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At least 1,747 records · Page 97

A Review of Lattice-Boltzmann Models Coupled with Geochemical Modeling Applied for Simulation of Advanced Waterflooding and Enhanced Oil Recovery Processes

To maintain economic profit and improve the oil production efficiency after the primary and secondary production phase, advanced waterflooding techniques such as low salinity waterflooding in carbonate reservoirs have been investigated in numerical simulations, laboratory experiments, and field pilot tests. Multiple underlying mechanisms have been proposed based on these studies, and they are still under debate. Various numerical modeling approaches are introduced, but there exists a lack of a pore-scale comprehensive modeling scheme to fully understand the processes. Lattice-Boltzmann method (LBM) is a type of numerical fluid flow modeling technique that shows capabilities and flexibilities in modeling pore-scale fluid flow to integrate physical–chemical processes within complex structures. The intrinsic feature of LBM makes it a promising framework for simulating advanced waterflooding due to its flexibility, accuracy, and parallel efficiency. LBM works either by itself for solving reactive transport problems or by coupling with a third-party reaction solver. This review mainly introduces the LBM fluid flow and reactive transport capabilities and the concept and modeling approaches to simulate advanced waterflooding techniques. Meanwhile, an evaluation of the coupled LBM models for enhanced oil recovery (EOR) simulations is discussed with future research challenges and directions concluded.

02 PETROLEUM↗

Optimal Power Flow With State Estimation in the Loop for Distribution Networks

Here in this article, we propose a framework for running optimal control-estimation synthesis in distribution networks. Our approach combines a primal-dual gradient-based optimal power flow solver with a state estimation feedback loop based on a limited set of sensors for system monitoring, instead of assuming exact knowledge of all states. The estimation algorithm reduces uncertainty on unmeasured grid states based on certain online state measurements and noisy "pseudomeasurements." We analyze the convergence of the proposed algorithm and quantify the statistical estimation errors based on a weighted least-squares estimator. The numerical results on a 4521-node network demonstrate that this approach can scale to extremely large networks and provide robustness to both large pseudomeasurement variability and inherent sensor measurement noise.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Quinoa, Version 0.2

Quinoa is a set of computational tools that enables research and numerical analysis in fluid dynamics. At this time it remains a test-bed to experiment with various algorithms using fully asynchronous runtime systems. Currently, Quinoa consists of the following tools: (1) Walker, a numerical integrator for systems of stochastic differential equations in time. It is a mathematical tool to analyze and design the behavior of stochastic differential equations. It allows the estimation of arbitrary coupled statistics and probability density functions and is currently used for the design of statistical moment approximations for multiple mixing materials in variable-density turbulence. (2) Inciter, an overdecomposition-aware finite element field solver for partial differential equations using 3D unstructured grids. Inciter is used to research asynchronous mesh-based algorithms and to experiment with coupling asynchronous to bulk-synchronous parallel code. Two planned new features of Inciter, compared to the previous release (LA-CC-16-015), to be implemented in 2017, are (a) a simple Navier-Stokes solver for ideal single-material compressible gases, and (b) solution-adaptive mesh refinement (AMR), which enables dynamically concentrating compute resources to regions with interesting physics. Using the NS-AMR problem we plan to explore how to scale such high-load-imbalance simulations, representative of large production multiphysics codes, to very large problems on very large computers using an asynchronous runtime system. (3) RNGTest, a test harness to subject random number generators to stringent statistical tests enabling quantitative ranking with respect to their quality and computational cost. (4) UnitTest, a unit test harness, running hundreds of tests per second, capable of testing serial, synchronous, and asynchronous functions. (5) MeshConv, a mesh file converter that can be used to convert 3D tetrahedron meshes from and to either of the following formats: Gmsh, http://www.geuz.org/gmsh, Netgen, http://sourceforge.net/apps/mediawiki/netgen-mesher, ExodusII, http://sourceforge.net/projects/exodusii, HyperMesh, http://www.altairhyperworks.com/product/HyperMesh.

