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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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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

PFLOTRAN: Reactive Flow & Transport Code for Use on Laptops to Leadership-Class Supercomputers. In: Groundwater Reactive Transport Models

PFLOTRAN, a next-generation reactive flow and transport code for modeling subsurface processes, has been designed from the ground up to run efficiently on machines ranging from leadership-class supercomputers to laptops. Based on an object-oriented design, the code is easily extensible to incorporate additional processes. It can interface seamlessly with Fortran 9X, C and C++ codes. Domain decomposition parallelism is employed, with the PETSc parallel framework used to manage parallel solvers, data structures and communication. Features of the code include a modular input file, implementation of high-performance I/O using parallel HDF5, ability to perform multiple realization simulations with multiple processors per realization in a seamless manner, and multiple modes for multiphase flow and multicomponent geochemical transport. Chemical reactions currently implemented in the code include homogeneous aqueous complexing reactions and heterogeneous mineral precipitation/dissolution, ion exchange, surface complexation and a multirate kinetic sorption model. PFLOTRAN has demonstrated petascale performance using 217 processor cores on problems composed of over 2 billion degrees of freedom. The code is currently being applied to simulate uranium transport at the Hanford 300 Area and CO2 sequestration in deep geologic formations.

carbon sequestration↗
DOE OSTI2016

A separate phase drag model and a surrogate approximation for simulation of the steam assisted gravity drainage (SAGD) process

General ensemble phase averaged equations for multiphase flows have been specialized for the simulation of the steam assisted gravity drainage (SAGD) process. In the average momentum equation, fluid-solid and fluid-fluid viscous interactions are represented by separate force terms. This equation has a form similar to that of Darcy’s law for multiphase flow but augmented by the fluid-fluid viscous forces. Models for these fluid-fluid interactions are suggested and implemented into the numerical code CartaBlanca. Numerical results indicate that the model captures the main features of the multiphase flow in the SAGD process, but the detailed features, such as plumes are missed. We find that viscous coupling among the fluid phases is important. Advection time scales for the different fluids differ by several orders of magnitude because of vast viscosity differences. Numerically resolving all of these time scales is time consuming. To address this problem, we introduce a steam surrogate approximation to increase the steam advection time scale, while keeping the mass and energy fluxes well approximated. This approximation leads to about a 40-fold speed-up in execution speed of the numerical calculations at the cost of a few percent error in the relevant quantities.

02 PETROLEUM↗
DOE OSTI2025

Multiphase computational fluid dynamics modeling of reacting flows in absorption columns for carbon capture

First-principles derived computational fluid dynamics (CFD) simulations have been proposed as a fundamental tool for investigating solvent-based CO 2 absorption in packed columns due to their ability to accurately represent the underlying nonlinear, multiscale dynamics. Numerous studies have previously utilized such CFD simulations to investigate hydrodynamics of columns with structured and random packings by assessing the key hydrodynamic metrics such as the interfacial and wetted areas. While mapping such metrics for different conditions is essential to the optimization of absorption columns, it is not sufficient, as the CO 2 capture rate depends also on the coupled, nonlinear dynamics from the underlying chemical reaction kinetics, thermodynamics, and heat-transfer rates. In this work, we present detailed CFD simulation results augmented by incorporating the effects of interfacial physical mass transfer of CO 2 , heat release from chemical reaction kinetics, and thermophysical property variations from resulting temperature gradients. We demonstrate the applicability of the proposed approach in numerically assessing the performance of packed columns by evaluating key hydrodynamic quantities, CO 2 absorption rates, and temperature rise in a reference column with packings that are structurally similar to the Sulzer Mellapak™ 250.Y packing, for different solvent inflow velocities and temperatures. Predictions from simulation results are found to be consistent with the trends in experimental observations from the literature, suggesting that the predictive capabilities of the simulation framework can be leveraged to guide the future development of absorber-column designs and optimized process flowsheets.

