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At least 37 records · Page 2

A physical-based gas–surface interaction model for rarefied gas flow simulation

Empirical gas–surface interaction models, such as the Maxwell model and the Cercignani–Lampis model, are widely used as the boundary condition in rarefied gas flow simulations. The accuracy of these models in the prediction of macroscopic behavior of rarefied gas flows is less satisfactory in some cases especially the highly non-equilibrium ones. Molecular dynamics simulation can accurately resolve the gas–surface interaction process at atomic scale, and hence can predict accurate macroscopic behavior. They are however too computationally expensive to be applied in real problems. In this work, a statistical physical-based gas–surface interaction model, which complies with the basic relations of boundary condition, is developed based on the framework of the washboard model. In virtue of its physical basis, this new model is capable of capturing some important relations/trends for which the classic empirical models fail to model correctly. As such, the new model is much more accurate than the classic models, and in the meantime is more efficient than MD simulations. Therefore, it can serve as a more accurate and efficient boundary condition for rarefied gas flow simulations. - Highlights: • The new physical-based gas–surface interaction model satisfies the basic relations of boundary condition so that it can be used in rarefied gas flow simulations. • The new physical model possesses several advantages comparing to the empirical gas–surface interaction models, hence it's a more accurate boundary condition for rarefied gas flow study. • The new physical model is a statistical model which can be efficiently implemented by Monte Carlo method. It's much more efficient comparing to the MD simulation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A comparative study of discrete fracture network and equivalent continuum models for simulating flow and transport in the far field of a hypothetical nuclear waste repository in crystalline host rock

One of the major challenges of simulating flow and transport in the far field of a geologic repository in crystalline host rock is related to reproducing the properties of the fracture network over the large volume of rock with sparse fracture characterization data. Various approaches have been developed to simulate flow and transport through the fractured rock. The approaches can be broadly divided into Discrete Fracture Network (DFN) and Equivalent Continuum Model (ECM). The DFN explicitly represents individual fractures, while the ECM uses fracture properties to determine equivalent continuum parameters. In this paper, we compare DFN and ECM in terms of upscaled observed transport properties through generic fracture networks. The major effort was directed on making the DFN and ECM approaches similar in their conceptual representations. This allows for separating differences related to the interpretation of the test conditions and parameters from the differences between the DFN and ECM approaches. The two models are compared using a benchmark test problem that is constructed to represent the far field (1 × 1 × 1 km 3 ) of a hypothetical repository in fractured crystalline rock. The test problem setting uses generic fracture properties that can be expected in crystalline rocks. The models are compared in terms of the: 1) effective permeability of the domain, and 2) nonreactive solute breakthrough curves through the domain. The principal differences between the models are mesh size, network connectivity, matrix diffusion and anisotropy. We demonstrate how these differences affect the flow and transport. Finally, we identify the factors that should be taken in consideration when selecting an approach most suitable for the site-specific conditions.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

PeleLMeX: an AMR Low Mach Number Reactive Flow Simulation Code without level sub-cycling

PeleLMeX simulates chemically reacting low Mach number flows with block-structured adaptive mesh refinement (AMR). The code is built upon the AMReX library, which provides the underlying data structures and tools to manage and operate on them across massively parallel computing architectures. PeleLMeX algorithmic features are inherited from its predecessor PeleLM but key improvements allow representation of more complex physical processes. Together with its compressible flow counterpart PeleC, the thermo-chemistry library PelePhysics and the multi-physics library PeleMP, it forms the Pele suite of open-source reactive flow simulation codes.

