Search NASA⌕ Search

SEARCH · Search NASA

Results for “computational multiphase 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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Direct Effect of Solvent Viscosity on the Physical Mass Transfer for Wavy Film Flow in a Packed Column

ABSTRACT Post-combustion carbon capture via solvent absorption in a packed column can be a promising technology for mitigating greenhouse gas emissions. The mass transfer between gas and liquid solvent phases plays a critical role in determining the packing height of the packed column. Recent experiments [1] involving physical mass transfer for aqueous amine in a packed column have distinguished the direct and indirect impacts of viscosity (µ_L) on the mass transfer coefficient ?( k?_L). The direct impact of viscosity on the mass transfer coefficient has been found to be significantly higher for a packed column ?(k?_L~µ_L^(-0.38)) than a wetted wall column (WWC) ?(k?_L~µ_L^(-0.17)). To explain the deviation from the well-controlled uniform film flow in a WWC, we propose a mechanism involving the unavoidable wavy film flow and eddy-enhanced mass transfer in a packed column. A mathematical analysis based on fundamental flow and mass transfer equations is presented to quantify this deviation. The correlation for mass transfer coefficient derived from the mathematical analysis is found to match the corresponding one derived from the experiments for a packed column. Multiphase flow simulations using the Volume of Fluid method also are conducted to verify the direct impact of viscosity on the mass transfer coefficient for both uniform and wavy film flows. The mass transfer coefficient calculated from simulations shows steeper variation with viscosity for wavy film compared to the uniform film, further confirming our proposed theory. A similar relation ?(k?_L~µ^(-0.38)) for wavy film flow in a packed column is observed for aqueous solvent from both theory, experiment, and computer simulations.

Mass transfer, viscosity, eddy diffusion↗
DOE OSTI2013

Fabrication of gold nanostructures through pulsed laser interference patterning

In this Letter, we report on the experimental development and computational modeling of a simple, one-step method for the fabrication of diverse 2D and 3D periodic nanostructures derived from gold films on silicon substrates and over areas spanning 1 cm{sup 2}. These nanostructures can be patterned on films of thickness ranging from 50 nm to 500 nm with pulsed interfering laser beams. A finite volume-based inhomogeneous multiphase model of the process shows reasonable agreement with the experimentally obtained topographies and provides insights on the flow physics including normal and radial expansion that results in peeling of film from the substrate.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2017

ASSESSMENT OF MULTIPHASE CFD WITH ZERO CLOSURE MODEL FOR BOILING WATER REACTOR FUEL ASSEMBLIES

Extension of existing boiling closures to the high void fraction conditions of BWRs is one of challenges for M-CFD applications. This paper presents the assessment of an Eulerian M-CFD model with Zero closure model that has been specifically designed for two-phase flow and heat transfer applications in BWR fuel assemblies. The baseline Zero closure aims at including the simplest and most robust representation of the key physical mechanisms, rather than aiming at absolute accuracy of the predictions. The capabilities of M-CFD with Zero were evaluated against the international OECD/NRC BFBT benchmark data through the comparative analyses of local void fraction, sub-channel void fraction error and exit quality. INL high performance computing system has been employed to demonstrate the scalability of the M-CFD application to nuclear reactor fuel assemblies. The M-CFD simulation results show a good agreement with the experimental data for both quantitative and qualitative results, with the highest uncertainty being observed in the prediction of the local void fraction profile at low void fraction condition. This paper presents a recent view of the best practices for M-CFD of BWR fuel assemblies to provide a useful reference to identify and overcome common challenges in the applications of M-CFD tools. We provide recommendations for geometric modeling, mesh generation and solver configurations to optimize the methodology application.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Numerical comparison of bubbling in a waste glass melter

