Search NASA⌕ Search

SEARCH · Search NASA

Results for “Two dimensional flow”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Experimental and Numerical Investigation of Flow Boiling in Additive Manufactured Foam Structures With Vapor Pathways

Abstract The unique properties of metal foams make them potential candidates for a range of applications, including microsystem thermal management. Using additive manufacturing to create foam-type structures can improve upon prior thermal solutions by eliminating thermal interface materials and allowing for customization/local control of parameters. In the present investigation, flow boiling in additive-manufactured metal foams is investigated both experimentally and numerically. Two test samples, one with uniform structure and the other with pathways for vapor removal, are compared both experimentally and numerically. A conjugate computational fluid dynamics and heat transfer (CFD-HT) model utilizing a three-dimensional volume of fluid (VOF) model with accompanying evaporation/condensation model provided in-depth visualization of the boiling flow phenomena. The experiments generated the thermohydraulic performance over a range of heat fluxes, demonstrating that the sample incorporating dedicated vapor pathways performed better in both pressure and heat transfer performance metrics compared to the uniform foam. Additionally, negative system-level effects (i.e., hydraulic oscillations) were shown to be abated using the vapor removal structures. The numerical model yielded further insight into the factors contributing to the improved performance. Results indicated the pathways functioned as vapor removal channels, allowing the generated vapor to vent from the foam structure into the lanes. Further computational investigations demonstrated changes in flow regimes, where the addition of vapor channels caused the flow to change from churn to annular. Bubble behavior unique to the vapor pathway structure was studied, showing stagnant regions that eject vapor into the channel.

Engineering↗
DOE OSTI2025

ForestFlow: predicting the Lyman-α forest clustering from linear to nonlinear scales

On large scales, the Lyman-α forest provides insights into the expansion history of the Universe, while on small scales, it imposes strict constraints on the growth history, the nature of dark matter, and the sum of neutrino masses. This work introduces ForestFlow, a novel framework that bridges the gap between large- and small-scale analyses, which have traditionally relied on distinct modeling approaches. Using conditional normalizing flows, ForestFlow predicts the two Lyman-α linear biases (b δ and b η ) and six parameters describing small-scale deviations of the three-dimensional flux power spectrum (P 3D ) from linear theory as a function of cosmology and intergalactic medium physics. These are then combined with a Boltzmann solver to make consistent predictions, from arbitrarily large scales down to the nonlinear regime, for P 3D and any other statistics derived from it. Trained on a suite of 30 fixed-and-paired cosmological hydrodynamical simulations spanning redshifts from z = 2 to 4.5, ForestFlow achieves 3 and 1.5% precision in describing P 3D and the one-dimensional flux power spectrum (P 1D ) from linear scales to k = 5 Mpc −1 and k ∥ = 4 Mpc −1 , respectively. Thanks to its conditional parameterization, ForestFlow shows similar performance for ionization histories and two ΛCDM model extensions – massive neutrinos and curvature – even though none of these are included in the training set. This framework will enable full-scale cosmological analyses of Lyman-α forest measurements from the DESI survey.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Pressure–strain interaction. III. Particle-in-cell simulations of magnetic reconnection

How energy is converted into thermal energy in weakly collisional and collisionless plasma processes, such as magnetic reconnection and plasma turbulence, has recently been the subject of intense scrutiny. The pressure–strain interaction has emerged as an important piece, as it describes the rate of conversion between bulk flow and thermal energy density. In two companion studies, we presented an alternate decomposition of the pressure–strain interaction to isolate the effects of converging/diverging flow and flow shear instead of compressible and incompressible flow, and we derived the pressure–strain interaction in magnetic field-aligned coordinates. Here, we use these results to study pressure–strain interaction during two-dimensional anti-parallel magnetic reconnection. We perform particle-in-cell simulations and plot the decompositions in both Cartesian and magnetic field-aligned coordinates. We identify the mechanisms contributing to positive and negative pressure–strain interaction during reconnection. Furthermore, this study provides a roadmap for interpreting numerical and observational data of the pressure–strain interaction, which should be important for studies of reconnection, turbulence, and collisionless shocks.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

