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The effect of turbulence models in the off-body grids on the accuracy of solutions for rotor flows in hover has been investigated. Results from the Reynolds-Averaged Navier-Stokes and Laminar Off-Body models are compared. Advection of turbulent eddy viscosity has been studied to find the mechanism leading to inaccurate solutions. A coaxial rotor result is also included.
Models of gas and particle motion in turbulent, particle-laden, round jets were evaluated using existing measurements of flow structure. Three models were considered: (1) a locally homogeneous flow model, where velocities and turbulent mixing properties of both phases were assumed to be equal; (2) a deterministic separated flow model, where interphase slip was considered but effects of turbulent dispersion were ignored; and (3) a stochastic separated flow model where effects of interphase slip and turbulent dispersion were considered using random sampling techniques. In all three cases, mean and turbulent properties of the continuous phase were found with a well-calibrated k-epsilon model. The locally homogeneous flow and deterministic separated flow models over- and underestimated particle spread and flow development rates, respectively. The stochastic separated flow model, however, yielded satisfactory predictions of flow structure - except at high particle loadings. Uncertainties in initial conditions for the measurements and possible effects of turbulence modulation by the particles are proposed as the reason for these errors.
Understanding the flow and reactivity of CO 2 injected into geological reservoirs is important for many subsurface applications including secure geologic carbon storage (GCS), critical mineral extraction, enhanced geothermal systems (EGS), and enhanced oil recovery (EOR). Traditionally, subsurface CO 2 injection for GCS applications has focused on geologic formations with favorable subsurface configurations for CO 2 migration and trapping through non-reactive mechanisms such as structural, solubility, and petrophysical trapping. Recently, CO 2 -reactive rocks such as mafic and ultramafic basalts have been investigated for their potential to react with injected CO 2 in situ to simultaneously dissolve host rock minerals and mineralize CO 2 as carbonates. Engineering rapid CO 2 mineralization in the subsurface is attractive because of the increased density of stored CO 2 , the additional safety factors associated with solidification, and the potential to extract valuable critical minerals. Here we present recent developments in the parallel flow and reactive transport simulator PFLOTRAN to model coupled CO 2 -brine flow and reactive transport for a wide range of injection and production applications involving reactive CO 2 -brine systems. These developments are based on the well established and trusted CO 2 flow capabilities in the STOMP-CO 2 simulator. New capabilities added to PFLOTRAN include new CO 2 -brine equations of state with optional thermal coupling, several new constitutive relationships like capillary pressure smoothing and scanning path hysteresis, a fully implicit well model, and native linkage with PFLOTRAN's well-established reactive transport libraries. A series of benchmarks between PFLOTRAN and STOMP-CO 2 verify the newly developed CO 2 -brine flow capabilities. Demonstrations of coupled CO 2 -brine flow modeling and reactive transport show how CO 2 mineralization can be engineered in reactive host rocks. Finally, an example use case involving copper leaching by CO 2 and critical mineral extraction is presented to showcase the strengths of this new implementation. Several limitations still remain, including limited availability of field data to parameterize models. Future work should constrain the evolution of mineral surface area during mineralization and the temperature and/or pH dependence of geochemical reactions for specific systems of interest.
A series of reactive-transport models of Enhanced Geothermal Systems (EGS) were constructed using the reactive transport code PFLOTRAN to examine the effect of matrix thermal contraction and mineral dissolution/precipitation on fracture flow in the context of grid cell size and model complexity. It was found that for thermal drawdown at production well, the impact of fracture zone grid cell size is negligible.
The biotechnology group at NASA Johnson Space Center is developing systems for culturing mammalian cells that stimulate some aspect of microgravity and provide a low shear environment for microgravity-based studies on suspension and anchorage dependent cells. The design of these vessels for culturing cells is based on the need to suspend cells and aggregates of cells and microcarrier beads continually in the culturing medium. The design must also provide sufficient circulation for adequate mass transfer of nutrients to the cells and minimize the total force on the cells. Forces, resulting from sources such as hydrodynamic fluid shear and collisions of cells and walls of the vessels, may damage delicate cells and degrade the formation of three dimensional structures. This study examines one particular design in both unit gravity and microgravity based on two concentric cylinders rotating in the same direction at different speeds to create a Couette flow between them. A numerical simulation for the flow field and the trajectories of particles in the vessel. The flow field for the circulation of the culturing medium is modeled by the Navier-Stokes equations. The forces on a particle are assumed to be drag from the fluid's circulation, buoyancy from the gravitational force and centrifugal force from the rotation of the vessel. The problem requires first solving the system of partial differential equations for the fluid flow by a finite difference method and then solving the system of ordinary differential equations for the trajectories by Gear's stiff method. Results of the study indicate that the trajectories in unit gravity and microgravity are very similar except for small spatial deviations on the fast time scale in unit gravity. The total force per unit cross sectional area on a particle in microgravity, however, is significantly smaller than the corresponding value in unit gravity, which is also smaller than anticipated. Hence, this study indicates that this design for a bioreactor with optimal rates of rotation can provide a good environment for culturing cells in microgravity with adequate circulation and minimal force on the cells.
