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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Time‐And‐Space Averaging Applied to Intermittent Multiphase Flow Experiments

Abstract Various researchers have studied fluctuations in pore‐scale phase occupancy during multiphase flow in porous media using synchrotron‐based X‐ray microcomputed tomography (micro‐CT). However, the impact of these fluctuations on the concept of a representative volume is not yet fully understood. In this study, we performed spatial and temporal averaging of multiphase flow experiments visualized with synchrotron‐based micro‐CT, focusing on oil saturation as the key parameter to determine a representative time‐and‐space average. Our findings revealed that a saturation value representative of both time and space was achieved during fractional flow experiments in drainage mode with fractional flows of 0.8, 0.5, and 0.3. Furthermore, we computed a range of relative permeabilities on the basis of whether momentaneous saturation or time‐and‐space averaged saturation was utilized for direct simulation. Our results highlighted the importance of time‐and‐space averaging in determining a representative relative permeability and indicated that the temporal and spatial scales covered in a typical micro‐CT flow experiment were sufficient to obtain a representative saturation value for sandstone rock under intermittent flow conditions.

Environmental Sciences & Ecology↗
DOE OSTI2025

A Multiscale Approach to Simulate Non‐Isothermal Multiphase Flow in Deformable Porous Materials

Coupled thermal, hydraulic, and mechanical processes in porous materials play important roles in several energy and environmental technologies. The Darcy-Brinkman-Biot (DBB) framework has proven effective in modeling multiphase fluid flow in deformable porous solids across both pore and Darcy scales, including in systems where fractures coexist with a porous matrix. In this study, we extend the DBB framework, originally designed for isothermal conditions, to address non-isothermal problems by incorporating an energy conservation equation. The resulting solver, hybridBiotThermalInterFoam, enables simulations of coupled multiphase fluid flow, heat transfer, and solid deformation in hybrid-scale systems containing both solid-free regions and ductile porous domains. The new solver is validated through comparisons with analytical solutions and, also, against established heat transfer solvers chtMultiRegionFoam and compressibleInterFoam. Further, a series of 2D and 3D case studies, including two-phase heat transfer in solid-free, static, or deformable porous media, highlights the solver's capacity to simulate complex flow dynamics and heat transport in systems involving high mobility ratios, viscous fingering, and fracture propagation. Our results establish the feasibility of incorporating thermal effects in simulations of a wide variety of energy geotechnics and environmental applications, including enhanced hydrocarbon recovery, soil remediation, and enhanced geothermal energy systems.

04 OIL SHALES AND TAR SANDS↗
DOE OSTI2025

Investigating the effect of heterogeneities across the electrode|multiphase polymer electrolyte interfaces in high-potential lithium batteries

Polymer electrolytes hold great promise for safe and high-energy batteries comprising solid or semi-solid electrolytes. Multiphase polymer electrolytes, consisting of mobile and rigid phases, exhibit fast ion conduction and desired mechanical properties. However, fundamental challenges exist in understanding and regulating interactions at the electrode|electrolyte interface, especially when using high-potential layered oxide active materials at the positive electrode. Here we demonstrate that depletion of the mobile conductive phase at the interface contributes to battery performance degradation. Molecular ionic composite electrolytes, composed of a rigid-rod ionic polymer with nanometric mobile cations and anions, serve as a multiphase platform to investigate the evolution of ion conductive domains at the interface. Chemical and structural characterizations enable the visualization of concentration heterogeneity and spatially resolve the interfacial chemical states over a statistically significant field of view for buried interfaces. We report that concentration and chemical heterogeneities prevail at electrode|electrolyte interfaces, leading to phase separation in polymer electrolytes. In conclusion, understanding the hidden roles of interfacial chemomechanics in polymer electrolytes enables us to design an interphase tailoring strategy based on electrolyte additives to mitigate the interfacial heterogeneity and improve battery performance.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Predictive machine learning approaches for the microstructural behavior of multiphase zirconium alloys

