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At least 1,801 records · Page 100

Evaluating the Rheo-electric Performance of Aqueous Suspensions of Oxidized Carbon Black

Here, the macroscopic properties of carbon black suspensions are primarily determined by the agglomerate microstructure built of primary aggregates. Conferring colloidal stability in aqueous carbon black suspensions should thus have a drastic impact on their viscosity and conductivity. Carbon black was treated with strong acids following a wet oxidation procedure. An analysis of the resulting particle surface chemistry and electrophoretic mobility was performed in evaluating colloidal stability. Changes in suspension microstructure due to oxidation were observed using small-angle X-ray scattering. Utilizing rheo-electric measurements, the evolution of the viscosity and conductivity of the carbon black suspensions as a function of shear rate and carbon content was thoroughly studied. The carboxyl groups installed on the carbon black surface through oxidation increased the surface charge density and enhanced repulsive interactions. Electrostatic stability inhibited the formation of the large-scale agglomerates in favor of the stable primary aggregates in suspension. While shear thinning, suspension conductivities were found to be weakly dependent on the shear intensity regardless of the carbon content. Most importantly, aqueous carbon black suspensions formulated from electrostatically repulsive primary aggregates displayed a smaller rise in conductivity with carbon content compared to those formulated from attractive agglomerates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Stochastic Galerkin methods for the steady-state Navier–Stokes equations

We study the steady-state Navier–Stokes equations in the context of stochastic finite element discretizations. Specifically, we assume that the viscosity is a random field given in the form of a generalized polynomial chaos expansion. For the resulting stochastic problem, we formulate the model and linearization schemes using Picard and Newton iterations in the framework of the stochastic Galerkin method, and we explore properties of the resulting stochastic solutions. We also propose a preconditioner for solving the linear systems of equations arising at each step of the stochastic (Galerkin) nonlinear iteration and demonstrate its effectiveness for solving a set of benchmark problems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Low-dissipation centred schemes for hyperbolic equations in conservative and non-conservative form

We propose a one-parameter family of low-dissipation centred numerical schemes for solving hyperbolic equations in conservative or non-conservative form, using finite volume or discontinuous Galerkin finite element methods. The new schemes spring out from the multi-dimensional FORCE method and are determined by a single parameter α ≥ 1. Given an increasing sequence of real numbers 1 ≤ α 1 < α 2 < . . . < α K , there corresponds a sequence of numerical schemes with stability restriction associated to a decreasing sequence of Courant numbers 1 > c 1 > c 2 > . . . > c K > 0 and a decreasing sequence of corresponding numerical viscosity functions d 1 > d 2 > . . . > d K . For a given Courant number c k ≤ 1 there is a real number α k > 0 and a corresponding stable scheme with minimal numerical viscosity d k . The proposed schemes suit very well the family of high-order discontinuous Galerkin finite element methods and the recently proposed class of ADER-TR schemes, whose orders of accuracy define decreasing sequences of Courant numbers, as the order of accuracy increases. The centred methods of this paper are stable in 2D and 3D in the frame of simultaneous updating formulae, unlike other centred methods, such as 1D FORCE, which are not. Furthermore, the schemes are highly accurate for slowly-moving waves, which is precisely the kind of waves that traditional centred methods smear disastrously. Additional features of the proposed schemes include ease of implementation and applicability to any hyperbolic system either in conservative or non-conservative form. Here, the proposed schemes are analysed and computationally assessed through a suite of test problems for a linear model system, for the Euler equations in one and two space dimensions, and for the Baer-Nunziato equations for compressible two-phase flow.

97 MATHEMATICS AND COMPUTING↗

Active- and transfer-learning applied to microscale-macroscale coupling to simulate viscoelastic flows

