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At least 1,495 records · Page 83

Computational fluid dynamics modeling and analysis of silica nanoparticle synthesis in a flame spray pyrolysis reactor

Flame Spray Pyrolysis (FSP) is a method for large-scale production of nanoparticles and nanoscale powders employed in a wide range of industrial applications. Particle size and morphology are complex functions of the physicochemical phenomena occurring in the FSP reactor. An extensive study of FSP-related phenomena can be utilized to develop effective strategies for achieving desired particle size/morphology and scaling up the overall yield of an FSP system. In this work, a computational fluid dynamics (CFD) model of an FSP reactor is developed to simulate the coupling of key phenomena involved in the particle synthesis process: liquid spray breakup and evaporation, mixing, combustion, and particle formation/growth of silica nanoparticles. Herein, the particle sizes and their distributions from the CFD simulations are validated against experimental data. Subsequently, the simulations are utilized to investigate the impact of process parameters on the resultant flame dynamics and particle growth. Firstly, the CFD results show that the particle sizes are strongly correlated with the precursor concentration in the solvent. At lower precursor concentrations, the spread of the distribution is relatively insensitive to the value of the concentration. At higher concentrations, the spread is higher as the collision probability between particles is higher. Secondly, increasing the pilot flow rate increases the length of the pilot flames impacting the local ignition location of the spray flame. Lastly, it is shown that the dispersion gas flow rate strongly influences the spray flame shape. This shape can be used for control of particle growth as it helps determine the regions of high temperature and the residence time of the particles in the high temperature region enabling the design and process optimization of the FSP reactor.

42 ENGINEERING↗

Multiscale dendritic needle network model of alloy solidification with fluid flow

We present a mathematical formulation of a multiscale model for solidification with convective flow in the liquid phase. The model is an extension of the dendritic needle network approach for crystal growth in a binary alloy. We propose a simple numerical implementation based on finite differences and step-wise approximations of parabolic dendritic branches of arbitrary orientation. Results of the two-dimensional model are verified against reference benchmark solutions for steady, unsteady, and buoyant flow, as well as steady-state dendritic growth in the diffusive regime. Simulations of equiaxed growth under forced flow yield dendrite tip velocities within 10% of quantitative phase-field results from the literature. Finally, we perform illustrative simulations of polycrystalline solidification using physical parameters for an aluminum-10wt% copper alloy. Resulting microstructures show notable differences when taking into account natural buoyancy in comparison to a purely diffusive transport regime. The resulting model opens new avenues for computationally and quantitatively investigating the influence of fluid flow and gravity-induced buoyancy upon the selection of dendritic microstructures. Further ongoing developments include an equivalent formulation for directional solidification conditions and the implementation of the model in three dimensions, which is critical for quantitative comparison to experimental measurements.

36 MATERIALS SCIENCE↗

Poromechanical cohesive interface element with combined Mode I-II cohesive zone elastoplasticity for simulating fracture in fluid-saturated porous media

A combined Mode I-II cohesive zone (CZ) elasto-plastic constitutive model, and a two-dimensional (2D) cohesive interface element (CIE) are formulated and implemented at small strain within an ABAQUS User Element (UEL) for simulating 2D crack nucleation and propagation in fluid-saturated porous media. Here, the CZ model mitigates problems of convergence for the global Newton-Raphson solver within ABAQUS, which when combined with a viscous stabilization procedure allows for simulation of post-peak response under load control for coupled poromechanical finite element analysis, such as concrete gravity dam stability analysis. Verification examples are presented, along with a more complex ambient limestone-concrete wedge fracture experiment, water-pressurized concrete wedge experiment, and concrete gravity dam stability analyses. A calibration procedure for estimating the CZ parameters is demonstrated with the limestone-concrete wedge fracture process. For the water-pressurized concrete wedge fracture experiment it is shown that the inherent time-dependence of the poromechanical CIE analysis provides a good match with experimental force versus displacement results at various crack mouth opening rates, yet misses the pore water pressure evolution ahead of the crack tip propagation. This is likely a result of the concrete being partially-saturated in the experiment, whereas the finite element analysis assumes fully water saturated concrete. For the concrete gravity dam analysis, it is shown that base crack opening and associated water uplift pressure leads to a reduced Factor of Safety, which is confirmed by separate analytical calculations.

