Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “multiphase flows”

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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Quantifying the Effect of Pore‐Size Dependent Wettability on Relative Permeability Using Capillary Bundle Model

Abstract Relative permeability is a key parameter for characterizing the multiphase flow dynamics in porous media at macroscopic scale while it can be significantly impacted by wettability. Recently, it has been reported in microfluidic experiments that wettability is dependent on the pore size (Van Rooijen et al., 2022). To investigate the effect of pore‐size‐dependent wettability on relative permeability, we propose a theoretical framework informed by digital core samples to quantify the deviation of relative permeability curves due to wettability change. We find that the significance of impact is highly dependent on two factors: (i) the function between contact angle and pore size (ii) overall pore size distribution. Under linear function, this impact can be significant for tight porous media with a maximum deviation of 1,000%.

Yu, Siqin↗
DOE OSTI2018

Pore geometry control of apparent wetting in porous media

Abstract Wettability, or preferential affinity of a fluid to a solid substrate in the presence of another fluid, plays a critical role in the statics and dynamics of fluid-fluid displacement in porous media. The complex confined geometry of porous media, however, makes upscaling of microscopic wettability to the macroscale a nontrivial task. Here, we elucidate the contribution of pore geometry in controlling the apparent wettability characteristics of a porous medium. Using direct numerical simulations of fluid-fluid displacement, we study the reversal of interface curvature in a single converging-diverging capillary, and demonstrate the co-existence of concave and convex interfaces in a porous medium—a phenomenon that we also observe in laboratory micromodel experiments. We show that under intermediate contact angles the sign of interface curvature is strongly influenced by the pore geometry. We capture the interplay between surface chemical properties and pore geometry in the form of a dimensionless quantity, the apparent wettability number, which predicts the conditions under which concave and convex interfaces co-exist. Our findings advance the fundamental understanding of wettability in confined geometries, with implications to macroscopic multiphase-flow processes in porous media, from fuel cells to enhanced oil recovery.

42 ENGINEERING↗
DOE OSTI2017

Are continuum predictions of clustering chaotic?

Gas-solid multiphase flows are prone to develop an instability known as clustering. Two-fluid models, which treat the particulate phase as a continuum, are known to reproduce the qualitative features of this instability, producing highly-dynamic, spatiotemporal patterns. However, it is unknown whether such simulations are truly aperiodic or a type of complex periodic behavior. By showing that the system possesses a sensitive dependence on initial conditions and a positive largest Lyapunov exponent, λ 1 ≈1/τ, we provide a tentative answer: continuum predictions of clustering are chaotic. We further demonstrate that the chaotic behavior is dimensionally dependent, a conclusion which unifies previous results and strongly suggests that the chaotic behavior is not a direct consequence of the fundamental kinematic instability, but requires a secondary (inherently multidimensional) instability. Granular matter is a collection of discrete, interacting solid particles which, like classic (molecular) matter, can be generally classified into one of three states:1 (i) under static conditions granular heaps or piles can sustain gravity-induced stress and behave like a solid; (ii) dense granular flows characterized by enduring and multi-particle contacts behave similarly to a fluid; and (iii) rapid granular flows characterized by instantaneous contacts described as a granular gas. However, it is worth noting that all three granular states are only superficially similar to their molecular counterparts due to the dissipative nature of particle-particle contacts (inelasticity, friction, etc.). In industrial operations, rapid (collision-dominated) granular flows are often encountered in devices in which the particles are fluidized by a gas; such gas-solid flows are the focus of this work. Rapid gas-solid flows are prone to an instability termed clustering in which particles tend to form spatially inhomogeneous patterns of high and low concentrations. Continuum or two-fluid models (TFM) have long been known to be able to predict the qualitative nature of the clustering instability and more recent quantitative assessments have also shown promising results. However, it is yet unknown whether or not such predictions are chaotic. We take a first step in answering this question by simulating fluidization in an unbounded domain and calculating a positive largest Lyapunov exponent (LLE), thereby indicating that continuum predictions of clustering are in fact chaotic. Further, we show that chaotic behavior may be reduced to periodic behavior by constraining the dimensionality of the system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