Bakosi, Jozsef↗

Development and Benchmarking of a Hybrid PIC Code For Dense Plasmas and Fast Ignition (Final Report)

Radiation processes play an important role in the study of both fast ignition and other inertial confinement schemes, such as plasma jet driven magneto-inertial fusion, both in their effect on energy balance, and in generating diagnostic signals. In the latter case, warm and hot dense matter may be produced by the convergence of a plasma shell formed by the merging of an assembly of high Mach number plasma jets. This innovative approach has the potential advantage of creating matter of high energy densities in voluminous amount compared with high power lasers or particle beams. An important application of this technology is as a plasma liner for the flux compression of magnetized plasma to create ultra-high magnetic fields and burning plasmas. HyperV Technologies Corp. has been developing plasma jet accelerator technology in both coaxial and linear railgun geometries to produce plasma jets of sufficient mass, density, and velocity to create such imploding plasma liners. An enabling tool for the development of this technology is the ability to model the plasma dynamics, not only in the accelerators themselves, but also in the resulting magnetized target plasma and within the merging/interacting plasma jets during transport to the target. Welch pioneered numerical modeling of such plasmas (including for fast ignition) using the LSP simulation code. Lsp is an electromagnetic, parallelized, plasma simulation code under development since 1995. It has a number of innovative features making it uniquely suitable for modeling high energy density plasmas including a hybrid fluid model for electrons that allows electrons in dense plasmas to be modeled with a kinetic or fluid treatment as appropriate. In addition to in-house use at Voss Scientific, several groups carrying out research in Fast Ignition (LLNL, SNL, UCSD, AWE (UK), and Imperial College (UK)) also use LSP. A collaborative team consisting of HyperV Technologies Corp., Voss Scientific LLC, FAR-TECH, Inc., Prism Computational Sciences, Inc. and Advanced Energy Systems Inc. joined efforts to develop new physics and numerical models for LSP in several key areas to enhance the ability of LSP to model high energy density plasmas (HEDP). This final report details those efforts. Areas addressed in this research effort include: adding radiation transport to LSP, first in 2D and then fully 3D, extending the EMHD model to 3D, implementing more advanced radiation and electrode plasma boundary conditions, and installing more efficient implicit numerical algorithms to speed complex 2-D and 3-D computations. The new capabilities allow modeling of the dominant processes in high energy density plasmas, and further assist the development and optimization of plasma jet accelerators, with particular attention to MHD instabilities and plasma/wall interaction (based on physical models for ion drag friction and ablation/erosion of the electrodes). In the first funding cycle we implemented a solver for the radiation diffusion equation. To solve this equation in 2-D, we used finite-differencing and applied the parallelized sparse-matrix solvers in the PETSc library (Argonne National Laboratory) to the resulting system of equations. A database of the necessary coefficients for materials of interest was assembled using the PROPACEOS and ATBASE codes from Prism. The model was benchmarked against Prism's 1-D radiation hydrodynamics code HELIOS, and against experimental data obtained from HyperV's separately funded plasma jet accelerator development program. Work in the second funding cycle focused on extending the radiation diffusion model to full 3-D, continued development of the EMHD model, optimizing the direct-implicit model to speed up calculations, add in multiply ionized atoms, and improved the way boundary conditions are handled in LSP. These new LSP capabilities were then used, along with analytic calculations and Mach2 runs, to investigate plasma jet merging, plasma detachment and transport, restrike and advanced jet accelerator design. In addition, a strong linkage to diagnostic measurements was made by modeling plasma jet experiments on PLX to support benchmarking of the code. A large number of upgrades and improvements advancing hybrid PIC algorithms were implemented in LSP during the second funding cycle. These include development of fully 3D radiation transport algorithms, new boundary conditions for plasma-electrode interactions, and a charge conserving equation of state that permits multiply ionized high-Z ions. The final funding cycle focused on 1) mitigating the effects of a slow-growing grid instability which is most pronounced in plasma jet frame expansion problems using the two-fluid Eulerian remap algorithm, 2) extension of the Eulerian Smoothing Algorithm to allow EOS/Radiation modeling, 3) simulations of collisionless shocks formed by jet merging, 4) simulations of merging jets using high-Z gases, 5) generation of PROPACEOS EOS/Opacity databases, 6) simulations of plasma jet transport experiments, 7) simulations of plasma jet penetration through transverse magnetic fields, and 8) GPU PIC code development. The tools developed during this project are applicable not only to the study of plasma jets, but also to a wide variety of HEDP plasmas of interest to DOE, including plasmas created in short-pulse laser experiments performed to study fast ignition concepts for inertial confinement fusion.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Elliptic flow computation by low Reynolds number two-equation turbulence models