Active- and transfer-learning are applied to microscale dynamics of polymer flows for the multiscale discovery of effective constitutive approximations required in viscoelastic flow simulation. The result is macroscopic rheology directly connected to a microstructural model. Micro and macroscale simulations are adaptively coupled by means of Gaussian process regression (GPR) to run the expensive microscale computations only as necessary. This multiscale method is demonstrated with flows of a polymer solution as a model system. At the microscale level dissipative particle dynamics (DPD) is employed to model the fluid as a suspension of bead-spring micro-structures subjected to steady shear flow. The results yield the non-Newtonian viscosity and the first normal stress difference at strain rates as training data used in a GPR model. DPD parameters are calibrated with respect to experimental data for a real polymer solution. Compliance with these data requires adjustment of the DPD model's cutoff radius, which then becomes a function of the second invariant of the strain rate tensor. The FENE-P model is chosen for the macroscale description using the spectral element method (SEM) to simulate channel flow and flow past a circular cylinder. The DPD results at the lowest possible shear strain rate yield an estimate of the zero-shear rate viscosity, which allows the initiation of the macroscale flow by SEM as a Newtonian fluid. The resulting strain-rate field is surveyed to determine additional shear strain rate sampling points for the DPD system. This new information allows an initial fitting of parameters of the constitutive equation followed by new SEM simulations at the macroscale. Additionally, guided by active-learning GPR to select new sampling points, this process continues until convergence is achieved. The effectiveness of this new simulation paradigm for viscoelastic flows is tested with different macroscale operating conditions. The effective closure learned in the channel simulation is then transferred directly to the flow past a circular cylinder at low Reynolds number, where the results show that only two additional DPD simulations are required to achieve a satisfactory constitutive model. With an increase of the Reynolds number, the active-learning scheme automatically detects the inaccuracy of the learned constitutive model, and initiates additional DPD simulations for the extra data needed to once again close the microscale-macroscale coupled system. This new paradigm of active- and transfer-learning for multiscale modeling is readily applicable to other microscale-macroscale coupled simulations of complex fluids and other materials. Furthermore, the coupling between microscale and macroscale solvers can be seamlessly implemented with our open source multiscale universal interface (MUI) library.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Surface fluctuating hydrodynamics methods for the drift-diffusion dynamics of particles and microstructures within curved fluid interfaces

Here we introduce fluctuating hydrodynamics approaches on surfaces for capturing the drift-diffusion dynamics of particles and microstructures immersed within curved fluid interfaces of spherical shape. We take into account the interfacial hydrodynamic coupling, traction coupling with the surrounding bulk fluid, and thermal fluctuations. For fluid-structure interactions, we introduce Immersed Boundary Methods (IBM) and related Stochastic Eulerian-Lagrangian Methods (SELM) for curved surfaces. We use these approaches to investigate the statistics of surface fluctuating hydrodynamics and microstructures. For velocity autocorrelations, we find characteristic power-law scalings $τ^{-1}, τ^{-2}$, and plateaus can emerge. This depends on the physical regime associated with the geometry, surface viscosity, and bulk viscosity. This differs from the characteristic $τ^{-3/2}$ scaling for bulk three dimensional fluids. We develop theory explaining these observed power-laws associated with time-scales for dissipation within the fluid interface and coupling to the surrounding fluid. We then use our introduced methods to investigate a few example systems and roles of hydrodynamic coupling and thermal fluctuations including for the kinetics of passive particles and active microswimmers in curved fluid interfaces.

97 MATHEMATICS AND COMPUTING↗

Siloxane-modified polycarbosilane flexible Prepregs for fabrication of ceramic matrix composites via compression molding and PIP densification

For this work, the development of ceramic matrix composites (CMCs) using 5 harness satin carbon fiber fabric impregnated with commercial polycarbosilane precursor plasticized by siloxane copolymer was investigated aiming to improve wetting behavior and shape conformability. The polycarbosilane precursor and polysiloxane plasticizer were mixed at varying weight ratios to obtain flexible preceramic resin prepreg cloths. 13 plies of preceramic polymer prepreg cloths were stacked in 0/90° layup and cured by compression molding, followed by densified via PIP process. The CMCs were densified with eight PIP cycles followed by final crystallization at 1600 °C. The CMCs made with 10 wt% polysiloxane loading showed lower viscosity of the prepreg resin as well as higher strength and displacement to failure compared to those fabricated from unplasticized polycarbosilane prepolymer. In contrast, at higher concentration of plasticizer, viscosity of the prepreg resin increased, and the CMC became more brittle; however, it exhibited considerably higher thermal conductivity.