On the effect of mixing-driven vaporization in a homogeneous relaxation modeling framework

The homogeneous relaxation model (HRM) is one of the most widely used models to describe the liquid–gas phase transition in multiphase flows due to the occurrence of cavitation. However, in its original formulation, the HRM does not account for the presence of ambient gas species, which generally limits its applicability to the injector's internal flow where ambient gases are negligible. In this work, a mixing-driven vaporization (MDV) model was developed to extend the capability of the HRM in handling the mixing effect in the regions external to the nozzle, where vapor–liquid equilibrium for multi-species mixtures of fuel and ambient gas is considered. Herein, to assess the model performance, simulations of the Engine Combustion Network's Spray G injector were performed with the HRM and the MDV model under both flash-boiling and evaporating conditions. It was found that the MDV model led to a better match against x-ray measurements of fuel density in the near-nozzle region. In contrast to the HRM, the MDV model was able to reproduce the vaporization process in the mixing zone at the edge of the fuel jet, which aligns with the expected physics. This resulted in substantial differences in the prediction of other flow characteristics such as mixture temperature and pressure. Furthermore, this work demonstrates that evaporation timescales have a considerable effect on the MDV model's predictions, as shown by a parametric study in which a time factor was introduced to mimic the effect of different timescales due to different phase change mechanisms.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Development of a Validation Approach for an Integrated Waste Glass Melter Model

Integrated models are being developed to represent the physics occurring within the high-level and low-activity waste melters that will be used to vitrify legacy tank waste at the Hanford site. These models couple the melt pool, cold cap, and plenum region within a single computational domain. Validation of the models is essential to ensure the reliability of the numerical predictions of the operational melters. Experimental data from laboratory- and pilot-scale tests are thus being used to inform and validate various aspects of the melter model. This study presents a tiered approach to model validation consisting of a series of progressively more complex test cases designed to model the physics occurring in the full-scale system. A hierarchical methodology has been developed to segregate and simplify the physical phenomena affecting the multiphase flow and heat transfer within a waste glass melter. Finally, four hierarchical levels are defined in a validation pyramid and built up in levels of increasing complexity from unit problems to subsystem cases, to pilot-scale systems, and then to the full-scale system.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Model Development for Thermal-Hydrology Simulations of a Full-Scale Heater Experiment in Opalinus Clay

Disposal of commercial spent nuclear fuel in a geologic repository is studied. In situ heater experiments in underground research laboratories provide a realistic representation of subsurface behavior under disposal conditions. Here, this study describes process model development and modeling analysis for a full-scale heater experiment in opalinus clay host rock. The results of thermal-hydrology simulation, solving coupled nonisothermal multiphase flow, and comparison with experimental data are presented. The modeling results closely match the experimental data.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2014

Bayesian Treed Multivariate Gaussian Process with Adaptive Design: Application to a Carbon Capture Unit

Computer experiments (numerical simulations) are widely used in scientific research to study and predict the behavior of complex systems, which usually have responses consisting of a set of distinct outputs. The computational cost of the simulations at high resolution are often expensive and become impractical for parametric studies at different input values. To overcome these difficulties we develop a Bayesian treed multivariate Gaussian process (BTMGP) as an extension of the Bayesian treed Gaussian process (BTGP) in order to model and evaluate a multivariate process. A suitable choice of covariance function and the prior distributions facilitates the different Markov chain Monte Carlo (MCMC) movements. We utilize this model to sequentially sample the input space for the most informative values, taking into account model uncertainty and expertise gained. A simulation study demonstrates the use of the proposed method and compares it with alternative approaches. We apply the sequential sampling technique and BTMGP to model the multiphase flow in a full scale regenerator of a carbon capture unit. The application presented in this paper is an important tool for research into carbon dioxide emissions from thermal power plants.