A method for examining ensemble averaging forms during the transition to turbulence in HED systems for application to RANS models

This paper discusses a strategy to initialize a two-dimensional (2D) Reynolds-averaged Navier–Stokes model [LANL's Besnard–Harlow–Rauenzahn (BHR) model] in order to describe an unsteady transitional Richtmyer–Meshkov (RM)-induced flow observed in on-going high-energy-density ensemble experiments performed on the OMEGA-EP facility. The experiments consist of a nominal single-mode perturbation (initial amplitude a 0 ≈ 10 and wavelength $λ$ = 100μm) with target-to-target variations in the surface roughness subjected to the RM instability with delayed Rayleigh–Taylor in a heavy-to-light configuration. Our strategy leverages high-resolution three-dimensional (3D) implicit large eddy simulations (ILES) simulations to initialize BHR-relevant parameters and subsequently validate the 2D BHR results against the 3D ILES simulations. A suite of five 3D ILES simulations corresponding to five experimental target profiles is undertaken to generate an ensemble dataset. Using ensemble averages from the 3D simulations to initialize the turbulent kinetic energy in the BHR model ( K 0 ) demonstrates the ability of the model to predict the time evolution of the interface as well as the density-specific-volume covariance, b . To quantify the sensitivity of the BHR results to the choice of K 0 and the initial turbulent length scale, S 0 , we execute a parameter sweep spanning four orders of magnitude for both S 0 and K 0 , generating a parameter space consisting of 26 simulations. The Pearson's correlation coefficient is used as a measure of discrepancy between the 2D BHR and 3D ILES simulations and reveals that the ranges 8≲S 0 ≲20 μm and 10 9 ≲K 0 ≲10 10 cm 2 /s 2 produce predictions that agree best with the 3D ILES results.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Numerical simulation of an atmospheric pressure plasma jet with coaxial shielding gas

A two-dimensional ( r, z ) numerical simulation of the discharge characteristics of an atmospheric pressure plasma jet (APPJ), with coaxial shielding gas, was performed. The helium working gas flowed in a central capillary tube, engulfing a needle electrode powered by 13.7 MHz radio frequency sinusoidal voltage. The N 2 shielding gas flowed in the annular space of a coaxial tube. These gases emerged, in laminar flow, in a 78%N 2 -21%O 2 -1%Ar dry air ambient. The characteristics of the APPJ with shielding gas were compared to those of the APPJ without shielding gas. The nitrogen shielding gas hindered the diffusion of oxygen and argon from the ambient air into the helium jet. With the shielding gas present, more nitrogen penetrated into the helium core, causing a shorter plasma ‘plume’. The flow rates of the working and shielding gas, critically affected the gas temperature, and in turn the discharge characteristics. For a He flow of 2 standard liters per minute (slm), switching on the nitrogen shielding gas flow (at 4.5 slm) reduced the on-axis O 2 and Ar mole fractions from 3.9 × 10 - 4 to 6.8 × 10 - 5 and from 1.9 × 10 - 5 to 3.3 × 10 - 6 , respectively, at an axial distance of 3 mm downstream of the nozzle. The radial profiles of the mole fractions of the ambient gases were monotonically and strongly decreasing towards the system axis, for short axial distances from the nozzle (~1 mm), but became progressively flatter at longer distances from the nozzle (3 mm and 5 mm). Simulation predictions captured the salient features of experimental data of ambient species mole fractions in the plasma jet, and the 706 nm optical emission intensity profiles of the He 3 3 S excited state.

