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At least 19 records

Applying uncertainty quantification to multiphase flow computational fluid dynamics

Multiphase computational fluid dynamics plays a major role in design and optimization of fossil fuel based reactors. There is a growing interest in accounting for the influence of uncertainties associated with physical systems to increase the reliability of computational simulation based engineering analysis. The U.S. Department of Energy's National Energy Technology Laboratory (NETL) has recently undertaken an initiative to characterize uncertainties associated with computer simulation of reacting multiphase flows encountered in energy producing systems such as a coal gasifier. The current work presents the preliminary results in applying non-intrusive parametric uncertainty quantification and propagation techniques with NETL's open-source multiphase computational fluid dynamics software MFIX. For this purpose an open-source uncertainty quantification toolkit, PSUADE developed at the Lawrence Livermore National Laboratory (LLNL) has been interfaced with MFIX software. In this study, the sources of uncertainty associated with numerical approximation and model form have been neglected, and only the model input parametric uncertainty with forward propagation has been investigated by constructing a surrogate model based on data-fitted response surface for a multiphase flow demonstration problem. Monte Carlo simulation was employed for forward propagation of the aleatory type input uncertainties. Several insights gained based on the outcome of these simulations are presented such as how inadequate characterization of uncertainties can affect the reliability of the prediction results. Also a global sensitivity study using Sobol' indices was performed to better understand the contribution of input parameters to the variability observed in response variable.

42 ENGINEERING↗

A reacting multiphase computational flow model for 2,3-butanediol synthesis in industrial-scale bioreactors

The microbe, Zymomonas mobilis, can efficiently convert sugars to 2,3 butanediol (BDO), an important intermediate for downstream chemical products, only in a well-controlled microaerated environment. However, controlling oxygen distribution in industrial-scale bioreactors is challenging, and at-scale BDO production is hard to optimize using traditional engineering methods. This study takes a step towards addressing this problem through a computational model for reacting multiphase flows in large-scale bioreactors. A phenomenological metabolic model was first developed and validated against experiments, and then it was coupled to a multiphase computational fluid dynamics (CFD) solver using a subcycling algorithm for simulating long conversion times (~30 hours). Large-scale (~500 m 3 ) bubble column simulations using this coupled approach demonstrated a 25% improvement in BDO yield with low sparging rates (0.002 m/s) and low height-to-diameter ratio (0.875) compared to a baseline bubble column (35 m height, 5 m diameter) with a superficial gas velocity of 0.06 m/s.

09 BIOMASS FUELS↗

Optimization of a Cyclone Using Multiphase Flow Computational Fluid Dynamics

The U.S. Department of Energy National Energy Technology Laboratory's (NETL) 50 kW th chemical looping reactor (CLR) has an underperforming cyclone, which was designed using empirical correlations. To improve the performance of this cyclone using computational fluid dynamics (CFD)-based modeling simulations, four critical design parameters including the vortex tube radius and length, barrel radius, and the inlet width and height were optimized. Here, NETL's open source multiphase flow with interphase exchange (MFiX) CFD code has been used to model a series of cyclones by systematically varying the geometric design parameters. To perform the optimization process, the surrogate modeling and sensitivity analysis followed by the optimization capability in nodeworks was used. The basic methodology for the process is to employ a statistical design of experiments (DOE) method to generate sampling simulations that fill the design space. Corresponding CFD models are then created, executed, and postprocessed. A response surface is created to characterize the relationship between input parameters and the quantities of interest (QoI). Finally, the CFD-surrogate is used by an optimization method to find the optimal design condition based on the objective and constraints prescribed. The resulting optimal cyclone has a larger diameter and longer vortex tube, a larger diameter barrel, and a taller and narrower solids inlet. The improved design has a predicted pressure drop 11 times lower than the original design while reducing the mass loss by a factor of 2.3.

42 ENGINEERING↗

Optimization of a cyclone using MFIX and Nodeworks

Video depicting the optimization process of a cyclone on NETL's chemical looping reactor (CLR) using MFIX and Nodeworks. MFIX is used to model the cyclone using PIC. Nodeworks is then used to generate proposed geometry changes using a Latin hypercube. Each design is simulated, with an objective value being computed based on the cyclone efficiency and pressure drop. A Gaussian Process surrogate model is then constructed from the objective values. This surrogate model is then used by a differential evolution optimization algorithm to identify the optimal cyclone design. Details published here: Weber, J., Fullmer, W., Gel, A., and Musser, J. (February 4, 2020). "Optimization of a Cyclone Using Multiphase Flow Computational Fluid Dynamics." ASME. J. Fluids Eng. March 2020; 142(3): 031111. https://doi.org/10.1115/1.4045952 OSTI: https://www.osti.gov/pages/servlets/purl/1763893

cyclone↗

Compressible, multiphase semi-implicit method with moment of fluid interface representation