Konomi, Bledar A.↗
DOE OSTI2016

Influence of phase connectivity on the relationship among capillary pressure, fluid saturation, and interfacial area in two-fluid-phase porous medium systems

Here, multiphase flow in porous medium systems is typically modeled using continuum mechanical representations at the macroscale in terms of averaged quantities. These models require closure relations to produce solvable forms. One of these required closure relations is an expression relating fluid pressures, fluid saturations, and, in some cases, the interfacial area between the fluid phases, and the Euler characteristic. An unresolved question is whether the inclusion of these additional morphological and topological measures can lead to a non-hysteretic closure relation compared to the hysteretic forms that are used in traditional models, which typically do not include interfacial areas, or the Euler characteristic. We develop a lattice-Boltzmann (LB) simulation approach to investigate the equilibrium states of a two-fluid-phase porous medium system, which include disconnected now- wetting phase features. The proposed approach is applied to a synthetic medium consisting of 1,964 spheres arranged in a random, non-overlapping, close-packed manner, yielding a total of 42,908 different equilibrium points. This information is evaluated using a generalized additive modeling approach to determine if a unique function from this family exists, which can explain the data. The variance of various model estimates is computed, and we conclude that, except for the limiting behavior close to a single fluid regime, capillary pressure can be expressed as a deterministic and non-hysteretic function of fluid saturation, interfacial area between the fluid phases, and the Euler characteristic. This work is unique in the methods employed, the size of the data set, the resolution in space and time, the true equilibrium nature of the data, the parameterizations investigated, and the broad set of functions examined. The conclusion of essentially non-hysteretic behavior provides support for an evolving class of two-fluid-phase flow in porous medium systems models.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Numerical calculation of the particle–fluid–particle stress in random arrays of fixed particles

Based on the nearest particle statistics [Zhang, J. Fluid Mech. 910, A16 (2021)], the phase interaction force in a multiphase flow is decomposed into a particle–mean-field force and the divergence of the particle–fluid–particle (PFP) stress. The PFP stress is proportional to the correlation product of the distance from a particle to its nearest neighbor and the force on the particle conditionally averaged on the nearest-neighbor location. In this work, a functional form of the stress is obtained corrected to the first order of the ratio between the interparticle distance and the macroscopic length scale of the flow. Particle-resolved numerical simulations are used to calculate the PFP stress in random arrays of fixed particles and to explore the physics represented by the stress. The numerical results show that the PFP stress is attractive along the direction of the flow and is repulsive in the directions perpendicular to the flow. In the flow regime simulated, this PFP stress can be considered as a macroscopic representation of the drafting–kissing–tumbling mechanism. Finally, the Reynolds stress for the fluid phase is also calculated and compared with the PFP stress.

42 ENGINEERING↗
DOE OSTI2023

Point-particle drag, lift, and torque closure models using machine learning: Hierarchical approach and interpretability

Developing deterministic neighborhood-informed point-particle closure models using machine learning has garnered interest recently from the dispersed multiphase flow community. The robustness of neural models for this complex multibody problem is hindered by the availability of particle-resolved data. Here, the present work addresses this unavoidable limitation of data paucity by implementing two strategies: (1) by using a rotation and reflection equivariant neural network and (2) by pursuing a physics-based hierarchical machine learning approach. The resulting machine-learned models are observed to achieve a maximum accuracy of 85% and 96% in the prediction of neighbor-induced force and torque fluctuations, respectively, for a wide range of Reynolds number and volume fraction conditions considered. Furthermore, we pursue force and torque network architectures that provide universal prediction spanning a wide range of Reynolds number (0.25 ≤ Re ≤250) and particle volume fraction (0 ≤ φ ≤0.4). The hierarchical nature of the approach enables improved prediction of quantities such as streamwise torque, by going beyond binary interactions to include trinary interactions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Controlling Viscous Fingering Using Time-Dependent Strategies