97 MATHEMATICS AND COMPUTING↗

Particlization in fluid dynamical simulations of heavy-ion collisions: The IS3D module

The IS3D particlization module simulates the emission of hadrons from heavy-ion collisions via Monte-Carlo sampling of the Cooper–Frye formula which converts fluid dynamical information into local phase-space distributions for hadrons. The code package includes multiple choices for the non-equilibrium correction to these distribution functions: the 14-moment approximation, first-order Chapman–Enskog expansion, and two types of modified equilibrium distributions. This makes it possible to explore to what extent heavy-ion experimental data are sensitive to different choices for δf n , presently the main source of theoretical uncertainty in the particlization stage. Here, we validate our particle sampler with a high degree of precision by generating several million hadron emission events from a longitudinally boost-invariant hypersurface and comparing the event-averaged particle spectra and space–time distributions to the Cooper–Frye formula.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

A computational fluid dynamics modeling study of guide walls for downstream fish passage

A partial-depth, impermeable guidance structure (or guide wall) for downstream fish passage is typically constructed as a series of panels attached to a floating boom and anchored across a water body (e.g. river channel, reservoir, or power canal). The downstream terminus of the wall is generally located nearby to a fish bypass structure. If guidance is successful, the fish will avoid entrainment in a dangerous intake structure (i.e. turbine intakes) while passing from the headpond to the tailwater of a hydroelectric facility through a safer passage route (i.e. the bypass). The goal of this study is to determine the combination of guide wall design parameters that will most likely increase the chance of surface-oriented fish being successfully guided to the bypass. To evaluate the flow field immediately upstream of a guide wall, a parameterized computational fluid dynamics model of an idealized power canal was constructed in © ANSYS Fluent v 14.5 (ANSYS Inc., 2012). The design parameters investigated were the angle and depth of the guide wall and the average approach velocity in the power canal. Results call attention to the importance of the downward to sweeping flow ratio and demonstrate how a change in guide wall depth and angle can affect this important hydraulic cue to out-migrating fish. The key findings indicate that a guide wall set at a small angle (15° is the minimum in this study) and deep enough such that sweeping flow dominant conditions prevail within the expected vertical distribution of fish approaching the structure will produce hydraulic conditions that are more likely to result in effective passage.

42 ENGINEERING↗

Coupling computational fluid dynamics with the high resolution rapid refresh model for forecasting dynamic line ratings

This study looks at forecasted dynamic line ratings in southern Idaho by using data from the High Resolution Rapid Refresh (HRRR) model for forecasted weather conditions. The HRRR model can provide accurate 18- hour forecasts with a 15-minute temporal resolution. Typical static ratings used for over head transmission lines use overly conservative assumptions for local weather conditions, such as using the maximum solar irradiance or temperature measured during the summer combined with low wind speed for an entire season. The HRRR forecast model used here has a high spatial resolution to provide local forecast conditions along the entire length of a transmission line. The area that is of interest in this study is in southern Idaho spanning a total of 15,000 square kilometers. The forecasted weather data is coupled with a computational fluid dynamics model of the wind in the region to improve the resolution to an even finer scale for resolving local convective cooling rates on each individual transmission line midpoint span. This high fidelity approach can be used to find the minimum ampacity limit across all given midpoints of a transmission line to determine the absolute minimum to be used for the line rating. The ability to increase the line rating above the conservative static approach with the forecasted weather data provides a large potential to alleviate congestion and provide data for the utility market transactions. Furthermore, this study shows that for the region of interest, using forecasted weather data coupled with CFD modeling will calculate DLR ampacity rating above static about 90% of the time, with only a small relative error in the forecasted ampacity over time.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Comment on “Solubilities of ammonia in basic imidazolium ionic liquids” [Fluid Phase Equilib. 297 (2010) 34–39]

The enthalpies of solvation of ammonia in imidazolium-based ionic liquids (and other associated thermodynamic properties) are re-analyzed based on the data of [Fluid Phase Equilib. 297 (2010) 34–39], correcting numerical errors in the original analysis. In contrast to the original conclusions, the re-analyzed data demonstrates that the enthalpy of solvation is not a strong function of alkyl chain length. Here, the errors and uncertainties of the analysis procedure are also discussed, suggesting that the strong observed temperature dependence of enthalpy may in fact be an artifact of the systematic neglect of the non-ideality of the ammonia solute.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Corrosion of stainless steels in the riser during co-processing of bio-oils in a fluid catalytic cracking pilot plant