97 MATHEMATICS AND COMPUTING↗

3-D Geological Modeling for Numerical Flow Simulation Studies of Gas Hydrate Reservoirs at the Kuparuk State 7-11-12 Pad in the Prudhoe Bay Unit on the Alaska North Slope

Accurate reservoir evaluation requires reliable three-dimensional (3-D) geological models. Here, this study conducted 3-D geological modeling for numerical flow simulation of the B1 sand gas hydrate reservoir at the Kuparuk State 7-11-12 pad, Prudhoe Bay Unit, Alaska North Slope. The model integrates well logs, core, and seismic data to address spatial heterogeneity in geological structures and reservoir properties. Two modeling types were performed: structural framework modeling and petrophysical property modeling. For structural framework modeling, seismic data and well log markers were used to reproduce subsurface structures characterized by a normal fault system. A volume-based modeling algorithm and stair-stepping grid were applied. The resulting 3-D model comprised 2,640,000 grid cells across 264 layers, including seven fault grids. For petrophysical property modeling, total porosity was initially modeled using sequential Gaussian simulation with collocated cokriging. To reproduce the upward coarsening of the B1 sand, upscaled log-derived total porosity and a three-dimensional (3-D) trend depicting total porosity variation were used as primary and secondary data, respectively. Gas hydrate saturation distribution was modeled similarly, with secondary data from estimated porosity distribution and seismic-derived acoustic impedance map enhancing accuracy. Results indicate higher gas hydrate saturation in the upper part of the B1 sand and areas with higher acoustic impedance. Intrinsic permeability was modeled from the total porosity and clay-bound water volume, and effective permeability was derived from the gas hydrate saturation and intrinsic permeability distributions based on the “Tokyo model”. Effective permeability distributions were influenced by the total porosity, gas hydrate saturation, and intrinsic permeability. Within the same layer, higher gas hydrate saturation leads to decreased effective permeability. In total, 100 sets of multiple scenarios were prepared, providing input data for dynamic flow simulations to evaluate the effects of lateral heterogeneity in reservoir properties and the hydraulic characteristics of faults on production behavior for preassessment before the long-term production test.

58 GEOSCIENCES↗

Oil in Alaska North Slope Gas Hydrate Reservoir: Micro-CT and Flow Simulation Insights into Permeability

Gas hydrate-bearing sands on the Alaska North Slope (ANS) host minor volumes of crude oil whose impact on formation permeability has never been quantified relative to a gas hydrate reservoir system. Here, we combine in situ pressure-core microcomputed-tomography (μ-CT), thermogravimetric analysis (TGA), gas-chromatography–mass-spectrometry (GC–MS), scanning-electron microscopy coupled with energy-dispersive spectroscopy (SEM-EDS), and Stokes-flow simulation to (i) quantify oil saturation, (ii) infer its source, and (iii) evaluate its influence on permeability after gas-hydrate dissociation. μ-CT and SEM-EDS imaging identify the host sediment as silty, with some grain-coating clay present. Eight representative 3003-voxel subvolumes extracted from a preserved pressure core (Core 15P-3c, from the B1 sand (unit B), HYDRATE 02 Geo Data Well (GDW), 886.96–887.29 m measured depth, MD) exhibit porosities of 0.34–0.37 and an average oil saturation of 0.09 ± 0.03, in comparison to an independent TGA-based estimate of 0.16. GC-MS fingerprints obtained from an adjacent depressurized core (Core 17P-1, 891.37–891.44 m MD), together with oil pore habit revealed by μ-CT, suggest that the oil is partly native but also includes contributions from mineral oil-based drilling fluid contamination. Further analysis of oil–porewater interactions and flushing tests confirms that native oil saturation in the analyzed samples ranges from 0.04 to 0.08 with an average of approximately 0.06, and the oil is highly immobile. Flow simulations demonstrate that the native oil saturation of ≈0.06 reduces permeability by approximately 50% due to both pore blockage and increased flow-path tortuosity. These findings reveal the potential presence of native oil within the ANS gas hydrate reservoir and suggest that future simulation models may need to account for its impact on permeability to improve long-term performance predictions of gas and water production.