Absorption columns↗
DOE OSTI2025

An eigenvalue-based method for computing the relaxed pressure in compressible multiphase flow with N phases

The modeling of compressible multiphase flows is a decades-old area of study with many applications across various fields. Many of these application areas use stiff pressure relaxation. This process involves the solution of a nonlinear system with N + 1 equations and N + 1 unknowns, where N is the number of phases. The resolution of this system with general equations of state (EOSs) is difficult. Furthermore, nonlinear systems can admit multiple solutions, and current solution methods do not address this possibility. Very recently, a thermodynamic relaxation method was introduced, which effectively maps a relatively simple predictor equation of state onto a more complex target equation of state. In this context, the target EOSs are the chosen EOSs for the thermodynamic model. Furthermore, this thermodynamic relaxation has the benefit of simplifying the stiff pressure relaxation system of equations. In this article, we show this system reduces to a polynomial of degree N, which can be recast as an eigenvalue problem through the use of the associated companion matrix. We show that although this eigenvalue method is generally less efficient than Newton–Raphson iteration, it does not suffer from convergence issues and finds all N roots of the polynomial. Hence, the method provides a fail-safe for root-finding iterative methods and a way to address the issue of multiple solutions to the nonlinear system of equations in stiff pressure relaxation.

Eigenvalue algorithm↗
DOE OSTI2015

Incompressible multiphase flow and encapsulation simulations using the moment-of-fluid method

A moment-of-fluid method is presented for computing solutions to incompressible multiphase flows in which the number of materials can be greater than two. In this work, the multimaterial moment-of-fluid interface representation technique is applied to simulating surface tension effects at points where three materials meet. The advection terms are solved using a directionally split cell integrated semi-Lagrangian algorithm, and the projection method is used to evaluate the pressure gradient force term. The underlying computational grid is a dynamic block-structured adaptive grid. The new method is applied to multiphase problems illustrating contact-line dynamics, triple junctions, and encapsulation in order to demonstrate its capabilities. Examples are given in two-dimensional, three-dimensional axisymmetric (R–Z), and three-dimensional (X–Y–Z) coordinate systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

A two-stage adaptive stochastic collocation method on nested sparse grids for multiphase flow in randomly heterogeneous porous media

A new computational method is proposed for efficient uncertainty quantification of multiphase flow in porous media with stochastic permeability. For pressure estimation, it combines the dimension-adaptive stochastic collocation method on Smolyak sparse grids and the Kronrod–Patterson–Hermite nested quadrature formulas. For saturation estimation, an additional stage is developed, in which the pressure and velocity samples are first generated by the sparse grid interpolation and then substituted into the transport equation to solve for the saturation samples, to address the low regularity problem of the saturation. Numerical examples are presented for multiphase flow with stochastic permeability fields to demonstrate accuracy and efficiency of the proposed two-stage adaptive stochastic collocation method on nested sparse grids.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2013

Unraveling the Geometry Dependence of In-Nozzle Cavitation in High-Pressure Injectors

Cavitation is an intricate multiphase phenomenon that interplays with turbulence in fluid flows. It exhibits clear duality in characteristics, being both destructive and beneficial in our daily lives and industrial processes. Despite the multitude of occurrences of this phenomenon, highly dynamic and multiphase cavitating flows have not been fundamentally well understood in guiding the effort to harness the transient and localized power generated by this process. In a microscale, multiphase flow liquid injection system, we synergistically combined experiments using time-resolved x-radiography and a novel simulation method to reveal the relationship between the injector geometry and the in-nozzle cavitation quantitatively. We demonstrate that a slight alteration of the geometry on the micrometer scale can induce distinct laminar-like or cavitating flows, validating the multiphase computational fluid dynamics simulation. Furthermore, the simulation identifies a critical geometric parameter with which the high-speed flow undergoes an intriguing transition from non-cavitating to cavitating.