Carbosilane↗

Core-scale numerical simulation and comparison of breakdown of shale and resulting fractures using sc-CO 2 and water as injectants

Supercritical carbon dioxide (sc-CO 2 ) is an alternative to water for stimulation of low permeability systems such as shale gas and geothermal resources. Previously core-scale experimental studies have compared the behavior of CO 2 to water injection for sample breakdown. Due to differences in experimental setup and core sample preparation, inconsistent or even apparently contradictory conclusions have resulted. To reconcile this contradiction, a phase-field numerical model is applied to understand hydraulic fracturing experiments using Green River shale found in the literature. The finite element numerical model incorporates a rate-dependent phase-field fracture model developed separately to describe fracture initiation and growth. We investigate the impact of various material and fluid properties on the resulting fractures. Most importantly, we study the effect of fluid properties and boundary conditions on the breakdown pressure, including the direction of the resulting fracture plane. Model results predict that (1) sc-CO 2 injection in the laboratory may result in greater breakdown pressure than that of water under no-flow boundary conditions because lower viscosity sc-CO 2 may result in pressure build up at the core boundary that opposes fracture initiation and (2) lower viscosity sc-CO 2 also produces fast-propagating fractures that are less influenced by the bedding plane on their resulting fracture topology. Here our model offers a straightforward explanation and reconciliation of existing experimental observations, as well as a means to extrapolate to new conditions. Exploration of field-scale conditions suggests less pronounced or no elevation in breakdown pressure when sc-CO 2 is injected because the pressure build up effect at the system boundary is significantly less or absent at field length scales.

42 ENGINEERING↗

A level set approach for the computational study of a yield stress fluid filling a thin mold

Many important engineering and scientific applications such as cement slurries, foams, crude oil, and granular avalanches involve the concept of yield stress. Therefore, modeling yield stress fluids in different flow configurations, including the accurate prediction of the yield surface, is important. In this paper, we present a computational model based on the finite element method to study the flow of yield stress fluids in a thin mold and compare the results with data from flow visualization experiments. Here, we use the level set method to describe the interface between the filling fluid and air. We use polypropylene glycol as a model Newtonian fluid and Carbopol for the model yield stress fluid, as the Carbopol solution demonstrates yielding without thixotropy. To describe the yielding and shear-thinning behavior, we use a generalized Newtonian constitutive equation with a Bingham–Carreau–Yasuda form. We compare the results obtained from the mold filling experiments with the results from the three-dimensional (3D) model and from a reduced-order Hele-Shaw (HS) model that is two-dimensional, including the effect of shear-thinning along the thin direction only approximately. We show that both the 3D and the HS model can capture the experimental meniscus shape reasonably well for all the fluids considered at three different flow rates. This indicates that the shape evolution is insensitive to the dimensionality of the model. However, the viscosity and yield surfaces predicted by the 3D and HS models are different. The HS model underestimates the high viscosity and unyielded regions compared to the estimation by the 3D model.

42 ENGINEERING↗

Cold crucible induction melter studies for making glass ceramic waste forms: A feasibility assessment

Glass ceramics are being developed to immobilize fission products, separated from used nuclear fuel by aqueous reprocessing, into a stable waste form suitable for disposal in a geological repository. This work documents the glass ceramic formulation at bench scale and for a scaled melter test performed in a pilot-scale (approximately 1/4 scale) cold crucible induction melter (CCIM). Melt viscosity, electrical conductivity, and crystallization behavior upon cooling were measured on a small set of compositions to select a formulation for melter testing. Property measurements also identified a temperature range for melter operation and cooling profiles necessary to crystallize the targeted phases in the waste form. Bench scale and melter run results successfully demonstrate the processability of the glass ceramic using the CCIM melter technology.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Iodine solubility in a low-activity waste borosilicate glass at 1000°C

The purpose of this study was to determine the solubility of iodine in a low-activity waste borosilicate glass when heated inside an evacuated and sealed fused quartz ampoule. The iodine was added to glass frit as KI in quantities of 100–24000 ppm iodine (by mass), each mixture was added to an ampoule, the ampoules were heated at 1000 °C for 2h, and then air quenched. In samples with ≥12000 ppm iodine, low viscosity salt phases were observed on the surface of the melts during cooling that solidified into a white coating upon cooling. These salts were identified as mixtures of KI, NaI, and Na 2 SO 4 with X-ray diffraction (XRD). The iodine concentrations in glass specimens were analyzed with inductively-coupled plasma mass spectrometry and the overall iodine solubility was determined to be 10000 ppm by mass. Several crystalline inclusions of iodine sodalite, Na 8 (AlSiO 4 ) 6 I 2 , were observed in the 24000 ppm specimen as determined by micro-XRD and wavelength dispersive spectroscopy.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Fluorinated Phosphazene Co-solvents for Improved Thermal and Safety Performance in Lithium-Ion Battery Electrolytes