Co-processing of bio-oils with conventional petroleum-based feedstocks is an attractive initial option to make use of renewable biomass as a fuel source while leveraging existing refinery infrastructures. But, bio-oils and their processing intermediates have high concentrations of organic oxygenates, which, among their other negative qualities, can result in increased corrosion issues. A range of stainless steel alloys (409, 410, 304L, 316L, 317L, and 201) was exposed at the base of the riser in a fluid catalytic cracking pilot plant while co-processing vacuum gas oil with pine-derived pyrolysis bio-oils that had been catalytically hydrodeoxygenated to ~ 2 to 28% oxygen. We studied the processing using a catalyst temperature of 704 °C, a reaction exit temperature of 520 °C, and total co-processing run times of 57–75 h. External oxide scaling 5–30 μm thick and internal attack 1–5 μm deep were observed in these short-duration exposures. The greatest extent of internal attack was observed for co-processing with the least stabilized bio-oil, and more so for types 409, 410, 304L, 316L, 317L stainless steel than for type 201. Finally, the internal attack involved porous Cr-rich oxide formation, associated with local Ni-metal enrichment and S-rich nanoparticles, primarily containing Cr or Mn. Implications for alloy selection and corrosion are discussed.

09 BIOMASS FUELS↗

A Eulerian three-fluid flow framework for the study of fuel dispersal behavior under loss-of-coolant accident conditions

As the nuclear industry explores new fuel designs to accommodate increased burnup, studying fuel behavior during loss-of-coolant accidents is essential for ensuring the safe operation of light-water reactors. Here, this study presents a computational model to simulate the intricate three-phase flow dynamics of fuel dispersal following cladding breach, where solid fuel particles and carrier fission gases interact with the surrounding liquid or gas medium. The model utilizes a Eulerian three-fluid framework to depict the phase interaction within interpenetrating continua, treating fragmented fuel as granular material. Closure relationships for bulk-flow properties of the solid phase and detailed interfacial exchange terms in high-temperature, high-speed gas-solid-liquid flow scenarios are proposed. The model was validated using adiabatic experimental results in the literature, focusing on characterizing fuel dispersal behavior during loss-of-coolant accidents conditions. Settlement characteristics of the solids, quantified by the probability distribution of equivalent particles, closely matched probability density functions reported in experimental studies. Key highlights of this study include the theoretical description of a coupled three-phase flow with phase change, interpretation of the high-pressure boundary conditions and insights into the transient behavior of gas-solid-liquid phase dynamics during a simulated high-speed dispersal event.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Modeling the dynamic response of rock masses with multiple compliant fluid saturated joint sets—Part I: Mesoscale simulations

Recently a mesoscale model was developed that includes thermomechanically consistent constitutive equations with dissipation due to porous compaction, inelastic distortional deformation rate, and slipping on persistent dry joint surfaces. In this Part I of a two-part paper, we describe enhancements of the mesoscale model which include: normal compliance with hysteresis, non-persistent joints with finite area, joint sets with angular deviation, and the weakening effect of fluid pressure in the joints. Examples study the influences of these effects on average strength. These computationally expensive simulations are used to inspire functional forms in a continuum model, described in Part II, which is needed for large scale simulations of real applications.

42 ENGINEERING↗

Subject-specific modeling framework for particle deposition using computational fluid dynamics

Quantifying particle deposition and dose in the respiratory tract requires a physiologically realistic representation and reproducible computational workflows. However, existing modeling frameworks, such as the International Commission on Radiological Protection (ICRP) compartmental models and the Multiple Path Particle Dosimetry (MPPD) tool, lack detailed deposition profiles and subject-specific capabilities. The combination of advances in computer vision algorithms applied to the respiratory tract and Computational Fluid and Particle Dynamics (CFPD) allows high-fidelity simulations of particle behavior in anatomically accurate geometries derived from individual CT scans. The segmentation, preprocessing, and file preparation task for a CFPD simulation was often time-consuming, and no prior studies to-date have yet presented a fully automated framework. This work presents a fully automated workflow to obtain individualized particle deposition profiles in the human respiratory tract. The pipeline starts with segmenting upper and lower airway geometries using morphological and deep learning-based methods, generating three-dimensional (3D) models from CT imaging data. Next, a series of algorithms are presented to quality check and prepare the 3D geometry for a CFD or CFPD simulation. The preprocessing step includes correcting geometric artifacts, enforcing a physically consistent mesh, and automatically identifying and capping multiple outlets, which is required for CFD/CFPD simulations. These processed models are then input into open-source (OpenFOAM) or commercial (StarCCM+) CFD solvers, where flow and transient particle transport equations — including turbulence and particle–wall interactions are solved under realistic breathing conditions. Finally, the resulting particle deposition profiles can be integrated with Monte Carlo radiation transport codes and state-of-the-art computational phantoms to assess organ-specific absorbed doses in scenarios of radioactive aerosol inhalation. The presented work streamlines respiratory tract segmentation, preprocessing for CFD/CFPD simulations, and integration with dose assessment workflows, reducing manual intervention and improving access to high-fidelity, subject-specific modeling. The high precision in predicted particle deposition and dose distributions can improve personalized treatment strategies in respiratory medicine and refine dose estimates for radiation protection.