FLUID DYNAMICS↗
DOE OSTI2018

Numerical Simulation of Multiphase Magnetohydrodynamic Flow and Deformation of Electrolyte–Metal Interface in Aluminum Electrolysis Cells

A computational fluid dynamics based multiphase magnetohydrodynamic (MHD) flow model for simulating the melt flow and bath–metal interface deformation in realistic aluminum reduction cells is presented. The model accounts for the complex physics of the MHD problem in aluminum reduction cells by coupling two immiscible fluids, electromagnetic field, Lorentz force, flow turbulence, and complex cell geometry with large length scale. Especially, the deformation of bath–metal interface is tracked directly in the simulation, and the condition of constant anode–cathode distance (ACD) is maintained by moving anode bottom dynamically with the deforming bath–metal interface. The metal pad deformation and melt flow predicted by the current model are compared to the predictions using a simplified model where the bath–metal interface is assumed flat. The effects of the induced electric current due to fluid flow and the magnetic field due to the interior cell current on the metal pad deformation and melt flow are investigated. The presented model extends the conventional simplified box model by including detailed cell geometry such as the ledge profile and all channels (side, central, and cross-channels). The simulations show the model sensitivity to different side ledge profiles and the cross-channel width by comparing the predicted melt flow and metal pad heaving. In addition, the model dependencies upon the reduction cell operation conditions such as ACD, current distribution on cathode surface and open/closed channel top, are discussed.

42 ENGINEERING↗
DOE OSTI2016

Uncertainty quantification tools for multiphase gas-solid flow simulations using MFIX

Computational fluid dynamics (CFD) has been widely studied and used in the scientific community and in the industry. Various models were proposed to solve problems in different areas. However, all models deviate from reality. Uncertainty quantification (UQ) process evaluates the overall uncertainties associated with the prediction of quantities of interest. In particular it studies the propagation of input uncertainties to the outputs of the models so that confidence intervals can be provided for the simulation results. In the present work, a non-intrusive quadrature-based uncertainty quantification (QBUQ) approach is proposed. The probability distribution function (PDF) of the system response can be then reconstructed using extended quadrature method of moments (EQMOM) and extended conditional quadrature method of moments (ECQMOM). The report first explains the theory of QBUQ approach, including methods to generate samples for problems with single or multiple uncertain input parameters, low order statistics, and required number of samples. Then methods for univariate PDF reconstruction (EQMOM) and multivariate PDF reconstruction (ECQMOM) are explained. The implementation of QBUQ approach into the open-source CFD code MFIX is discussed next. At last, QBUQ approach is demonstrated in several applications. The method is first applied to two examples: a developing flow in a channel with uncertain viscosity, and an oblique shock problem with uncertain upstream Mach number. The error in the prediction of the moment response is studied as a function of the number of samples, and the accuracy of the moments required to reconstruct the PDF of the system response is discussed. The QBUQ approach is then demonstrated by considering a bubbling fluidized bed as example application. The mean particle size is assumed to be the uncertain input parameter. The system is simulated with a standard two-fluid model with kinetic theory closures for the particulate phase implemented into MFIX. The effect of uncertainty on the disperse-phase volume fraction, on the phase velocities and on the pressure drop inside the fluidized bed are examined, and the reconstructed PDFs are provided for the three quantities studied. Then the approach is applied to a bubbling fluidized bed with two uncertain parameters, particle-particle and particle-wall restitution coefficients. Contour plots of the mean and standard deviation of solid volume fraction, solid phase velocities and gas pressure are provided. The PDFs of the response are reconstructed using EQMOM with appropriate kernel density functions. The simulation results are compared to experimental data provided by the 2013 NETL small-scale challenge problem. Lastly, the proposed procedure is demonstrated by considering a riser of a circulating fluidized bed as an example application. The mean particle size is considered to be the uncertain input parameter. Contour plots of the mean and standard deviation of solid volume fraction, solid phase velocities, and granular temperature are provided. Mean values and confidence intervals of the quantities of interest are compared to the experiment results. The univariate and bivariate PDF reconstructions of the system response are performed using EQMOM and ECQMOM.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

