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At least 1,045 records · Page 58

The role of the spatial heterogeneity and correlation length of surface wettability on two-phase flow in a CO 2 -water-rock system

This study characterized and modeled heterogeneous surface wettability in sandstone and investigated the role of spatial heterogeneity and correlation length of surface wettability on relative permeability in a supercritical CO 2 (scCO 2 )-brine-rock system. Understanding the role of wettability heterogeneity on relative permeability is essential to geological CO 2 sequestration, oil and gas recovery, and contaminated groundwater remediation. Although numerous studies have attempted to understand the influences of surface wettability, capillary number (Ca), and viscosity ratio, the role of the spatial variation and correlation length of surface wettability on two-phase flow in three-dimensional (3D) porous media has not been unraveled due to the challenges in the measurement and representation of realistic rock surface wettability. In this work, we conducted in-situ measurements of surface contact angle (CA) in a Bentheimer sandstone after CO 2 flooding using micro-computed tomography (micro-CT), and found that the pore-scale CA distribution on rock surfaces followed a log-normal distribution associated with a spatial correlation length. Based on the statistical information from CT scanning, a Gaussian random field was used to model CA distributions that had desired standard deviations and spatial correlation lengths, which were then adjusted within a certain range of values for sensitivity analyses to study their combined effects on the two-phase flow in the porous medium using the lattice Boltzmann (LB) method. The LB two-phase flow simulation was accelerated using hybrid, multicore parallel computing to overcome the challenges in simulating multiphase flow in a large 3D domain having 800 × 800 × 600 nodes. The simulation results showed that the surface wettability heterogeneity (i.e., standard deviation of CA) had a lesser effect on the relative permeability of the wetting fluid (water) but a more significant impact on the relative permeability of the non-wetting fluid (scCO 2 ). The Corey model was used to fit the LB-simulated relative permeability curves of water and scCO 2 and showed that the variations in the relative permeability curves for both water and scCO 2 increased as the standard deviation and spatial correlation length of CA increased. This study illustrated that the assumption of homogeneous surface wettability may cause errors in multiphase flow simulations. Furthermore, the impacts of both the standard deviation and spatial correlation length of CAs should be accounted for. This is the first study that explored the spatial correlation lengths associated with CA distributions on sandstone surfaces and comprehensively investigated the roles of both spatial variation and correlation length of CA on two-phase flow properties in 3D porous media. The optimized LB multiphase flow model was proved a powerful tool to study the interplays and combined effects of these statistical parameters, which had critical applications in numerous natural and engineering processes that involved multiphase flow in porous media.

58 GEOSCIENCES↗

Irreversible Trace Metal Binding to Goethite Controlled by the Ion Size

The dynamics of trace metals at mineral surfaces influence their fate and bioaccessibility in the environment. Trace metals on iron (oxyhydr)oxide surfaces display adsorption–desorption hysteresis, suggesting entrapment after aging. However, desorption experiments may perturb the coordination environment of adsorbed metals, the distribution of labile Fe(III), and mineral aggregation properties, influencing the interpretation of labile metal fractions. In this study, we investigated irreversible binding of nickel, zinc, and cadmium to goethite after aging times of 2–120 days using isotope exchange. Dissolved and adsorbed metal pools exchange rapidly, with half times <90 min, but all metals display a solid-associated fraction inaccessible to isotope exchange. The size of this nonlabile pool is the largest for nickel, with the smallest ionic radius, and the smallest for cadmium, with the largest ionic radius. Spectroscopy and extractions suggest that the irreversibly bound metals are incorporated in the goethite structure. Rapid exchange of labile solid-associated metals with solution demonstrates that adsorbed metals can sustain the dissolved pool in response to biological uptake or fluid flow. Trace metal fractions that irreversibly bind following adsorption provide a contaminant sequestration pathway, limit the availability of micronutrients, and record metal isotope signatures of environmental processes.

