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At least 811 records · Page 45

Spectral induced polarization signatures of smoldering remediation enhanced with colloidal activated carbon: An experimental study

Monitoring the remediation of soil and groundwater contaminated by organic compounds remains highly challenging. The spectral induced polarization (SIP) method exhibits significant promise for monitoring changes to the electrical properties of soils that are undergoing remediation. Thermal treatments, such as smoldering combustion, have become established remediation techniques for destroying contaminants. Smoldering combustion is now being supported by colloidal activated carbon (CAC), with CAC able to adsorb contaminants and supplement the fuel source for destroying contaminants. The objective of this study is to investigate the potential of SIP for tracking the smoldering remediation of imitated field soils supplemented with CAC. SIP column experiments were first conducted to assess the response of SIP to varying concentrations of CAC in field soils that contain, or do not contain, organic material (OM). Here these results demonstrate that increasing OM and CAC contents increase both the real and imaginary components of the complex conductivity, with the imaginary conductivity also showing frequency dependence. Next, a suite of smoldering and SIP column experiments was conducted to investigate if SIP can detect changes in imitated field soils of varying OM and CAC contents that have been remediated by smoldering combustion. The SIP results on the examined soils both before and after smoldering show that SIP can detect changes in the real conductivity, and particularly the imaginary conductivity, between different soil compositions and different stages of the remediation process. High resolution scanning electron microscopy (SEM) imaging was performed on all samples to validate the SIP and smoldering experiments, confirming significant reductions in carbon after smoldering. Overall, this study suggests that SIP has potential to detect changes in the electrical properties of field soils due to the addition of remedial fluids like CAC and contaminant destruction by smoldering remediation.

54 ENVIRONMENTAL SCIENCES↗

MOOSE ProbML: Parallelized probabilistic machine learning and uncertainty quantification for computational energy applications

Here, this paper presents the development and demonstration of massively parallel probabilistic machine learning (ML) and uncertainty quantification (UQ) capabilities within the Multiphysics Object-Oriented Simulation Environment (MOOSE), an open-source computational platform for parallel finite element and finite volume analyses. In addressing the computational expense and uncertainties inherent in complex multiphysics simulations, this paper integrates Gaussian process (GP) variants, active learning, Bayesian inverse UQ, adaptive forward UQ, Bayesian optimization, evolutionary optimization, and Markov chain Monte Carlo (MCMC) within MOOSE. It also elaborates on the interaction among key MOOSE systems — Sampler, MultiApp, Reporter, and Surrogate — in enabling these capabilities. The modularity offered by these systems enables development of a multitude of probabilistic ML and UQ algorithms in MOOSE. Example code demonstrations include parallel active learning and parallel Bayesian inference via active learning. The impact of these developments is illustrated through five applications relevant to computational energy applications: UQ of nuclear fuel fission product release, using parallel active learning Bayesian inference; very rare events analysis in nuclear microreactors using active learning; advanced manufacturing process modeling using multi-output GPs (MOGPs) and dimensionality reduction; fluid flow using deep GPs (DGPs); and tritium transport model parameter optimization for fusion energy, using batch Bayesian optimization. These capabilities are part of the MOOSE framework.

97 - MATHEMATICS AND COMPUTING↗

Capability in Theory, Modeling, and Validation for a Range of Innovative Fusion Concepts using High-Fidelity Moment-Kinetic Models