Abstract Zirconium alloys are widely used in harsh environments characterized by high temperatures, corrosivity, and radiation exposure. These alloys, which have a hexagonal closed packed (h.c.p.) structure thermo-mechanically degrade, when exposed to severe operating environments due to hydride formation. These hydrides have a different crystalline structure, than the matrix, which results in a multiphase alloy. To accurately model these materials at the relevant physical scale, it is necessary to fully characterize them based on a microstructural fingerprint, which is defined here as a combination of features that include hydride geometry, parent and hydride texture and crystalline structure of these multiphase alloys. Hence, this investigation will develop a reduced order modeling approach, where this microstructural fingerprint is used to predict critical fracture stress levels that are physically consistent with microstructural deformation and fracture modes. Machine Learning (ML) methodologies based on Gaussian Process Regression, random forests, and multilayer perceptrons (MLP) were used to predict material fracture critical stress states. MLPs, or neural networks, had the highest accuracy on held-out test sets across three predetermined strain levels of interest. Hydride orientation, grain orientation or texture, and hydride volume fraction had the greatest effect on critical fracture stress levels and had partial dependencies that were highly significant, and in comparison hydride length and hydride spacing have less effects on fracture stresses. Furthermore, these models were also used accurately predicted material response to nominal applied strains as a function of the microstructural fingerprint.

36 MATERIALS SCIENCE↗
DOE OSTI2016

An approach towards tailoring interfacial structures and properties of multiphase renewable thermoplastics from lignin–nitrile rubber

Lignin-derived thermoplastics and elastomers with both versatile performance and commercialization potential have been an elusive pursuit for the past several decades. Lignin content has been limited to about 30 wt %, often requiring chemical modification, solvent fractionation of lignin, or prohibitively expensive additives. Each of these factors is a deterrent to industrial adoption of lignin-based polymers, limiting the potential of this renewable resource. Herein we describe high-performance multiphase thermoplastics made with a blend of 41 wt % unmodified industrial lignin and low-cost additives in a matrix of general-purpose acrylonitrile-butadiene rubber (NBR). Hardwood soda lignin (HSL) and softwood kraft lignin (SKL) were blended under high shear conditions with NBR, carbon black (CB), polyethylene oxide (PEO), boric acid (BA), and dicumyl peroxide (DCP). This combination with SKL lignin in the proper proportions resulted in a thermoplastic with a tensile strength and failure strain of 25.2 MPa and 9 %, respectively; it exhibited an unexpected tensile yield, similar to that of ABS, a commodity thermoplastic. The analogous HSL lignin compositions are tough materials with tensile strengths of 7.3 16.7 MPa and failure strain of 80 140 %. The contrasting ductility and yield stress behavior were analyzed based on the compositions morphology and interfacial structure arising from the nature of each lignin studied. Lastly, the roles of CB as a reinforcement in the rubbery phase, DCP and BA as cross-linkers to create multiphase networks, and PEO to promote the adhesion and compatibility of lignin in commercial-grade NBR are also discussed in detail.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Active motion of multiphase oil droplets: emergent dynamics of squirmers with evolving internal structure

Synthetic soft matter systems, when driven beyond equilibrium by active processes, offer the potential to achieve dynamical states and functions of a complexity found in living matter. Emulsions offer the basis of a simple yet versatile system for identification of the physicochemical principles underlying active soft matter, but how multiple internal phases within emulsion droplets (e.g., Janus morphologies) organize to impact emergent dynamics is not understood. Here, we create multiphase oil droplets with ultralow interfacial tensions but distinct viscosities, and drive them into motion in aqueous micellar solutions. Preferential solubilization of select components of the oil both drives the droplet motion and yields a progression of internal phase morphological states with distinct symmetries. In this work, we find the active droplets to exhibit five dynamical states during morphogenesis. By quantifying microscopic flow fields, we show that it is possible to map the diverse droplet behaviors to squirmer models of spherical microswimmers in Stokes flow, thus showing that multiphase droplets offer the basis of a versatile platform with which to study and engineer the hydrodynamics of microswimmers.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Determining conductivity and mobility values of individual components in multiphase composite Cu{sub 1.97}Ag{sub 0.03}Se

The intense interest in phase segregation in thermoelectrics as a means to reduce the lattice thermal conductivity and to modify the electronic properties from nanoscale size effects has not been met with a method for separately measuring the properties of each phase assuming a classical mixture. Here, we apply effective medium theory for measurements of the in-line and Hall resistivity of a multiphase composite, in this case Cu{sub 1.97}Ag{sub 0.03}Se. The behavior of these properties with magnetic field as analyzed by effective medium theory allows us to separate the conductivity and charge carrier mobility of each phase. This powerful technique can be used to determine the matrix properties in the presence of an unwanted impurity phase, to control each phase in an engineered composite, and to determine the maximum carrier concentration change by a given dopant, making it the first step toward a full optimization of a multiphase thermoelectric material and distinguishing nanoscale effects from those of a classical mixture.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