58 GEOSCIENCES↗

Irreversible Trace Metal Binding to Goethite Controlled by the Ion Size

The dynamics of trace metals at mineral surfaces influence their fate and bioaccessibility in the environment. Trace metals on iron (oxyhydr)oxide surfaces display adsorption–desorption hysteresis, suggesting entrapment after aging. However, desorption experiments may perturb the coordination environment of adsorbed metals, the distribution of labile Fe(III), and mineral aggregation properties, influencing the interpretation of labile metal fractions. Here, in this study, we investigated irreversible binding of nickel, zinc, and cadmium to goethite after aging times of 2–120 days using isotope exchange. Dissolved and adsorbed metal pools exchange rapidly, with half times <90 min, but all metals display a solid-associated fraction inaccessible to isotope exchange. The size of this nonlabile pool is the largest for nickel, with the smallest ionic radius, and the smallest for cadmium, with the largest ionic radius. Spectroscopy and extractions suggest that the irreversibly bound metals are incorporated in the goethite structure. Rapid exchange of labile solid-associated metals with solution demonstrates that adsorbed metals can sustain the dissolved pool in response to biological uptake or fluid flow. Trace metal fractions that irreversibly bind following adsorption provide a contaminant sequestration pathway, limit the availability of micronutrients, and record metal isotope signatures of environmental processes.

58 GEOSCIENCES↗

Characterizing the seismic response of a molten salt nuclear reactor

Abstract One Generation IV nuclear reactor, which uses a fluoride salt as a coolant, graphite reflector blocks as a moderator, and circulating buoyant TRISO pebbles as fuel is at an advanced stage of development. To characterize the seismic behavior of components of this reactor, validate numerical models for analysis, and develop recommendations for design, a set of earthquake‐simulator experiments on a scaled model of the reactor vessel and its internals was executed on a six‐degree‐of‐freedom earthquake simulator. The model was seismically isolated at its base using two types of spherical sliding bearings. The scaled model involved representations of the prototype reactor vessel, core barrel, reflector blocks, coolant, and spherical fuel pebbles. The material and geometric properties of different test components were selected based on a dynamic similitude scaling analysis and an approximate length scale of 0.4. Four sets of three‐component earthquake motions were used as inputs for testing. Instrumentation on the test specimen recorded the dynamic responses of the outer vessel, core barrel, and reflector‐block assembly, the hydrodynamic responses (sloshing and hydrodynamic pressure) of the liquid coolant, pebble consolidation under earthquake shaking, and the behavior of the isolation systems. This paper describes the design of the experiments and presents key results from the tests. The dynamic responses of the outer vessel, core barrel, and the reflector blocks revealed that the components responded as a unit for the intense shaking used in the experiments. The sloshing response of the fluid in a thin annulus near the perimeter of the vessel was heavily damped. The change in the packing fraction of the pebble bed under repeated, intense 3D earthquake shaking was less than 3%. Seismically isolating the vessel substantially reduced demands on its internal components.

Engineering↗

SECARB-USA: Needs Assessment Framework for Storage Complexes (Task 2.1.b)

A team of SECARB storage experts examined 63 formations at 39 sites that were selected to represent the range of diversity of newly assessed, as well as well-advanced, storage prospects in the SECARB region. We inventoried the data needs triggered by the requirements to obtain a Class VI UIC storage permit, the data needs that results from the requirement to create geocellular fluid flow models to support that permit, and by pragmatic and best practice inputs such as public acceptance, regulatory readiness, and pore space leasing. We anchored both the needs inventory and the processes for and cost of meeting the needs with data from 9 sites in in the SECARB area that have advanced far in characterization. Results show that the total cost of characterization prior to obtaining a permit is convergent, because the permit and modeling requirements drive projects to obtain the same types of data for all cases. The high cost data that control cost are 1) drilling, coring, core-testing, logging, sampling and testing a characterization well and 2) collection of a 3-D seismic survey to map reservoir and confining system properties over the area of the plume or the area of elevated pressure. In 5 of our case study sites we determined that one or both of these costs could be avoided because the needs are met by available data.