Physics↗
DOE OSTI2020

Intrinsic orbital and spin Hall effects in monolayer transition metal dichalcogenides

The orbital Hall effect (OHE) is the phenomenon of transverse flow of orbital moment in the presence of an applied electric field. Solids with broken inversion symmetry are expected to exhibit a strong OHE due to the presence of an intrinsic orbital moment at individual momentum points in the Brillouin zone, which in the presence of an applied electric field flows in different directions causing a net orbital Hall current. Here we provide a comprehensive understanding of the effect and its tunability in the monolayer two-dimensional (2D) transition metal dichalcogenides (TMDCs). Both metallic and insulating TMDCs are investigated from full density-functional calculations and effective d-band tight-binding models, as well as a minimal four-band model for the valley points that captures the key physics of the system. For the tuning of the OHE, we examine the role of hole doping as well as the change in the band parameters, which, e.g., can be controlled by strain.We demonstrate that the OHE is a more fundamental effect than the spin Hall effect (SHE), with the momentum-space orbital moments inducing a spin moment in the presence of the spin-orbit coupling, leading to the SHE. The physics of the OHE, described here, is relevant for 2D materials with broken inversion symmetry in general, even beyond the TMDCs, providing a broad platform for future research.

2D materials↗
DOE OSTI2020

Development of a Reference Model for Molten-Salt-Cooled Pebble-Bed Reactor Using SAM

To support the development and utilization of the SAM code for fluoride-salt-cooled high-temperature pebble-bed reactor (PB-FHR) safety analysis and licensing, an effort was devoted to developing reference models for PB-FHR primary loop and the reactor cavity cooling system (RCCS). A reference standard problem of a prototypical reactor design is foundational to NRC and industry to verify the adequacy of computer codes and evaluation models for a specific reactor type. The SAM code was enhanced for the reference PB-FHR model development, including a 1D-3D flow coupling scheme and conjugate heat transfer between porous media and solid structures. The reference FHR primary loop model was developed based on the UC Berkeley Mk1 FHR design with additional design features from the Kairos Power’s KP-FHR core. The PB-FHR core is modeled by a two-dimensional porous medium while the rest of the primary loop is represented by a SAM one-dimensional model. A SAM one-dimensional primary loop model was also developed for comparison using a single channel approach for the reactor core. Furthermore, the water-based NSTF cavity was modeled using SAM multi-dimensional flow module, to assist in evaluating SAM capabilities of modeling the emergency heat removal systems relying on RCCS concepts.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

A Probabilistic Autoencoder for Type Ia Supernova Spectral Time Series

We construct a physically parameterized probabilistic autoencoder (PAE) to learn the intrinsic diversity of Type Ia supernovae (SNe Ia) from a sparse set of spectral time series. The PAE is a two-stage generative model, composed of an autoencoder that is interpreted probabilistically after training using a normalizing flow. We demonstrate that the PAE learns a low-dimensional latent space that captures the nonlinear range of features that exists within the population and can accurately model the spectral evolution of SNe Ia across the full range of wavelength and observation times directly from the data. By introducing a correlation penalty term and multistage training setup alongside our physically parameterized network, we show that intrinsic and extrinsic modes of variability can be separated during training, removing the need for the additional models to perform magnitude standardization. We then use our PAE in a number of downstream tasks on SNe Ia for increasingly precise cosmological analyses, including the automatic detection of SN outliers, the generation of samples consistent with the data distribution, and solving the inverse problem in the presence of noisy and incomplete data to constrain cosmological distance measurements. We find that the optimal number of intrinsic model parameters appears to be three, in line with previous studies, and show that we can standardize our test sample of SNe Ia with an rms of 0.091 ± 0.010 mag, which corresponds to 0.074 ± 0.010 mag if peculiar velocity contributions are removed.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

EXPERIMENTAL AND COMPUTATIONAL STUDY OF DIRECT CONTACT MEMBRANE DISTILLATION

Experimental and computational studies of direct contact membrane distillation (DCMD) are conducted. The permeate flux is measured in a module containing a flat sheet membrane. Polytetrafluoroethylene (PTFE) hydrophobic membrane (Membrane Solutions, FPB045A16) with a nominal pore size of 0.45 μm, the thickness of 179~239 μm, the porosity of 80% is used in the experiments. The feed solution is a binary mixture of water and NaCl. The inlet feed temperature is fixed at 70°C, and the feed Reynolds number is varied between 500 and 2000. Two inlet feed concentrations, 0 and 35g/L, are considered. The permeate flow rate was kept constant at Re of 1300 and temperature of 20°C. Three-dimensional steady-state computational fluid dynamics (CFD) simulations are performed using the laminar model. The Navier’s Stokes, energy, and mass transport equations in each channel coupled with flux boundary conditions imposed at the membrane surface are solved. The predicted module-averaged flux is compared to measured data for all operating conditions. Measured and predicted flux agrees well; validating both experiments and model, Temperature polarization in the feed and permeate channel and concentration polarization in the feed channel are characterized by validated CFD simulations.

