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Results for “multiphase flows”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Integrated rheology model: Explosive Composition B-3

Composition B-3 (Comp B-3) is a high explosive formulation composed of 60/40wt% RDX (1,3,5-trinitroperhydro-1,3,5-triazine) /TNT (2,4,6 trinitrotoluene). Above approximately 78°C this formulation partially melts to form a multiphase system with solid RDX particles in a molten TNT matrix. This multiphase system presents a number of phenomena that influence its apparent viscosity. In an earlier study explosive Composition B-3 (Comp B-3, 60/40wt% RDX/TNT) was examined for evidence of yield stress using a non-isothermal falling ball viscometer and a yield stress model was proposed in this paper. An integrated viscosity model suitable for use in computational fluid dynamics (CFD) simulations is developed to capture the transition from a heterogeneous solid to a Bingham viscoplastic fluid. This viscosity model is used to simulate the motion of imbedded spheres falling through molten Comp B-3. Finally, comparison of the simulations to physical tests show agreement between the positions predicted by the model and the measured locations of the spheres as a function of temperature between 90C and 165C.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Learning unknown physics of non-Newtonian fluids

Here, we use physics-informed neural networks (PINNs) to learn viscosity models of two non-Newtonian systems (polymer melts and suspensions of particles) using only velocity measurements. For synthetic velocity data generated with the power-law viscosity model, the PINN-inferred viscosity model agrees with the analytical model for shear rates with large absolute values but deviates for shear rates near zero where the analytical model has an unphysical singularity. Once the viscosity model is learned the PINN method can solve the momentum conservation equation using only the boundary conditions.

42 ENGINEERING↗
DOE OSTI2025

Metriplectic four-bracket algorithm for constructing thermodynamically consistent dynamical systems

A unified thermodynamic algorithm is presented for constructing thermodynamically consistent dynamical systems, i.e., systems that have Hamiltonian and dissipative parts that conserve energy while producing entropy. The algorithm is based on the metriplectic 4-bracket given in Morrison and Updike [Phys. Rev. E 109, 045202 (2024)]. A feature of the unified thermodynamic algorithm is the force-flux relation 𝐉 𝛼 =−𝐿 𝛼⁢𝛽 𝛁(𝛿⁢𝐻⁡/𝛿⁢𝜉 𝛽 ) for phenomenological coefficients 𝐿 𝛼⁢𝛽 , Hamiltonian 𝐻, and dynamical variables 𝜉 𝛽 . The algorithm is applied to the Navier-Stokes-Fourier, the Cahn-Hilliard-Navier-Stokes, and Brenner-Navier-Stokes-Fourier systems, and significant generalizations of these systems are obtained.

Multiphase flows↗
DOE OSTI2020

A Relaxed PV Bus Model in Linear Power Flow

The emerging multimodal active energy resource units make it necessary to introduce constant voltage amplitude buses (PV bus) in the operation of modern distribution systems. To enable the analysis of PV bus using linear power flow models, this letter proposes a relaxed PV bus model for solving power flow related problems using an indirect modeling approach. The developed PV bus model can be applied to linear power flow models in both rectangular and polar coordinates. Besides, the approximation error of the relaxed PV bus model can also be controlled and quantified. Lastly, the proposed relaxed PV bus model is validated using different test systems. According to the numerical studies, the maximum error on the PV bus approximation in all case studies is only 0.61%, and the maximum error of the supporting power at the PV buses is 6.5%.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Thermophysical modeling of raw glaze liquidus temperature and viscosity

Raw glazes, which do not contain pre-melted glass frits, are widely used due to their low cost. The natural variability of the mineral compositions used in raw glazes affects their viscosity during firing. Molten glaze viscosity plays an important role in determining the final surface quality; therefore, it is important to determine how raw glaze composition and firing conditions affect viscosity. Thermophysical modeling provides a way to evaluate the liquidus temperature and viscosity of molten glazes as a function of composition and oxygen activity. Equilibrium phase volume fraction and composition of 242 raw glaze recipes were evaluated under oxidizing and reducing conditions. Undissolved or precipitation of solid phases explain the secondary flux transition from anti-fluxing to fluxing near the liquidus temperature. The liquidus temperature and viscosity of iron glazes decrease as a function of increasing iron content under a reducing atmosphere. The empirical probability distribution of molten glaze viscosity follows a lognormal distribution, with lead glazes having significantly lower viscosity compared with glazes without lead. Here, the peak firing temperature viscosity of lead-free glazes is near the working point of glass. Multiple linear regression analysis shows that the peak firing temperature viscosity and liquidus temperature significantly predict the viscosity factor.