54 ENVIRONMENTAL SCIENCES↗

CLASSY. VI. The Density, Structure, and Size of Absorption-line Outflows in Starburst Galaxies

Galaxy formation and evolution are regulated by the feedback from galactic winds. Absorption lines provide the most widely available probe of winds. However, since most data only provide information integrated along the line of sight, they do not directly constrain the radial structure of the outflows. In this paper, we present a method to directly measure the gas electron density in outflows (n e ), which in turn yields estimates of outflow cloud properties (e.g., density, volume filling factor, and sizes/masses). We also estimate the distance (r n ) from the starburst at which the observed densities are found. We focus on 22 local star-forming galaxies primarily from the COS Legacy Archive Spectroscopic SurveY (CLASSY). In half of them, we detect absorption lines from fine-structure excited transitions of Si $\tiny{II}$ (i.e., Si $\tiny{II}$ * ). We determine n e from relative column densities of Si $\tiny{II}$ and Si $\tiny{II}$ * , given Si $\tiny{II}$ * originates from collisional excitation by free electrons. We find that the derived n e correlates well with the galaxy's star formation rate per unit area. From photoionization models or assuming the outflow is in pressure equilibrium with the wind fluid, we get r n ~ 1–2r * or ~5r * , respectively, where r * is the starburst radius. Based on comparisons to theoretical models of multiphase outflows, nearly all of the outflows have cloud sizes large enough for the clouds to survive their interaction with the hot wind fluid. Most of these measurements are the first ever for galactic winds detected in absorption lines and, thus, will provide important constraints for future models of galactic winds.

79 ASTRONOMY AND ASTROPHYSICS↗

Advanced supercritical water-based process concepts for treatment and beneficial reuse of brine in oil/gas production

Produced water generated from oil/gas reservoirs is a cost burden for oil/gas producers, with over 21 billion barrels of the waste generated in 2019. Average disposal costs range from 4.00–8.00·bbl -1 , with up to 20·bbl -1 spent on transportation alone. Dissolved solids content is a contributing factor which limits economical treatment options for this waste stream. This work proposes a novel technique that can handle high salinity waste, employing favorable properties past the critical point of water. In this study, process simulation of two supercritical water desalination (SCWD) scenarios was completed. Zero liquid discharge (ZLD) and brine concentration operating scenarios were compared, weighing the associated economics and benefits for each case. The results were shown to be economically feasible for brines with a high dissolved solids content, ranging from 3.49 to 17.28·bbl -1 in an expanded sensitivity analysis.

42 ENGINEERING↗

Predicting Cement-Sheath Integrity with Consideration of Initial State of Stress and Thermoporoelastic Effects

In conventional wellbore-integrity analysis, the cement sheath’s initial state of stress and transient thermoporoelastic effects are often neglected. However, the initial state of stress is prerequisite information for accurately predicting the safe operating conditions that prevent a cemented well from being damaged. In addition, transient thermoporoelastic effects can have a profound effect on when damage will occur. Here in this paper, we propose a model that includes these effects to predict the safe operating pressures and temperatures that will prevent cement-sheath failure. For the initial state of stress, we proposed an empirical model using measurements. Subsequent stress changes are evaluated by a fully coupled transient thermoporoelastic model to analyze the mechanical behavior of the cement sheath. We predict the safe operating envelope (SOE) for shear, tensile, and debonding cement-sheath failures caused by pressure and temperature perturbations after the cement sets. Our model predicts that pore pressure is a key factor for cement failure, especially for rapid temperature changes. If the formation is low permeability, the transient pore pressures are amplified, causing the risk of damage to increase. Compared with conventional thermoelastic models, the thermoporoelastic model predicts a smaller SOE when heating the internal casing fluid and a larger envelope when cooling the internal casing fluid. Finally, the heating rate was considered with respect to field applications. The heating rate was also considered, and slower heating/cooling rates can prevent damage to the cement sheath. Finally, the thermoporoelastic model was applied to explain several laboratory and field experiments and achieved good matches.