02 PETROLEUM↗

Flow simulation and analysis of high-power flow batteries

The cost of a flow battery system can be reduced by increasing its power density and thereby reducing its stack area. If per-pass utilizations are held constant, higher battery power densities can only be achieved using higher flow rates. Here, a 3D computational fluid dynamics model of a flow battery flow field and electrode is used to analyze the implications of increasing flow rates to high power density operating conditions. Interdigitated and serpentine designs, and cell sizes ranging from 10 cm 2 to 400 cm 2 , are simulated. The results quantify the dependence of pressure loss on cell size and design, demonstrating that the details of the passages that distribute flow between individual channels and the inlet and outlet have a major impact on pressure losses in larger cells. Additionally, in-cell flow behavior is analyzed as a function of cell size and design. Flow structures are interrogated to show how and where electrode parameters influence pressure drops, and how regions where transport is slow are correlated with the presence of experimentally observed cell degradation.

25 ENERGY STORAGE↗

Deep learning interfacial momentum closures in coarse-mesh CFD two-phase flow simulation using validation data

Multiphase flow phenomena have been widely observed in the industrial applications while it remains a challenging yet unsolved problems. Three-dimensional computational fluid dynamics (CFD) approaches resolve the flow fields on a finer special and temporal scales which can complement the dedicated experimental study. However, closures have to be introduced to reflect the underlying physics in multiphase flow. Among them, the interfacial forces, including drag, lift, turbulent dispersion and wall lubrication forces, play in important role on the bubble’s distribution and migration in liquid-vapor two-phase flow. Development of those closures traditionally rely on the experimental data and analytical derivation with simplified assumptions which usually cannot deliver a universal solution across wide range of flow conditions. In this paper, a data-driven approach, named as Feature Similarity Measurement (FSM), is developed and applied to improve the simulation capability of two-phase flow with coarse-mesh CFD approach. Interfacial momentum transfer in adiabatic bubbly flow serves as the focus of the present study. Both a mature and a simplified set of interfacial closures are taken as the low fidelity data. Experimental data and fine mesh CFD simulations results are adopted as high-fidelity data. Qualitative and quantitative analysis are performed in this paper which reveals that FSM can substantially improve the prediction of coarse mesh CFD model regardless of the choice of interfacial closures and it provides scalability and consistency across discontinuous flow regimes. Furthermore, it demonstrates that data-driven method can aid the multiphase flow modeling by exploring the connections between local physical features and simulation errors.

97 MATHEMATICS AND COMPUTING↗

Predictive Flow Simulation with the P2R Model for the Composite Analysis Base Case

In order to meet the requirements of U.S. Department of Energy (DOE) in DOE O 435.1, Radioactive Waste Management, a composite analysis (CA) must be completed for the Central Plateau at the Hanford Site. The CA requires estimates of fate and transport of radionuclides in the groundwater from multiple sources within the modeling domain. This document details the application of the Plateau-to-River (P2R) Model version 8.3 to predict the flow of groundwater on the Central Plateau for the 10,000-year simulation to support the CA. The simulated flow field will support the simulation of fate and transport of contaminants for use in predicting dose as part of the CA. This document describes the changes made to model inputs in order to simulate the predictive flow field for the CA.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

An improved consistent, conservative, non-oscillatory and high order finite difference scheme for variable density low Mach number turbulent flow simulation

A consistent, conservative and truly high order finite difference scheme for low Mach number turbulent variable density flow simulation is presented. In the present scheme, the scalar transport equation is discretized with the explicit weighted compact nonlinear scheme (WCNS) while the continuity and momentum equations are discretized with a conservative centered high order finite difference scheme on a staggered grid. Bounded hybrid high order upwind interpolation is proposed for the evaluation of density on the cell faces of the staggered grid. The use of explicit WCNS along with the bounded density interpolation resolves the issue of degraded order of accuracy in the existing high order finite difference schemes where the centered finite difference scheme for mass and momentum conservation is combined with a total variation stable scheme for scalar transport. With the same difference operator used for the continuity and scalar transport equations, the present scheme is consistent naturally, and resolves the inconsistency problem reported in Trisjono et al. (J. Comp. Phys., 327, 612-628, 2016) without employing any modification to a scheme. Such improvements are demonstrated for several test cases.