Origin of resistivity anomaly in p-type leads chalcogenide multiphase compounds

The electrical resistivity curves for binary phase compounds of p-type lead chalcogenide (PbTe){sub (0.9−x)}(PbSe){sub 0.1}(PbS){sub x,} (x = 0.15, 0.2, 0.25), which contain PbS-rich secondary phases, show different behaviour on heating and cooling between 500-700 K. This is contrast to single phase compounds which exhibit similar behaviour on heating and cooling. We correlate these anomalies in the electrical resistivities of multiphase compounds to the variation in phase composition at high temperatures. The inhomogeneous distribution of dopants between the matrix and secondary phase is found to be crucial in the electronic transport properties of the multiphase compounds. These results can lead to further advances in designing composite Pb-chalcogenides with high thermoelectric performance.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A physics-constrained neural network for multiphase flows

The present study develops a physics-constrained neural network (PCNN) to predict sequential patterns and motions of multiphase flows (MPFs), which includes strong interactions among various fluid phases. To predict the order parameters, which locate individual phases in the future time, a neural network (NN) is applied to quickly infer the dynamics of the phases by encoding observations. The multiphase consistent and conservative boundedness mapping algorithm (MCBOM) is next implemented to correct the predicted order parameters. This enforces the predicted order parameters to strictly satisfy the mass conservation, the summation of the volume fractions of the phases to be unity, the consistency of reduction, and the boundedness of the order parameters. Then, the density of the fluid mixture is updated from the corrected order parameters. Finally, the velocity in the future time is predicted by another NN with the same network structure, but the conservation of momentum is included in the loss function to shrink the parameter space. The proposed PCNN for MPFs sequentially performs (NN)-(MCBOM)-(NN), which avoids nonphysical behaviors of the order parameters, accelerates the convergence, and requires fewer data to make predictions. Numerical experiments demonstrate that the proposed PCNN is capable of predicting MPFs effectively.

Mechanics↗
DOE OSTI2018

Integrating geophysical monitoring data into multiphase fluid flow reservoir simulation

Simulation of multiphase flow systems are of critical importance in managing hydrological systems. Flow simulations are affected by a number of factors including structure and flow properties including porosity and permeability as well as the anisotropy and heterogeneity of these properties. In many cases traditional hydrological and reservoir data are highly affected by these parameters, but are not directly sensitive to them. As such modellers often adjust these parameters in an ad hoc manner until solutions numerically converge. Simulation models are generally based on structural data from reflection seismics whose physical flow properties are then populated using geostatistical extrapolation techniques utilizing a sparse number of borehole logs and core analysis. In multiphase systems including enhanced oil recovery and carbon capture and sequestration uncertainties regarding phase-dependent physical properties confounds this challenge further. Geophysical methods provide a means by which to gain an improved understanding of phase distributions in the subsurface. In this paper we will look at applications from active carbon capture and sequestration and enhanced oil recovery applications, as well as synthetic examples. Geophysical data including electromagnetic and gravity are inverted using structural constraints from the reservoir model. Inversions are then mapped into flow properties using calibrated relations such as Archie’s Equation. The coupled models can then be used to both verify and improve on the reservoir flow model which improves it’s predictive power and utility as a management tool.

02 PETROLEUM↗
DOE OSTI2021

Velocity structure functions in multiphase turbulence: interpreting kinematics of Hα filaments in cool-core clusters