02 PETROLEUM↗

Small Molecule Sorting: A Fluorescence Study of Microemulsions

The application of microemulsions to a wide range of industries relies on their ability to solubilize small molecules with vastly different structures. Herein, we use multiple fluorescence techniques to probe ionic (rhodamine 6g, r6g), polar (coumarin 153, c153), nonpolar (diphenylanthracene, DPA), and amphiphilic (laurdan) small molecules in a nonionic, bicontinuous microemulsion of varying hydration. All fluorophores investigated were found to associate with the surfactant region despite their different structures and properties. The hydration of the surfactant layer was found to increase linearly with water addition, but while this initially increases the fluidity of the surfactant layer, fluorescence anisotropy of c153 and r6g indicates a stiffening of the surfactant at water content >60%. This stiffening of the surfactant layer at higher water content correlates with a morphological change in the microemulsion from a bicontinuous structure to droplets. In contrast, the nonpolar DPA shows a change in partitioning as hydration changes, increasing its association with the oil domain. Altogether, these studies elucidate not only the capability of these microemulsions to host a range of small molecules in the surfactant layer with tunable position but also the ability to probe the driving force of bulk structural changes in these heterogeneous fluids.

25 ENERGY STORAGE↗

Frictional Behavior Downdip Along the Subduction Megathrust: Insights From Laboratory Experiments on Exhumed Samples at In Situ Conditions

Subduction megathrusts exhibit a spectrum of slip modes, including catastrophic earthquakes. Although the mechanical and frictional properties of materials sampled from subduction zones have been studied extensively, few datasets have been collected for compositions and at pressure and temperature conditions representative of those in situ. The Nankai subduction zone in southwest Japan is a well-studied margin, and abundant data provide an opportunity to advance our understanding of fault and earthquake physics. Here, we use samples exhumed in the Shimanto and Sanbagawa Belts on Shikoku Island of southwest Japan that represent analogs for materials along the present-day megathrust at depths of ~5–>25 km, and we shear these at their peak in situ pressure-temperature (P-T) conditions. Effective normal stresses range from 28 to 192 MPa, and temperatures from 105°C to 470°C. We used pore fluid pressures of 45–240 MPa, corresponding to fluid overpressure ratios λ of 0.65 and 0.90. Slip velocities of 0.1–100 μm/s were used, in order to focus on the nucleation of instability and earthquakes. We found predominantly velocity-strengthening (inherently stable) behavior under all conditions for λ = 0.65. For λ = 0.90, velocity-weakening behavior was observed at 350°C, with velocity-strengthening behavior at lower and higher temperatures. The rate/state frictional stability parameter (a-b) increases with slip velocity at temperatures up to ~200°C and remains constant or decreases with slip velocity at higher temperatures. Altogether, our results demonstrate the potentially important roles of both temperature and slip velocity in controlling the distribution of stress and frictional rheology along subduction thrusts.

58 GEOSCIENCES↗

Ionization waves in low-current dc discharges in noble gases obtained with a hybrid kinetic-fluid model

A hybrid kinetic-fluid model is used to study ionization waves (striations) in a low-current plasma column of dc discharges in noble gases. Coupled solutions of a kinetic equation for electrons, a drift-diffusion equation for ions, and a Poisson equation for the electric field are obtained to clarify the nature of plasma stratification in the positive column. A simplified two-level excitation-ionization model is used for the conditions when the nonlinear effects due to stepwise ionization, gas heating, and Coulomb interactions among electrons are negligible. It is confirmed that the nonlocal effects are responsible for the formation of moving striations in dc discharges at low plasma densities and low values of pR (the product of gas pressure and tube radius). Here, the calculated properties of self-excited waves of S–, P–, and R types in neon and S type in argon agree with available experimental data. The reason for helium plasma stability to stratification is clarified. It is shown that sustaining stratified plasma is more efficient than striation-free plasma when the ionization rate is a nonlinear function of the electric field. However, the nonlinear dependence of the ionization rate on the electric field is not required for plasma stratification. Striations of S–, P–, and R types in neon exist with minimal or no ionization enhancement. Effects of the column length and plasma density on the wave properties are demonstrated.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Numerical Investigation of a Central Fuel Property Hypothesis under Boosted Spark-ignition Conditions