02 PETROLEUM↗

Predictive Flow Simulation with the P2R Model for the Composite Analysis Base Case

In order to meet the requirements of U.S. Department of Energy (DOE) in DOE O 435.1 Chg.1, Radioactive Waste Management, a Composite Analysis (CA) must be completed for the Central Plateau at the Hanford Site. The CA requires estimates of fate and transport of radionuclides in the groundwater from multiple sources within the modeling domain. This document details the application of the P2R Model version 8.3 to predict the flow of groundwater on the Central Plateau for the 10,000-year simulation to support the CA. The simulated flow field will support the simulation of fate and transport of contaminants for use in predicting dose as part of the CA.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Predictive Flow Simulation with the P2R Model for the Composite Analysis Base Case

In order to meet the requirements of U.S. Department of Energy (DOE) in DOE O 435.1 Chg. 1, Radioactive Waste Management, a Composite Analysis (CA) must be completed for the Central Plateau at the Hanford Site. The CA requires estimates of fate and transport of radionuclides in the groundwater from multiple sources within the modeling domain. This document details the application of the P2R Model version 8.3 to predict the flow of groundwater on the Central Plateau for the 10,000-year simulation to support the CA. The simulated flow field will support the simulation of fate and transport of contaminants for use in predicting dose as part of the CA.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Predictive Flow Simulation with the P2R Model for the 200-IA-1 Preliminary Remediation Goal Saturated Zone Abstraction

In order to develop and evaluate alternatives for remediation of waste sites constituting the 200-IA-1 Operable Unit (OU), a focused feasibility study (FFS) is currently underway. The 200-IA-1 OU FFS requires preliminary remediation goals (PRGs) protective of groundwater be evaluated which includes estimates of fate and transport of contaminants in the groundwater from multiple sources within the Central Plateau Inner Area. This document details the application of the Plateau-to-River (P2R) Model version 8.3 to predict the flow of groundwater on the Central Plateau for the 10,000-year simulation to support the 200-IA-1 OU PRG calculation. The simulated flow field will support the simulation of fate and transport of contaminants for use in estimating peak unit-length concentration as part of the 200-IA-1 OU PRG calculation presented in a separate environmental calculation file (ECF) (ECF-200IA1-20-0108, Determination of Preliminary Remediation Goals for 200-IA-1 Source Operable Unit).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Hanford Composite Analysis Special Studies FY2025 - Groundwater Flow Simulation for use in a Comparison of Simulated Concentrations in the Saturated Zone Estimated by the Plateau-to-River Model Versions 8.3 and 9.1

In order to meet the requirements of U.S. Department of Energy (DOE) in DOE O 435.1, Radioactive Waste Management, a composite analysis (CA) must be completed for the Central Plateau at the Hanford Site. The CA requires estimates of fate and transport of radionuclides in the groundwater from multiple sources within the modeling domain. This Environmental Calculation File (ECF) details the application of the Plateau-to-River (P2R) Model (CP-57037, Rev. 3, Model Package Report for the P2R Model: Version 9.1) to predict the flow of groundwater on the Central Plateau for the 10,000-year simulation to support a special analysis associated with the Hanford Site CA. The simulated flow field will support the simulation of fate and transport of contaminants for comparison to the results obtained as part of the CA to evaluate impact of the updated version of the P2R Model.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Researchers Mine Information from Next-Generation Subsurface Flow Simulations

A research team based at Virginia Tech University leveraged computing resources at the US Department of Energy's (DOE's) Oak Ridge National Laboratory to explore subsurface multiphase flow phenomena that can't be experimentally observed. Using the Cray XK7 Titan supercomputer at the Oak Ridge Leadership Computing Facility, the team took Micro-CT images of subsurface geologic systems and created two-phase flow simulations. The team's model development has implications for computational research pertaining to carbon sequestration, oil recovery, and contaminant transport.