A computational modeling capability is created and available to the fusion community to understand and design lower-cost and innovative fusion concepts. The approach uses high- fidelity kinetic, moment-kinetic, and moment models and includes sophisticated plasma- boundary interactions. A majority of fusion-relevant simulations are performed with magnetohydrodynamic models and hybrid particle-in-cell codes, with limited-fidelity electron and kinetic physics. However, in fusion configurations like Z-pinches, field-reversed- configurations, plasma jet magneto-inertial fusion, spinning mirrors, and others, kinetic effects (both electron and ions) are critical to understand the physics and design scaling into the highly kinetic regime of a burning fusion plasma. Furthermore, as present fusion machines move towards a burning plasma regime, liquid-metal blankets are needed to handle first-wall heat- flux, reduce erosion, and eventually for energy conversion and fuel breeding. The work performed under this ARPA-E BETHE Capability Team advances the state-of-the-art in modeling and understanding plasma dynamics in fusion devices and its coupling with liquid-metal dynamics. These are critical areas of research for fusion energy to become realizable. To address these complex problems, we have leveraged and extended computational capabilities through the code, Gkeyll (developed jointly with Princeton Plasma Physics Laboratory and academic partners), for kinetic and moment modeling of fusion plasmas. The Concept Teams supported by this Capability Team include the Wisconsin High-field Axisymmetric Mirror (WHAM), Centrifugal Mirror Experiment (CFME), Plasma-Jet Magneto- Inertial Fusion (PJMIF), and solid and liquid wall plasma-material interaction studies relevant to a number of fusion concepts including Zap Energy’s Z-pinch. This software is open-source and available to the fusion community as a high-fidelity tool for the design of lower-cost fusion experiments. 3D gyrokinetic simulations of WHAM are now possible for long enough time scales to understand the evolution of interchange instabilities. 3D multi-fluid simulations of CMFE at higher Mach numbers are now possible for detailed design iterations with the goal of stability. The state-of-the-art in understanding shock formation and shock mitigation regimes in merging liners for PJMIF have been furthered by our kinetic simulations. Our novel models and frameworks studying plasma-material interaction by incorporating wall emission for various solid wall materials of relevance to pulsed and steady fusion concepts have advanced the state-of-the-art in our understanding of particle fluxes, heat fluxes, and other quantities at cathodes and anodes. The results from this work may explain discrepancies between experimental and theoretical predictions of achieved current densities in pulsed concepts such as Z-pinches. Another significant contribution of this Capability Team is the development and deployment of a novel experimental platform, LEX (Liquid Electrode eXperiment), at Virginia Tech to understand liquid metal free-surface response to electromagnetic pulses. The novel experiments along with model validation quantified the effect of different materials and sizes of liquid metal droplets on the radiative power balance of fusion plasmas for pulsed concepts. Furthermore, these experiments provided mitigation strategies for violent liquid metal response for high current pulses as would be expected in fusion regimes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

High-fidelity pool boiling simulations on multiple nucleation sites using interface capturing method

Boiling has proved to be one of the most efficient means for heat transfer and is a very important phenomenon during severe accident scenarios in light water reactors. High-fidelity pool boiling simulations can provide a numerical database for improving mechanistic boiling models by allowing for specific evaluation of interactions among bubbles. Previously published pool boiling simulations investigated two nucleation sites in which bubble growth at one site suppressed nucleation at the other site. Based on previous study results, more complicated interface-capturing simulations on pool boiling were conducted using PHASTA code with locally refined unstructured mesh. First, different boundary conditions (BCs) were assessed to support robustness and reproducibility of the boiling model. Then, a scale study was conducted at a larger domain with nine nucleation sites where either nine or four nucleation sites are activated. Involving more nucleation sites increased the complexity of bubble interactions from surrounding sites. Finally, bubble departure behavior influenced by wall heat flux was investigated. In this work, when heat flux was increased, the order of bubble departure changed, but diagonal bubbles always departed after one another. The departure time interval between the first and second bubble reduced as heat flux increased. The corresponding frequency was almost linearly proportional to the heat flux. In addition, bubble departure behavior was found to be greatly influenced by the nucleation site pattern. Multiple nucleation sites resulted in superimposed inhibitive effects from surrounding sites to each bubble, which extensively delayed the departure. This new observation was not discussed in previously published works. The work presented here provides new insight on the fundamental understanding of boiling phenomena, contributes to the development of a 3D multiphase computational fluid dynamics (M-CFD) model, and provides a more comprehensive database for data-driven pool boiling studies.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Qualification and Commissioning of Helium Flow Loop Experiment for Blanket Design Measurements

