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At least 235 records · Page 13

Recommended direct simulation Monte Carlo collision model parameters for modeling ionized air transport processes

A systematic approach for calibrating the direct simulation Monte Carlo (DSMC) collision model parameters to achieve consistency in the transport processes is presented. The DSMC collision cross section model parameters are calibrated for high temperature atmospheric conditions by matching the collision integrals from DSMC against ab initio based collision integrals that are currently employed in the Langley Aerothermodynamic Upwind Relaxation Algorithm (LAURA) and Data Parallel Line Relaxation (DPLR) high temperature computational fluid dynamics solvers. The DSMC parameter values are computed for the widely used Variable Hard Sphere (VHS) and the Variable Soft Sphere (VSS) models using the collision-specific pairing approach. The recommended best-fit VHS/VSS parameter values are provided over a temperature range of 1000-20 000 K for a thirteen-species ionized air mixture. Use of the VSS model is necessary to achieve consistency in transport processes of ionized gases. The agreement of the VSS model transport properties with the transport properties as determined by the ab initio collision integral fits was found to be within 6% in the entire temperature range, regardless of the composition of the mixture. The recommended model parameter values can be readily applied to any gas mixture involving binary collisional interactions between the chemical species presented for the specified temperature range.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Directional solidification of aqueous TiO 2 suspensions under reduced gravity

Porous materials exhibiting aligned, elongated pore structures can be created by directional solidification of aqueous suspensions—where particles are rejected from a propagating ice front and form interdendritic, particle-packed walls—followed by sublimation of the ice, and sintering of the particle walls. Theoretical models that predict dendritic lamellae spacing—and thus wall and pore width in the final materials—are currently limited due to an inability to account for gravity-driven convective effects during solidification. In this work, aqueous suspensions of 10–30 nm TiO 2 nanoparticles are solidified on parabolic flights under micro-, lunar (~0.17 g; g l = 1.62 m/s 2 ), and Martian (~0.38 g; g m = 3.71 m/s 2 ) gravity and compared to terrestrially-solidified samples. After ice sublimation and sintering, all resulting TiO 2 materials exhibit elongated lamellar pores replicating the ice dendrites. Furthermore, increasing the TiO 2 fraction in the suspensions leads to decreased lamellar spacing in all samples, regardless of gravitational acceleration. Consistent with previous studies of microgravity solidification of binary metallic alloys, lamellar spacing decreases with increasing gravitational acceleration. Furthermore, mean lamellar spacing for 20 wt% TiO 2 nanoparticles suspensions under micro-, lunar, Martian, and terrestrial gravity are, respectively: 50 ± 8, 34 ± 11, 30 ± 6, and 23 ± 9 μm, indicating that gravity-driven convection strongly affects lamellae spacing under terrestrial gravity conditions. Gravitational effects on lamellar spacing are highest at low TiO 2 fractions in the suspension; for 5 wt% TiO 2 suspensions, the microgravity lamellar spacing is more than twice that under terrestrial gravity (182 ± 21 vs. 81 ± 23 μm). Results of this study are in good agreement with previous studies of binary metallic alloy solidification where primary dendrite spacing increases under microgravity. Additionally, literature data from ice-templating systems are used to discuss a dependence on lamellae spacing of the density ratio of particles and fluid.

36 MATERIALS SCIENCE↗

Efficient data-driven models for prediction and optimization of geothermal power plant operations

Increasing the capacity of geothermal energy as a renewable resource calls for development and deployment of efficient control and optimization technologies for geothermal power plants. A data-driven prediction and optimization model is presented as a cost-effective and efficient alternative to physics-based approach. The model predicts power output and operational cost by propagating the influence of control and disturbance variables within an artificial neural network (ANN). Numerical experiments with simulated and field data from a real geothermal power plant are first used to demonstrate the prediction performance of the ANN model. The model is then adopted to maximize the net predicted power production by automatically adjusting the working fluid circulation rate. The optimization performance of the model in evaluated using a thermodynamic flowsheet simulation model. The workflow is applied to model and control the effect of ambient temperature on an air-cooled binary cycle power plant, which is complex and costly to perform using a physics-based predictive model. As a result, the performance of the method is demonstrated by applying it to both simulated and field datasets from a binary cycle geothermal power plant.