Radioactive tank waste is scheduled for vitrification at the Hanford Tank Waste Treatment and Immobilization Plant, also known as the Vit Plant, being constructed at the Hanford Site. Testing of the pilot-scale, joule-heated DuraMelter 1200 at the Vitreous State Laboratory has shown that bubbling increases the melt rate, and as a result, melter throughput. Computational fluid dynamics (CFD) models of this pilot-scale waste glass melter were developed to improve our understanding of the processes that occur within the melter to aid in process optimization and troubleshooting of the Vit Plant melters. Unfortunately, model validation is complicated by the difficulty of obtaining suitable experimental data for operational melters attributed to the large-scale, radioactivity and high temperatures at which these melters are operated. This study focuses on confirming the fidelity of the CFD models to accurately reproduce the bubbling behavior. Because of the paucity of experimental data at the resolution required for CFD validation, a code-to-code comparison was used to evaluate two common approaches for simulating flows of immiscible fluids on numerical grids and resolving multiphase interfaces. Here, the volume of fluid and level set methods are used to track the dynamically evolving interfaces between the molten glass and the air bubbles. To aid in the verification of the results of these codes, a comparison of the bubble behavior, growth, and frequency of bubble generation are presented and a grid convergence study is performed for the two approaches. In addition to comparing the numerical results to available experimental data and observations from pilot-scale testing, the results are evaluated in relation to laboratory experiments with bubbles injected into viscous fluids, empirical correlations obtained from the published literature, and the basic laws of fluid dynamics. Furthermore, the results of this work can assist in validating waste glass melter models and provide a better understanding of the flow patterns within the WTP melters.

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

Discrete models of fluids: spatial averaging, closure and model reduction

We consider semidiscrete ODE models of single-phase fluids and two-fluid mixtures. In the presence of multiple fine-scale heterogeneities, the size of these ODE systems can be very large. Spatial averaging is then a useful tool for reducing computational complexity of the problem. The averages satisfy exact balance equations of mass, momentum, and energy. These equations do not form a satisfactory continuum model because evaluation of stress and heat flux requires solving the underlying ODEs. To produce continuum equations that can be simulated without resolving microscale dynamics, we recently proposed a closure method based on the use of regularized deconvolution. Here we continue the investigation of deconvolution closure with the long term objective of developing consistent computational upscaling for multiphase particle methods. The structure of the fine-scale particle solvers is reminiscent of molecular dynamics. For this reason we use nonlinear averaging introduced for atomistic systems by Noll, Hardy, and Murdoch-Bedeaux. We also consider a simpler linear averaging originally developed in large eddy simulation of turbulence. We present several simple but representative examples of spatially averaged ODEs, where the closure error can be analyzed. Based on this analysis we suggest a general strategy for reducing the relative error of approximate closure. For problems with periodic highly oscillatory material parameters we propose a spectral boosting technique that augments the standard deconvolution and helps to correctly account for dispersion effects. We also conduct several numerical experiments, one of which is a complete mesoscale simulation of a stratified two-fluid flow in a channel. In this simulation, the operation count per coarse time step scales sublinearly with the number of particles.

Multiscale modeling, discrete models, fluid flow↗
NASA NTRS2019

Numerical Predictions of Dust-Induced Heat Flux Augmentation in Hypersonic Blunt-Body Flows Using a Discontinuous Galerkin Multiphase Flow Solver

Recent interest in human-scale missions to Mars has motivated the need for high-fidelity simulations of reentry flows. During a dust storm, there can be high levels of suspended dust in the Martian atmosphere, which cannot only enhance erosion of thermal protection systems but also transfer energy and momentum to the shock layer, thereby significantly augmenting the surface heat flux. Second-order finite-volume schemes are typically employed for hypersonic flow simulations, but such schemes suffer from a number of disadvantages. An attractive alternative is discontinuous Galerkin methods, which benefit from arbitrarily high spatial order of accuracy, geometric flexibility, and other properties. To enable accurate computations of high-speed particle-laden flows, an Euler-Lagrange methodology was developed in which the Eulerian field of the carrier gas is calculated using a discontinuous Galerkin scheme while the disperse phase is treated with Lagrangian particle tracking. We discuss challenges associated with coupling these two formulations and how to handle them. Momentum and energy transfer between the carrier gas and the particle phase is considered, and the importance of accounting for interparticle collisions is assessed. In addition, we describe the physical model of the particle phase and examine effects of its uncertainties on the numerical solution. We demonstrate the performance of the Euler-Lagrange method in representative testcases, with focus on the accurate prediction of particle trajectories and heating augmentation. Quantitative comparisons with experiments are provided.