Sufficient cooling of plasma-facing materials remains an outstanding challenge in the design of fusion reactor blankets in commercial power demonstration plants. Due to its chemical inertness and low neutron interaction cross section, pressurized helium is a candidate coolant fluid for such systems; however, helium has a small thermal mass compared to liquid coolants, potentially reducing heat removal performance. To address this need, a number of heat transfer enhancements have been proposed to improve the cooling efficiency of such components, thereby decreasing pumping power needs and improving overall plant efficiency. Toward this end, a helium flow loop experiment (HFLE) has been designed and commissioned to test advanced passive heat transfer enhancements in unit-cell test sections, providing necessary data for model validation and subsequent system design. The HFLE is designed to provide flow of pressurized (up to 4 MPa) helium at flow rates up to 80 g/s, enabling heat transfer and pressure drop measurements in test pieces at Reynolds numbers in excess of 180 000. To explore the effects of novel and complex heat transfer enhancements, test sections are produced via additive manufacturing, providing geometries not typically obtainable by conventional machining. Here in this work, we present results from HFLE commissioning and the initial thermal-hydraulic tests of an additively manufactured rifled-rib test section. Results are compared to smooth pipe correlations, and plans are described for future HFLE measurements. These preliminary experiments indicate the utility of the HFLE for heat transfer enhancement testing and simulation validation activities.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Media matters! Alterations in the loading and release of Histoplasma capsulatum extracellular vesicles in response to different nutritional milieus

Histoplasma capsulatum is a dimorphic fungus that most frequently causes pneumonia, but can also disseminate and proliferate in diverse tissues. H. capsulatum has a complex secretion system that mediates the release of macromolecule-degrading enzymes and virulence factors. The formation and release of extracellular vesicles (EVs) are an important mechanism for non-conventional secretion in both ascomycetes and basidiomycetes. H. capsulatum EVs contain diverse proteins associated with virulence and are immunologically active. Despite the growing knowledge of EVs from H. capsulatum and other pathogenic fungi, the extent that changes in the environment impact the sorting of organic molecules in EVs has not been investigated. In our research, we cultivated H. capsulatum with distinct culture media to investigate the potential plasticity in EV loading in response to differences in nutrition. Our findings reveal that nutrition plays an important role in EV loading and formation, which may translate into differences in biological activities of these fungi in various fluids and tissues.

59 BASIC BIOLOGICAL SCIENCES↗

Programmable chiral states in flocks of active magnetic rollers

Inspired by nature, active matter exemplified by self-organization of motile units into macroscopic structures holds great promise for advanced tunable materials capable of flocking, shape-shifting, and self-healing. Active particles driven by external fields have repeatedly demonstrated potential for complex self-organization and collective behavior, yet how to guide the direction of their collective motion largely remains unexplored. Here, we report a system of microscopic ferromagnetic rollers driven by an alternating magnetic field that demonstrates programmable control of the direction of a self-organized coherent vortical motion (i.e., chirality). Facilitated by a droplet confinement, the rollers get synchronized and display either right- or left-handed spontaneous vortical motion, such that their moving direction determines the vortex chirality. Here, we reveal that one can remotely command a flock of magnetic rollers to switch or maintain its chiral state by modulating a phase shift of the sinusoidal magnetic field powering the active rollers. Building on our findings, we realize a self-assembled remotely controlled micro-pump architecture capable of switching the fluid transport direction on demand. Our studies may stimulate new design strategies for directed transport and flocking robotics at the microscale based on active colloids.

36 MATERIALS SCIENCE↗

Geochemical Changes in Response to CO 2 Injection in a CO 2 -EOR Complex in Northern Michigan (Volume II.1)

The Midwest Regional Carbon Sequestration Partnership (MRCSP) was founded in 2003 as part of the U.S. Department of Energy’s (DOE’s) Regional Carbon Sequestration Partnership initiative. Since its founding, MRCSP has made significant strides toward making CCUS a viable option for states in the region. The public/private consortium, funded through the DOE Regional Carbon Sequestration Initiative, brings together nearly 40 industry partners and 10 states. Battelle, as the project lead, oversees research, development and operations and coordinates activities among the partners. The incremental, phased approach has built a valuable knowledge base for the industry and paved the way for commercial-scale adoption of CCUS technologies. From 2008 to 2020, MRCSP Phase III focused on the development of large-scale injection projects. This report is part of a series of reports prepared under the Midwestern Regional Carbon Sequestration Partnership (MRCSP) Phase III (Development Phase). These reports summarize and detail the findings of the work conducted under the Phase III project. The report describes the geochemical monitoring program under MRCSP to use stable and radiogenic isotope geochemistry in concert with analysis of general geochemical parameters of fluids and gases and analysis of core samples to determine geochemical processes occurring in the reef structure because of CO 2 injection. Specifically, brine and gas samples were collected and analyzed to determine changes occurring between reefs prior to and following CO 2 injection. The analytical results for general geochemical parameters were modeled with chemical equilibrium models to determine if the injection of CO 2 resulted in the mineral dissolution or precipitation. Finally, core samples were collected and analyzed to determine if there was evidence of dissolution features or mineral precipitation.

