Multiphase carbon mineralization for the reactive separation of CO[subscript 2] and directed synthesis of H[subscript 2]
Abstract not provided
Gadikota, Greeshma↗
SEARCH · Engineering Papers
Results for “multiphase”
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.
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Neural network representations of multiphase Equations of State
Abstract Equations of State model relations between thermodynamic variables and are ubiquitous in scientific modelling, appearing in modern day applications ranging from Astrophysics to Climate Science. The three desired properties of a general Equation of State model are adherence to the Laws of Thermodynamics, incorporation of phase transitions, and multiscale accuracy. Analytic models that adhere to all three are hard to develop and cumbersome to work with, often resulting in sacrificing one of these elements for the sake of efficiency. In this work, two deep-learning methods are proposed that provably satisfy the first and second conditions on a large-enough region of thermodynamic variable space. The first is based on learning the generating function (thermodynamic potential) while the second is based on structure-preserving, symplectic neural networks, respectively allowing modifications near or on phase transition regions. They can be used either “from scratch” to learn a full Equation of State, or in conjunction with a pre-existing consistent model, functioning as a modification that better adheres to experimental data. We formulate the theory and provide several computational examples to justify both approaches, highlighting their advantages and shortcomings.
Science & Technology - Other Topics↗
Predicting multiphase flow and tracer transport for an underground chemical explosive test
Detecting radionuclide gas seepage from clandestine underground nuclear tests is central to nonproliferation explosion monitoring research. Yet, early-time (<6 day) gas transport driven by the explosive pressure wave remains poorly constrained due to scarcity of field data. We simulate multi-phase gas transport in the vadose zone using pre-shot data from a recent chemical explosion in P-Tunnel at the Nevada National Security Site, USA. Despite using a simplified 2D-radial model, predictions of tracer arrival matched observations within one order-of-magnitude. Our results show how transient blast forcing rapidly mobilizes gases from the cavity into surrounding rock – critical for optimizing sensor placement and test planning. This unique integration of field data and modeling represents a significant improvement in our ability to predict gas migration from underground explosions. More broadly, it offers insights into the coupled dynamics of pressure waves and contaminant transport in the vadose zone, with implications for monitoring and hazard assessment.
54 ENVIRONMENTAL SCIENCES↗
Identifying chemically similar multiphase nanoprecipitates in compositionally complex non-equilibrium oxides via machine learning
Abstract Characterizing oxide nuclear fuels is difficult due to complex fission products, which result from time-evolving system chemistry and extreme operating environments. Here, we report a machine learning-enhanced approach that accelerates the characterization of spent nuclear fuels and improves the accuracy of identifying nanophase fission products and bubbles. We apply this approach to commercial, high-burnup, irradiated light-water reactor fuels, demonstrating relationships between fission product precipitates and gases. We also gain understanding of the fission versus decay pathways of precipitates across the radius of a fuel pellet. An algorithm is provided for quantifying the chemical segregation of the fission products with respect to the high-burnup structure, which enhances our ability to process large amounts of microscopy data, including approaching the atomistic-scale. This may provide a faster route for achieving physics-based fuel performance modeling.
36 MATERIALS SCIENCE↗
Separating a multicomponent and multiphase liquid mixture with a 3D-printed membrane device
3D printed membrane device, supported ionic liquid membrane, hydrogel-coated hydrophilic/oleophobic membrane, multi-component multi-phase separation.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
A DFT-based kinetic Monte Carlo simulation of multiphase oxide-metal thin film growth
Functional thin films of nanoscale metal pillars in oxide or nitride matrices known as vertically aligned nanocomposite (VAN) have gained much interest owing to their unique strain-coupled and highly anisotropic properties. So far, the deposition of these films has been explored mostly experimentally. In this work, a density functional theory (DFT)-based kinetic Monte Carlo simulation model using Bortz–Kalos–Lebowitz algorithm was developed to understand the growth of VAN films deposited by pulsed laser technique on mismatching substrates. The model has been parameterized and applied to understand the kinetics of growth thin films consisting of Au pillars in CeO2 matrix deposited on SrTiO3 substrates. The effects of pulsed laser deposition (PLD) conditions including the pulse frequency, deposition flux, and substrate temperature were explored. The simulations indicate that the Au pillar size and shape exhibit significant dependence on the PLD conditions. Namely, increasing the temperature increases the average pillar size and lowers the pillar density, and vice versa. In addition, the simulations revealed that increasing the deposition rate results in lowering the average pillar size and increasing the density. Particularly, the DFT results suggest that Au pillar size can be tuned during the initial growth of the first monolayer due to the significantly low activation barrier. Our analysis showed that the relationship between the average pillar size and pillar density is influenced by the kinetics. Furthermore, autocorrelation analysis showed that pillars self-organize in quasi-ordered patterns at certain windows of the deposition conditions, which is attributed to the complex nature of the chemical interactions in the system, the kinetics, and the deposition parameters.