15 GEOTHERMAL ENERGY↗

Closures for multicomponent reacting flows based on dispersion analysis

This work presents algebraic closure models associated with advective transport and nonlinear reactions in a Reynolds-averaged Navier-Stokes context for a system of species subject to binary reactions and transport by advection and diffusion. Expanding upon analysis originally developed for non-reactive transport in the context of Taylor dispersion of scalars, this work extends the modified gradient diffusion model explicated by Peters [N. Peters, Turbulent Combustion, Cambridge Monographs on Mechanics (Cambridge University Press, Cambridge, 2000)] and based on work by Corrsin [S. Corrsin, The reactant concentration spectrum in turbulent mixing with a first-order reaction, J. Fluid Mech. 11, 407 (1961)] beyond single-component transport phenomena and involving nonlinear reactions. The presented model forms, from this weakly nonlinear extension of the original dispersion theory, lead to an analytic expression for the eddy diffusivity matrix that explicitly captures the influence of the reaction kinetics on the closure operators. Furthermore, we demonstrate that the derived model form directly translates between flow topologies through a priori and a posteriori testing of a binary species system subject to homogeneous isotropic turbulence. Using two- and three-dimensional direct numerical simulations involving laminar and turbulent flows, it is shown that this framework improves prediction of mean quantities compared to previous results. Lastly, the presented model form, collapses to the earlier gradient diffusion and its modified version derived by Corrsin in the limits of nonreactive species and linear reactions, respectively.

42 ENGINEERING↗

Detailed finite element method modeling of evaporating multi-component droplets

The evaporation of sessile multi-component droplets is modeled with an axisymmetic finite element method. The model comprises the coupled processes of mixture evaporation, multi-component flow with composition-dependent fluid properties and thermal effects. Based on representative examples of water–glycerol and water–ethanol droplets, regular and chaotic examples of solutal Marangoni flows are discussed. Furthermore, the relevance of the substrate thickness for the evaporative cooling of volatile binary mixture droplets is pointed out. It is shown how the evaporation of the more volatile component can drastically decrease the interface temperature, so that ambient vapor of the less volatile component condenses on the droplet. Finally, results of this model are compared with corresponding results of a lubrication theory model, showing that the application of lubrication theory can cause considerable errors even for moderate contact angles of 40°. - Graphical abstract:.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Integrated modeling methodology for ash agglomeration in poly-disperse fluidized beds using particle population framework

This article discusses a unique agglomeration modeling methodology developed based on binary collisions to combine the effects of heterogeneity in ash chemistry and granular physics. A simple population balance is defined to find changes in the particle size distribution (PSD) of a fluidized bed. Thermodynamic equilibrium calculations and a computational fluid dynamics (CFD) code, are used to obtain hydrodynamic parameters. A method to calculate and use a distribution of collision frequencies in fluidized beds, corresponding to a poly-disperse particle size distribution, was developed in order to incorporate the particle level heterogeneities. A distribution of collision frequencies obtained for poly-dispersed particles showed a three orders of magnitude higher collision frequency amongst the smaller particles than the coarser ones, at the initiation of agglomeration. Ash agglomeration occurred when the slag amount (binder) was less than 10 wt% at temperatures <850 °C for Pittsburgh No. 8 coal.