A detailed comparison of ten low-Reynolds-number k-epsilon models is carried out. The flow solver, based on an implicit approximate factorization method, is designed for incompressible, steady two-dimensional flows. The conservation of mass is enforced by the artificial compressibility approach and the computational domain is discretized using centered finite differences. The turbulence model predictions of the flow past a hill are compared with experiments at Re = 10 exp 6. The effects of the grid spacing together with the numerical efficiency of the various formulations are investigated. The results show that the models provide a satisfactory prediction of the flow field in the presence of a favorable pressure gradient, while the accuracy rapidly deteriorates when a strong adverse pressure gradient is encountered. A newly proposed model form that does not explicitly depend on the wall distance seems promising for application to complex geometries.

Michelassi, V.↗

Spectral Analysis of Regular Material Point Method and its Application to Study High Pressure Reverse Osmosis Membrane Compaction and Embossing

Material Point Method (MPM) is gaining widespread interest in applied continuum mechanics. The fact that all the continuum properties are stored on the particles (or material points) and the governing equations are solved on these material points makes MPM extremely suited to problems involving severe material deformations, such as crack propagation, soil movement, and fluid flows. Despite its popularity, only a few studies have focused on the numerical properties of MPM. This presentation introduces a global spectral analysis of the regular material point method. Contrary to previous studies, the analysis focuses on the numerical properties of the method in the spectral space. The amplification factor is derived as a function of the non- dimensional wave numbers. It provides insights into the stability and dissipative properties of the method for various CFL and Fourier numbers. The effect of the grid shape functions, number of particles per cell and their locations inside the grid cell are also analyzed. The EXAGOOP MPM solver (https://github.com/NREL/Exagoop.git) is developed at the National Renewable Energy Laboratory as a part of the NAWI UHPRO project and is based on the AMReX framework. A single-level, uniform cartesian grid is used as the background mesh, while the particle class in AMReX is used to manage the material point operations. Linear hat and B-splines are used as grid shape functions, while the time integration is performed using explicit Euler time integration. EXAGOOP is both CPU and GPU compatible and has been demonstrated to work well on multiple compute architectures. The performance of EXAGOOP on various computing architectures is presented along with its application to study compaction and embossing of high-pressure reverse osmosis membranes. The MPM solution accurately reproduces the membrane deformation. The deformed pore size and structure simulated using MPM also agree well with experimental SEM images.

material point method↗

gpde

The R package gpde is an R implementation of a probabilistic differential equation solver. The package has a basic implementation of the Chkrebtii (2013) probabilistic ODE solver and an extension using the connection between Kalman Filtering for SDEs and Gaussian Processes from work by Simo Sarkka. The package also implements the Integrated Wiener covariance function from Schober 2014 to obtain probabilistic ODE solutions with the Runge-Kutta solution as the mean result. This collection of tools has been built into an R package for easy use at LANL and in the probabilistic numerics community.

Grosskopf, Michael↗

Input-output-controlled nonlinear equation solvers

To upgrade the efficiency and stability of the successive substitution (SS) and Newton-Raphson (NR) schemes, the concept of input-output-controlled solvers (IOCS) is introduced. By employing the formal properties of the constrained version of the SS and NR schemes, the IOCS algorithm can handle indefiniteness of the system Jacobian, can maintain iterate monotonicity, and provide for separate control of load incrementation and iterate excursions, as well as having other features. To illustrate the algorithmic properties, the results for several benchmark examples are presented. These define the associated numerical efficiency and stability of the IOCS.