In the present work, a central fuel property hypothesis (CFPH), which states that fuel properties are sufficient to provide an indication of a fuel's performance irrespective of its chemical composition, was numerically investigated In particular, the objective of the study was to determine whether Research Octane Number (RON) and Motor Octane Number (MON), as fuel properties, are sufficient to describe a fuel's knock-limited performance under boosted spark-ignition (SI) conditions within the framework of CFPH. To this end, four TPRF-bioblendstock surrogates having different compositions but matched RON (= 98) and MON (= 90), were first generated using a non-linear regression model based on artificial neural network (ANN). Three unconventional bioblendstocks were included in the analysis: Di-isobutylene (DIB), Isobutanol and Anisole. Skeletal reaction mechanisms were generated for the TPRF-DIB, TPRF-isobutanol and TPRF-anisole blends from a detailed kinetic mechanism. Thereafter, numerical simulations were performed for the fuel surrogates using the skeletal mechanisms and a virtual cooperative fuel research (CFR) engine model, under a representative boosted operating condition. In the computational fluid dynamics (CFD) model, the G-equation approach was employed to track the turbulent flame front and the well-stirred reactor model combined with multi-zone binning strategy was used to capture auto-ignition in the end-gas. In addition, laminar flame speed was tabulated for each blend as a function of pressure, temperature and equivalence ratio a priori, and the lookup tables were used to prescribe laminar flame speed as an input to the G-equation model. Parametric spark timing sweeps were performed for each fuel blend to determine the corresponding knock-limited spark advance (KLSA) and 50% burn point (CA50) at the respective KLSA timing. It was observed that despite same RON, MON and engine operating conditions, the TPRF-Anisole blend exhibited markedly different knock-limited performance from the other three blends. This deviation from the octane index (DI) expectation was shown to be caused by differences in laminar flame speed (LFS). However; it was found that relatively large fuel-specific differences in LFS (> 20%) would have to be present to cause any appreciable deviation from the 01 framework. Otherwise, RON and MON would still be robust enough to predict a fuel's knock-limited performance.

Pal, Pinaki↗

Temporally-consistent koopman autoencoders for forecasting dynamical systems

Absence of sufficiently high-quality data often poses a key challenge in data-driven modeling of high-dimensional spatio-temporal dynamical systems. Koopman Autoencoders (KAEs) harness the expressivity of deep neural networks (DNNs), the dimension reduction capabilities of autoencoders, and the spectral properties of the Koopman operator to learn a reduced-order feature space with simpler, linear dynamics. However, the effectiveness of KAEs is hindered by limited and noisy training datasets, leading to poor generalizability. To address this, we introduce the Temporally-Consistent Koopman Autoencoder (tcKAE), designed to generate accurate long-term predictions even with limited and noisy training data. This is achieved through a consistency regularization term that enforces prediction coherence across different time steps, thus enhancing the robustness and generalizability of tcKAE over existing models. We provide analytical justification for this approach based on Koopman spectral theory and empirically demonstrate tcKAE’s superior performance over state-of-the-art KAE models across a variety of test cases, including simple pendulum oscillations, kinetic plasma, and fluid flow data.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Numerical Investigation of a Central Fuel Property Hypothesis Under Boosted Spark-Ignition Conditions