42 ENGINEERING↗

Hydra-TH Extensions for Multispecies and Thermosolutal Convection

This report describes the Consortium for Advanced Simulation of Light Water Reactors (CASL) work conducted for completion of the Thermal Hydraulics Methods (THM) Level 3 Milestone THM.CFD.P11.02: Hydra-TH Extensions for Multispecies and Thermosolutal Convection. A critical requirement for modeling reactor thermal hydraulics is to account for species transport within the fluid. In particular, this capability is needed for modeling transport and diffusion of boric acid within water for emergency, reactivity-control scenarios. To support this need, a species transport capability has been implemented in Hydra-TH for binary systems (for example, solute within a solvent). A species transport equation is solved for the species (solute) mass fraction, and both thermal and solutal buoyancy effects are handled with specification of a Boussinesq body force. Species boundary conditions can be specified with a Dirichlet condition on mass fraction or a Neumann condition on diffusion flux. To enable enhanced species/fluid mixing in turbulent flow, the molecular diffusivity for the binary system is augmented with a turbulent diffusivity in the species transport calculation. The new capabilities are demonstrated by comparison of Hydra-TH calculations to the analytic solution for a thermosolutal convection problem, and excellent agreement is obtained.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Natural convection in binary gases driven by combined horizontal thermal and vertical solutal gradients

An investigation of natural convection is presented to examine the influence of a horizontal temperature gradient and a concentration gradient occurring from the bottom to the cold wall in a cavity. As the solutal buoyancy force changes from augmenting to opposing the thermal buoyancy force, the fluid motion switches from unicellular to multicellular flow (fluid motion is up the cold wall and down the hot wall for the bottom counterrotating flow cell). Qualitatively, the agreement between predicted streamlines and smoke flow patterns is generally good. In contrast, agreement between measured and predicted temperature and concentration distributions ranges from fair to poor. Part of the discrepancy can be attributed to experimental error. However, there remains considerable discrepancy between data and predictions due to the idealizations of the mathematical model, which examines only first-order physical effects. An unsteady flow, variable thermophysical properties, conjugate effects, species interdiffusion, and radiation were not accounted for in the model.

Weaver, J. A.↗

Deep Neural Network Based Convergence Classification for Computational Fluid Dynamics

A supervised deep learning approach is coupled with heuristic convergence criteria to construct a classification model for detecting the completion (convergence) of computational fluid dynamics (CFD) simulations. Heuristic convergence criteria alone are not always sufficient and more complex decisions are often left to a human analyst. The proposed approach leverages heuristic convergence criteria as well as two deep neural network (DNN) models, one binary and one multi-class, to improve the efficiency and consistency of convergence classification across a wide range of flight regimes. The DNN models presented are each trained on a subset of ascent aerodynamic CFD simulations for NASA’s Space Launch System and were produced using NASA’s unstructured Navier-Stokes solver FUN3D. Individual solutions are analyzed intermittently and are classified as sufficiently converged, further iterations required, or switch from steady Reynolds Averaged Navier-Stokes (RANS) to unsteady RANS CFD based on the iterative histories of four aerodynamic coefficients. The implemented classification model is shown to produce solutions that closely correlate to solutions produced by a human analyst. This work lays groundwork for expanding the capabilities of DNNs for automating and improving more of the CFD process.

SLS↗

Homogeneous states in driven granular mixtures: Enskog kinetic theory versus molecular dynamics simulations

The homogeneous state of a binary mixture of smooth inelastic hard disks or spheres is analyzed. The mixture is driven by a thermostat composed by two terms: a stochastic force and a drag force proportional to the particle velocity. The combined action of both forces attempts to model the interaction of the mixture with a bath or surrounding fluid. The problem is studied by means of two independent and complementary routes. First, the Enskog kinetic equation with a Fokker-Planck term describing interactions of particles with thermostat is derived. Then, a scaling solution to the Enskog kinetic equation is proposed where the dependence of the scaled distributions φ{sub i} of each species on the granular temperature occurs not only through the dimensionless velocity c = v/v{sub 0} (v{sub 0} being the thermal velocity) but also through the dimensionless driving force parameters. Approximate forms for φ{sub i} are constructed by considering the leading order in a Sonine polynomial expansion. The ratio of kinetic temperatures T{sub 1}/T{sub 2} and the fourth-degree velocity moments λ{sub 1} and λ{sub 2} (which measure non-Gaussian properties of φ{sub 1} and φ{sub 2}, respectively) are explicitly determined as a function of the mass ratio, size ratio, composition, density, and coefficients of restitution. Second, to assess the reliability of the theoretical results, molecular dynamics simulations of a binary granular mixture of spheres are performed for two values of the coefficient of restitution (α = 0.9 and 0.8) and three different solid volume fractions (ϕ = 0.00785, 0.1, and 0.2). Comparison between kinetic theory and computer simulations for the temperature ratio shows excellent agreement, even for moderate densities and strong dissipation. In the case of the cumulants λ{sub 1} and λ{sub 2}, good agreement is found for the lower densities although significant discrepancies between theory and simulation are observed with increasing density.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Data Base for CFD Validation