High Performance Computing to Enable Next-Generation Low-Temperature Waste Heat Recovery

US manufacturing industry fails to recover an estimated 900 trillion BTUs of low-temperature waste heat from its processes each year. A grand research challenge has been to develop waste heat recovery technology that can be applied to industrial manufacturing processes and vehicle operations. The Oak Ridge National Laboratory (ORNL)/Eaton research team performed computational research and development to design an innovative direct-contact heat exchanger (DCHE) technology to deliver low-cost, compact, longer-lifetime, high-efficiency waste heat recovery that is optimized for a low-temperature organic Rankine cycle. ORNL resources and expertise in high performance computing (HPC) and multiphase flows were utilized to realize this goal while advancing the fundamental understanding of two-phase, two-immiscible-fluid turbulent flow heat transfer for heat exchangers. In the first stage of the project, a computational fluid dynamics (CFD) model of a DCHE was developed. Verification and limited validation of the numerical solution were performed using experimental data from published literature. To support efforts in verification and validation, two-dimensional CFD models were also developed with the objective of investigating different boundary conditions to reach converged, steady-state solutions.Based on benchmarking efforts, a baseline industry-grade design of a DCHE was developed, which consists of two horizontal pipes of different cross-sectional areas – joined by a converging-diverging nozzle in the middle and relies on a three-phase system with co-current flows for operation. Evaporation of the cold liquid (n-pentane or methanol) by the hot liquid water occurs in the first pipe. The first pipe contains two inlets for liquid water and liquid pentane (or liquid methanol). The second pipe with the larger cross-sectional area serves as a gravity-driven phase-separator. It contains two outlets that are staggered to avoid entrainment of the liquid water phase by the gas phase. This baseline design resulted from several trial-and-error evaluations using two-dimensional CFD models. Confirmatory three-dimensional CFD models were also run for different mass flow rates and inlet temperatures (inlet water temperature ranging from 50°C to 90°C), and efficiency plots were produced to fully characterize the proposed industrial-grade design of the DCHE.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

NETL Crosscutting Research Video Series: Multiphase Flow (Short Version)

For over 30 years, NETL’s work in multiphase flow science has served as one of the cornerstones of the lab’s research portfolio. Multiphase flow refers to the simultaneous flow of gases, liquids and/or solid materials. The goal of the multiphase flow science team is to provide computational modeling tools to help offset the risk and cost of multiphase reactor development.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

NETL Crosscutting Research Video Series: Multiphase Flow

For over 30 years, NETL’s work in multiphase flow science has served as one of the cornerstones of the lab’s research portfolio. Multiphase flow refers to the simultaneous flow of gases, liquids and/or solid materials. The goal of the multiphase flow science team is to provide computational modeling tools to help offset the risk and cost of multiphase reactor development.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Experimental measurements of gas-particle flows in large-scale strippers

Measurements of gas–solid particle flow in a large-scale stripper unit are reported. The experiments target industrial (pilot) scale measurements of gas-particle flow that can be used to validate numerical methods for modeling multiphase flows, such as computational fluid dynamics coupled to the discrete element method (CFD-DEM). Specifically, experiments were performed with Geldart Group B (533 µm) glass beads in a stripper unit. In general, previous CFD-DEM validation datasets were performed in benchtop experimental systems and limited to O(10 5 ) particles. Here, in this work, the number of particles in the isolated section of the stripper is O(10 7 ) for all tests. Measurements are reported for a ~2 m tall section of the ~1 m diameter stripper. Radial mass flux profiles measured at five axial positions and three axial pressure drop measurements are reported for six operating conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Effects of Nozzle Radial Position, Separation Angle, and Gas Flow Partitioning on the Mixing, Eye Area, and Wall Shear Stress in Ladles Fitted with Dual Plugs