In the present work, a central fuel property hypothesis (CFPH), which states that fuel properties are sufficient to provide an indication of a fuel’s performance irrespective of its chemical composition, was numerically investigated. In particular, the objective of the study was to determine whether Research Octane Number (RON) and Motor Octane Number (MON), as fuel properties, are sufficient to describe a fuel’s knock-limited performance under boosted spark-ignition (SI) conditions within the framework of CFPH. To this end, four TPRF-bioblendstock surrogates having different compositions but matched RON (=98) and MON (=90), were first generated using a non-linear regression model based on artificial neural network (ANN). Additionally, three unconventional bioblendstocks were included in the analysis: di-isobutylene (DIB), isobutanol, and Anisole. Skeletal reaction mechanisms were generated for the TPRF-DIB, TPRF-isobutanol, and TPRF-anisole blends from a detailed kinetic mechanism. Thereafter, numerical simulations were performed for the fuel surrogates using the skeletal mechanisms and a virtual cooperative fuel research (CFR) engine model, under a representative boosted operating condition. In the computational fluid dynamics (CFD) model, the G-equation approach was employed to track the turbulent flame front and the well-stirred reactor model combined with the multi-zone binning strategy was used to capture auto-ignition in the end-gas. In addition, laminar flame speed (LFS) was tabulated for each blend as a function of pressure, temperature, and equivalence ratio a priori, and the lookup tables were used to prescribe laminar flame speed as an input to the G-equation model. Parametric spark timing sweeps were performed for each fuel blend to determine the corresponding knock-limited spark advance (KLSA) and 50% burn point (CA50) at the respective KLSA timing. It was observed that despite same RON, MON, and engine operating conditions, the TPRF-anisole blend exhibited markedly different knock-limited performance from the other three blends. This deviation from the octane index (OI) expectation was shown to be caused by differences in laminar flame speed. However, it was found that relatively large fuel-specific differences in LFS (>20%) would have to be present to cause any appreciable deviation from the OI framework. Otherwise, RON and MON would still be robust enough to predict a fuel’s knock-limited performance.

42 ENGINEERING↗

Thermal-Mechanical Analysis of an Additive Manufacturing Ceramic Heat Exchanger for High-Temperature Recuperator in a sCO2 Power System

Supercritical CO2 (sCO2) Brayton power cycle can be configured in a closed-loop power system and has a potentially high cycle efficiency. Compactness and high efficiency of a sCO2 power block make the sCO2 Brayton cycle a versatile power cycle in broad applications. While many heat sources are of sufficient intensity to produce high temperature working fluids to achieve high cycle efficiency, the thermal-mechanical stability of traditional materials (e.g., steels and nickel-based superalloys) used in construction of heat exchangers and turbine components limits the operating conditions and thus thermodynamic efficiency of the system. This effort seeks to establish the viability of ceramic heat exchanger technologies for the most extreme operating conditions envisioned for power generation and other high temperature processes. Heat exchangers constructed from ultra-high temperature ceramics, a class of extreme environment materials featuring melting points (Tmp.) above 3000 degrees C, is particularly appealing for sCO2 Brayton cycles given their ultra-low creep rates and very high retained strength at low homologous temperatures (i.e., T < 0.5 Tmp., or at least 1500 degrees C). To translate these materials properties to ultra-high temperature heat exchangers, innovations are required in ceramic manufacturing techniques to realize the complex architectures featured in compact heat exchangers with high power density. With appropriate processing, ZrB2-SiC based compositions can be sintered to near full density and shaped into complex topologies via ceramic additive manufacturing methods. This paper analyzes heat exchanger designs and explores thermal-mechanical implications of the operating environment. Thermal flow, heat transfer, and conjugate mechanical analyses provide insights into benefits and risks associated with the design approach.

additive manufacturing↗

Geophysical borehole logging data of wells ER-GLS1, ER-GUM1, ER-PLM7, and ER-PLM8 at the East River Watershed, Colorado

The purpose of this data set is to provide a means of characterizing the bedrock variability both within a single borehole location and across the East River Watershed. The East River is part of the Watershed Function Scientific Focus Area (WFSFA) located in the Upper Colorado River Basin, United States, and all boreholes are located within Mancos shale bedrock. The data set contains geophysical borehole logging data acquired in October 2018 in boreholes ER-GUM1 (East River- Gothic Upper Montane Borehole #1) and ER-GLS1 (East River- Gothic Lower Subalpine Borehole #1), and acquired in October 2019 in boreholes ER-PLM7 (East River- Pumphouse Lower Montane Borehole #7) and ER-PLM8 (East River- Pumphouse Lower Montane Borehole #8). It contains depth, natural gamma ray emission, spectral gamma ray emission(Th, K, U), magnetic susceptibility, fluid temperature and electrical conductivity, electromagnetic (EM) induction derived rock electrical resistivity, heat pulse and spinner flow measurements to estimate groundwater flow, and Nuclear Magnetic Resonance (NMR) derived water content and hydraulic conductivity. Data for each borehole are provided as comma delimited text files. For each borehole accurate location information is provided (based on RTK GPS (Real Time Kinematic Global Positioning System) surveying). Borehole logging data were acquired using Mount Sopris borehole tools, and Vista Clara Javelin for NMR data.