Control and stabilization of viscous fingering of immiscible fluids impacts a wide variety of pressure-driven multiphase flows. Here, we report theoretical and experimental results on time-dependent control strategy by manipulating the gap thickness b(t) in a lifting Hele-Shaw cell in the power-law form b(t) = b 1 t 1/7 . Experimental results show good quantitative agreement with the predictions of linear stability analysis. Furthermore, by choosing the value of a single time-independent control parameter we can either totally suppress the viscous fingering instability or maintain a series of non-splitting viscous fingers during the fluid displacement process. Besides the gap thickness of a Hele-Shaw cell, in principle, time-dependent control strategies can also be placed on the injection rate, viscosity of the displaced fluid, and interfacial tensions between the two fluids.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Cross-Plane Acquisitions in Electrical Capacitance Volume Tomography

Electrical capacitance tomography (ECT) is a widely used imaging modality to image two-dimensional cross sections of multiphase flows. Recent developments in electrical capacitance volume tomography (ECVT) have made it possible to directly obtain volumetric images from measured data. An ECVT is instrumental for obtaining accurate phase hold up information and velocity information that are needed for the optimization of certain flow processes. However, compared to ECT, the high correlation between the measurements in ECVT exacerbates the ill-conditioning of the associated image reconstruction problem. Previous studies have suggested that neglecting mutual capacitance data between the ECVT electrodes located at cross-planes that are well separated along the sensor axis can be done without significantly affecting the reconstructed image. In addition, this may help constrain the ill-conditioning of the reconstruction problem. Here, we examine in detail and quantify the effect of reduced cross-plane acquisition strategies for optimizing the image reconstruction and constraining the ill-conditioning of typical ECVT settings.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2021

Feature Analysis, Tracking, and Data Reduction: An Application to Multiphase Reactor Simulation MFiX-Exa for In-Situ Use Case

As we enter the exascale computing regime, powerful supercomputers continue to produce much higher amounts of data than what can be stored for offline data processing. To utilize such high compute capabilities on these machines, much of the data processing needs to happen in situ, when the full high-resolution data is available at the supercomputer memory. In this article, we discuss our MFiX-Exa simulation, which models multiphase flow by tracking a very large number of particles through the simulation domain. In one of the use cases, the carbon particles interact with air to produce carbon dioxide bubbles from the reactor. These bubbles are of primary interest to the domain experts for these simulations. For this particle-based simulation, we propose a streaming technique that can be deployed in situ to efficiently identify the bubbles, track them over time, and use them to down-sample the data with minimal loss in these features.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

An Investigation of the Effects of Volume Fraction on Drag Coefficient of Non-Spherical Particles Using PR-DNS

Prediction of the drag coefficient is required in gas-particle multiphase flow modeling and simulation. Experimental data and correlations on the fixed-bed system of spherical particles with high volume fractions for various possible arrangements are available in the literature. However, the effect of volume fraction on the drag coefficient of non-spherical particles is not well studied. In solving the momentum equation, the volume fraction plays a vital role in determining the flow resistances. In this paper, we study the impact of volume fraction in the range of 0.069 to 0.65 on the drag coefficient using the computational fluid dynamics (CFD) simulation of air for Reynold number in the range of 10 to 10000 using particle resolved direct numerical solution (PR-DNS). Regular non-spherical particles such as a cube, tetrahedron, and spheroids are used in this study since their single particle’s drag coefficient data are available in the literature for comparison. For this work, the simulations are carried out in the Ansys Fluent using polyhedral mesh, which consumes significantly less computational time and power. The study showed the sphericity and volume fraction have significant impact on the bed pressure drop and average drag coefficient of the particles in the bed especially in high Reynolds number regime. The bed of the spheroid experiences the lowest drag being the most streamlined particle, and the particles with the edges result in a large drag coefficient due to flow separation at the discontinuity. The vector plots verify this behavior where large wake regions are observed behind the tetrahedron particle.