The safety of lithium-ion batteries is coming under increased scrutiny as they are being adopted for large format applications especially in the vehicle transportation industry and for grid-scale energy storage. The primary short-comings of lithium-ion batteries are the flammability of the liquid electrolyte and sensitivity to high voltage and elevated temperatures. We have synthesized a series of non-flammable fluorinated phosphazene liquids and blended them with conventional carbonate solvents. While the use of these phosphazenes as standalone electrolytes is highly desirable, they simply do not satisfy all of the many requirements that must be met such as high LiPF6 solubility and low viscosity, thus we have used them as additives and co-solvents in blends with typical carbonates. The physical and electrochemical properties of the electrolyte blends were characterized, and then the blends were used to build 2032-type coin cells which were evaluated at constant current cycling rates from C/10 to C/1. We have evaluated the performance of the electrolytes by determining the conductivity, viscosity, flash point, vapor pressure, thermal stability, electrochemical window, cell cycling data, and the ability to form solid electrolyte interphase (SEI) films. This paper presents our results on a series of chemically similar fluorinated cyclic phosphazene trimers, the FM series, which has exhibited numerous beneficial effects on battery performance, lifetimes, and safety aspects.

25 ENERGY STORAGE↗

Microrheological modeling of lithium ion battery anode slurry

The rheological properties of electrode slurries used in the manufacturing of lithium-ion batteries affect the manufacturing processes as well as the battery quality, such as electrochemical and durability performance. There is thus an urgent need to develop a physics-based model to describe the rheological properties of these electrode slurries to enable further optimization of battery electrode production. Here in this paper, we present a microrheological model for estimating the viscosity of electrode slurries that incorporates colloidal forces such as van der Waals and polymeric steric repulsion forces. Finally, the model shows good agreement with the experimentally determined viscosities of a graphite-based anode slurry and should be extendable to describe the rheological properties of cathode slurries.

25 ENERGY STORAGE↗

Supported ionic liquid membranes (SILMs) with exceptional selectivity and permeability for dilute CO 2 separations

Supported ionic liquid membranes (SILMs), containing phosphonium ionic liquids with aprotic N-heterocyclic anions (AHA ILs) in an inert inorganic support, were tested under both dry and humidified (40 % RH) mixed-gas conditions down to 420 ppm CO 2 in N 2 at 35 °C. In the dry case, the best performing IL, triethyl(octyl)phosphonium 4-bromopyrazolide ([P 2228 ][4-BrPyra]) exhibited mixed-gas CO 2 permeabilities and CO 2 /N 2 permeability selectivities as high as 26,800 barrer and 7,000, respectively. In the presence of humidity, the CO 2 permeability and CO 2 /N 2 selectivity increased to 49,100 barrer and 13,200, respectively, and these are the highest reported combination in the literature. Humidity amplifies CO 2 permeabilities and CO 2 /N 2 permeability selectivities through increases in CO 2 capacity due to bicarbonate formation and through faster mobility of the mobile carrier from decreased viscosity. Furthermore, N 2 permeability stayed roughly invariant in the presence of humidity, likely from competing effects of viscosity reduction and lower N 2 solubility.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Pressure-stable supported ionic liquid membranes using isoporous supports for evaluating pure- and mixed-gas light paraffin fractionation

Advances in horizontal drilling and hydraulic fracturing have spurred the growth of domestic U.S. energy production. Membranes, typically silicone rubbers, have found utility in shale gas treatment as fuel gas conditioning units to selectively remove C 2 + hydrocarbons at pressures up to 30 bar, producing clean CH 4 for gas engines. However, more selective materials could be beneficial for broader shale gas treatment applications, such as dew point control units. Supported ionic liquid membranes (SILMs) offer a potential opportunity for improving C 3 H 8 /CH 4 selectivity, but they lack pressure-stability. Here, we report C 3 H 8 /CH 4 selective and pressure-stable SILMs using isoporous supports. SILMs with supports that had minimal defects remained stable up to 15 bar of transmembrane pressure. This stability allowed for pure- and mixed-gas testing of the resulting membranes at elevated pressures. Furthermore, these tests revealed that low viscosity ILs (<100 cp) may display mixed-gas permeances and permselectivity nearly identical to pure-gas results. On the other hand, higher viscosity ILs may display increasing permeances and permselectivity with increasing C 3 H 8 fugacity, similar to rubbery polymers. Ultimately, the SILMs demonstrated relatively high pressure-stability due to the isoporous supports and competitive mixed-gas C 3 H 8 /CH 4 permselectivity compared to silicone rubber.