01 COAL, LIGNITE, AND PEAT↗

Non-Boussinesq subgrid-scale model with dynamic tensorial coefficients

A major drawback of Boussinesq-type subgrid-scale stress models used in large-eddy simulations is the inherent assumption of alignment between large-scale strain rates and filtered subgrid-stresses. A priori analyses using direct numerical simulation (DNS) data have shown that this assumption is invalid locally as subgrid-scale stresses are poorly correlated with the large-scale strain rates [J. Bardina, J. Ferziger, and W. Reynolds, Improved subgrid-scale models for large-eddy simulation, in Proceedings of the 13th Fluid and Plasmadynamics Conference, AIAA (1980); C. Meneveau and K. Katz, Scale-invariance and turbulence models for large-eddy simulation, Ann. Rev. Fluid Mech. 32, 1 (2000)]. In the present work, a new, non-Boussinesq subgrid-scale model is presented where the model coefficients are computed dynamically. Some previous non-Boussinesq models have observed issues in providing adequate dissipation of turbulent kinetic energy [e.g., Bardina et al., Proceedings of the 13th Fluid and Plasmadynamics Conference (1980); R. A. Clark, J. Ferziger, and W.C. Reynolds. Evaluation of subgrid-scale models using an accurately simulated turbulent flow, J. Fluid Mech. 91, 1 (1979); S. Stolz and N. A. Adams, An approximate deconvolution procedure for large-eddy simulation, Phys. Fluids 11, 1699 (1999)]; however, the present model is shown to provide sufficient dissipation using dynamic coefficients. Modeled subgrid-scale Reynolds stresses satisfy the consistency requirements of the governing equations for large-eddy simulation (LES), vanish in laminar flow and at solid boundaries, and have the correct asymptotic behavior in the near-wall region of a turbulent boundary layer. The new model, referred to as the dynamic tensor-coefficient Smagorinsky model (DTCSM), has been tested in simulations of canonical flows: decaying and forced homogeneous isotropic turbulence, and wall-modeled turbulent channel flow at high Reynolds numbers. The results show favorable agreement with DNS data. It has been shown that DTCSM offers similar predictive capabilities as the dynamic Smagorinsky model for canonical flows. In order to assess the performance of DTCSM in more complex flows, wall-modeled simulations of high Reynolds number flow over a Gaussian bump (Boeing speed bump) exhibiting smooth-body flow separation are performed. Predictions of surface pressure and skin friction, compared against DNS and experimental data, show improved accuracy from DTCSM in comparison to existing static coefficient (Vreman) and dynamic Smagorinsky model. The computational cost of performing LES with this model is up to 15% higher than the dynamic Smagorinsky model.

42 ENGINEERING↗

Predictive Modeling of Electrodeposition in a Single Pore Flow-Through Electrode: From Electronucleation to Coating Thickness Uniformity

The emergence of advanced manufacturing methods capable of producing porous three-dimensional structures has expanded the design space for next-generation functional components. The ability to fabricate ordered 3D foams for use in electrocatalysis reactors has increased the need for controlled deposition of catalytic metals onto porous support materials, such as carbon. However, there is a lack of clear design guidelines for electrodeposition onto 3D substrates, due to the geometric complexity and multi-scale nature of the problem. Furthermore, electro-nucleation phenomena are often overlooked in macro-scale models of current distribution during deposition. Here, a graphite flow-through electrode (FTE) is used as a model system for copper deposition within a single pore. Potential distributions and electro-nucleation phenomena are coupled in a continuum level model by incorporating nucleation size and density as a function of overpotential, determined experimentally using in situ atomic force microscopy (AFM). The model predictions are validated by measuring the coating uniformity in the pore using micro-computed X-ray tomography (μCT). A scaling analysis comprising dimensionless parameters such as the Wagner number is presented. The simplified scaling relationship framework can guide the electrodeposition process and electrode design to optimize plating of porous substrates under fluid flow conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Simulation of ENSO Teleconnections to Precipitation Extremes over the United States in the High-Resolution Version of E3SM

