Computational fluid dynamics correlative

Computational fluid dynamics (CFD) programs are more specialized, and most have been designed to solve sets of equations that are appropriate to specific industries. They can then include approximations and correlations for some features that would be difficult to solve for directly. Four major packages widely used are Fluent (http //www.fluent.com/), CFX (now part of ANSYS), Comsol Multiphysics (formerly FEMLAB) (http //www.comsol.com/), and ANSYS (http //www.ansys.com/). Of these, Comsol Multiphysics is particularly useful because it has a convenient graphical-user interface, permits easy mesh generation and refinement (including adaptive mesh refinement), allows the user to add phenomena and equations easily, permits solution by continuation methods (thus enhancing... 

Over recent years, a great deal of numerical modeling work has been carried out using computational fluid dynamics to derive particle charging models " however, the basic models need experimental support because the equations cannot be analytically solved. A reasonable alternative to modeling is proposed by Cochet, " who developed an equation, which appears to give reasonable correlation to actual precipitator measurements in the critical size range, as tested and reported by Hewitt. 

The majority of models for treating fireballs is based on correlations for its diameter and duration [2, 40]. More fundamental models are discussed in [2] and the application of methods of computational fluid dynamics ( CFD ) to fireballs is treated, for example, in [41]. 

Beginning with fundamentals of fluid dynamics, correlations for the pressure loss in channel elements are presented, which are concatenated to fluidic networks to distribute fluid homogeneously over a certain area. Computational fluid dynamic (CFD) simulations of single elements are exploited for analytical pressure loss correlations. These are employed in lumped element modeling of networks and manifolds, which are too complex for direct simulations. Design strategies and methods are presented for charmel networks, manifolds for parallel channels on a plate and headers for stacked-plate devices. 

The comparison of the experimental results with computational fluid dynamics calculations of the gas flow indicates a clear correlation of the flow model behavior with the appearance of recirculation loops in the reaction chamber and the effect of the gas jet at the entrance of the gas-liquid contact zone (Figure 14.4). The latter considerably increases the mixing in the gas phase and prevents the development of plug-flow behavior in the gas phase. 

Solving the full Navier-Stokes equations in the channels requires a rigorous computational fluid dynamics (CFD) simulation. During transient operation, such as start-up and shut-down, the flow fields can have a significant effect on the concentration and temperature profiles in the system. Under normal operation, it may be desirable to assume fuUy developed laminar flow to reduce the computational time and quickly estimate flow parameters based on fluid dynamics correlations. 

Gas-liquid mixed tanks are used for various operations in industrial practise. The design of gas-liquid mixing units and reactors is still done by empirical correlations, which are usually valid for specific components, mixing conditions and geometries. Computational Fluid Dynamic (CFD) techniques have been used successfully for single-phase flow, but gas-liquid flow calculations are still tedious for computers. Therefore, simpler and more accurate multiphase models are needed. In order to verify multiphase CFD calculations and to fit unknown parameters in the multiphase models, experimental local bubble size distributions and flow patterns are needed. 

Not only are these tools important for injector development, they also provide critical information used as inputs for computational fluid dynamics (CFD) analysis. As mentioned previously, simulation plays a critical role in SCR system development. The more accurate the measurements are while quantifying an injector s spray quality, the more accurate the simulated spray quality will be which will in turn give better correlation between simulation and hardware testing. 

To date, the design of three-phase fluidized beds still relies heavily on experimental observations, empirical correlations, and engineering models. With increasing computer power, the employment of the computational fluid dynamics approach has gained consider-... 

The model presented here is a significant step forward in the simulation of fixed bed catalytic reactors. It is an early computational fluid dynamics (CFD) model of the continuum type. In recent years supercomputers have led to an increased application of CFD to studies of heat transfer in packed beds. In modeling the fluid flow in the voids confined by the catalyst particles, Nijemeisland and Dixon [2004] investigated the possibility of deriving values for the heat transfer coefficient between the bed and the wall in terms of the local properties of the flow field, but found no statistically valid correlation. They... 

Empirical correlations for the key aspects of mixing, such as power consumption, emulsification, liquid circulation, and mixing time, can be found elsewhere [111]. The advances in computational fluid dynamics (CFD) combined with new techniques of measuring the local flow pattern are likely to transform the whole field. 

There are in general several steps of refinement to model a gasification system. Zero-dimensional models show the lowest complexity, and rely on empirical correlations or thermodynamic equilibrium calculations. The next step is a onedimensional model that usually requires kinetic expressions either to resolve the space or time coordinate using idealized chemical reactor models. Approaching two- or three-dimensional calculations provokes the use of computational fluid dynamics (CFD) that may incorporate either equiUbriiun or kinetics-based turbulence chemistry interactions. Each step of modeling adds significant complexity and calculation time. 

Multiscale descriptions of particle-droplet interactions in spray processing of composite particles are realized based on Multiphase Computational Fluid Dynamics (M-CFD) models, in which processes such as liquid atomization and particle-droplet mixing spray (macro-scale), particle-droplet collision (mesoscale), and particle penetration into droplet (micro-scale) are taken into account as shown in Fig. 18.52. Thereby, the incorporation efficiency and sticking efficiency of solid particles in matrix particles are correlated with the operatiOTi conditions and material properties. 

Adsorption process has been widely used in many chemical and related industries, such as the separation of hydrocarbon mixtures, the desulfurization of natural gas, and the removal of trace impurities in fine chemical production. Most of the adsorption researches in the past are focused on the experimental measurement of the breakthrough curve for studying the dynamics. The conventional model used for the adsorption process is based on one-dimensional or two-dimensional dispersion, in which the adsorbate flow is either simplified or computed by using computational fluid dynamics (CFD), and the distribution of adsorbate concentration is obtained by adding dispersion term to the adsorption equation with unknown turbulent mass dififusivity D(. Nevertheless, the usual way to find the D, is either by employing empirical correlation obtained from inert tracer experiment or by guessing a Schmidt number applied to the whole process. As stated in Chap. 3, such empirical method is unreliable and lacking theoretical basis. 

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