97 MATHEMATICS AND COMPUTING↗

Micro-CT Imaging and Fluid Flow Simulations of Fractures in MSEEL Shale

micro-CT scans of a naturally fractured MSEEL shale sample as a shear fracture is generated and displaced in the center, intact region of the sample. Steady State laminar fluid flow simulations were then performed on each individual fracture during each experimental segment as effective stress and shear displacement changed. Released under LA-UR-21-24335.

Fractures,Fracturing Initiation,Marcellus Shale↗

Numerical Uncertainties vs. Model Uncertainties in Two-phase Flow Simulations

In recent years, verification, validation and uncertainty quantification (VVUQ) have become a common practice in thermal-hydraulics analysis. In general, these activities deal with propagations of uncertainties in computer code simulations, e.g., through system analysis codes. However, most existing such activities in thermal-hydraulics analysis have been primarily focused on model uncertainties, while numerical uncertainties were largely overlooked. Numerical uncertainties (or numerical errors) can appear in many different forms, e.g., round-off error, statistical sampling error, and discretization error. As pointed out by Oberkampf and Roy, discretization error is usually the largest however the most difficult type of error to estimate reliably. In thermal-hydraulics analysis, especially two-phase flow simulations commonly encountered in reactor safety analysis, the lack of consideration on discretization error is mainly due to the difficulty in estimating them. Accurate estimations on discretization error require continuous mesh refinement and/or implementation of high-order numerical schemes in system analysis code, both of which are unfortunately difficult to achieve for existing codes. At first, it should be emphasized that mesh refinement (or mesh sensitivity study) is a well-understood concept in the thermal-hydraulics field. However, it is not commonly practiced for many reasons, e.g., lack of understanding on numerical errors by code users, consideration on computational cost, deteriorated numerical stability performance with refined meshes, and etc. Secondly, high-order (e.g., second-order) numerical schemes are simply unavailable in almost any existing system analysis code. Implementation of high-order numerical schemes in these codes is difficult, if not impossible, given the complexity of these codes. On the other hand, people tend to argue that numerical uncertainties (or discretization error as we have emphasized) are not as important as the commonly large uncertainties in two-phase flow models, e.g., closure correlations. As a result, nodalization is sometimes played unintentionally, or maybe intentionally, to match experimental data, which is referred as 'user effects' or 'compensating errors' in thermal-hydraulics community. Such a practice is highly criticized by Levy. In this work, we will at first build a computer code that incorporates both first-order and second-order numerical methods to solve the two-phase flow problems. The first-order method resembles the one used in many existing system analysis codes; and the second-order method works as the reference to estimate numerical errors. Numerical verifications on spatial discretization schemes will be presented in the form of mesh convergence study. It will also be demonstrated that, in practical scenarios, discretization errors can be as large as, or even larger than, model uncertainties via case studies.

42 ENGINEERING↗

Multiphase flow simulations of a moving fluidized bed regenerator in a carbon capture unit

To accelerate the commercialization and deployment of carbon capture technologies, computational fluid dynamics (CFD)-based tools may be used to model and analyze the performance of carbon capture devices. This work presents multiphase CFD-based flow simulations for the regeneration device responsible for extracting CO 2 from CO 2 -loaded sorbent particles before the particles are recycled. The use of solid particle sorbents in this design is a departure from previously reported systems, where aqueous sorbents are employed. Another new feature is the inclusion of a series of perforated plates along the regenerator height. The influence of these plates on sorbent distribution is examined for varying sorbent holdup, fluidizing gas velocity, and particle size. The residence time distribution of sorbents is also measured to classify the low regime as plug flow or well-mixed flow. The purpose of this work is to better understand the sorbent flow characteristics before reaction kinetics of CO 2 desorption can be implemented.

01 COAL, LIGNITE, AND PEAT↗