Physics↗
Observational constraints on the multiphase nature of outflows using large spectroscopic surveys at z ∼ 0
ABSTRACT Mass outflow rates and loading factors are typically used to infer the quenching potential of galactic-scale outflows. However, these generally rely on observations of a single gas phase that can severely underestimate the total ejected gas mass. To address this, we use observations of high mass (≥1010 M⊙), normal star-forming galaxies at z ∼ 0 from the MaNGA, xCOLD GASS, xGASS, and ALFALFA surveys and a stacking of Na d, Hα, CO(1–0), and H i 21 cm tracers with the aim of placing constraints on an average, total mass outflow rate, and loading factor. We find detections of outflows in both neutral and ionized gas tracers, with no detections in stacks of molecular or atomic gas emission. Modelling of the outflow components reveals velocities of |vNa d| = 131 km s−1 and |vHα| = 439 km s−1 and outflow rates of $\dot{M}_{\rm {Na\,\small{D}}}$ = 7.55 M⊙ yr−1 and $\dot{M}_{\text{H}\alpha }$ = 0.10 M⊙ yr−1 for neutral and ionized gas, respectively. Assuming a molecular/atomic outflow velocity of 200 km s−1, we derive upper limits of $\dot{M}_{\text{CO}}\lt 19.43$ M⊙ yr−1 and $\dot{M}_{\rm {H\,\small {I}}}\lt $ 26.72 M⊙ yr−1 for the molecular and atomic gas, respectively. Combining the detections and upper limits, we find average total outflow rates of $\dot{M}_{\text{tot}}\lesssim$27 M⊙ yr−1 and a loading factor of ηtot ≲ 6.39, with molecular gas likely contributing ≲72 per cent of the total mass outflow rate, and neutral and ionized gas contributing ∼28 and <1 per cent, respectively. Our results suggest that, to first order, a degree of quenching via ejective feedback could occur in normal galaxies when considering all gas phases, even in the absence of an active galactic nucleus.
Roberts-Borsani, G. W.↗
Multiphase outflows in post-starburst E+A galaxies – I. General sample properties and the prevalence of obscured starbursts
ABSTRACT E+A galaxies are believed to be a short phase connecting major merger ultraluminous infrared galaxies (ULIRGs) with red and dead elliptical galaxies. Their optical spectrum suggests a massive starburst that was quenched abruptly, and their bulge-dominated morphologies with tidal tails suggest that they are merger remnants. Active galactic nucleus (AGN)-driven winds are believed to be one of the processes responsible for the sudden quenching of star formation and for the expulsion and/or destruction of the remaining molecular gas. Little is known about AGN-driven winds in this short-lived phase. In this paper, we present the first and unique sample of post-starburst galaxy candidates with AGNs that show indications of ionized outflows in their optical emission lines. Using Infrared Astronomical Satellite–far infrared (IRAS–FIR) observations, we study the star formation in these systems and find that many systems selected to have post-starburst signatures in their optical spectrum are in fact obscured starbursts. Using SDSS spectroscopy, we study the stationary and outflowing ionized gas. We also detect neutral gas outflows in 40 per cent of the sources with mass outflow rates 10–100 times more massive than in the ionized phase. The mean mass outflow rate and kinetic power of the ionized outflows in our sample ($\dot{M}\sim 1\, \mathrm{M_{\odot }\, yr^{-1}}$, $\dot{E}\sim 10^{41}\, \mathrm{erg\, s}^{-1}$) are larger than those derived for active galaxies of similar AGN luminosity and stellar mass. For the neutral outflow ($\dot{M}\sim 10\, \mathrm{M_{\odot }\, yr^{-1}}$, $\dot{E}\sim 10^{42}\, \mathrm{erg\, s}^{-1}$), their mean is smaller than that observed in (U)LIRGs with and without AGN.
79 ASTRONOMY AND ASTROPHYSICS↗
The generation of a multiphase medium in ‘Splash’ bridge systems: towards an understanding of star formation suppression in turbulent galaxy systems
ABSTRACT Cloud–cloud collisions in splash bridges produced in gas-rich disc galaxy collisions offer a brief but interesting environment to study the effects of shocks and turbulence on star formation rates in the diffuse intergalactic medium, far from the significant feedback effects of massive star formation and active galactic nucleus. Expanding on our earlier work, we describe simulated collisions between counter-rotating disc galaxies of relatively similar mass, focusing on the thermal and kinematic effects of relative inclination and disc offset at the closest approach. This includes essential heating and cooling signatures, which go some way towards explaining the luminous power in H$_2$ and [C ii] emission in the Taffy bridge, as well as providing a partial explanation of the turbulent nature of the recently observed compact CO-emitting clouds observed in Taffy by the Atacama Large Millimeter Array (ALMA). The models show counter-rotating disc collisions result in swirling, shearing kinematics for the gas in much of the post-collision bridge. Gas with little specific angular momentum due to collisions between counter-rotating streams accumulates near the centre of mass. The disturbances and mixing in the bridge drive continuing cloud collisions, differential shock heating, and cooling throughout. A wide range of relative gas phases and line-of-sight velocity distributions are found in the bridges, depending sensitively on initial disc orientations, and the resulting variety of cloud collision histories. Most cloud collisions can occur promptly or persist for quite a long duration. Cold and hot phases can largely overlap throughout the bridge or can be separated into different parts of the bridge.
