Large Impact Features on Icy Galilean Satellites: New Modeling of Fluid Ejecta Emplacement
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Jeffrey Moore↗
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Computational Fluid Dynamics Combustion Modeling for Rotating Detonation Engines
This paper focuses on the development and validation of a combustion model for Computational Fluid Dynamics (CFD) modeling of Rotating Detonation Engines. A zero-dimensional Partially Stirred Reactor (PaSR) with a detailed chemical kinetic mechanism for hydrogen and air is used to model turbulent combustion. The model is computationally efficient and is based on the notion of partial mixing at the sub-grid level with turbulent exchange between mixed and unmixed regions. The ability of the PaSR model to accurately represent both detonative and deflagrative combustion is assessed by validating the results against experimental data. The effects of mesh resolution on the solution are also studied in order to determine if a mesh independent solution is obtainable with the Large Eddy Simulation (LES) approach to modeling turbulence. A comparison is made between the PaSR model and simply ignoring turbulence chemistry interactions which assumes that all species are perfectly mixed at the sub-grid level.
Strakey, Peter↗
Discretization of the Multi-fluid Plasma Model using IMEX and Mixed Continuous/Discontinuous FEM.
Abstract not provided.
Miller, Sean↗
Computational Fluid Dynamics Modeling of Solar Thermal Dry Reforming of Methane in a Parabolic Trough (paper).
Abstract not provided.
Ho, Clifford↗
A Hybrid Gyrokinetic Ion - Fluid Electron Model For Edge Plasma Simulations
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Physics - Plasma physics↗
Computational fluid dynamic control
A general technique is presented for modeling fluid, or gas, dynamic systems specifically for the development of control systems. The numerical methods which are generally used in computational fluid dynamics are borrowed to create either continuous-time or discrete-time models of the particular fluid system. The resulting equations can be either left in a nonlinear form, or easily linearized about an operating point. As there are typically very many states in these systems, the usual linear model reduction methods can be used on them to allow a low-order controller to be designed. A simple example is given which typifies many internal flow control problems. The resulting control is termed computational fluid dynamic control.
Hartley, Tom T.↗
Lattice Boltzmann model for compressible fluids
A lattice Boltzmann model is derived which simulates compressible fluids. By choosing the parameters of the equilibrium distribution appropriately, the sound speed (which may be set arbitrarily low), bulk viscosity, and kinematic viscosity can be selected. This model simulates compressible flows and can include shocks. With a proper rescaling and zero-sound speed, this model simulates Burgers's equation. The viscosity determined by a Chapman-Enskog expansion compares well with that measured form simulations. The exact solutions of Burgers's equation on the unit circle are compared to solutions of lattice Boltzmann model finding reasonable agreement.
Alexander, F. J.↗
A two-fluid single-column model of turbulent shallow convection, Part III: Results and parameter sensitivity
Two-fluid modelling has recently emerged as a promising approach to representing cumulus convection in weather and climate models. This study applies the two-fluid model described in Part II Thuburn et al., 2021b to a shallow cumulus convection case study over land (ARM). Large eddy simulation data is used to tune the majority of the closures that determine the properties of entrained and detrained air. The two-fluid model is generally able to reproduce the profiles of the mean and turbulent quantities over all stages of the diurnal cycle. As such, the initiation of shallow convection and the evolution of the cloud layer are well captured. The robustness of the two-fluid model is further verified using a steady-state test case (BOMEX), in which the cloud properties are also well modelled.
54 ENVIRONMENTAL SCIENCES↗
Chemical and Hydrodynamical Models of Cometary Comae
Multi-fluid modelling of the outflowing gases which sublimate from cometary nuclei as they approach the Sun is necessary for understanding the important physical and chemical processes occurring in this complex plasma. Coma chemistry models can be employed to interpret observational data and to ultimately determine chemical composition and structure of the nuclear ices and dust. We describe a combined chemical and hydrodynamical model [1] in which differential equations for the chemical abundances and the energy balance are solved as a function of distance from the cometary nucleus. The presence of negative ions (anions) in cometary comae is known from Giotto mass spectrometry of 1P/Halley. The anions O(-), OH(-), C(-), CH(-) and CN(-) have been detected, as well as unidentified anions with masses 22-65 and 85-110 amu [2]. Organic molecular anions such as C4H(-) and C6H(-) are known to have a significant impact on the charge balance of interstellar clouds and circumstellar envelopes and have been shown to act as catalysts for the gas-phase synthesis of larger hydrocarbon molecules in the ISM, but their importance in cometary comae has not yet been fully explored. We present details of new models for the chemistry of cometary comae that include atomic and molecular anions and calculate the impact of these anions on the coma physics and chemistry af the coma.