Rosenthal, Justin J. [University of Texas at Austi↗

Carbon molecular sieve membranes on porous composite tubular supports for high performance gas separations

Thin carbon molecular sieve membranes (<500 nm) were fabricated inside of long geometry (9 inch) of stainless steel tubes with all welded construction. Alumina intermediate layer on porous stainless steel tube support was used to reduce effective support pore size and to provide a more uniform surface roughness. Novolac phenolic resin solution was then coated on the inside of porous stainless steel tube by slip casting while their viscosities were controlled from 5 centipoises to 30 centipoises. Carbonization was carried out at 700 °C in which thermal stress was minimized and high quality carbon films were prepared. The highest separation performance characteristics were obtained using 20 cP phenolic resin solutions. The fabricated CMSM showed good separation factor for He/N 2 462, CO 2 /N 2 97, and O 2 /N 2 15.4. As the viscosity of polymer precursor solution was reduced from 20 cP to 15 cP, gas permeance values almost doubled with somewhat lower separation factor He/N 2 156, CO 2 /N 2 88, and O 2 /N 2 7.7.

36 MATERIALS SCIENCE↗

Deep glassy state dynamic data challenge glass models: Elastic models

The idea of an “ideal” glass transition temperature has persisted at least since the work from Kauzmann when it was observed that the entropy of glass-forming liquids extrapolated to below that of the crystal, thus suggesting the need for a phase transition at a finite or non-zero absolute temperature. This thermodynamic paradox was also found to be related to the observations of a diverging of the extrapolated viscosity or relaxation times at a temperature near to this ideal glass transition. Recently, however, we have carried out experiments using both an ancient amber material and an ultra-stable amorphous fluoropolymer that challenge the ideas of the divergence of the viscosity or relaxation times at this ideal glass transition. In the present manuscript we have evaluated two theories of the glass transition that are based on ideas related to elasticity of the amorphous glass-forming material. We find that the models from both J. Dyre and his group and of K.S. Schweizer and his group not only show non-diverging behavior but are also in some agreement with the new data, though still showing somewhat slower dynamics than those observed in the experiments. The work shows that the data are good enough to distinguish between theories and it is suggested that other mechanisms may be needed to fully describe the non-diverging responses of the ultra-stable glasses.

36 MATERIALS SCIENCE↗

Data-driven modeling of coarse mesh turbulence for reactor transient analysis using convolutional recurrent neural networks

Advanced nuclear reactors often exhibit complex thermal-fluid phenomena during transients. To accurately capture such phenomena, a coarse-mesh three-dimensional (3-D) modeling capability is desired for modern nuclear-system code. In the coarse-mesh 3-D modeling of advanced-reactor transients that involve flow and heat transfer, accurately predicting the turbulent viscosity is a challenging task that requires an accurate and computationally efficient model to capture the unresolved fine-scale turbulence. In this work, we propose a data-driven coarse-mesh turbulence model based on local flow features for the transient analysis of thermal mixing and stratification in a sodium-cooled fast reactor. The model has a coarse mesh setup to ensure computational efficiency, while it is trained by fine-mesh computational fluid dynamics (CFD) data to ensure accuracy. A novel neural network architecture, combining a densely connected convolutional network and a long-short-term-memory network, is developed that can efficiently learn from the spatial temporal CFD transient simulation results. The neural network model was trained and optimized on a loss-of flow transient and demonstrated high accuracy in predicting the turbulent viscosity field during the whole transient. The trained model's generalization capability was also investigated on two other transients with different inlet conditions. The study demonstrates the potential of applying the proposed data-driven approach to support the coarse-mesh multi-dimensional modeling of advanced reactors.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

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