79 ASTRONOMY AND ASTROPHYSICS↗
Wide-ranged multiphase equation of state for iron and model variations addressing uncertainties in high-pressure melting
Not Available
36 MATERIALS SCIENCE↗
RMCProfile7 : reverse Monte Carlo for multiphase systems
This work introduces a completely rewritten version of the programRMCProfile(version 7), big-box, reverse Monte Carlo modelling software for analysis of total scattering data. The major new feature ofRMCProfile7is the ability to refine multiple phases simultaneously, which is relevant for many current research areas such as energy materials, catalysis and engineering. Other new features include improved support for molecular potentials and rigid-body refinements, as well as multiple different data sets. An empirical resolution correction and calculation of the pair distribution function as a back-Fourier transform are now also available.RMCProfile7is freely available for download at https://rmcprofile.ornl.gov/.
Chemistry↗
Self-Evolving Digital Twin-Based Online Health Monitoring of Multiphase Boost Converters
Not provided.
Engineering↗
Multiphase Modeling in a Parallel Plate Fluidized Bed Receiver for Concentrating Solar Power
A novel high temperature particle solar receiver is developed by using a light trapping planar cavity configuration. As particles fall through the cavity, the concentrated solar radiation warms the boundaries of the receiver and in turn heats the particles. Particles flow through the system, forming a packed bed at the lower end, leaving the system from the bottom at a constant flow rate. Air is introduced to the system as the fluidizing medium to improve particle heat transfer and mixing. A laboratory scale cavity receiver is built and a near IR quartz lamp is used to provide flux to the vertical wall of the heat exchanger. The system is modeled using a continuum two-fluid method. The computational model matches the experimental system size and the particle size distribution is assumed monodisperse. A conduction model that accounts for the effects of solid concentration is implemented, and the heat flux boundary condition matches the experimental setup. Radiative heat transfer is estimated using a widely used correlation during the post-processing step to determine an overall heat transfer coefficient. The model is validated against testing data and achieves less than 30% discrepancy and a heat transfer coefficient greater than 1000 W/m2K.
CSP↗
Hierarchical and heterogeneous multiphase metallic nanomaterials and laminates
Not provided.
Materials Science↗
Additive manufacturing of high-strength multiphase nanostructures in the binary Ni–Nb system for the discovery of new types of superalloys
Abstract Ni-based superalloys have been studied extensively due to their impressive mechanical properties, including strength and creep resistance at high temperatures. Growing interest surrounding additive manufacturing (AM) methods has led to recent investigations of alloys that are traditionally difficult to process, including Ni-based superalloys. Recent work has shown that AM methods enable high-throughput materials discovery and optimization of difficult- or impractical-to-process alloys, including those with high or even majority refractory element compositions. This work focuses on AM-enabled investigations of composition-dependent mechanical and microstructural properties for Ni–Nb binary alloys. Specifically, we report on the mechanical behavior of compositionally-graded Ni x Nb 1− x and uniform composition Ni 59.5 Nb 40.5 specimens made with AM. The AM fabrication process resulted in extraordinarily high strength, attributed to the formation of a dual-phase microstructure consisting of δ-Ni 3 Nb and µ-Ni 6 Nb 7 intermetallic compounds with nanostructured and multimodal grain size and eutectic lamellar spacing. Graphic Abstract
Jones, M. R.↗
User’s Manual for StrmtbFlow, the Stream Tube Multiphase Flow Part of the FE/NETL CO 2 Prophet Model, Version 2
The United States (U.S.) Department of Energy (DOE) Office of Fossil Energy (FE) at the National Energy Technology Laboratory (NETL) has developed the FE/NETL CO 2 Prophet Model, which is an updated version of the CO 2 Prophet. This document is a user’s manual for StrmtbFlow, which is one part of the FE/NETL CO 2 Prophet Model. CO 2 Prophet was originally developed in the 1990s by Texaco Exploration and Production Technology Department for DOE. The FE/NETL CO 2 Prophet Model is an oil reservoir simulator that is suitable for simulating water floods and supercritical carbon dioxide (CO 2 ) enhanced oil recovery (EOR). The FE/NETL CO 2 Prophet Model uses a number of assumptions to simplify the equations describing the flow of oil, water (or brine), and CO 2 in the oil reservoir.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