A unified method for simulating multiphase flows using an exactly mass, momentum, and energy conserving Cell-Integrated Semi-Lagrangian advection algorithm is presented. The deforming material boundaries are represented using the moment-of-fluid method. Our new algorithm uses a semi-implicit pressure update scheme that asymptotically preserves the standard incompressible pressure projection method in the limit of infinite sound speed. The asymptotically preserving attribute makes the new method applicable to compressible and incompressible flows including stiff materials; enabling large time steps characteristic of incompressible flow algorithms rather than the small time steps required by explicit methods. Moreover, shocks are captured and material discontinuities are tracked, without the aid of any approximate or exact Riemann solvers. As a result, wimulations of underwater explosions and fluid jetting in one, two, and three dimensions are presented which illustrate the effectiveness of the new algorithm at efficiently computing multiphase flows containing shock waves and material discontinuities with large “impedance mismatch.”

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Abstract - Cooperative Research and Development Agreement between Sotacarbo and National Energy Technology Laboratory

The objective of this CRADA between NETL and Sotacarbo is to develop mutual collaboration in the areas of: CFD Modeling for optimization of coal/biomass gasification processes, CO 2 Separation by Membranes, CO 2 -to-Liquids, & CO 2 Sequestration. The CFD modeling and optimization of coal/biomass gasification processes project will bring together NETL’s expertise in the area of computational multiphase flows with Sotacarbo’s expertise in the area of design and operation of coal and biomass gasifiers. The outcome of this collaboration should be validated coal/biomass CFD models, which can assist in design and scale-up studies of gasifiers. There are several gasification units at Sotacarbo’s Research Center which can be used for gasification model development and validation using NETL’s MFiX Suite of multiphase flow CFD software. The other remaining technical topic outcomes will be determined at a later time as a result of further discussions.

01 COAL, LIGNITE, AND PEAT↗

Geomechanical Analysis of Initial Stage of Gas Production from Interbredded Hydrate-bearing Sediment

Geomechanical stability of marine hydrate reservoirs during gas production by depressurization is the focus of this study. The reservoir considered here consists of thin hydrate rich sandy layers interbedded with mud layers. Because of the input parameter uncertainties involved, it is prudent from a geomechanical perspective to estimate the likely bounds of potential responses. A decoupled approach is presented herein for which the pressure and hydrate saturation in the sediments during gas production are obtained from multiphase flow computation, but could also be synthesized from various scenarios. This procedure is illustrated with sample problems.

Lin, Jeen-Shang↗

Compact high-resolution gamma-ray computed tomography system for multiphase flow studies

In this paper, a compact high-resolution gamma-ray Computed Tomography (CompaCT) measurement system for multiphase flow studies and tomographic imaging of technical objects is presented. Its compact and robust design makes it particularly suitable for studies on industrial facilities and outdoor applications. Special care has been given to thermal ruggedness, shock resistance, and radiation protection. Main components of the system are a collimated {sup 137}Cs isotopic source, a thermally stabilised modular high-resolution gamma-ray detector arc with 112 scintillation detector elements, and a transportable rotary unit. The CompaCT allows full CT scans of objects with a diameter of up to 130 mm and can be operated with any tilting angle from 0 Degree-Sign (horizontal) to 90 Degree-Sign (vertical).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

AOI 1 — Computational Energy Sciences: Multiphase Flow Research: High-fidelity multi-phase radiation module for modern coal combustion systems (Final Scientific/Technical Report)

The effects of radiation in particle-laden flows were the object of the present research. The presence of particles increases optical thickness substantially, making the use of the “optically thin” approximation in most cases a very poor assumption. However, since radiation fluxes peak at intermediate optical thicknesses, overall radiative effects may not necessarily be stronger than in gas combustion. Also, the spectral behavior of particle radiation properties is much more benign, making spectral models simpler (and making the assumption of a gray radiator halfway acceptable, at least for fluidized beds when gas radiation is not large). On the other hand, particles scatter radiation, making the radiative transfer equation (RTE) much more di fficult to solve. The research carried out in this project encompassed three general areas: (i) assessment of relevant radiation properties of particle clouds encountered in fluidized bed and pulverized coal combustors, (ii) development of proper spectral models for gas–particulate mixtures for various types of two-phase combustion flows, and (iii) development of a Radiative Transfer Equation (RTE) solution module for such applications. The resulting models were validated against artificial cases since open literature experimental data were not available. The final models are in modular form tailored toward maximum portability, and were incorporated into two research codes: (i) the open-source CFD code OpenFOAM, which we have extensively used in our previous work, and (ii) the open-source multi-phase flow code MFIX, which is maintained by NETL.