AI↗

Computing the ankle-brachial index with parallel computational fluid dynamics

The ankle-brachial index (ABI), a ratio of arterial blood pressure in the ankles and upper arms, is used to diagnose and monitor circulatory conditions such as coarctation of the aorta and peripheral artery disease. Computational simulations of the ABI can potentially determine the parameters that produce an ABI indicative of ischemia or other abnormalities in blood flow. However, 0- and 1-D computational methods are limited in describing a 3-D patient-derived geometry. Thus, we present a massively parallel framework for computational fluid dynamics (CFD) simulations in the full arterial system. Additionally, using the lattice Boltzmann method to solve the Navier–Stokes equations, we employ highly parallelized and scalable methods to generate the simulation domain and efficiently distribute the computational load among processors. For the first time, we compute an ABI with 3-D CFD. In this proof-of-concept study, we investigate the dependence of ABI on the presence of stenoses, or narrowed regions of the arteries, by directly modifying the arterial geometry. As a result, our framework enables the computation a hemodynamic factor characterizing flow at the scale of the full arterial system, in a manner that is extensible to patient-specific imaging data and holds potential for treatment planning.

59 BASIC BIOLOGICAL SCIENCES↗

Gradient Theory simulations of pure fluid interfaces using a generalized expression for influence parameters and a Helmholtz energy equation of state for fundamentally consistent two-phase calculations

The fidelity of Gradient Theory simulations depends on the accuracy of saturation properties and influence parameters, and require equations of state (EoS) which exhibit a fundamentally consistent behavior in the two-phase regime. Widely applied multi-parameter EoS, however, are generally invalid inside this region. Hence, they may not be fully suitable for application in concert with Gradient Theory despite their ability to accurately predict saturation properties. The commonly assumed temperature-dependence of pure component influence parameters usually restricts their validity to subcritical temperature regimes. This may distort predictions for general multi-component interfaces where temperatures often exceed the critical temperature of vapor phase components. Then, the calculation of influence parameters is not well defined. In this paper, one of the first studies is presented in which Gradient Theory is combined with a next-generation Helmholtz energy EoS which facilitates fundamentally consistent calculations over the entire two-phase regime. Illustrated on pentafluoroethane as an example, reference simulations using this method are performed. They demonstrate the significance of such high-accuracy and fundamentally consistent calculations for the computation of interfacial properties. These reference simulations are compared to corresponding results from cubic PR EoS, widely-applied in combination with Gradient Theory, and mBWR EoS. The analysis reveals that neither of those two methods succeeds to consistently capture the qualitative distribution of obtained key thermodynamic properties in Gradient Theory. Furthermore, a generalized expression of the pure component influence parameter is presented. This development is informed by its fundamental definition based on the direct correlation function of the homogeneous fluid and by presented high-fidelity simulations of interfacial density profiles. As a result, the new model preserves the accuracy of previous temperature-dependent expressions, remains well-defined at supercritical temperatures, and is fully suitable for calculations of general multi-component two-phase interfaces.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Numerical schemes for dynamically orthogonal equations of stochastic fluid and ocean flows