Padovan, Joseph↗

An Adaptive Flow Solver for Air-Borne Vehicles Undergoing Time-Dependent Motions/Deformations

This report describes a concurrent Euler flow solver for flows around complex 3-D bodies. The solver is based on a cell-centered finite volume methodology on 3-D unstructured tetrahedral grids. In this algorithm, spatial discretization for the inviscid convective term is accomplished using an upwind scheme. A localized reconstruction is done for flow variables which is second order accurate. Evolution in time is accomplished using an explicit three-stage Runge-Kutta method which has second order temporal accuracy. This is adapted for concurrent execution using another proven methodology based on concurrent graph abstraction. This solver operates on heterogeneous network architectures. These architectures may include a broad variety of UNIX workstations and PCs running Windows NT, symmetric multiprocessors and distributed-memory multi-computers. The unstructured grid is generated using commercial grid generation tools. The grid is automatically partitioned using a concurrent algorithm based on heat diffusion. This results in memory requirements that are inversely proportional to the number of processors. The solver uses automatic granularity control and resource management techniques both to balance load and communication requirements, and deal with differing memory constraints. These ideas are again based on heat diffusion. Results are subsequently combined for visualization and analysis using commercial CFD tools. Flow simulation results are demonstrated for a constant section wing at subsonic, transonic, and a supersonic case. These results are compared with experimental data and numerical results of other researchers. Performance results are under way for a variety of network topologies.

Singh, Jatinder↗

RANS and DES Computations for a Wing with Ice Accretion

A computational investigation was performed to assess the effectiveness of Detached Eddy Simulation (DES) as a tool for predicting icing effects. The AVUS code, a public domain flow solver, was employed to compute solutions for an iced wing configuration using DES and steady Reynolds Averaged Navier-Stokes (RANS) equation methodologies. The wing section considered here was a business jet airfoil (GLC305) with a 22.5-minute glaze ice accretion (944-ice shape). The section was extruded to form a rectangular planform. The model was mounted between two walls so no tip effects were considered. The numerical results were validated by comparison with experimental data for the same configuration. The time-averaged DES computations showed some improvement in lift and drag results near stall when compared to steady RANS results. However, comparisons of the flow field details did not show the level of agreement suggested by the integrated quantities. More validation is needed to determine what role DES can play as part of an overall icing effects prediction strategy.

Mogili, P.↗

Computational Support of 9x7 Wind Tunnel Test of Sonic Boom Models with Plumes

NASA and its industry partners are performing studies of supersonic aircraft concepts with low sonic boom pressure signatures. The interaction of the nozzle jet flow with the aircrafts' aft components is typically where the greatest uncertainly in the pressure signature is observed with high-fidelity numerical simulations. An extensive wind tunnel test was conducted in February 2016 in the NASA Ames 9- by 7- Foot Supersonic Wind Tunnel to help address the nozzle jet effects on sonic boom. Five test models with a variety of shock generators of differing waveforms and strengths were tested with a convergent-divergent nozzle for a wide range of nozzle pressure ratios. The LAVA unstructured flow solver was used to generate first CFD comparisons with the new experimental database using best practice meshing and analysis techniques for sonic boom vehicle design for all five different configurations. LAVA was also used to redesign the internal flow path of the nozzle and to better understand the flow field in the test section, both of which significantly improved the quality of the test data.

9x7 Wind Tunnel↗

Large-Eddy / Reynolds-Averaged Navier-Stokes Simulations of a Dual-Mode Scramjet Combustor