ABSTRACT The central regions of cool-core galaxy clusters harbour multiphase gas, with gas temperatures ranging from $10$ to $10^7\, \mathrm{K}$. Feedback from active galactic nuclei jets prevents the gas from undergoing a catastrophic cooling flow. However, the exact mechanism of this feedback energy input is unknown, mainly due to the lack of velocity measurements of the hot-phase gas. However, recent observations have measured the velocity structure functions (VSFs) of the cooler molecular (${\sim} 10\, \mathrm{K}$) and Hα filaments (${\sim} 10^4\, \mathrm{K}$) and used them to indirectly estimate the motions of the hot phase. In the first part of this study, we conduct high-resolution (3843–15363 resolution elements) simulations of homogeneous isotropic subsonic turbulence, without radiative cooling. We analyse the second-order velocity structure functions (VSF2) in these simulations and study the effects of varying spatial resolution, the introduction of magnetic fields, and the effect of projection along the line of sight (LOS) on it. In the second part of the study, we analyse high-resolution (7683 resolution elements) idealized simulations of multiphase turbulence in the intracluster medium from the companion study Mohapatra et al. We compare the VSF2 for both the hot ($T\sim 10^7\, \mathrm{K}$) and cold ($T\sim 10^4\, \mathrm{K}$) phases and find that their amplitude depends on the density contrast between the phases. They have similar scaling with separation, but introducing magnetic fields steepens the VSF2 of only the cold phase. We also find that projection along the LOS steepens the VSF2 for the hot phase and mostly flattens it for the cold phase.

Mohapatra, Rajsekhar (ORCID:0000000216007552)↗
DOE OSTI2019

Modeling Multiphase Effects in CO 2 Compressors at Subcritical Inlet Conditions

An advanced numerical framework to model CO 2 compressors over a wide range of subcritical conditions is presented in this paper. Thermodynamic and transport properties are obtained through a table look-up procedure with specialized features for subcritical conditions. Phase change is triggered by the difference between the local values of pressure and saturation pressure, and both vaporization and condensation can be modeled. Rigorous validation of the framework is presented for condensation in high pressure CO 2 using test data in a De Laval nozzle. The comparisons between computations and test data include: condensation onset locations, Wilson line, and nozzle pressure profiles as a function of inlet pressures. The framework is applied to the Sandia compressor that has been modeled over broad range of conditions spanning the saturation dome including: near critical inlet conditions (305.4 K, and 7.843 MPa), pure liquid inlet conditions (at 295 K), pure vapor inlet conditions (at 302 K), and two-phase inlet conditions (at 290 K). Multiphase effects ranging from cavitation at the liquid line to condensation at the vapor line have been simulated. Here, the role of real fluid effects in enhancing multiphase effects at elevated temperatures closer to the critical point has been identified. The performance of the compressor has been compared with test data; the computational fluid dynamics (CFD) results also show that the head-flow coefficient curve collapses with relatively minor scatter, similar to the test data, when the flow coefficient is defined on the impeller exit meridional velocity.

14 SOLAR ENERGY↗
DOE OSTI2022

Effects of Carbonic Acid-Rock Interactions on CO2/Brine Multiphase Flow Properties in the Upper Minnelusa Sandstones

Summary Carbon dioxide (CO2) injection into a deep saline aquifer can dissolve into formation brine and generate carbonic acid. The resulting acid can drive fluid-rock geochemical reactions. The impact of these fluid-rock geochemical reactions on porosity, permeability, and multiphase flow responses is relevant to the determination of CO2 storage capacity of deep saline aquifers. In this research, carbonic acid flooding experiments were performed on core samples consisting of poorly sorted, quartz-rich sand with laminated bedding from a possible CO2 storage target in northwest Wyoming. Complementary pre- and post-injection porosity and permeability, thin-section, Brunauer-Emmett-Teller (BET) surface area, mercury intrusion capillary pressure (MICP), and time-domain nuclear magnetic resonance (TD-NMR) measurements were conducted. Overall, both core porosity and permeability increased after a 7-day carbonic acid injection, from 6.2 to 8.4% and 1.6 to 3.7 md, respectively. We attributed these changes to carbonate mineral dissolution, which was evidenced by the effluent brine geochemistry, pore-throat size distribution (PTSD), and BET surface area. To be more specific, within the more-permeable section of core samples containing larger pore size, the permeability increment is apparent due to dolomite mineral grains and cements dissolution. However, for the lower-permeability section corresponding to the smaller pore size, mineral precipitation possibly lessened dissolution effects, leading to insignificant petrophysical properties changes. Consequently, the observed heterogeneous carbonic acid-rock interactions resulted in alterations of CO2/brine relative permeability (i.e., the initial CO2 saturation decreased and the CO2 flow capacity was enhanced). This research provides a fundamental understanding regarding effects of fluid-rock reactions on changes in static and multiphase flow properties of eolian sandstones, which lays the foundation for more accurate prediction/simulation of CO2 injection into deep saline aquifers.