Ching, Eric J.↗
DOE OSTI2016

A spectral cascade-transport turbulence model for wall-bounded flows

A spectral cascade-transport model has been developed and applied to turbulent channel flows (Re{sub τ} = 550, 950, and 2000 based on friction velocity, u{sub τ}; or Re{sub δ} = 8,500; 14,800 and 31,000, based on the mean velocity and channel half-width). This model is an extension of a spectral model previously developed for homogeneous single and two-phase decay of isotropic turbulence and uniform shear flows; and a spectral turbulence model for wall-bounded flows without resolving the boundary layer. A direct numerical simulation (DNS) of turbulent channel flow was used to help develop this model and to assess its performance in the 1D direction across the channel width. The resultant spectral model is capable of predicting the mean velocity, turbulent kinetic energy and energy spectrum distributions for single-phase wall-bounded flows all the way to the wall, where the model source terms have been developed to account for the wall influence. The model is in the process of implementation into the 3D multiphase CFD code NPHASE-CMFD and the latest results are within reasonable error of the 1D predictions. (authors)

42 ENGINEERING↗
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 OSTI2019

Dynamics of rapidly depressurized multiphase shock tubes

Rapid depressurization is a fluid phenomenon that occurs in many industrial and natural applications. Its behaviour is often complicated by the formation, propagation and interaction of waves. In this work, we perform computer simulations of the rapid depressurization of a gas–solid mixture in a shock tube. Our problem set-up mimics previously performed experiments, which have been historically used as a laboratory surrogate for volcanic eruptions. The simulations are carried out with a discontinuous Galerkin compressible fluid solver with four-way coupled Lagrangian particle tracking capabilities. The results give an unprecedented look into the complex multiphase physics at work in this problem. Different regimes have been characterized in a regime map that highlights the key observations. While the mean flow behaviour is in good agreement with experiments, the simulations show unexpected accelerations of the particle front as it expands. Additionally, a new lifting mechanism for gas bubble (void) growth inside the gas–solid mixture is detailed.

Mechanics↗
DOE OSTI2018

Beyond Relaxation and Newton–Raphson: Solving AC OPF for Multi-Phase Systems With Renewables

This paper focuses on the AC Optimal Power Flow (OPF) problem for multi-phase systems. Particular emphasis is given to systems with high integration of renewables, where adjustments of the real and reactive output powers from renewable sources of energy are necessary in order to enforce voltage regulation. The AC OPF problem is known to be nonconvex (and, in fact, NP-hard). Convex relaxation techniques have been recently explored to solve the OPF task with reduced computational burden; however, sufficient conditions for tightness of these relaxations are only available for restricted classes of system topologies and problem setups. Identifying feasible power-flow solutions remains hard in more general problem formulations, especially in unbalanced multi-phase systems with renewables. To identify feasible and optimal AC OPF solutions in challenging scenarios where existing methods may fail, this paper leverages the Feasible Point Pursuit - Successive Convex Approximation algorithm - a powerful approach for general nonconvex quadratically constrained quadratic programs. The merits of the approach are illustrated using single- and multiphase distribution networks with renewables, as well as several transmission systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Predicting CO 2 Plume Migration in Heterogeneous Formations Using Conditional Deep Convolutional Generative Adversarial Network

Numerical simulation of flow and transport in heterogeneous formations has long been studied, especially for uncertainty quantification and risk assessment. The high computational cost associated with running large-scale numerical simulations in a Monte Carlo sense has motivated the development of surrogate models, which aim to capture the important input-output relations of physics-based models but require only a fraction of the cost of full model runs. In this work, we formulate a conditional deep convolutional generative adversarial network (cDC-GAN) surrogate model to learn the dynamic functional mappings in multiphase models. The cDC-GAN belongs to a class of semisupervised learning methods that can be used to learn the data generation processes. Like the original GAN, a main strength of the cDC-GAN is that it includes a self-training scheme for improving the quality of generative modeling in a game theoretic framework, without requiring extensive statistical knowledge and assumptions on input data distributions. In particular, our cDC-GAN model is designed to learn cross-domain mappings between high-dimensional input (e.g., permeability) and output (e.g., phase saturations) pairs, with the ability to incorporate conditioning information (e.g., prediction time). As a use case, we demonstrate the performance of cDC-GAN for predicting the migration of carbon dioxide (CO 2 ) plume in heterogeneous carbon storage reservoirs, which has both numerical and practical significance because of the safe storage requirements now mandated in many countries. Results show that cDC-GAN achieves high accuracy in predicting the spatial and temporal evolution patterns of the injected CO 2 plume, as compared to the original results obtained using a compositional reservoir simulator. The performance of cDC-GAN models, trained using the same number of training samples, stays relatively robust when the level of spatial heterogeneity is increased. Our cDC-GAN is pattern based and is not limited by the underlying physics. Thus, it provides a general framework for developing surrogate models, and for conducting uncertainty analyses for a wide range of physics-based models used in both groundwater and subsurface energy exploration applications.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1991