42 ENGINEERING↗

A computer code for multiphase all-speed transient flows in complex geometries. MAST version 1.0

The operation of the MAST code, which computes transient solutions to the multiphase flow equations applicable to all-speed flows, is described. Two-phase flows are formulated based on the Eulerian-Lagrange scheme in which the continuous phase is described by the Navier-Stokes equation (or Reynolds equations for turbulent flows). Dispersed phase is formulated by a Lagrangian tracking scheme. The numerical solution algorithms utilized for fluid flows is a newly developed pressure-implicit algorithm based on the operator-splitting technique in generalized nonorthogonal coordinates. This operator split allows separate operation on each of the variable fields to handle pressure-velocity coupling. The obtained pressure correction equation has the hyperbolic nature and is effective for Mach numbers ranging from the incompressible limit to supersonic flow regimes. The present code adopts a nonstaggered grid arrangement; thus, the velocity components and other dependent variables are collocated at the same grid. A sequence of benchmark-quality problems, including incompressible, subsonic, transonic, supersonic, gas-droplet two-phase flows, as well as spray-combustion problems, were performed to demonstrate the robustness and accuracy of the present code.

Chen, C. P.↗

Modeling Multiscale-Multiphase-Multicomponent Subsurface Reactive Flows Using Advanced Computing

The DOE SciDAC program funded a team that developed PFLOTRAN, the next-generation (peta-scale) massively parallel, multiphase, multicomponent reactive flow and transport code. These codes are required to improve understanding and risk management of subsurface contaminant migration and geological sequestration of carbon dioxide. The important fate and transport processes occurring in the subsurface span a wide range of spatial and temporal scales, and involve nonlinear interactions among many different chemical constituents. Due to the complexity of this problem, modeling subsurface processes normally requires simplifying assumptions. However, tools of advanced scientific computing that have been used in other areas such as energy and materials research can also help address challenging problems in the environmental and geoscience fields. The overall project was led by Los Alamos National Laboratory and included Argonne, Oak Ridge and Pacific Northwest National Laboratories, in addition to the University of Illinois. This report summarizes the results of the research done at the University of Illinois, which focused on improvements to the underlying physical and computational modeling of certain transport and mixing processes.

58 GEOSCIENCES↗

Solving multiphysics-based inverse problems with learned surrogates and constraints

Abstract Solving multiphysics-based inverse problems for geological carbon storage monitoring can be challenging when multimodal time-lapse data are expensive to collect and costly to simulate numerically. We overcome these challenges by combining computationally cheap learned surrogates with learned constraints. Not only does this combination lead to vastly improved inversions for the important fluid-flow property, permeability, it also provides a natural platform for inverting multimodal data including well measurements and active-source time-lapse seismic data. By adding a learned constraint, we arrive at a computationally feasible inversion approach that remains accurate. This is accomplished by including a trained deep neural network, known as a normalizing flow, which forces the model iterates to remain in-distribution, thereby safeguarding the accuracy of trained Fourier neural operators that act as surrogates for the computationally expensive multiphase flow simulations involving partial differential equation solves. By means of carefully selected experiments, centered around the problem of geological carbon storage, we demonstrate the efficacy of the proposed constrained optimization method on two different data modalities, namely time-lapse well and time-lapse seismic data. While permeability inversions from both these two modalities have their pluses and minuses, their joint inversion benefits from either, yielding valuable superior permeability inversions and CO 2 plume predictions near, and far away, from the monitoring wells.

Yin, Ziyi (ORCID:0000000250248771)↗

Voronoi Meshing to Accurately Capture Geological Structure in Subsurface Simulations

Mesh generation lies at the interface of geological modeling and reservoir simulation. Highly skewed or very small grid cells may be necessary to accurately capture the geometry of geological features, but the resulting poorly scaled or small grid cells can have a substantial negative impact on simulator accuracy and speed. One way to minimize numerical errors caused by gridding complex structures is to simulate on high-quality Voronoi meshes, which reduce grid orientation effects in fluid flow. This work presents a complete methodology to create Voronoi simulation grids, model fluid flow in complex geological systems, and visualize the results. A recently developed Voronoi meshing method that can automatically generate provably good unstructured meshes that conform to input surfaces creating closed volumes is used. Initially an analytical benchmark simulation is presented to validate the quality of the meshes and simulation results and demonstrate the superiority of simulation results using Voronoi meshes over flexed-hexahedral meshes on a domain with internal features. Next, meshes are created for test structures representing four of the most common geological features in the subsurface: layering, pinch-out, an interior lens that tapers to zero thickness on all sides and a fault with offset. Two benchmark flow simulations are run for each test structure. Finally, a realistic geological example for CO 2 injection into an anticline is simulated. Three realizations of the Voronoi mesh at the same resolution are generated for the simulations. Each mesh is highly refined near the injection wells and coarse in areas of less interest. These three meshes are used to model the CO 2 plume in the subsurface as it migrates to the top of the structure and then fills downward. Simulations on the meshes with randomly generated elements inside the input volumes each give slightly different fingering patterns for the viscous-unstable buoyant gas flow. The results presented in this work show a promising step towards utilizing fully automated Voronoi meshing for subsurface flow simulations in complex geology.

58 GEOSCIENCES↗