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A controlled flow tunnel employs active control of flow through the walls of the wind tunnel so that the model is in approximately free air conditions during the test. This improves the wind tunnel test environment, enhancing the validity of the experimentally obtained test data. This concept is applied to a three dimensional jet flapped wing with full span jet flap. It is shown that a special treatment is required for the high energy wake associated with this and other V/STOL models. An iterative numerical scheme is developed to describe the working of an actual controlled flow tunnel and comparisons are shown with other available results. It is shown that control need be exerted over only part of the tunnel walls to closely approximate free air flow conditions. It is concluded that such a tunnel is able to produce a nearly interference free test environment even with a high lift model in the tunnel.
Hot gas turbulent flow distribution around the main injector assembly of the Space Shuttle Main Engine (SSME) and LOX flow distribution through the LOX posts have a great effect on the combustion phenomena inside the main combustion chamber. In order to design a CFD model to be an effective engineering analysis tool with good computational turn-around time (especially for 3-D flow problems) and still maintain good accuracy in describing the flow features, the concept of porosity was employed to describe the effects of blockage and drag force due to the presence of the LOX posts in the turbulent flow field around the main injector assembly of the SSME. Two-dimensional numerical studies were conducted to identify the drag coefficients of the flows, both through tube banks and round the shielded posts, over a wide range of Reynolds numbers. Empirical, analytical expressions of the drag coefficients as a function of local flow Reynolds number were then deduced. The porosity model was applied to the turbulent flow around the main injector assembly of the SSME, and analyses were performed. The 3-D CFD analysis was divided into three parts: LOX dome, hot gas injector assembly, and hydrogen cavity. The numerical results indicate that the mixture ratio at the downstream of injector face was close to stoichiometric around baffle elements.
The topics are covered in viewgraph form and include: (1) basic equations and model terms; (2) model constraints and assumptions; (3) the present state of various closure models; and (4) future directions.
The topics are presented in viewgraph form and include: (1) Reynolds stress closure models; (2) Favre averages and governing equations; (3) the model for the deviatoric part of the pressure-strain rate correlation; (4) the SSG pressure-strain correlation model; (5) a compressible turbulent dissipation rate model; (6) variable viscosity effects; (7) near-wall stiffness problems; (8) models of the Reynolds mass and heat flux; and (9) a numerical solution of the compressible turbulent transport equation.
A nonlinear algebraic Reynolds stress model, derived using the renormalization group, is applied to equilibrium homogeneous shear flow and fully developed flow in a square duct. The model, which is quadratically nonlinear in the velocity gradients, successfully captures the large-scale inhomogeneity and anisotropy of the flows studied. The ratios of normal stresses, as well as the actual magnitudes of the stresses are correctly predicted for equilibrium homogeneous shear flow. Reynolds normal stress anisotropy and attendant turbulence driven secondary flow are predicted for a square duct. Profiles of mean velocity and normal stresses are in good agreement with measurements. Very close to walls, agreement with measurements diminishes. The model has the benefit of containing no arbitrary constants; all values are determined directly from the theory. It seems that near wall behavior is influenced by more than the large scale anisotropy accommodated in the current model. More accurate near wall calculations may well require a model for anisotropic dissipation.
The interest in underground CO 2 storage has increased significantly over the last decade because of the rising concern about global warming due to the growing levels of greenhouse gases in the atmosphere. Considering that CO 2 accounts for 80% of these greenhouse gases, carbon capture, utilization, and storage (CCUS) is regarded as one of the most direct approaches to achieving the net zero carbon target. Although CO 2 storage in deep saline aquifers and depleted gas reservoirs has been studied extensively, most studies use commercial simulators that model faults/fractures by simply modifying the transmissibility in the direction perpendicular to the fault surfaces. Here, this work shows that this simplistic approach ignores the accelerated flow in the directions parallel to the fault plane, leading to significantly higher leakage along the fault surface. To accurately model the flow of CO 2 in faulted reservoirs, we present the first transient embedded discrete fracture model for corner-point grids (tEDFM-CPG). By comparing the results of the tEDFM-CPG to high-resolution reference solutions, we show that this approach is accurate and efficient at predicting CO 2 flow in faulted/fractured reservoirs. Finally, this work presents the use of mixed reality (MR) to efficiently observe CO 2 gas migration in the interior of these corner-point grid systems.
A numerical model of two-dimensional confined flows is presented. The flow in the duct is partitioned into finite streams. The difference equations are then obtained by applying conservation principles directly to the individual streams. A listing of a computer code based on this approach in FORTRAN 4 language is presented. The code computes two dimensional compressible turbulent flows in ducts when the duct area along the flow is specified and the pressure gradient is unknown.