Theoretical and computational dynamics of a compressible flow

An introduction to the theoretical and computational fluid dynamics of a compressible fluid is presented. The general topics addressed include: thermodynamics and physical properties of compressible fluids; 1D flow of an inviscid compressible fluid; shock waves; fundamental equations of the dynamics of a compressible inviscid non-heat-conducting and radiating fluid, method of small perturbations, linearized theory; 2D subsonic steady potential flow; hodograph and rheograph methods, exact solutions of 2D insentropic steady flow equations, 2D steady transonic and hypersonic flows, method of characteristics, linearized theory of 3D potential flow, nonlinear theory of 3D compressibe flow, anisentropic (rotational) flow of inviscid compressible fluid, electromagnetogasdynamics, multiphase flows, flows of a compressible fluid with transport phenomena.

Pai, Shih-I↗
DOE OSTI2025

Advanced Computational Modeling of High-Level Waste Vitrification at the Hanford Site

The U.S. Department of Energy (DOE) has selected vitrification for stabilizing legacy tank waste at the Hanford site, where radioactive waste from plutonium production was historically stored in underground tanks. This waste will be separated into low-activity waste (LAW) and high-level waste (HLW) fractions and processed at the Waste Treatment and Immobilization Plant (WTP). At WTP, glass melters are used for the vitrification of radioactive tank waste, transforming it into a stable borosilicate glass form for safe long-term storage. The melter vessel is constructed from highly durable and heat-resistant materials, where the vitrification process occurs. The main regions that are modeled are the melt pool, plenum, cold cap, riser/discharge chamber, and surrounding structure with insulation layers. Forced convection induced by air bubblers at the base of the melter ensure uniform temperature distribution and provide heat to the cold cap layer. The cold cap is a region of reacting batch feed that floats on top of the molten glass and is where the batch-to-glass reactions occur. Joule heating provided by electrodes mounted along the vertical walls of the melter and immersed directly in the glass, generates the necessary heat for the net endothermic conversion processes that occur in the cold cap. The high temperatures, radioactivity, and opaque nature of the glass prevent direct observation inside the melters. Therefore, computational models are essential for providing insight into factors that affect melter throughput. Thermocouples in the plenum provide operators with plenum temperature measurements. Operational adjustments include bubbling rate, voltage supplied to the electrodes, feed adjustments, and glass removal rate. Different computational fluid dynamics (CFD) models have been developed, each serving a specific purpose. There are CFD models of different scale melters, as well as models that capture the two-phase flow interfaces of rising bubbles in the molten glass or models with a simplified molten glass region so that the surrounding structure and plenum can be feasibly incorporated. Pilot-scale melter models have been developed to serve as validation of the methods employed in the simulation of the full-scale WTP melters. Models incorporating resolved bubbling are used to develop momentum source terms to implement into a single phase, multi-region, steady-state flow model that is being validated by measured process parameters such as glass production rate, voltage, input power, plenum temperatures, etc. The resolved bubbling model uses the multiphase volume of fluid approach to model the system with a high-resolution interface capturing scheme to maintain sharp interfaces between the molten glass and the air phase. The suite of CFD models is continually being improved to incorporate more realistic physics and achieve faster turnaround time. For example, an incremental controller is implemented to automatically adjust electrode voltage within the simulation to a molten glass set point temperature of 1150°C. Newer models feature improved meshes to ensure conformal meshes between regions and eliminate unnecessary mesh refinement in areas that are not of interest (such as boundary layers in offgas ports). Instead of explicitly modeling the structural, refractory, and insulation layers of the melter, a thermal resistance approach is used with published correlations used for boundary conditions. The development of robust and efficient CFD models will be instrumental in enabling the WTP to successfully fulfill its mission of safely stabilizing legacy nuclear waste.