54 ENVIRONMENTAL SCIENCES↗

Autonomous Fracture Conductivity Using Expandable Proppants in Enhanced Geothermal Systems

Summary Early thermal breakthrough in enhanced geothermal systems (EGS) due to the presence of preferential flow channels is a major challenge that endangers efficient and economic heat extraction in such systems. Previous studies mainly focused on adjusting circulation rates of the working fluid, which still leaves significant amounts of untapped heat behind. Currently, there is a lack of technologies for altering flow distribution within the fracture network to achieve uniform heat sweeping in the reservoir. This work presents a novel concept for making proppants to autonomously control fracture conductivity based on the surrounding temperature. Here, proppants with negative thermal expansion coefficients have demonstrated the capability for appropriate fracture conductivity adjustment as a function of temperature to achieve uniform flow across the fracture network. Particle-particle interactions governing such functions are explicitly modeled, and then the Lattice Boltzmann methods (LBM) is used to determine the potential impact of closure stress and temperature changes on the permeability of the proposed proppant packs. Microscale analyses are further used to determine the required material properties to achieve a certain improvement in the permeability of the proppant pack. Our analyses show an enhancement in permeability and the associated fracture conductivity by half of their initial values. Field-scale analysis further confirms the effectiveness of the proposed concept as 31.4% more heat can be extracted from EGS over 50 years of production when the proposed proppants are used. Such novel proppants may effectively delay thermal breakthrough, sweep heat from larger rock volumes, and elongate the life span of the EGS project.

Engineering↗

Noise and error analysis and optimization in particle-based kinetic plasma simulations

In this paper we analyze the noise in macro-particle methods used in plasma physics and fluid dynamics, leading to approaches for minimizing the total error, focusing on electrostatic models in one dimension. We begin by describing kernel density estimation for continuous values of the spatial variable x, expressing the kernel in a form in which its shape and width are represented separately. The covariance matrix of the noise in the density is computed, first for uniform true density. The bandwidth of the covariance matrix C(x,y) is related to the width of the kernel. A feature that stands out is the presence of constant negative terms in the elements of the covariance matrix both on and off-diagonal. These negative correlations are related to the fact that the total number of particles is fixed at each time step; they also lead to the property ∫C(x,y)dy = 0. We investigate the effect of these negative correlations on the electric field computed by Gauss's law, finding that the noise in the electric field is related to a process called the Ornstein-Uhlenbeck bridge, leading to a covariance matrix of the electric field with variance significantly reduced relative to that of a Brownian process. For non-constant density, p(x), still with continuous x, we analyze the total error in the density estimation and discuss it in terms of bias-variance optimization (BVO). For some characteristic length l, determined by the density and its second derivative, and kernel width h, having too few particles within h leads to too much variance; for h that is large relative to l, there is too much smoothing of the density. The optimum between these two limits is found by BVO. For kernels of the same width, it is shown that this optimum (minimum) is weakly sensitive to the kernel shape. Next, we repeat the analysis for x discretized on a grid. In this case the charge deposition rule is determined by a particle shape. An important property to be respected in the discrete system is the exact preservation of total charge on the grid; this property is necessary to ensure that the electric field is equal at both ends, consistent with periodic boundary conditions. We find that if the particle shapes satisfy a partition of unity property, the particle charge deposited on the grid is conserved exactly. Further, if the particle shape is expressed as the convolution of a kernel with another kernel that satisfies the partition of unity, then the particle shape obeys the partition of unity. This property holds for kernels of arbitrary width, including widths that are not integer multiples of the grid spacing. Furthermore, we show results relaxing the approximations used to do BVO optimization analytically, by doing numerical computations of the total error as a function of the kernel width, on a grid in x. The comparison between numerical and analytical results shows good agreement over a range of particle shapes. We discuss the practical implications of our results, including the criteria for design and implementation of computationally efficient particle shapes that take advantage of the developed theory.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