Oztekin, Alparslan↗
DOE OSTI2024

The shape of convection in 2D and 3D global simulations of stellar interiors

Context. Theoretical descriptions of convective overshooting in stellar interiors often rely on a basic one-dimensional parameterization of the flow called the filling factor for convection. Several different definitions of the filling factor have been developed for this purpose, based on: (1) the percentage of the volume, (2) the mass flux, and (3) the convective flux that moves through the boundary. Aims. We examine these definitions of the filling factor with the goal of establishing their ability to explain differences between 2D and 3D global simulations of stellar interiors that include fully compressible hydrodynamics and realistic microphysics for stars. Methods. We study convection and overshooting in pairs of identical two-dimensional (2D) and three-dimensional (3D) global simulations of stars produced with MUSIC , a fully compressible, time-implicit hydrodynamics code. We examine pairs of simulations for (1) a 3 M ⊙ red giant star near the first dredge-up point, (2) a 1 M ⊙ pre-main-sequence star with a large convection zone, (3) the current sun, and (4) a 20 M ⊙ main-sequence star with a large convective core. Results. Our calculations of the filling factor based on the volume percentage and the mass flux indicate asymmetrical convection near the surface for each star with an outer convection zone. However, near the convective boundary, convective flows achieve inward-outward symmetry for each star that we study; for 2D and 3D simulations, these filling factors are indistinguishable. A filling factor based on the convective flux is contaminated by boundary-layer-like flows, making a theoretical interpretation difficult. We present two possible new alternatives to these frequently used definitions of a filling factor, which instead compare flows at two different radial points. The first alternative is the penetration parameter of Anders et al. (2022, ApJ, 926, 169). The second alternative is a new statistic that we call the plume interaction parameter. We demonstrate that both of these parameters captures systematic differences between 2D and 3D simulations around the convective boundary.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Flow and transport in three-dimensional discrete fracture matrix models using mimetic finite difference on a conforming multi-dimensional mesh

Here, we present a comprehensive workflow to simulate single-phase flow and transport in fractured porous media using the discrete fracture matrix approach. The workflow has three primary parts: (1) a method for conforming mesh generation of and around a three-dimensional fracture network, (2) the discretization of the governing equations using a second-order mimetic finite difference method, and (3) implementation of numerical methods for high-performance computing environments. A method to create a conforming Delaunay tetrahedralization of the volume surrounding the fracture network, where the triangular cells of the fracture mesh are faces in the volume mesh, that addresses pathological cases which commonly arise and degrade mesh quality is also provided. Our open-source subsurface simulator uses a hierarchy of process kernels (one kernel per physical process) that allows for both strong and weak coupling of the fracture and matrix domains. We provide verification tests based on analytic solutions for flow and transport, as well as numerical convergence. We also provide multiple expositions of the method in complex fracture networks. In the first example, we demonstrate that the method is robust by considering two scenarios where the fracture network acts as a barrier to flow, as the primary pathway, or offers the same resistance as the surrounding matrix. In the second test, flow and transport through a three-dimensional stochastically generated network containing 257 fractures is presented.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

An Efficient 1-D Thermal Stratification Model for Pool-Type Sodium-Cooled Fast Reactors