12 - MGMT OF RADIOACTIVE AND NON-RADIOACTIVE WASTE↗
DOE OSTI2023

NRAP-Open-IAM Multisegmented Wellbore Reduced-Order Model: Improvement and Quality Assurance

The multisegmented wellbore model (MSW) semi-analytically estimates the amount of CO 2 and brine leakage from a leaking legacy well by segmenting it into intervals to simulate site-specific stratigraphic and hydrogeologic properties. The model is a component of the National Risk Assessment Partnership Open-Source Integrated Assessment Model (NRAP-Open-IAM), which was developed to perform risk assessment for geologic CO 2 storage. The new wellbore leakage model, which uses deep learning networks for a caprock segment, was developed to enhance the analytical MSW. The model was trained and validated using a synthetic data set of Subsurface Transport Over Multiple Phases (STOMP) multiphase flow simulations from various geological, well attribute, and operational conditions to ensure its quality. The results demonstrate that the model is more accurate than the existing model in predicting the transport of two-phase fluids (brine and injected CO 2 ) through the well. This report provides a detailed explanation of the model development and quality assurance.

58 GEOSCIENCES↗
DOE OSTI2019

Systems and methods for convex relaxations and linear approximations for optimal power flow in multiphase radial networks

Centralized node controllers in accordance with embodiments of the invention enable linear approximation of optimal power flow. One embodiment includes a centralized node controller including: a network interface, a processor, and a memory containing: a centralized power control application a network topology, where the network is multiphase unbalanced and comprises a plurality of connected nodes; wherein the processor is configured by the centralized controller application to: request node operating parameters from the plurality of connected nodes; calculate network operating parameters using a linear approximation of optimal power flow and the node operating parameters from the plurality of connected nodes; send network operating parameters to the plurality of connected nodes.

97 MATHEMATICS AND COMPUTING↗
NASA NTRSDate not supplied

CFD Model Development of a Cryogenic Storage Tank Self-Pressurization in Normal Gravity and Validation against SHIIVER Experiment

Two-phase flow and heat transfer simulations with interfacial phase change of the Structural Heat Intercept, Insulation, and Vibration Evaluation Rig (SHIIVER) self-pressurization experiment were conducted using storage tank CFD model in the framework of the ANSYS Fluent CFD code. The simulations were performed for the 70% fill level case with MLI on domes and no vapor cooling. All the phase change calculations in these simulations were generated by in-house Schrage-based evaporation-condensation model. The calculations were performed using both the Volume of Fluid (VOF) and Sharp Interface multiphase 2D axisymmetric models. A number of parametric and sensitivity studies were performed to check the various aspects of the CFD model. These studies helped to understand the effects of varying several parameters on the tank pressure and temperature during self-pressurization. Turbulence modeling; turbulence damping at the interface; and using constant vs. temperature dependent fluid properties were shown to have the most profound influence on predicted tank pressures and temperatures. Current study indicates that including phase change at the interface into the computational model is crucial for accurate prediction of the tank self-pressurization process. The effect of accommodation coefficient was also studied. Tank pressure values predicted by the VOF, and Sharp Interface models are within 4% of the experimental ones.

Computational Fluid Dynamics↗
DOE OSTI2016

Understanding Hydraulic Fracturing: A Multi-Scale Problem

Despite the impact that hydraulic fracturing has had on the energy sector, the physical mechanisms that control its efficiency and environmental impacts remain poorly understood in part because the length scales involved range from nano-meters to kilo-meters. We characterize flow and transport in shale formations across and between these scales using integrated computational, theoretical, and experimental efforts. At the field scale, we use discrete fracture network modeling to simulate production at a well site whose fracture network is based on a site characterization of a shale formation. At the core scale, we use triaxial fracture experiments and a finite-element discrete-element fracture propagation model with a coupled fluid solver to study dynamic crack propagation in low permeability shale. We use lattice Boltzmann pore-scale simulations and microfluidic experiments in both synthetic and real micromodels to study pore-scale flow phenomenon such as multiphase flow and mixing. A mechanistic description and integration of these multiple scales is required for accurate predictions of production and the eventual optimization of hydrocarbon extraction from unconventional reservoirs.

03 NATURAL GAS↗