36 MATERIALS SCIENCE↗
DOE OSTI2024

PeleMP: The Multiphysics Solver for the Combustion Pele Adaptive Mesh Refinement Code Suite

Combustion encompasses multiscale, multiphase reacting flow physics spanning a wide range of scales from the molecular scales, where chemical reactions occur, to the device scales, where the turbulent flow is affected by the geometry of the combustor. This scale disparity and the limited measurement capabilities from experiments make modeling combustion a significant challenge. Recent advancements in high-performance computing (HPC), particularly with the Department of Energy's Exascale Computing Project (ECP), have enabled high-fidelity simulations of practical applications to be performed. The major physics submodels, including chemical reactions, turbulence, sprays, soot, and thermal radiation, exhibit distinctive computational characteristics that need to be examined separately to ensure efficient utilization of computational resources. This paper presents the multiphysics solver for the Pele code suite, called PeleMP, which consists of models for spray, soot, and thermal radiation. Here, the mathematical and algorithmic aspects of the model implementations are described in detail as well as the verification process. The computational performance of these models is benchmarked on multiple supercomputers, including Frontier, an exascale machine. Results are presented from production simulations of a turbulent sooting ethylene flame and a bluff-body swirl stabilized spray flame with sustainable aviation fuels to demonstrate the capability of the Pele codes for modeling practical combustion problems with multiphysics. This work is an important step toward the exascale computing era for high-fidelity combustion simulations providing physical insights and data for predictive modeling of real-world devices.

42 ENGINEERING↗
DOE OSTI2020

toughio v1.2.2

TOUGH is a widely used general purpose numerical simulator designed for fluid and heat flows of multiphase, multicomponent fluid mixtures in porous and fractured media, which has been applied to many real-world problems such as underground geological storage, geothermal reservoir engineering or nuclear waste disposal, to name a few. `toughio` is a lightweight, object-oriented and vectorized Python library that aims to provide user-friendly routines to facilitate pre- and post-processing of a TOUGH simulation. Although its primary target is the latest version TOUGH3, `toughio` can also be used to read/write TOUGH2 input/output files. Currently, to the best of our knowledge, only PyTOUGH offers an exhaustive number of features to carry out a complete TOUGH simulation using a scripting language. `toughio` and PyTOUGH share the same objectives, yet with different approaches and philosophies. On the one hand, a PyTOUGH mesh is represented as a MULGRAPH geometry where elements can be unstructured horizontally but only layered vertically. It also checks that the model parameters are valid to ensure that a TOUGH simulation runs smoothly. On the other hand, although it provides basic meshing features, `toughio` mostly relies on common third-party softwares (e.g. Abaqus, FLAC3D, Gmsh, LaGriT) to generate the mesh by importing and converting it to a TOUGH mesh, which also conveniently facilitates the coupling of TOUGH with any other simulator that also supports the same mesh formats. Besides, `toughio` is designed to be just a TOUGH input and output file reader/writer. It assumes that the user knows what he is doing and does not verify the validity of the model parameters (`toughio` does verify the functional arguments).

Luu, Keurfon↗
DOE OSTI2019

Heat‐Generating Nuclear Waste in Salt: Field Testing and Simulation

Core Ideas A field‐scale experiment and numerical simulations confirm salt backfill behavior. Simulations closely match temperature around and under the piled salt backfill. Results indicate limited dissolution–precipitation reactions around the heat source. Alteration of backfill is unlikely if the drift is allowed to dry before emplacement. Investigations relating to in‐drift disposal of heat‐generating nuclear waste in salt have raised questions about heat–brine interactions in the unsaturated run‐of‐mine (RoM) salt pile used as backfill. These interactions have the potential to change the structure of the RoM salt surrounding the canister, possibly altering long‐term containment of the source. An experiment is in progress at the Waste Isolation Pilot Plant (WIPP), New Mexico, in which a heated canister was placed on the floor of an open drift, covered in a pile of RoM salt, and energized with 1000 W. Temperature in the RoM salt pile had stabilized after about 15 d, allowing evaluation of the heat‐up period of the ongoing experiment. Using a multiphase porous flow simulator that has been modified to handle salt‐specific coupled processes, we examined coupled thermal–hydrological–chemical behavior in the RoM salt pile. Our simulations suggest that for the relatively dry cases examined, porosity changes within RoM salt in a generic salt repository are likely to be minor in the period between waste emplacement and plastic closure of the drift. The primary sensitivity for porosity change is to the early moisture content of the RoM salt used to cover the canister. Secondary influences include moisture availability from the disturbed rock zone (DRZ) surrounding the drift and the capillary pressure ratio between the DRZ and the RoM salt. Early changes in porosity and permeability may be affected by moisture content, but this was not observed in the test. Such changes would be most likely to occur when using damp RoM salt or if waste is emplaced in a drift immediately following opening of the drift before evaporative dewatering of the drift walls occurs.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2015

Enhancements to the TOUGH2 Simulator as Implemented in iTOUGH2

iTOUGH2 is a program for parameter estimation, sensitivity analysis, and uncertainty propagation analysis. It is based on the TOUGH2 simulator for non-isothermal multiphase, multicomponent flow and transport in fractured and porous media [Pruess, 1987, 1991, 2005, 2011; Falta et al., 1995; Pruess et al., 1999, 2002, 2012; Doughty, 2013]. The core of iTOUGH2 contains slightly modified versions of TOUGH2 modules. Most code modifications are editorial and do not affect the simulation results. As a result, standard TOUGH2 input files can be used in iTOUGH2, and identical results are obtained if iTOUGH2 is run in forward mode. However, a number of modifications have been made as described in this report. They enhance the functionality, flexibilitu, and eas-of-use of the forward simulator. This report complements the reports iTOUGH2 User's Guide, iTOUGH2 Command Referecne, and the collection of tutorial examples in iTOUGH2 Sample Problems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