Mixing time, slag eye area, and wall shear stress in a ladle fitted with dual plugs have been studied as a function of operating variables, namely, gas flow rate, radial nozzle position, separation angle between nozzles and flow rate partitioning. While the mixing time and slag eye area have been experimentally investigated in a scaled water model (with and without a top slag layer), the shear stress on the vessel wall has been studied computationally via a RANS-based turbulent, three-dimensional coupled Eulerian–Lagrangian (VOF-DPM), multiphase flow model. Experimental and computational results have indicated that the mixing, eye area, and wall shear stress depend on the gas flow rate, i.e., while mixing efficiency increases with the increasing gas flow rate, the slag eye area, and wall shear stress, in contrast, become more pronounced with the increasing gas flow, leading to an undesirable operating regime. The radial nozzle position, separation angle between the nozzles and flow rate partitioning at any given flow rate also influence the ladle process performance, influencing the mixing, eye area, and wall shear stress, albeit to a varied degree. Within the range of operating conditions studied, an expected inverse correspondence between mixing time and shear behavior was observed. Experimental and computational results in conjunction have indicated that the best arrangement of porous plugs or gas injection nozzles for superior ladle process performance is dependent on the gas flow rate and is specific to the desired objective (i.e., decreasing the mixing time, or slag eye area and wall shear stress). Hence, a unique gas injection practice cannot and should not be suggested as the optimum for ladle metallurgy in steelmaking. Nevertheless, if the mixing time is the parameter of primary interest, a nozzle configuration with equal flow partitioning (1:1) between the nozzles and identical nozzle radial positions (0.7R/0.7R, 45 deg) should suffice for both low and high gas flow rates. In contrast, a nonidentical nozzle radial position (0.7R/0.5R, 90 deg) and an unequal gas flow rate per nozzle (1:3) appear preferable if both ladle eye and shear stresses, rather than mixing, are the issues of concern.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Numerical Simulation of an Industrial Fluid Catalytic Cracking Regenerator

Fluid catalytic cracking (FCC) is one of the most important conversion processes in petroleum refineries, and the FCC regenerator is a key part of an FCC unit utilized in the recovery of solid catalyst reactivity by burning off the deposited coke on the catalyst surface. Furthermore, a three-dimensional multiphase, multispecies reacting flow computational fluid dynamics (CFD) model was established to simulate the flow and reactions inside an FCC regenerator. The Euler–Euler approach, where the two phases (gas and solid) are considered to be continuous and fully interpenetrating, is employed. The model includes gas–solid momentum exchange, gas–solid heat exchange, gas–solid mass exchange, and chemical reactions. Chemical reactions incorporated into the model simulate the combustion of coke which is present on the catalyst surface. We validated the simulation results using plant data.

42 ENGINEERING↗
DOE OSTI2021

High-Accuracy Simulations to Model Pyrometallurgical Processes in a Secondary Lead Reverberatory Furnace

The US manufacturing industry produces about 1.3 million tons of refined lead each year using secondary sources consisting mainly of lead batteries. ORNL is partnering with Gopher resource, the second largest lead recycling company in the United States, and GTI, to develop a high-fidelity CFD model of a directly fired, reverberatory-style, secondary lead furnace. These High Performance Computing (HPC) simulations are aimed to use first principles modeling for combustion and melting processes of the secondary lead feed while accounting for complex interphase interactions between the gas, solid charge (lead) material, slag, and metal phases. Through validation against operating plant data, this effort will enable significant improvements in design, operational parameters, and energy efficiency, thus improving productivity and refractory lifetime of secondary lead melting furnaces. Estimated savings/reduction of, at least, 1 trillion BTU, 1 million ton/year of greenhouse gas emissions, and $\$50$ million/year to the US lead industry can be expected. ORNL resources and expertise in high-performance computing and multicomponent, multiphase flows were utilized to realize this goal while advancing the understanding of the smelting and melting processes occurring within the furnace.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