Abstract We evaluate the simulated teleconnection of El Niño–Southern Oscillation (ENSO) to winter season precipitation extremes over the United States in a long (98 years) 1950 control high-resolution version (HR; 25-km nominal atmosphere model horizontal resolution) of the U.S. Department of Energy’s (DOE) Energy Exascale Earth System Model version 1 (E3SMv1). The model bias and spatial pattern of ENSO teleconnections to mean and extreme precipitation in HR overall are similar to the low-resolution model’s (LR; 110 km) historical simulation (four-member ensemble, 1925–59). However, over the southeastern United States (SE-U.S.), HR produces stronger El Niño–associated extremes, reducing LR’s model bias. Both LR and HR produce weaker than observed increase in storm track activity during El Niño events there, but HR improves the ENSO-associated variability of moisture transport over SE-U.S. During El Niño, stronger vertical velocities in HR produce stronger large-scale precipitation, causing larger latent heating of the troposphere that pulls in more moisture from the Gulf of Mexico into the SE-U.S. This positive feedback also contributes to the stronger mean and extreme precipitation response in HR. Over the Pacific Northwest, LR’s bias of stronger than observed La Niña associated extremes is amplified in HR. Both models simulate stronger than observed moisture transport from the Pacific Ocean into the region during La Niña years. The amplified HR bias there is due to stronger orographically driven vertical updrafts that create stronger large-scale precipitation, despite weaker La Niña–induced storm track activity. Significance Statement New high-resolution Earth system models (ESMs) solve mathematical equations of fluid flow at much smaller spatial scales than prevalent ESMs, and thus are prohibitively expensive to compute. However, they can be useful for simulating accurate details of regional climate extremes that are driven by naturally occurring climate oscillations like El Niño–Southern Oscillation (ENSO). Here, we evaluate the simulation of ENSO-driven precipitation extremes over the United States in the high-resolution version of the U.S. Department of Energy’s new Energy Exascale Earth System Model version 1. We find that the high-resolution model improves upon its low-resolution counterpart over the southeastern United States by producing a better transport of moisture into the region from the Gulf of Mexico during El Niño. Over the U.S. Pacific Northwest, the high-resolution model simulates the atmospheric flow in more detail over the complex mountainous terrain. However, it also brings in more moisture from the Pacific Ocean just like the low-resolution model. This causes it to produce precipitation extremes during La Niña years there that are stronger than that observed in the real world.

54 ENVIRONMENTAL SCIENCES↗

High-Fidelity and High-Performance Computational Simulations for Rapid Design Optimization of Sulfur Thermal Energy Storage