Charnley, Steven↗
Demonstration of Fluid Dynamics for Plant Growing Systems in Varied Gravity Environments Through Scaled Capillary Models
The development of reliable and bioregenerative crop growth production systems is vital for human exploration into deep space. As humans prepare for space travel beyond LEO, scientists need to find a way to provide reliable and adequate water delivery for all stages of the plant's life cycle. Past production systems struggled with this and often led to overwatering in the system. To better understand this issue, NASA's Plant Water Management (PWM) experiments were able to model fluid flow through granular substrates, specifically a clay-based material arcilite, in 0-G. The PWM study can help researchers to predict fluid flow through the systems, however their model only works for an arcilite based system and was unable to account for different stages of plant growth. For future missions, payload requirements to support crop production system will need to be limited, leading to the use of in situ resources. This project aims to validate the PWM experiments as well as incorporate various materials into the design for growth systems. To meet these objectives, a series of terrestrial experiments will be deployed to mimic all gravities. By modifying the material, fluid, and size of the test subjects, the effect of Earth's gravity can be minimized. This project will aid researchers in the design of future crop production systems for surface missions by creating a refined model that can be used at all stages of plant growth and utilize in situ resources.
Plant Biology↗
RELAP-7 Application and Enhancement for FLEX Strategies and ATF Behavior under Extended Loss of AC Power Conditions
This report summarizes the results of a three-year research project sponsored by the U.S. Department of Energy (DOE) Nuclear Energy University Program (NEUP) to enhance and apply the RELAP-7 code by adding and improving several important components (e.g., a mechanistic Reactor Core Isolation Cooling (RCIC) system model) for thermal hydraulic studies of LWRs under ELAP conditions and evaluating the time available for transition to portable FLEX equipment. The project team included University of Massachusetts–Lowell, The Ohio State University, Texas A&M University, Idaho National Laboratory and Oak Ridge National Laboratory. In the Fukushima accident, it was found that the RCIC system played a crucial role in delaying core meltdown by almost three days in Fukushima Daiichi Unit 2, because of self-regulated operation of the steam driven RCIC turbine-pump injection system. Steam flow in the convergent-divergent nozzles of the RCIC Terry turbine is two-phase non-equilibrium transonic flow with homogenous nucleation condensation. To more accurately predict the dynamic process and behavior of the transonic compressible steam flow, a one-dimensional transient two-phase analytical model is presented. A simplified four-fluid model was employed in the present work with the consideration of four separate fluid fields: vapor, liquid film, entrained droplets and condensed droplets. The mass, momentum and energy interactions between the fluids were considered and modeled. An extended seven-equation non-equilibrium critical flow model was developed to obtain the critical pressure and velocities of each phase at the nozzle throat. To predict the wetness in the divergent section, a mechanistic nucleation condensation model was integrated in the nozzle analysis model, considering the generation and consequent growth of droplets. The governing differential equations on a staggered grid were discretized using the second-order Lax-Wendroff scheme with a flux limiter, and the Semi-Implicit Method for Pressure-Linked Equation (SIMPLE) algorithm was employed to solve the discrete linear system. To demonstrate the predictability and reliability of the physical models and the numerical method proposed in the present work, three representative nozzles were modeled and simulated. The results show good agreement with the available experimental data, even for condensation shock. Then, the 1D nozzle model was employed to obtain nozzle flow tables of the Terry turbine nozzle for different working pressures which can cover the operation pressure range of the RCIC system. A mechanistic RCIC turbine-pump system model was developed and implemented in the system code TRACE to simulate dynamic responses of the RCIC system under Beyond Design Basis Accident (BDBA) conditions. The turbine-pump governing equations are based on the control volume approach of the angular momentum balance. The physics based mechanistic RCIC model was developed using the TRACE control system components (i.e., signal variables, control blocks, and tables), and incorporated into a TRACE boiling water reactor (BWR) model. The TRACE model in this report has a detailed nodalization of the reactor pressure vessel (RPV), and all of the major flow paths and system components, including the safety relief valves (SRVs) and the containment suppression pool and drywell. Based on the nozzle flow tables generated from the 1D nozzle model developed, the turbine drive torque can be calculated from table lookup. Since the detailed specifications of the RCIC pump are unavailable, the homologous curves for a Bingham pump were used in the current pump component. A station black-out (SBO) accident test problem was selected to demonstrate the TRACE RCIC model. The short-term SBO simulations were performed for two cladding materials: Zircaloy and FeCrAl, to demonstrate the effect of the accident tolerant fuel cladding on fuel heat-up under BDBA accident conditions. The wetwell plays a vital safety role in SBO and other BWR accident scenarios in that it can reduce containment pressure and supply additional core make-up water. The suppression pool temperature distribution has a very large impact on both RPV and containment pressure. Thus, another novel contribution of the project comes mainly from an improved, systems-level wetwell model which can capture buoyancy-induced thermal stratification effects due to steam injection and condensation. A two-zone stratified wetwell model has been implemented in RELAP-7 and some results from that model are presented. This wetwell model is capable of simulating thermal stratification due to a low steam mass injection rate. With a low mass flow rate, the model assumes that all the steam condenses within the pipe and the resulting plume can be approximated with a purely buoyant, heat-source driven model. The wetwell model developed with these assumptions is adequate to simulate slow transients such as extended SBO transients.