The quantification of uncertainties is critical when systems are nonlinear and have uncertain terms in their governing equations or are constrained by limited knowledge of initial and boundary conditions. Such situations are common in multiscale, intermittent and non-homogeneous fluid and ocean flows. The dynamically orthogonal (DO) field equations provide an adaptive methodology to predict the probability density functions of such flows. The present work derives efficient computational schemes for the DO methodology applied to unsteady stochastic Navier-Stokes and Boussinesq equations, and illustrates and studies the numerical aspects of these schemes. Semi-implicit projection methods are developed for the mean and for the DO modes, and time-marching schemes of first to fourth order are used for the stochastic coefficients. Conservative second-order finite-volumes are employed in physical space with new advection schemes based on total variation diminishing methods. Other results include: (i) the definition of pseudo-stochastic pressures to obtain a number of pressure equations that is linear in the subspace size instead of quadratic; (ii) symmetric advection schemes for the stochastic velocities; (iii) the use of generalized inversion to deal with singular subspace covariances or deterministic modes; and (iv) schemes to maintain orthonormal modes at the numerical level. To verify our implementation and study the properties of our schemes and their variations, a set of stochastic flow benchmarks are defined including asymmetric Dirac and symmetric lock-exchange flows, lid-driven cavity flows, and flows past objects in a confined channel. Different Reynolds number and Grashof number regimes are employed to illustrate robustness. Optimal convergence under both time and space refinements is shown as well as the convergence of the probability density functions with the number of stochastic realizations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Fluid preconditioning for Newton–Krylov-based, fully implicit, electrostatic particle-in-cell simulations

A recent proof-of-principle study proposes an energy- and charge-conserving, nonlinearly implicit electrostatic particle-in-cell (PIC) algorithm in one dimension [9]. The algorithm in the reference employs an unpreconditioned Jacobian-free Newton–Krylov method, which ensures nonlinear convergence at every timestep (resolving the dynamical timescale of interest). Kinetic enslavement, which is one key component of the algorithm, not only enables fully implicit PIC as a practical approach, but also allows preconditioning the kinetic solver with a fluid approximation. This study proposes such a preconditioner, in which the linearized moment equations are closed with moments computed from particles. Effective acceleration of the linear GMRES solve is demonstrated, on both uniform and non-uniform meshes. The algorithm performance is largely insensitive to the electron–ion mass ratio. Numerical experiments are performed on a 1D multi-scale ion acoustic wave test problem.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A hyperbolic-equation system approach for magnetized electron fluids in quasi-neutral plasmas

A new approach using a hyperbolic-equation system (HES) is proposed to solve for the electron fluids in quasi-neutral plasmas. The HES approach avoids treatments of cross-diffusion terms which cause numerical instabilities in conventional approaches using an elliptic equation (EE). A test calculation reveals that the HES approach can robustly solve problems of strong magnetic confinement by using an upwind method. The computation time of the HES approach is compared with that of the EE approach in terms of the size of the problem and the strength of magnetic confinement. The results indicate that the HES approach can be used to solve problems in a simple structured mesh without increasing computational time compared to the EE approach and that it features fast convergence in conditions of strong magnetic confinement.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A flux-splitting method for hyperbolic-equation system of magnetized electron fluids in quasi-neutral plasmas

A flux-splitting method is proposed for the hyperbolic-equation system (HES) of magnetized electron fluids in quasi-neutral plasmas. The numerical fluxes are split into four categories, which are computed by using an upwind method which incorporates a flux-vector splitting (FVS) and advection upstream splitting method (AUSM). The method is applied to a test calculation condition of uniformly distributed and angled magnetic lines of force. All of the pseudo-time advancement terms converge monotonically and the conservation laws are strictly satisfied in the steady state. The calculation results are compared with those computed by using the elliptic–parabolic-equation system (EPES) approach using a magnetic-field-aligned mesh (MFAM). Both qualitative and quantitative comparisons yield good agreements of results, indicating that the HES approach with the flux-splitting method attains a high computational accuracy.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A stochastic asymptotic-preserving scheme for a kinetic-fluid model for disperse two-phase flows with uncertainty

In this paper we consider a kinetic-fluid model for disperse two-phase flows with uncertainty. We propose a stochastic asymptotic-preserving (s-AP) scheme in the generalized polynomial chaos stochastic Galerkin (gPC-sG) framework, which allows the efficient computation of the problem in both kinetic and hydrodynamic regimes. The s-AP property is proved by deriving the equilibrium of the gPC version of the Fokker–Planck operator. The coefficient matrices that arise in a Helmholtz equation and a Poisson equation, essential ingredients of the algorithms, are proved to be positive definite under reasonable and mild assumptions. The computation of the gPC version of a translation operator that arises in the inversion of the Fokker–Planck operator is accelerated by a spectrally accurate splitting method. Numerical examples illustrate the s-AP property and the efficiency of the gPC-sG method in various asymptotic regimes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