STAR-CCM+ Verification and Validation Plan

The commercial Computational Fluid Dynamics (CFD) code STAR-CCM+ provides general purpose finite volume method solutions for fluid dynamics and energy transport. This document defines plans for verification and validation (V&V) of the base code and models implemented within the code by the Consortium for Advanced Simulation of Light water reactors (CASL). The software quality assurance activities described herein are port of the overall software life cycle defined in the CASL Software Quality Assurance (SQA) Plan [Sieger, 2015]. STAR-CCM+ serves as the principal foundation for development of an advanced predictive multi-phase boiling simulation capability within CASL. The CASL Thermal Hydraulics Methods (THM) team develops advanced closure models required to describe the subgrid-resolution behavior of secondary fluids or fluid phases in multiphase boiling flows within the Eulerian-Eulerian framework of the code. These include wall heat partitioning models that describe the formation of vapor on the surface and the forces the define bubble/droplet dynamic motion. The CASL models are implemented as user coding or field functions within the general framework of the code. This report defines procedures and requirements for V&V of the multi-phase CFD capability developed by CASL THM. Results of V&V evaluations will be documented in a separate STAR-CCM+ V&V assessment report. This report is expected to be a living document and will be updated as additional validation cases are identified and adopted as part of the CASL THM V&V suite.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Numerical simulation of a full-loop circulating fluidized bed under different operating conditions

Both experimental and computational studies of the fluidization of high-density polyethylene (HDPE) particles in a small-scale full-loop circulating fluidized bed are conducted. Experimental measurements of pressure drop are taken at different locations along the bed. The solids circulation rate is measured with an advanced Particle Image Velocimetry (PIV) technique. The bed height of the quasi-static region in the standpipe is also measured. Comparative numerical simulations are performed with a Computational Fluid Dynamics solver utilizing a Discrete Element Method (CFD-DEM). This paper reports a detailed and direct comparison between CFD-DEM results and experimental data for realistic gas-solid fluidization in a full-loop circulating fluidized bed system. The comparison reveals good agreement with respect to system component pressure drop and inventory height in the standpipe. In addition, the effect of different drag laws applied within the CFD simulation is examined and compared with experimental results.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2018

TOUGH3 User’s Guide, Version 1.0

TOUGH3 is a general-purpose numerical simulator for multi-dimensional fluid and heat flows of multiphase, multicomponent fluid mixtures in porous and fractured media. It is developed as an enhanced, more efficient version of the TOUGH2 suite of codes. The present report provides a summary of the mathematical models and numerical methods, discusses new user features, and gives complete specifications for preparing input data. It also includes a quick start guide to TOUGH3 that describes how to install the code, set up the problem, execute the simulation, and analyze the output. To make this report self-contained, we include much of the material that was covered in the TOUGH2 user’s guide (Pruess et al., 2012).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

LANL Salt International Update

This milestone presents material relating to international salt investigations during the 2018 fiscal year. Overall salt efforts this year were divided between the currently in-progress borehole experiments (see test plan TP-18-001, rev. 0 and DOE Milestone M3SF-18LA010303014), model development (see DOE milestone M3SF-18LA010303015), and validation of numerical modeling for generic salt repository applications domestically (intranational) and abroad (international). The present milestone focuses on the last of these subject areas. Work for international dissemination was conducted during the first half of the 2018 fiscal year and includes two international conference presentations - Geological Society of America (GSA) and the International Society for Porous Media (IntePore) - and a manuscript which is currently in review in Vadose Zone Journal.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

High Fidelity Computational Model for Fluidized Bed Experiments (Final Report)

MFiX was integrated with preconditioners and linear solver packages in Trilinos via MFIX, Fortran, C, and C++ wrappers. The MFIX wrapper interpreted the structure of the matrix and vector from MFiX while the Fortran wrapper transfers this information to a low-level language, C. C-wrapper transforms the memory semantic between Fortran and C++ language. C++ wrapper passes the matrix and vector to a Trilinos package and gets the solution. This solution was transferred to MFiX via C++, C, Fortran, MFIX wrapper. The framework is used to integrate first, second and third generation linear solvers in Trilinos with MFiX.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2020

Multiphase representation of hotspot formation and growth

Multiphase reacting flow approach has been adopted for modeling of hotspot formation and growth on sub-zonal scale. Mechanical response of the high explosive (HE) is modeled by the Visco-Plastic SCRAM model which includes plastic work, crack growth, and frictional heating along the cracks. In this work a sub-zonal regions with high temperature, hotspots, are modeled as a new phase. Formation and growth of the hotspot phase from the cold phase is modeled as a phase change. Each phase has its own temperature and pressure. Chemical reactions also progress in both phases. The growth of hotspots are determined by the solution of the heat conduction equation with appropriate heat sources due to friction and plastic heating. Sample calculations using the BABBO code show successful detonation calculations with hotspot formation and growth.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