42 ENGINEERING↗
Fluid-driven fractures in granular media: Insights from numerical investigations
We investigate the mechanisms of opening-mode fracture initiation in granular media. The study is based on a simulation of grain-scale fluid-grain interactions through a coupled numerical approach in which the discrete element method is used to solve for the mechanics of a solid granular medium, and computational fluid dynamics is used to model fluid flow and drag forces. In this work, we present benchmark problems with analytical solutions and validate this numerical model against experiments on a viscous-drag-driven cavity in the literature. Additional simulation results show fracture initiation mechanisms in a random granular packing subjected to constant boundary stresses and to fluid injection with a localized source. The dimensionless variable $F_s/F_{sk}$ (ratio of seepage force $F_s$ and skeletal force $F_{sk}$) incorporates the impacts of physical properties and injection parameters including fluid viscosity, injection velocity, grain size, and effective stresses, and it has been used as a criterion separating regimes of fluid invasion and drag-driven fracture opening. Our simulation results show that $F_s/F_{sk}$ in combination with $τ_1$ (ratio of diffusion time from hydromechanical coupling and injection time) serves as a prediction of fracture opening within granular packing. We suggest a simple criterion ($F_s/F_{sk}$ > 1 or $τ_1$ > 0.17) that is valid for various types of granular media and injection conditions to determine if fracture opening will occur. Among other applications, this study is useful to predict the initiation and propagation of fractures in natural sediments.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Statistical inference of anomalous thermal transport with uncertainty quantification for interpretive 2D SOL models
The critical task of inferring anomalous cross-field transport coefficients is addressed in simulations of boundary plasmas with fluid models. A workflow for parameter inference in the UEDGE fluid code is developed using Bayesian optimization with parallelized sampling and integrated uncertainty quantification. In this workflow, transport coefficients are inferred by maximizing their posterior probability distribution, which is generally multidimensional and non-Gaussian. Uncertainty quantification is integrated throughout the optimization within the Bayesian framework that combines diagnostic uncertainties and model limitations. As a concrete example, we infer the anomalous electron thermal diffusivity $\chi_\perp$ from an interpretive 2D model describing electron heat transport in the conduction-limited region with radiative power loss. The workflow is first benchmarked against synthetic data and then tested on H-, L-, and I-mode discharges to match their midplane temperature and divertor heat flux profiles. We demonstrate that the workflow efficiently infers diffusivity and its associated uncertainty, generating 2D profiles that match 1D measurements. Future efforts will focus on incorporating more complicated fluid models and analyzing transport coefficients inferred from a large database of experimental results.
Bayesian optimization↗
Flow Simulation in Secondary Flow Passages of a Rocket Engine Turbopump
This paper presents application of a Generalized Fluid System Simulation Program (GFSSP) to model fluid flow in a very complex secondary flow circuit of a rocket engine turbopump, SIMPLEX. SIMPLEX was a low cost turbopump designed, manufactured and tested to demonstrate the ability to reduce the overall cost and design cycle time of turbomachinery. GFSSP is a general purpose computer program for analyzing flowrate, pressure, temperature and concentration distribution in a complex flow network. The program employs a finite volume formulation of mass, momentum and energy conservation equations in conjunction with thermodynamic equation of state of a real fluid. The secondary flow passages modeled include flow between the impeller shroud and housing, impeller back face and housing, flow through labyrinth seal and bearing, return line flow to inducer and flow adjacent to front and back face of the turbine. Axial load on the bearing are calculated from the predicted pressure on all axial faces of the rotor. The predicted pressure and temperature distributions compared well with the test data.
Schallhorn, Paul↗
Traction drive performance prediction for the Johnson and Tevaarwerk traction model
The fluid rheology model is used to investigate the traction behavior for typical traction drive contacts. The aspect ratio of the contact and the invariably present spin are investigated. Contacts with a low aspect ratio predict a superior performance in that they show less slip for the same degree of traction. Spin always has a diminishing effect on the traction at the same slip. At sufficiently high spin the model may be simplified to a limiting shear stress model. The conventional rigid plastic analysis applies here equally well.