Industrial process heating (IPH) accounts for approximately 70% of US manufacturing energy use and is primarily produced by fossil fuel combustion. Approximately 1500 TWht (approximately 60%) of IPH demand is in the temperature range of 100-300. Industrial applications in this temperature range include drying, hydrothermal processing, thermal enhanced oil recovery, food and beverage, bioethanol production, etc. Cost-effective thermal energy storage (TES) that increases the utilization of waste and renewable heat (solar, geothermal, etc.) could provide significant energy savings and reliable heat sources, decrease emissions, and increase US manufacturing competitiveness through reductions in fuel consumption. TES development has historically been dominated by technologies suitable for deployment with concentrating solar power (CSP). State-of-the-art thermal storage deployed commercially with power tower CSP plants uses a 60%/40% NaNO3/KNO3 molten salt and operates between temperatures of approximately 280 degrees Celsius and 570 degrees Celsius using a two-tank configuration. However, these nitrate salts are unsuitable for operation outside of this temperature range due to a high freezing point of approximately 220 degrees Celsius, and limits on high-temperature salt stability and corrosion resistance of containment alloys. Other materials being investigated for TES include those based on: (1) sensible energy storage (various molten salt compositions, inert solid particles, rocks or pebble beds, sulfur, water, concrete, graphite, etc.), (2) latent energy storage in materials that undergo solid-liquid phase change at relevant temperatures (organic materials for low-temperature applications, inorganic salts and/or metals for high-temperature applications), or (3) thermochemical energy storage (hydrides, hydroxides, carbonates, metal oxides, etc.). The application temperature and challenges pertaining to storage material and/or containment cost, energy density, long-term thermal and cyclic stability, and charge/discharge heat transfer effectiveness drive material selection for a given IPH or electricity generation application. Sulfur is a cheap commodity at $80/ton compared to $1100 - 1300/ton for conventional salts. When using a metric of storage cost per kWh, sulfur costs around 2-3 $/kWh. Previous sulfur TES development focused on high temperature (>600 degrees) concentrated solar power applications with sulfur encapsulated in pipes and flow of gaseous HTF (air) in the shell side. However, for lower-temperature IPH applications in the range of approximately 100-300 degrees Celsius Element 16 adopted a compact and scalable TES design with molten sulfur in the shell and HTF pipes submerged in the molten sulfur bath. The low-cost molten sulfur TES for dispatchable IPH has deployment potential for broad applications. The spatial and temporal evolution of the HTF and sulfur temperature is critical to the TES system performance, and thus detailed modeling can improve understanding of the performance and facilitate design improvements. Using high performance computing and computational fluid dynamics (CFD) a low-cost molten sulfur thermal energy storage (TES) system for industrial process heating (IPH) applications was developed. The unique challenges in CFD modeling of sulfur TES are the sharp property changes of sulfur relevant to the working temperatures. Above 159, liquid sulfur undergoes polymerization, and the viscosity of sulfur rapidly increases by several orders of magnitude between 159 degrees Celsius and 188 degrees Celsius, followed by a decrease in viscosity beyond 188 degrees Celsius due to thermal bound dissociation. In addition, various concentrations of H2S impurities can also modify sulfur viscosity. This numerical challenge is especially relevant to transient simulation of the sulfur TES charging and discharging processes as the extreme property variations limit the applicability of traditional heat transfer correlations. Transient CFD simulations including the temperature-dependent sulfur properties and geometric complexity of the TES design were used to predict the effect of natural convection during charging and discharging on the heat transfer process, sulfur temperature uniformity, charge/discharge rates, and performance of the storage devices. The CFD model was validated with experimental results for a full charge and discharge cycle. The work will show 3D and 2D simulation comparisons aimed to facilitate rapid design iterations and a machine learning based design optimization approach.

CFD↗

pH-SWITCHABLE DYNAMIC BINARY COMPLEXES AS VISCOSITY MODIFYING AGENTS

The study of supramolecular structures has been gaining a lot of momentum in recent years due to their potential application in several interesting areas such as medicine, catalysis, energy, oil and gas, etc. Hydraulic fracturing is one area where the ongoing demand for novel viscosity modifiers has prompted researchers to explore various facets of chemistry. In this study, a dynamic binary complex (DBC) solution is presented, with the potential to be useful in the hydraulic fracturing domain. It has a supramolecular structure that is formed by the self-assembly of oleic acid and diethylenetriamine into an elongated network under alkaline conditions. With less than 2 wt% of constituents in aqueous solution, a viscous gel that exhibits high viscosities even under shear was formed. It was sensitive to pH and salinity, and its zero-shear viscosity could be tuned by a factor of ~280 by changing the pH. Furthermore, its viscous properties were pronounced in the presence of salt. Sand settling tests revealed its potential to hold up sand particles for extended periods of time, longer than 24 hours. In conclusion, this DBC solution system has potential to be utilized as a smart pH-switchable hydraulic fracturing fluid that can be prepared using seawater.