We have modeled the cooling of lava bodies on Io after solidification of the lava, a process that has been little explored since Carr (1986). With recent estimates of lava flow thicknesses on Io ranging from 1 m to 10 m, the modeling of thermal emission from active volcanism must take into account the cooling behaviour after the solidification of the lava, which we model using a finite-element model. Once a lava body is fully solidified, the surface temperature decreases faster, as heat loss is no longer buffered by release of latent heat. This is significant as observed surface temperature is often the only clue available to determine lava surface age. We also find that cooling from the base of the lava is an important process that accelerates the solidification of a flow and therefore subsequent cooling. It is necessary to constrain the cooling process in order to better understand temperature-area relationships on Io's surface and to carry out stochastic modelling of lava flow emplacement.
The Reynolds-averaged Navier–Stokes (RANS) equations remain a workhorse technology for simulating compressible fluid flows of practical interest. Due to model-form errors, however, RANS models can yield erroneous predictions that preclude their use on mission-critical problems. This report summarizes work performed from FY22-FY24 focused on improving RANS models for hypersonic flows using data-driven modeling and scientific machine learning. In this work we: 1. Investigate the current capabilities of RANS models in Sandia’s parallel aerodynamics and re-entry code (SPARC) for hypersonic flows with a focus on shock boundary layer interactions (SBLIs), 2. Assess several established corrections that exist in the literature aimed at improving predictions for SBLIs, 3. Develop improved models for the Reynolds stress tensor using tensor-basis neural networks, 4. Develop a neural-network-based variable turbulent Prandtl number model to reduce errors in wall heating in SBLIs. 5. Begin future investigations including employing the LIFE framework to improve wall heating predictions in SBLIs as well as the ensemble Kalman filter. We find that current RANS models in SPARC are deficient for complex SBLI flows. In particular, no current model jointly predicts wall heat flux, wall shear stress, and wall pressure with reasonable accuracy. Existing corrections help, but do not alleviate this issue altogether. The development of improved models for the Reynolds stress tensor via tensor-basis neural networks results in more predictive RANS models across a suite of low-speed and high-speed cases. For hypersonic boundary layers, the inclusion of the wall-normal Reynolds stress via TBNNs has an appreciable impact on the wall-normal momentum balance and wall quantities. However, we find that improvements to the Reynolds stress tensor do not address the over-prediction in wall heat flux in SBLIs. We find that a neural-network-based variable turbulent Prandtl number model systematically and substantially improves wall heating predictions for a range of SBLI cases.
In this paper, we explore the potential of generative machine learning models as an alternative to the computationally expensive Monte Carlo (MC) simulations commonly used by the Large Hadron Collider (LHC) experiments. Our objective is to develop a generative model capable of efficiently simulating detector responses for specific particle observables, focusing on the correlations between detector responses of different particles in the same event and accommodating asymmetric detector responses. Here, we present a conditional normalizing flow model ($\mathcal{CNF}$) based on a chain of Masked Autoregressive Flows, which effectively incorporates conditional variables and models high-dimensional density distributions. We assess the performance of the $\mathcal{CNF}$ model using a simulated sample of Higgs boson decaying to diphoton events at the LHC. We create reconstruction-level observables using a smearing technique. We show that conditional normalizing flows can accurately model complex detector responses and their correlation. This method can potentially reduce the computational burden associated with generating large numbers of simulated events while ensuring that the generated events meet the requirements for data analyses. We make our code available at https://github.com/allixu/normalizing_flow_for_detector_response
The structure of fuel sprays in a combustion chamber is theoretically investigated using computer models of current interest. Three representative spray models are considered: (1) a locally homogeneous flow (LHF) model, which assumes infinitely fast interphase transport rates; (2) a deterministic separated flow (DSF) model, which considers finite rates of interphase transport but ignores effects of droplet/turbulence interactions; and (3) a stochastic separated flow (SSF) model, which considers droplet/turbulence interactions using random sampling for turbulence properties in conjunction with random-walk computations for droplet motion and transport. Two flow conditions are studied to investigate the influence of swirl on droplet life histories and the effects of droplet/turbulence interactions on flow properties. Comparison of computed results with the experimental data show that general features of the flow structure can be predicted with reasonable accuracy using the two separated flow models. In contrast, the LHF model overpredicts the rate of development of the flow. While the SSF model provides better agreement with measurements than the DSF model, definitive evaluation of the significance of droplet/turbulence interaction is not achieved due to uncertainties in the spray initial conditions.
The structure of fuel sprays in a combustion chamber is theoretically investigated using computer models of current interest. Three representative spray models are considered: (1) a locally homogeneous flow (LHF) model, which assumes infinitely fast interphase transport rates; (2) a deterministic separated flow (DSF) model, which considers finite rates of interphase transport but ignores effects of droplet/turbulence interactions; and (3) a stochastic separated flow (SSF) model, which considers droplet/turbulence interactions using random sampling for turbulence properties in conjunction with random-walk computations for droplet motion and transport. Two flow conditions are studied to investigate the influence of swirl on droplet life histories and the effects of droplet/turbulence interactions on flow properties. Comparison of computed results with the experimental data show that general features of the flow structure can be predicted with reasonable accuracy using the two separated flow models. In contrast, the LHF model overpredicts the rate of development of the flow. While the SSF model provides better agreement with measurements than the DSF model, definitive evaluation of the significance of droplet/turbulence interaction is not achieved due to uncertainties in the spray initial conditions.