Tevaarwerk, J. L.↗
A critical evaluation of various turbulence models as applied to internal fluid flows
Models employed in the computation of turbulent flows are described and their application to internal flows is evaluated by examining the predictions of various turbulence models in selected flow configurations. The main conclusions are: (1) the k-epsilon model is used in a majority of all the two-dimensional flow calculations reported in the literature; (2) modified forms of the k-epsilon model improve the performance for flows with streamline curvature and heat transfer; (3) for flows with swirl, the k-epsilon model performs rather poorly; the algebraic stress model performs better in this case; and (4) for flows with regions of secondary flow (noncircular duct flows), the algebraic stress model performs fairly well for fully developed flow, for developing flow, the algebraic stress model performance is not good; a Reynolds stress model should be used. False diffusion and inlet boundary conditions are discussed. Countergradient transport and its implications in turbulence modeling is mentioned. Two examples of recirculating flow predictions obtained using PHOENICS code are discussed. The vortex method, large eddy simulation (modeling of subgrid scale Reynolds stresses), and direct simulation, are considered. Some recommendations for improving the model performance are made. The need for detailed experimental data in flows with strong curvature is emphasized.
Nallasamy, M.↗
Reynolds-Averaged Turbulence Modeling Using Deep Learning with Local Flow Features: An Empirical Approach
Reynolds-Averaged Navier-Stoke (RANS) models offer an alternative avenue in predicting flow characteristics when the corresponding experiments are difficult to achieve due to geometry complexity, limited budget, or knowledge. RANS models require the knowledge of subgrid scale physics to solve conservation equations for mass, energy, and momentum. Mechanistic turbulence models, such as k-epsilon, are generally evaluated and calibrated for specific flow conditions with various degrees of uncertainty. These models have limited capability to assimilate a substantial amount of data due to model form constraints. Meanwhile, deep learning (DL) has been proven to be universal approximators with the potential to assimilate available, relevant, and adequately evaluated data. Moreover, deep neural networks (DNNs) can create surrogate models without knowing function forms. Such a data-driven approach can be used in updating fluid models based on observations as opposed to hard-wiring models with precalibrated correlations. The paper presents progress in applying DNNs to model Reynolds stress using two machine learning (ML) frameworks. A novel flow feature coverage mapping is proposed to quantify the physics coverage of DL-based closures. It can be used to examine the sufficiency of training data and input flow features for data-driven turbulence models. The case of a backward-facing step is formulated to demonstrate that not only can DNNs discover underlying correlation behind fluid data but also they can be implemented in RANS to predict flow characteristics without numerical stability issues. Finally, the presented research is a crucial stepping-stone toward the data-driven turbulence modeling, which potentially benefits the design of data-driven experiments that can be used to validate fluid models with ML-based fluid closures.
42 ENGINEERING↗
Modelling general-relativistic plasmas with collisionless moments and dissipative two-fluid magnetohydrodynamics
ABSTRACT Relativistic plasmas are central to the study of black hole accretion, jet physics, neutron star mergers, and compact object magnetospheres. Despite the need to accurately capture the dynamics of these plasmas and the implications for relativistic transients, their fluid modelling is typically done using a number of (overly) simplifying assumptions, which do not hold in general. This is especially true when the mean free path in the plasma is large compared to the system size, and kinetic effects start to become important. Going beyond common approaches used in the literature, we describe a fully relativistic covariant 14-moment based two-fluid system appropriate for the study of electron–ion or electron–positron plasmas. This generalized Israel-Stewart-like system of equations of motion is obtained directly from the relativistic Boltzmann–Vlasov equation. This new formulation can account for non-ideal effects, such as anisotropic pressures and heat fluxes, not present in previous formulations of two-fluid magnetohydrodynamics. We show that a relativistic two-fluid plasma can be recast as a single fluid coupled to electromagnetic fields with (potentially large) out-of-equilibrium corrections. We keep all electron degrees of freedom, which provide self-consistent evolution equations for electron temperature and momentum. The out-of-equilibrium corrections take the form of a collisional 14-moment closure previously described in the context of viscous single fluids. The equations outlined in this paper are able to capture the full two-fluid character of collisionless plasmas found in black hole accretion and flaring processes around compact objects, as well Braginskii-like two-fluid magnetohydrodynamics applicable to weakly collisional plasmas inside accretion discs.
79 ASTRONOMY AND ASTROPHYSICS↗