Mahyawansi, Pratik↗
DOE OSTI2017

Evenly spaced columns in the Bishop Tuff (California, USA) as relicts of hydrothermal cooling

A few square kilometers of the Bishop Tuff in eastern California (USA) have evenly spaced columns that are more resistant to erosion than the surrounding tuff owing to the precipitation of mordenite, a low-temperature (100-130 °C) zeolite. We hypothesize that the columns are a result of instabilities at the liquid water and steam interface as cold water seeped into the still-cooling Bishop Tuff. We use two methods to quantitatively assess this hypothesis. First, scaling shows which hydrodynamic instabilities exist in the system. Second, to account for the effects of multiphase flow, latent heat, and the finite amplitude and temporal evolution of these instabilities we use two-dimensional numerical models of liquid water infiltrating hot tuff. These tests highlight several features of boiling hydrothermal systems. (1) The geometry of at least some convection appears to be broadly captured by linear stability theory that neglects reactive transport, heterogeneity of the host rock, and the finite amplitude of instabilities. (2) Slopes > 10% set the wavelength of convection, meaning that these columns formed somewhere with relatively gentle topography. (3) For permeabilities of > 10 -13 m 2 , the wavelength of the instability changes through time, slowing infiltration, while for permeabilities < 10 -15 m 2 , cooling is dominated by conduction. The spacing and stability of columns increase with higher vertical permeability and decrease with higher horizontal permeability. These columns are a rare window into hydrothermal processes that may be widespread.

58 GEOSCIENCES↗
DOE OSTI2020

(Invited) Virtual Analysis of Gas-Diffusion-Electrode CO 2 Electrolyzers

The electrochemical reduction of CO 2 (CO 2 R) to value-added products is an attractive technology for tackling the rising atmospheric CO 2 levels and storing intermittent renewable energy into chemical bonds. Fundamental understanding of CO 2 R has progressed significantly in recent years and is critical in the development of CO 2 R to liquid-fuel electrolyzers, where gas-diffusion electrodes (GDEs) have been shown to be key enabling architectures. Various designs have been proposed and studied in the literature to enhance overall selectivity, rates, and maximize the conversion of CO 2 , the latter of which is only now being recognized as a critical issue. In this respect, there is a need to explore the governing phenomena inherent in these architectures to enable optimization. Mathematical modeling is ideally suited to tackle and explore these multiphysics interactions and provide virtual design analysis. In this talk, we discuss modeling methodologies and physics inherent in these devices and present our recent modeling of GDEs for CO 2 reduction. We specifically examine the impacts of multiphase flow and related phenomena on overall cell performance. We then explore the performance and limitations of various cell designs guided by simulation results and examine potential methods for improving water management and tuning catalyst selectivity including the use of different anion-exchange and bipolar membranes. Finally, we discuss the disparities in local environments between aqueous and GDE devices and propose strategies to reduce the gap in knowledge between the two systems.

42 ENGINEERING↗
DOE OSTI2020

Virtual Analysis of Gas-Diffusion-Electrode CO 2 Electrolyzers

The electrochemical reduction of CO 2 (CO2R) to value-added products is an attractive technology for tackling the rising atmospheric CO 2 levels and storing intermittent renewable energy into chemical bonds. Fundamental understanding of CO 2 R has progressed significantly in recent years and is critical in the development of CO 2 R to liquid-fuel electrolyzers, where gas-diffusion electrodes (GDEs) have been shown to be key enabling architectures. Various designs have been proposed and studied in the literature to enhance overall selectivity, rates, and maximize the conversion of CO 2 , the latter of which is only now being recognized as a critical issue. In this respect, there is a need to explore the governing phenomena inherent in these architectures to enable optimization. Mathematical modeling is ideally suited to tackle and explore these multiphysics interactions and provide virtual design analysis. In this talk, we discuss modeling methodologies and physics inherent in these devices and present our recent modeling of GDEs for CO 2 reduction. Here, we specifically examine the impacts of multiphase flow and related phenomena on overall cell performance. We then explore the performance and limitations of various cell designs guided by simulation results and examine potential methods for improving water management and tuning catalyst selectivity including the use of different anion-exchange and bipolar membranes. Finally, we discuss the disparities in local environments between aqueous and GDE devices and propose strategies to reduce the gap in knowledge between the two systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