02 PETROLEUM↗

Characterization of lift force and torque in prolate ellipsoid suspensions

The paper derives correlations for lift force and fluid torques acting on stationary prolate ellipsoid suspensions of aspect ratio (AR) 2.5, 5, and 10 subjected to uniform flow. Here, Particle Resolved Simulations (PRS) are conducted on a suspension of infinite extent in two directions for Reynolds number 10≤Re≤200 and solid fractions (φ) between 0.1≤φ≤0.3.The suspension-mean lift-to-drag ratio varies between 7% to 14% at Re=10 which increases to 14%~22% at Re=200. The torque-induced tip rotational acceleration can reach 38%~85% of drag-induced translational acceleration at Re=200. Single particle lift force and torque correlations of (Fröhlich et al., 2020) are modified and adapted to predict current angular-mean lift and torque data. The resulting lift correlation captures the PRS data within an average deviation below 7%. Torque exhibits a somewhat more complex dependency at AR=10 than the assumed sinθ ∙ cosθ variation but nevertheless the correlations predict angular-mean values with mean relative deviations of 16.6% at AR=10.

42 ENGINEERING↗

Effective Permeability of a Nuclear Fuel Assembly

This report aids in the development of models to perform characterization studies of aerosol dispersal and deposition within a spent fuel cask system. Due to the complex geometry in a spent-fuel canister, direct simulation of buoyancy-driven flow through the fuel assemblies to model aerosol deposition within the fuel canister is computationally expensive. Identification of an effective permeability as given in this work for a nuclear fuel assembly greatly simplifies the requirements for thermal hydraulic computations. The results of computations performed using OpenFOAM® to solve the Navier-Stokes Equations for laminar flow are used to determine an effective permeability by applying Darcy's Law. The computations are validated against an analytical solution for the special case of an infinite array of pins for which the numerical and analytical solutions have excellent agreement. The effective permeability of a 1717 PWR nuclear fuel assembly in a basket without spacer grids is numerically determined to be 1.85010 -6 m 2 for the range of fluid viscosities and pressure drops expected in a spent fuel storage canister. However, the flow is not uniform on the scale of multiple pins. Instead, significantly higher velocities are attained in the space between the assembly and the basket walls compared to the flow between the fuel pins within the assembly. Comparison with an analytical solution for fully developed flow through an infinite array of pins shows that the larger spacing near the basket walls results in about a 20% larger permeability compared to the analytical solution which does not include the enhanced flow in the space between the assembly and basket wall, or entrance and exit effects. A preliminary assessment of turbulence effects shows that with a k-epsilon model, significantly higher flow velocities are attained between the fuel pins within the assembly compared to the flow velocity in the space between the assembly and the basket walls. This is the opposite of what is determined for laminar flow.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Enhanced Laplace Pressures for Functional Surfaces: Wicking, Switchability, and Selectivity

Abstract Wetting functionalities of rough surfaces are largely determined by the Laplace pressure generated across liquid–gas interfaces formed within surface structures. Typically, rough wetting surfaces create negative Laplace pressures, enabling capillary wicking, while rough non‐wetting surfaces create positive Laplace pressures, exhibiting fluid repellency. Here, with microfabricated reentrant structures, it is shown that the same surface can exhibit either a negative or positive Laplace pressure, regardless of its intrinsic wettability. This material‐independent Laplace pressure duality enables or enhances a range of wetting functionalities including wicking, switchability, and selectivity. On the same surface, capillary rise, capillary dip, and the combination of the two which leads to further enhancement of the total sustainable capillary height and Laplace pressure, the driving force for wicking is demonstrated. Further, active switching of wetting states between the hemiwicking and the repellent Cassie state on reentrant structures is shown. Moreover, with a water‐hexane mixture system, selective wetting of reentrant structures are demonstrated, that is, water can be selectively wicked or repelled in the presence of hexane, and vice versa. These functionalities are achieved, which would typically require complex chemical coatings, solely using surface structures, thus largely expanding the design space for a wide range of thermofluidic applications.