Investigating thermal stratification in the upper plenum of a sodium fast reactor (SFR) is presently a technology gap in SFR safety analysis. Understanding thermal stratification will promote safe operation of the SFR before its commercial deployment. Stratified layers of liquid sodium with a large vertical temperature gradient could be established in the upper plenum of an SFR during a down-power or a loss-of-flow transient. These stratified layers are unstable and could result in uncertainties for the core safety of an SFR. In order to predict the occurrence of the thermal stratification efficiently, we developed a one-dimensional (1-D) transport model to estimate the temperature profile of the ambient fluid in the upper plenum. This model demands much less computational effort than computational fluid dynamics (CFD) codes and provides calculations with higher fidelity than historical system-level codes. Two flow conditions were considered separately in the current study depending on if in-vessel components are presented in the upper plenum. For the condition where in-vessel components, specifically the upper internal structure, are presented, we assumed that the impinging sodium was evenly dispersed in the ambient fluid within the distance between the bottom of the in-vessel component and the jet inlet surface. For the condition where no in-vessel components are presented, we assumed that the impinging sodium was evenly dispersed in the ambient fluid within the jet length, which was determined through data-driven trainings. The newly developed 1-D model showed similar performance with the CFD model in both cases. However, due to the assumption of flat profiles of the impinging jet axial dispersion rate, nonnegligible discrepancies between the 1-D prediction and the measured data were observed.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2026

Spatially Mapping the CO 2 Alkaline Sorbent Diffuse Microenvironment Using Operando Raman Spectroscopy

When designing a chemical process, the local balance of transport and kinetics, collectively referred to as the diffuse microenvironment, plays a critical role in performance but is difficult to directly observe. This work demonstrates a method of two-dimensional spatial chemical mapping of the diffuse microenvironment in the context of alkali metal hydroxide direct air capture of carbon dioxide using a custom operando gas-absorption flow cell along with confocal Raman spectroscopy. Notably, we observe the concentration boundary layer near the gas–liquid interface and elucidate the interplay of carbonate and bicarbonate ions within it while inferring local hydroxide depletion through continuum modeling. These first of their kind observations provide a technique to compare the performance of direct air capture solvents based on diffuse microenvironment dynamics while also providing metrics important for air contactor design such as boundary layer thickness. Overall, this work showcases a new experimental platform to study interfacial diffuse microenvironments in and outside of the field of direct air capture of carbon dioxide.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

pnnl/EZBattery

Cell performance optimization is important for improving the system efficiency of a redox flow battery. To gain better insights into key controlling factors Of system efficiency, this work first proposed a theoretical model for a unit cell by extending a two-dimensional analytic model to a full cell. The model is then used for cell performance optimization after validating it with experimental and numerical modeling data.

Bao, Jie↗
DOE OSTI2025

Bulk Motions in the Black Hole Jet Sheath as a Candidate for the Comptonizing Corona

Abstract Using two-dimensional general relativistic resistive magnetohydrodynamic simulations, we investigate the properties of the sheath separating the black hole jet from the surrounding medium. We find that the electromagnetic power flowing through the jet sheath is comparable to the overall accretion power of the black hole. The sheath is an important site of energy dissipation as revealed by the copious appearance of reconnection layers and plasmoid chains. About 20% of the sheath power is dissipated between 2 and 10 gravitational radii. The plasma in the dissipative sheath moves along a nearly paraboloidal surface with transrelativistic bulk motions dominated by the radial component, whose dimensionless 4-velocity is ∼1.2 ± 0.5. In the frame moving with the mean (radially dependent) velocity, the distribution of stochastic bulk motions resembles a Maxwellian with an “effective bulk temperature” of ∼100 keV. Scaling the global simulation to Cygnus X-1 parameters gives a rough estimate of the Thomson optical depth across the jet sheath, ∼0.01–0.1, and it may increase in future magnetohydrodynamic simulations with self-consistent radiative losses. These properties suggest that the dissipative jet sheath may be a viable “coronal” region, capable of upscattering seed soft photons into a hard, nonthermal tail, as seen during the hard states of X-ray binaries and active galactic nuclei.