The flow behind the shock wave formed around objects which fly at hypervelocity behaves differently from that of a perfect gas. Molecules become vibrationally excited, dissociated, and ionized. The hot gas may emit or absorb radiation. When the atoms produced by dissociation reach the wall surface, chemical reactions, including recombination, may occur. The thermochemical phenomena of vibration, dissociation, ionization, surface chemical reaction, and radiation are referred to commonly as high-temperature real-gas phenomena. The phenomena cause changes in the dynamic behavior of the flow and the surface pressure and heat transfer distribution around the object. The character of a real gas is described by the internal degrees of freedom and state of constituent molecules; nitrogen and oxygen for air. The internal energy states, rotation, vibration and electronic, of the molecules are excited and, in the limit, the molecular bonds are exceeded and the gas dissociated into atomic and, possibly, ionic constituents. The process of energy transfer causing excitation, dissociation and recombination is a rate process controlled by particle collisions. Binary, two-body, collisions are sufficient to cause internal excitation, dissociation and ionization while three-body collisions are required to recombine the particles into molecular constituents. If the rates of energy transfer are fast with respect to the local fluid dynamic time scale the gas is in, or nearly in, equilibrium. If the energy transfer rates are very slow the gas can be described as frozen. In all other instances, wherein any of the energy exchange rates are comparable to the local fluid time scale, the gas will be thermally or chemically reacting and out of equilibrium. Real gas thermochemical nonequilibrium processes are important in the determination of aerodynamic heating; both convective (including wall catalytic effects) and radiative heating. To illustrate this we consider the hypervelocity flow over a bluff body typical of an atmospheric entry vehicle or an aerospace transfer vehicle (ASTV). The qualitative aspects of a hypersonic flow field over a bluff body are discussed in two parts, forebody and afterbody, with attention to which particular physical effects must be included in an analysis. This will indicate what type of numerical modeling will be adequate in each region of the flow. A bluff forebody flow field is dominated by the presence of the strong bow shock wave and the consequent heating, and chemical reaction of the gas. At high altitude hypersonic flight conditions the thermal excitation and chemical reaction of the gas occur slowly enough that a significant portion of the flow field is in a state of thermochemical nonequilibrium. A second important effect is the presence of the thick boundary layer along the forebody surface. In this region there are large thermal and chemical species gradients due to the interaction of the gas with the wall. Also at high altitudes the shock wave and the boundary layer may become so thick that they merge; in this case the entire shock layer is dominated by viscous effects.

Deiwert, George S.↗

Accurate and Data‐Efficient Micro X‐ray Diffraction Phase Identification Using Multitask Learning: Application to Hydrothermal Fluids

Traditional analysis of highly distorted micro X‐ray diffraction (μ‐XRD) patterns from hydrothermal fluid environments is a time‐consuming process, often requiring substantial data preprocessing and labeled experimental data. Herein, the potential of deep learning with a multitask learning (MTL) architecture to overcome these limitations is demonstrated. MTL models are trained to identify phase information in μ‐XRD patterns, minimizing the need for labeled experimental data and masking preprocessing steps. Notably, MTL models show superior accuracy compared to binary classification convolutional neural networks. Additionally, introducing a tailored cross‐entropy loss function improves MTL model performance. Most significantly, MTL models tuned to analyze raw and unmasked XRD patterns achieve close performance to models analyzing preprocessed data, with minimal accuracy differences. This work indicates that advanced deep learning architectures like MTL can automate arduous data handling tasks, streamline the analysis of distorted XRD patterns, and reduce the reliance on labor‐intensive experimental datasets.