Numerical simulations of reacting and non-reacting flows within a scramjet combustor configuration experimentally mapped at the University of Virginia s Scramjet Combustion Facility (operating with Configuration A ) are described in this paper. Reynolds-Averaged Navier-Stokes (RANS) and hybrid Large Eddy Simulation / Reynolds-Averaged Navier-Stokes (LES / RANS) methods are utilized, with the intent of comparing essentially blind predictions with results from non-intrusive flow-field measurement methods including coherent anti-Stokes Raman spectroscopy (CARS), hydroxyl radical planar laser-induced fluorescence (OH-PLIF), stereoscopic particle image velocimetry (SPIV), wavelength modulation spectroscopy (WMS), and focusing Schlieren. NC State's REACTMB solver was used both for RANS and LES / RANS, along with a 9-species, 19- reaction H2-air kinetics mechanism by Jachimowski. Inviscid fluxes were evaluated using Edwards LDFSS flux-splitting scheme, and the Menter BSL turbulence model was utilized in both full-domain RANS simulations and as the unsteady RANS portion of the LES / RANS closure. Simulations were executed and compared with experiment at two equivalence ratios, PHI = 0.17 and PHI = 0.34. Results show that the PHI = 0.17 flame is hotter near the injector while the PHI = 0.34 flame is displaced further downstream in the combustor, though it is still anchored to the injector. Reactant mixing was predicted to be much better at the lower equivalence ratio. The LES / RANS model appears to predict lower overall heat release compared to RANS (at least for PHI = 0.17), and its capability to capture the direct effects of larger turbulent eddies leads to much better predictions of reactant mixing and combustion in the flame stabilization region downstream of the fuel injector. Numerical results from the LES/RANS model also show very good agreement with OH-PLIF and SPIV measurements. An un-damped long-wave oscillation of the pre-combustion shock train, which caused convergence problems in some RANS simulations, was also captured in LES / RANS simulations, which were able to accommodate its effects accurately.

Fulton, Jesse A.↗

PyTrilinos: Recent Advances in the Python Interface to Trilinos

PyTrilinos is a set of Python interfaces to compiled Trilinos packages. This collection supports serial and parallel dense linear algebra, serial and parallel sparse linear algebra, direct and iterative linear solution techniques, algebraic and multilevel preconditioners, nonlinear solvers and continuation algorithms, eigensolvers and partitioning algorithms. Also included are a variety of related utility functions and classes, including distributed I/O, coloring algorithms and matrix generation. PyTrilinos vector objects are compatible with the popular NumPy Python package. As a Python front end to compiled libraries, PyTrilinos takes advantage of the flexibility and ease of use of Python, and the efficiency of the underlying C++, C and Fortran numerical kernels. This paper covers recent, previously unpublished advances in the PyTrilinos package.

Spotz, William F.↗

PETSc Users Manual (Rev. 3.13)

This manual describes the use of PETSc for the numerical solution of partial differential equations and related problems on high-performance computers. The Portable, Extensible Toolkit for Scientific Computation (PETSc) is a suite of data structures and routines that provide the building blocks for the implementation of large-scale application codes on parallel (and serial) computers. PETSc uses the MPI standard for all message-passing communication. PETSc includes an expanding suite of parallel linear solvers, nonlinear solvers, and time integrators that may be used in application codes written in Fortran, C, C++, and Python. PETSc provides many of the mechanisms needed within parallel application codes, such as parallel matrix and vector assembly routines. The library is organized hierarchically, enabling users to employ the level of abstraction that is most appropriate for a particular problem. By using techniques of object-oriented programming, PETSc provides enormous flexibility for users. PETSc is a sophisticated set of software tools; as such, for some users it initially has a much steeper learning curve than a simple subroutine library. In particular, for individuals without some computer science background, experience programming in C, C++, python, or Fortran and experience using a debugger such as gdb or dbx, it may require a significant amount of time to take full advantage of the features that enable efficient software use. However, the power of the PETSc design and the algorithms it incorporates may make the efficient implementation of many application codes simpler than \rolling them" yourself.

97 MATHEMATICS AND COMPUTING↗

Development of Reduced-Order Models for Aeroelastic and Flutter Prediction Using the CFL3Dv6.0 Code

A reduced-order model (ROM) is developed for aeroelastic analysis using the CFL3D version 6.0 computational fluid dynamics (CFD) code, recently developed at the NASA Langley Research Center. This latest version of the flow solver includes a deforming mesh capability, a modal structural definition for nonlinear aeroelastic analyses, and a parallelization capability that provides a significant increase in computational efficiency. Flutter results for the AGARD 445.6 Wing computed using CFL3D v6.0 are presented, including discussion of associated computational costs. Modal impulse responses of the unsteady aerodynamic system are then computed using the CFL3Dv6 code and transformed into state-space form. Important numerical issues associated with the computation of the impulse responses are presented. The unsteady aerodynamic state-space ROM is then combined with a state-space model of the structure to create an aeroelastic simulation using the MATLAB/SIMULINK environment. The MATLAB/SIMULINK ROM is used to rapidly compute aeroelastic transients including flutter. The ROM shows excellent agreement with the aeroelastic analyses computed using the CFL3Dv6.0 code directly.