36 MATERIALS SCIENCE↗

Investigation of thermal damage in explosive bridgewire detonators via discrete element method simulations

Exploding bridgewire (EBW) detonators are used to rapidly and reliably initiate energetic reactions by exploding a bridgewire via Joule heating. While the mechanisms of EBW detonators have been studied extensively in nominal conditions, comparatively few studies have addressed thermally damaged detonator operability. We present a mesoscale simulation study of thermal damage in a representative EBW detonator, using discrete element method (DEM) simulations that explicitly account for individual particles in the pressed explosive powder. We use a simplified model of melting, where solid spherical particles undergo uniform shrinking, and fluid dynamics are ignored. The subsequent settling of particles results in the formation of a gap between the solid powder and the bridgewire, which we study under different conditions. In particular, particle cohesion has a significant effect on gap formation and settling behavior, where sufficiently high cohesion leads to coalescence of particles into a free-standing pellet. This behavior is qualitatively compared to experimental visualization data, and simulations are shown to capture several key changes in pellet shape. We derive a minimum and maximum limit on gap formation during melting using simple geometric arguments. In the absence of cohesion, results agree with the maximum gap size. With increasing cohesion, the gap size decreases, eventually saturating at the minimum limit. In conclusion, we present results for different combinations of interparticle cohesion and detonator orientations with respect to gravity, demonstrating the complex behavior of these systems and the potential for DEM simulations to capture a range of scenarios.

cohesive powders↗

The impact of capillary heterogeneity on CO 2 flow and trapping across scales

Capillary heterogeneity has been identified over the last decade as a key control on subsurface CO 2 flow behavior during geological CO 2 sequestration. These heterogeneities can be formed in all sedimentary rocks, ranging from slight variations in the sand grain sizes to extensive sequences of interbedded sands, shales, and limestones. Capillary heterogeneity has been largely, although not entirely, overlooked in subsurface flow modeling because it is assumed to only directly influence fluid redistribution over scales of centimeters to meters. However, even small-scale fluid movements can result in dramatic impacts on the mobility and trapping of the CO 2 over kilometers. Therefore, neglecting capillary heterogeneity at multiple scales could potentially lead to errors in modeling and predicting field-scale plume migration. In this review paper, we aim to provide a consistent overview to (1) establish that capillary heterogeneity can have a major impact on CO 2 plume migration, (2) establish the respective length scales at which capillary heterogeneity matters, and (3) provide guidance for numerical modeling. This review covers pertinent literature and extracts key observations from the core to the field scales. Experimental studies have shown that millimeter-decimeter scale capillary heterogeneity can cause the so-called capillary heterogeneity trapping in addition to pore-scale residual trapping. Even at such a small scale, capillary heterogeneity can already lead to complex upscaled constitutive relationships, such as flow-rate dependent and anisotropic relative permeability, which affects field-scale CO 2 migration even when field-scale heterogeneities are present. Under gravity-dominated flow regimes, centimeter-meter scale capillary heterogeneity can entrap a significant amount of CO 2 at field scale, not just after imbibition but also during drainage. In certain cases, the presence of capillary heterogeneity can even completely stop the vertical movement of the CO 2 plume, hence greatly reducing leakage risks. At meter-kilometer scale, the influence of capillary heterogeneity is more pronounced and can hinder or redirect CO 2 migration in both lateral and vertical directions. The impact of capillary heterogeneity across multiple spatial scales poses a great challenge in modeling CO 2 migration at field scale, because it is practically impossible to build a field-scale earth model with grid blocks at millimeter scale. We recommend a hierarchical modeling approach to address this challenge. At field scale, earth models are built to capture geological features and heterogeneities in high but still practical grid resolutions. For each facies or rock type of the field-scale model, high- resolution meter-scale “conceptual” models are built with millimeter-scale grid blocks to capture representative fine-scale bedding geometries and heterogeneities in various environments of deposition, bridging the gap from subcore scale to the size of a field-scale simulation grid block. Upscaling is then used to preserve the smaller-scale flow dynamics of various rock types in field-scale simulations. Here, future work is needed to (1) refine, improve, and validate the hierarchical modeling approach; (2) build libraries of fine-scale bedding models for facies in various environments of deposition; (3) quantify multiscale capillary heterogeneity effects under subsurface uncertainties; (4) gain learning from different storage formations; and (5) establish best practices that balance accuracy and computational speed.

Capillary heterogeneity↗