulates this dual nature. While many existing mucus simulants do not target bioadhesion particularly, poly(vinyl alcohol) (PVA)-based simulants make an exception. Despite their bioadhesion tendency, unlike mucus, they do not gelate. In this study, we added a physical cross-linking agent to PVA in order to add the gelation aspect and to better represent mucous properties. We show that the resultant mucus simulant develops into two regions: a highly sticky region near the surface of a foreign object (we used hydrophobized silicon to mimic the foreign object) and a fluid region far away from that surface. We show that the sticky part can slide past the less sticky part, while the foreign object is stuck to it. However, this mechanism changes with time. At short gelation times, this tendency to separate into two parts is enhanced and the foreign object remains stuck, while the rest of the gel flows. With time, the force required to allow the sticky part to slide over the fluid part is further reduced. However, if the gelation is allowed to proceed for even longer times without disturbance, the force required to slide the two parts past each other increases and the separation between the two parts is inhibited. The hydrogel becomes a sticky goo, which requires a higher force to move or unclog if placed in a duct (much like what happens with mucus in the tracheal duct). We explain the physics of our findings in terms of a competition between the tendency of the polymer to form a gel network and the tendency of the polymer to adsorb onto the foreign object.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

The Study of Magnetic Fluid Flows in a Laterally Heated Vertical Channel

Convection of a stratified magnetic fluid in a laterally heated vertical channel is investigated experimentally and theoretically. The dynamics of the behavior of convective rolls, their velocity and deformation, are investigated. It is shown that the complex inhomogeneous structure of the flow is attributed to the stratification of nanoparticles in the gravitational field. On the basis of a mathematical model of convection in the Boussinesq approximation, a large series of computational experiments are carried out for various parameters of the problem: the initial distribution of nanopartciles, the Boltzmann number, the Soret parameter, and the sedimentation length. A range of parameters is found in which the numerical and experimental results are qualitatively similar.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Electrical Conductivity of Clayey Rocks and Soils: A Non-Linear Model

It is well-accepted that Archie's law is only applicable to “clean” rocks and soils but fails in “dirty” ones where clay minerals possess an additional component of surface conductivity. Although several models, for example, Waxman-Smits model, were presented to account for this phenomenon, surface conductivity is always inappropriately treated as constant, which actually only holds at high salinities. The essential non-linear characteristic differing over fluid salinities has not been physically or mathematically explained well in those models. Here, we scrutinize the conduction mechanism of clayey rocks and soils and ascribe this non-linear feature to (a) variation of the electrical double layer and (b) the intrinsic clay-and-water conduction pattern. With effective medium theory, we develop an easy-to-use non-linear model that both reflects electrochemical theories and explains the measurement data well. Our model can be used to produce more accurate results for laboratory- and field-scale petrophysical parameter evaluations than the previous models.

58 GEOSCIENCES↗
DOE OSTI2022

Effects of Coulomb collisions on lower hybrid drift waves inside a laboratory reconnection current sheet

We have developed a local, linear theoretical model for lower hybrid drift waves that can be used for plasmas in the weakly collisional regime. Two cases with typical plasma and field parameters for the current sheet of the magnetic reconnection experiment have been studied. For a case with a low electron beta (β e =0.25, high guide field case), the quasi-electrostatic lower hybrid drift wave is unstable, while the electromagnetic lower hybrid drift wave has a positive growth rate for a high-β e case (β e =8.9, low guide field case). For both cases, including the effects of Coulomb collisions reduces the growth rate but collisional impacts on the dispersion and growth rate are limited (≲20%).

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