Engineering↗
DOE OSTI2016

Nonequilibrium Physics and Phase-Field Modeling of Multiphase Flow in Porous Media

The overarching goal of this project was to develop a new continuum theory of multiphase flow in porous media. The theory follows a phase-field modeling approach, and therefore has a sound thermodynamical basis. It is a phenomenological theory in the sense that its formulation is driven by macroscopic phenomena, such as viscous instabilities during multifluid displacement. The research agenda was organized around a set of hypothesis on hitherto unexplained behavior of multiphase flow. All these hypothesis are nontrivial, and testable. Indeed, a central aspect of the project was testing each hypothesis by means of carefully-designed laboratory experiments, therefore probing the validity of the proposed theory. The proposed research places an emphasis on the fundamentals of flow physics, but is motivated by important energy-driven applications in earth sciences, as well as microfluidic technology.

42 ENGINEERING↗
DOE OSTI2017

Development of Multi-physics (Multiphase CFD + MCNP) simulation for generic solution vessel power calculation

The current study aims to predict the steady state power of a generic solution vessel and to develop a corresponding heat transfer coefficient correlation for a Moly99 production facility by conducting a fully coupled multi-physics simulation. A prediction of steady state power for the current application is inherently interconnected between thermal hydraulic characteristics (i.e. Multiphase computational fluid dynamics solved by ANSYS-Fluent 17.2) and the corresponding neutronic behavior (i.e. particle transport solved by MCNP6.2) in the solution vessel. Thus, the development of a coupling methodology is vital to understand the system behavior at a variety of system design and postulated operating scenarios. In this study, we report on the k-effective (keff) calculation for the baseline solution vessel configuration with a selected solution concentration using MCNP K-code modeling. The associated correlation of thermal properties (e.g. density, viscosity, thermal conductivity, specific heat) at the selected solution concentration are developed based on existing experimental measurements in the open literature. The numerical coupling methodology between multiphase CFD and MCNP is successfully demonstrated, and the detailed coupling procedure is documented. In addition, improved coupling methods capturing realistic physics in the solution vessel thermal-neutronic dynamics are proposed and tested further (i.e. dynamic height adjustment, mull-cell approach). As a key outcome of the current study, a multi-physics coupling methodology between MCFD and MCNP is demonstrated and tested for four different operating conditions. Those different operating conditions are determined based on the neutron source strength at a fixed geometry condition. The steady state powers for the generic solution vessel at various operating conditions are reported, and a generalized correlation of the heat transfer coefficient for the current application is discussed. The assessment of multi-physics methodology and preliminary results from various coupled calculations (power prediction and heat transfer coefficient) can be further utilized for the system code validation and generic solution vessel design improvement.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

Final Project Report CFA-14-6357: A New Paradigm for Understanding Multiphase Ceramic Waste Form Performance

This project fabricated model multiphase ceramic waste forms with processing-controlled microstructures followed by advanced characterization with synchrotron and electron microscopy-based 3D tomography to provide elemental and chemical state-specific information resulting in compositional phase maps of ceramic composites. Details of 3D microstructural features were incorporated into computer-based simulations using durability data for individual constituent phases as inputs in order to predict the performance of multiphase waste forms with varying microstructure and phase connectivity.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Using density functional theory to construct multiphase equations of state: tin as an example

We present a general methodology for using density functional theory (DFT) calculations as a basis for constructing multiphase equations of state (EOS). Focusing on tin as an example, we discuss the full process of generating a tabular EOS, starting from first-principles calculations and arriving at a full EOS in agreement with existing experimental data. We begin by describing DFT calculations for the five solid phases and liquid phase of tin, including cold curve, phonon, and DFT-based molecular dynamics calculations. We then discuss methods for incorporating DFT results into materials models used in OpenSesame, the program used to create a full tabular multiphase EOS. Next, we outline a general strategy for adjusting model parameters in OpenSesame to fit to a variety of experimental data, including isobaric data, isothermal data, shock data, solid-solid phase boundary measurements, and measurements of the melt curve. We end with a discussion of the advantages of using DFT data as a foundation for EOS generation and discuss potential strategies for automated EOS generation based on the fitting process highlighted in this work.

74 ATOMIC AND MOLECULAR PHYSICS↗