97 MATHEMATICS AND COMPUTING↗

Bimodal particle distributions with increased thermal conductivity for solid particles as heat transfer media and storage materials

Solid particles are being considered in several high temperature thermal energy storage systems and as heat transfer media in a variety of advanced power generation systems, particularly in concentrated solar power plants. The downside of such an approach is the low overall heat transfer coefficients caused by the inherently low thermal conductivity values of the low-cost solid media when coupled to heat exchanger for the power cycle working fluid. Choosing the right particle size distribution, emittance, and material of the solid media can all make a substantial difference in packed bed thermal conductivity. Current research though exclusively focuses on continuous unimodal distributions of particles. Here, in this work, we propose the use of a binary particle system with a bimodal size distribution to significantly increase packed bed thermal conductivity by reducing packed bed porosity. This is the first study related to ceramic solid particle heat transfer that has considered the thermal conductivity of non-unimodal size distributions at room and elevated temperatures. The following study found that for the binary particle system using Carbo particles CP 16/30 – CP 70/140 where the large particle volume fraction was 50% there was an 17–47% increase in packed bed thermal conductivity when compared with a nearly unimodal particle size distribution of CP 16/30 between 50 and 300 °C. Two different porosity and effective thermal conductivity models were studied, with one providing better prediction of porosity but both effective thermal conductivity models providing less predictive capacity. Importantly this approach can have a substantial impact of thermal performance, with little to no impact on the particle cost.

36 MATERIALS SCIENCE↗

Effects of thermophoresis on high-pressure binary-species boundary layers with uniform and non-uniform compositions

Direct numerical simulations of high-pressure binary-species temporal boundary layers are performed to investigate the flow physics for three situations: (1) uniform and equal composition, (2) uniform but unequal compositions and (3) non-uniform composition. Both colder- and hotter-wall situations compared with the free stream are simulated. The working fluid is a nitrogen/methane mixture. The analysis is performed at a case-specific self-similar state. Even when the initial composition is uniform, the methane mean mass fraction decreases near the colder wall, whereas it increases near the hotter wall and the mass fraction fluctuates in the entire boundary layer. Analysis of the species-mass diffusion balance and flow structures reveal that both mass-fraction variation and fluctuations are induced by the Soret effect. When the initial composition is non-uniform and the wall is colder, the methane mean mass fraction monotonically increases from the wall akin to its initial profile. However, when the wall is hotter the mean mass fraction decreases near the wall in contrast to its initial profile, a fact traced through the species-mass diffusion balance to the Soret effect being large and enriching methane near the wall. In contrast, the direction of the Soret flux is opposite for the colder wall, thus keeping the methane concentration small. Although the initial magnitude of the difference between the wall and free-stream temperature is the same in all cases, the situation is not symmetric between colder- and hotter-wall cases; the flow structure exhibits much smaller scales when the wall is hotter than when the wall is colder.

Mechanics↗

Experimental study of elliptical jet from sub to supercritical conditions

The jet mixing at supercritical conditions involves fluid dynamics as well as thermodynamic phenomena. All the jet mixing studies at critical conditions to the present date have focused only on axisymmetric jets. When the liquid jet is injected into supercritical environment, the thermodynamic transition could be well understood by considering one of the important fluid properties such as surface tension since it decides the existence of distinct boundary between the liquid and gaseous phase. It is well known that an elliptical liquid jet undergoes axis-switching phenomena under atmospheric conditions due to the presence of surface tension. The experimental investigations were carried out with low speed elliptical jet under supercritical condition. Investigation of the binary component system with fluoroketone jet and N{sub 2} gas as environment shows that the surface tension force dominates for a large downstream distance, indicating delayed thermodynamic transition. The increase in pressure to critical state at supercritical temperature is found to expedite the thermodynamic transition. The ligament like structures has been observed rather than droplets for supercritical pressures. However, for the single component system with fluoroketone jet and fluoroketone environment shows that the jet disintegrates into droplets as it is subjected to the chamber conditions even for the subcritical pressures and no axis switching phenomenon is observed. For a single component system, as the pressure is increased to critical state, the liquid jet exhibits gas-gas like mixing behavior and that too without exhibiting axis-switching behavior.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Geometric and thermodynamic characterization of binary neutron star accretion discs