Sridhar, Navin (ORCID:0000000255199550)↗
DOE OSTI2023

Airfoil Computational Fluid Dynamics - 9k shapes, 2 AoA's

This dataset contains aerodynamic quantities - including flow field values (momentum, energy, and vorticity) and summary values (coefficients of lift, drag, and momentum) - for 8,996 airfoil shapes, computed using the HAM2D CFD (computational fluid dynamics) model. The airfoil shapes were designed using the separable shape tensor parameterization that encodes two-dimensional shapes as elements of the Grassmann manifold. This data-driven approach learns two independent spaces of parameter from a collection of sample airfoils. The first captures large-scale, linear perturbations, and the second defines small-scale, higher-order perturbations. For this data, we used the G2Aero database of over 19,000 airfoil shapes to learn a parameter space that captured a wide array of shape characteristics. We fixed the linear deformations to be the mean over the database and sampled new shapes over a four-dimensional parameter space of higher-order perturbation. This sampling approaches allows for isolated analysis of non-linear airfoil shape deformations while holding other aspects (e.g., airfoil thickness) approximately constant. The aerodynamic quantities for the generated airfoil were obtained using the HAM2D code, which is a finite-volume Reynolds-averaged Navier-Stokes (RANS) flow solver. We employ a fifth-order WENO scheme for spatial reconstruction with Roe's flux difference scheme for inviscid flux and second-order central differencing for viscous flux. A preconditioned GMRES method is applied for implicit integration. The Spalart-Allmaras 1-eq turbulence model is used for the turbulence closure, and the Medida-Baeder 2-eq transition model is applied to account for the effects of laminar turbulent transition. The airfoil grid is generated with a total of 400 points on the airfoil surface, the initial wall-normal spacing of y+ = 1, and an outer boundary located at 300 chord lengths away from the wall. The CFD simulations are performed at a freestream Mach number of 0.1, Reynolds number of 9M, and at two angles of attack, 4 deg. and 12 deg. The simulations were performed using the Bridges-2 system at the Pittsburgh Supercomputing Center in February 2023 as part of the INTEGRATE project funded by the Advanced Research Projects Agency - Energy in the U.S. Department of Energy. The data was collected, reformatted, and preprocessed for this OEDI submission in July 2023 under the Foundational AI for Wind Energy project funded by the U.S. Department of Energy Wind Energy Technologies Office. This dataset is intended to serve as a benchmark against which new artificial intelligence (AI) or machine learning (ML) tools may be tested. Baseline AI/ML methods for analyzing this dataset have been implemented, and a link to their repository containing those models has been provided. The .h5 data file structure can be found in the GitHub Repository resource under explore_airfoil_9k_data.ipynb.

9k↗
DOE OSTI2025

Computationally efficient models for aqueous organic redox flow batteries

The rising usage of intermittent energy has garnered the need for large scale energy storage systems. Redox flow batteries (RFB) based energy storage system shows promising potential. Numerical simulations and machine learning approaches have been widely used to study RFB performance. The development of autonomous material discovery framework and digital twin of energy storage system usually needs to query cell performance through fast response models. In this study, two computationally efficient models are introduced: a physics-based analytical flow battery model (EZBattery), and a machine learning operator model (Deep Operator Network, denoted by DeepONet). Both models can provide cell performance near instantly, and prediction accuracy was systematically examined on an application of evaluating the performances of a 780 cm 2 aqueous organic redox flow battery (AORFB), using potential anolyte candidates in dihydroxyphenazine (DHP)-based family of organic materials. A validated computationally expansive 3-dimensional multi-physics finite element model by COMSOL was used as the ground truth and provided the training data set for the DeepONet. 1280 samples were generated with 10 properties to mimic the different possible anolyte candidates, and the cell performances were evaluated under 10 different combined operating conditions. The accuracy comparisons for the two computationally efficient models show that both models can provide comparable accuracy in predicting cell charging/discharging voltage curves. DeepONet can provide slightly higher overall accuracy than EZBattery with faster calculation speed, but highly relies on the training dataset. EZBattery does not need a training dataset and can provide interpretable physics-based explanations of the results, while being more flexible to adjust to adapt any different cell designs, flow battery architectures, and electrolyte materials.

Analytical model↗
DOE OSTI2022

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↗