Silva, Walter A.↗

Gas-Particle Interaction Model Development in Plume Surface Interaction Erosion and Cratering

As part of the Game Changing Development (GCD) Program, funded by NASA’s Space Technology Mission Directorate (STMD), the development of simulation capability for the prediction of extra-terrestrial Plume Surface Interaction (PSI) environments has been undertaken by the Fluid Dynamics Branch at NASA/MSFC. The GCD PSI Project, planned to be completed over a four year period, contains a Predictive Simulation Capability (PSC) Element focused on creating simulation capability for the reliable and accurate prediction of PSI in Martian (~650 Pa) and Lunar (vacuum) ambient environments. In addition to the PSC Element, the GCD Program also contains a companion Ground Testing Element for development of focused datasets for validation of predictive capability as well as a Flight-focused Instrumentation Element. This paper describes the activities and accomplishments of the past year in the gas-particle interaction modeling portion of the GCD PSI project. The objectives of this task are to investigate and construct models of particle drag and gas-particle cloud interactions leading to what is known as particle turbulent kinetic energy (PTKE). While drag on a lone particle suspended in a flow gas of gas is well-known, the drag and drag-induced dynamics of a cloud of particles in a gas flow are not. The PSC element of the PSI project requires models of gas-particle cloud interactions to implement in the Gas Granular Flow Solver (GGFS) in order to arrive at a predictive simulation capability for PSI-induced soil erosion, cratering and ejecta transport. Experiments of dilute mixtures of soil particles in supersonic gas flow are being conducted at Johns Hopkins University in order to provide a dataset describing gas-particle cloud interactions. Augmented by a separate funding source are efforts to perform small-scale particle-resolved direct numerical simulations (PR-DNS) and larger scale Eulerian-Lagrangian simulations. Together, these experiments and simulations are being used to devise models of particle cloud drag and particle cloud drag-induced dynamics. The final product of these efforts will be particle drag models suitable for implementation into the GGFS application and a PTKE model suitable for the same purpose.

Jeff West↗

PCLAM: a Python Module for Computing Surface Lineloads and Moments

Lineloads serve a unique and important role in aerodynamic database development as well as configuration design and analysis. A new software suite was constructed which can compute lineloads rapidly enough that the calculations can run in tandem with high-fidelity fluid flow solvers. This enables the calculation of iteration- or time-dependent lineloads, which have thus far been too computationally costly to create for complicated systems like launch vehicles. The suite is organized into a standalone Python module named PCLAM (PCLAM Computes Lineloads And Moments) which can be imported into other software with minimal restructuring by the user or developer. The computed lineloads are integrated with a $C^0$ numerical quality and exhibit the expected sensitivity to underlying grid resolution. Even at low grid and lineload resolutions, the computed lineloads were found to be in strong agreement with several analytical test cases.

sectional loads↗

Fast Multilevel Solvers for a Class of Discrete Fourth Order Parabolic Problems

In this paper, we study fast iterative solvers for the solution of fourth order parabolic equations discretized by mixed finite element methods. We propose to use consistent mass matrix in the discretization and use lumped mass matrix to construct efficient preconditioners. We provide eigenvalue analysis for the preconditioned system and estimate the convergence rate of the preconditioned GMRes method. Furthermore, we show that these preconditioners only need to be solved inexactly by optimal multigrid algorithms. Our numerical examples indicate that the proposed preconditioners are very efficient and robust with respect to both discretization parameters and diffusion coefficients. We also investigate the performance of multigrid algorithms with either collective smoothers or distributive smoothers when solving the preconditioner systems.

97 MATHEMATICS AND COMPUTING↗