Accretion disks formed in binary neutron star mergers play a central role in many astrophysical processes of interest, including the launching of relativistic jets or the ejection of neutron-rich matter hosting heavy element nucleosynthesis. In this work we analyze in detail the properties of accretion disks from 44 ab initio binary neutron star merger simulations for a large set of nuclear equations of state, binary mass ratios, and remnant fates, with the aim of furnishing reliable initial conditions for disk simulations and a comprehensive characterization of their properties. We find that the disks have a significant thermal support, with an aspect ratio decreasing with the mass ratio of the binary from ~0.7 to 0.3. Even if the disk sample spans a broad range in mass and angular momentum, their ratio is independent from the equation of state and from the mass ratio. This can be traced back to the rotational profile of the disk, characterized by a constant specific angular momentum (as opposed to a Keplerian one) of 3 – 5×10 16 cm 2 s –1 . The profiles of the entropy per baryon and of the electron fraction depend on the mass ratio of the binary. For more symmetric binaries, they follow a sigmoidal distribution as a function of the rest mass density, for which we provide a detailed description and a fit. Furthermore, the disk properties discussed in this work can be used as a robust set of initial conditions for future long-term simulations of accretion disks from binary neutron star mergers, posing the basis for progress in the quantitative study of the outflow properties.

79 ASTRONOMY AND ASTROPHYSICS↗

Grand canonical Monte Carlo using solvent repacking: Application to phase behavior of hard disk mixtures

A new “solvent repacking Monte Carlo” strategy for performing grand canonical ensemble simulations in condensed phases is introduced and applied to the study of hard-disk systems. The strategy is based on the configuration-bias approach, but uses an auxiliary biasing potential to improve the efficiency of packing multiple solvent particles in the cavity formed by removing one large solute. The method has been applied to study the coexistence of ordered and isotropic phases in three binary mixtures of hard disks with a small mole fraction (x{sub L} < 0.02) of the larger “solute” component. A chemical potential of 12.81 ± 0.01 k{sub B}T was found to correspond to the freezing transition of the pure hard disk “solvent.” Simulations permitted the study of partitioning of large disks between ordered and isotropic phases, which showed a distinct non-monotonic dependence on size; the isotropic phase was enriched approximately 10-fold, 20-fold, and 5-fold over the coexisting ordered phases at diameter ratios d = 1.4, 2.5, and 3, respectively. Mixing of large and small disks within both phases near coexistence was strongly non-ideal in spite of the dilution. Structures of systems near coexistence were analyzed to determine correlations between large disks’ positions within each phase, the orientational correlation length of small disks within the fluid phases, and the nature of translational order in the ordered phase. The analyses indicate that the ordered phase coexists with an isotropic phase resembling a nanoemulsion of ordered domains of small disks, with large disks enriched at the disordered domain interfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

C–IBI: Targeting cumulative coordination within an iterative protocol to derive coarse-grained models of (multi-component) complex fluids

We present a coarse-graining strategy that we test for aqueous mixtures. The method uses pair-wise cumulative coordination as a target function within an iterative Boltzmann inversion (IBI) like protocol. We name this method coordination iterative Boltzmann inversion (C–IBI). While the underlying coarse-grained model is still structure based and, thus, preserves pair-wise solution structure, our method also reproduces solvation thermodynamics of binary and/or ternary mixtures. In addition, we observe much faster convergence within C–IBI compared to IBI. To validate the robustness, we apply C–IBI to study test cases of solvation thermodynamics of aqueous urea and a triglycine solvation in aqueous urea.

74 ATOMIC AND MOLECULAR PHYSICS↗