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Separation computation fluid dynamics modeling

The simple analytical models discussed below demonstrate that in many cases, the cell operation depends on a composite of several parameters, rather than on the separate terms (factors) of this composite. This greatly lowers the dimensionahty of the parameter space. Analytical models explicitly show the parametric dependences, indicating the direction to a cheap and robust fuel cell in this space. These models can be used to characterize the cells. Further, analytical models serve as building blocks for growing hybrid analytical + computational fluid dynamics modeling of cells and stacks. [Pg.648]

Advantages of a new burner concept were developed for the FlammaTec Flex Burner in the years 2006 and 2007. The Flex Burner utilizes two (2) fully separate gas inlets and gas flows into the burner which would be controlled and measured independently. The burner tip was optimized utilizing computational fluid dynamic modeling to minimize turbulence at the burner tip. The burner nozzle was also designed to be fully adjustable. Hence, the new burner design offered some technological advanti es. [Pg.92]

The highest level of integration would be to establish one large set of equations and to apply one solution process to both thermal and airflow-related variables. Nevertheless, a very sparse matrix must be solved, and one cannot use the reliable and well-proven solvers of the present codes anymore. Therefore, a separate solution process for thermal and airflow parameters respectively remains the most promising approach. This seems to be appropriate also for the coupling of computational fluid dynamics (CFD) with a thermal model. ... [Pg.1096]

There have been several studies in which the flow patterns within the body of the cyclone separator have been modelled using a Computational Fluid Dynamics (CFD) technique. A recent example is that of Slack et a/. 54 in which the computed three-dimensional flow fields have been plotted and compared with the results of experimental studies in which a backscatter laser Doppler anemometry system was used to measure flowfields. Agreement between the computed and experimental results was very good. When using very fine grid meshes, the existence of time-dependent vortices was identified. These had the potentiality of adversely affecting the separation efficiency, as well as leading to increased erosion at the walls. [Pg.75]

The key reactive separation topics to be addressed in the near future are a proper hydrodynamic modeling for catalytic internals, including residence time distribution account and scale-up methodology. Further studies on the hydrodynamics of catalytic internals are essential for a better understanding of RSP behavior and the availability of optimally designed catalytic column internals for them. In this regard, the methods of computational fluid dynamics appear very helpful. [Pg.362]

Computational fluid dynamics were used to describe the flow which undergoes a fast transition from laminar (at the fluid outlets) to turbulent (in the large mixing chamber) [41]. Using the commercial tool FLUENT, the following different turbulence models were applied a ke model, an RNC-ki model and a Reynolds-stress model. For the last model, each stream is solved by a separate equation for the two first models, two-equation models are applied. To have the simulations at... [Pg.119]

Thus, expectedly no rigorous mathematical models are available that can accurately describe the detailed flow behavior of the fluid streams in a membrane separation process or membrane reactor process. Recent advances in computational fluid dynamics (CFD), however, have made this type of problem amenable to detailed simulation studies which will assist in efficient design of optimal membrane filtration equipment and membrane reactors. [Pg.488]

Takeuchi et al. 7 reported a membrane reactor as a reaction system that provides higher productivity and lower separation cost in chemical reaction processes. In this paper, packed bed catalytic membrane reactor with palladium membrane for SMR reaction has been discussed. The numerical model consists of a full set of partial differential equations derived from conservation of mass, momentum, heat, and chemical species, respectively, with chemical kinetics and appropriate boundary conditions for the problem. The solution of this system was obtained by computational fluid dynamics (CFD). To perform CFD calculations, a commercial solver FLUENT has been used, and the selective permeation through the membrane has been modeled by user-defined functions. The CFD simulation results exhibited the flow distribution in the reactor by inserting a membrane protection tube, in addition to the temperature and concentration distribution in the axial and radial directions in the reactor, as reported in the membrane reactor numerical simulation. On the basis of the simulation results, effects of the flow distribution, concentration polarization, and mass transfer in the packed bed have been evaluated to design a membrane reactor system. [Pg.33]

Computational fluid dynamics based flow models were then developed to simulate flow and mixing in the loop reactor. Even here, instead of developing a single CFD model to simulate complex flows in the loop reactor (gas dispersed in liquid phase in the heater section and liquid dispersed in gas phase in the vapor space of the vapor-liquid separator), four separate flow models were developed. In the first, the bottom portion of the reactor, in which liquid is a continuous phase, was modeled using a Eulerian-Eulerian approach. Instead of actually simulating reactions in the CFD model, results obtained from the simplified reactor model were used to specify vapor generation rate along the heater. Initially some preliminary simulations were carried out for the whole reactor. However, it was noticed that the presence of the gas-liquid interface within the solution domain and inversion of the continuous phase. [Pg.268]

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. [Pg.185]

Initially, the void space between the particles is completely filled with liquid ( = 0 for all voxels). Evaporation from the liquid-gas interface and liquid relaxation into capillary equilibrium are then computed in an alternating sequence. For this simulation we assume a scale separation in time, i.e., that the evaporation occurs on a much slower time scale than the liquid motion. We resolve only the evaporation time scale, which yields a quasi-static approach in each evaporation step, liquid is removed according to the local evaporation rates computed from the solution of the vapor diffusion problem in the gas phase. Then the liquid is relaxed to the capillary equilibrium by volume-preserving mean curvature flow. This quasi-static approach is in contrast to a fully dynamic simulation (via computational fluid dynamics), but may come with considerably lower computational cost. Evaporation is modeled by vapor diffusion in the gas phase, with a no-flux condition at solid-gas interfaces and equilibrium vapor pressure imposed on liquid-gas interfaces (for more details, see [15]). The equilibrium liquid disttibution... [Pg.100]

In general, simulation methods can be divided into those that use a computer and those that do not, as shown in Fig. 14.1. Those simulations without computer can be separated into destructive and nondestructive methods. Simulations that use a computer can either be based on technical models (for example, finite element method for structural composites, computational fluid dynamics for polymer flows), on examples taken from nature (for example, artificial neural networks, evolutionary algorithms for machine setting optimization), and those based on analytical equations (for example, warp tension during weaving). [Pg.397]

One important assumption in models predicting cyclone flow pattern and separation performance is that the surface CS defines the boundary between axial upflow and downflow. We can test this both experimentally and by CFD. We shall discuss CFD (computational fluid dynamics) for cyclone modeling in Chap. 7. [Pg.78]

We have examined some of the most widely acclaimed and cited cyclone models. There is one more way of predicting the flow pattern, pressure drop and the separation efficiency in cyclones and swirl tubes, however by Computational Fluid Dynamics, or CFD for short. [Pg.139]

This feattire conducts water and salt removal. The vanes, which are constructed from corrosion-resistant marine grade aluminum (other materials are available), are produced with a profile that allows the maximum removal of salt and water, yet produces an extremely low pressure loss. This optimal profile has been achieved by the very latest design methods, and in particular by utilizing a Computational Fluid Dynamics (CFD) flow modeling system. Hydra also incorporates a unique and novel method of separating water droplets from the air stream, and this has led to improvements in bulk water removal compared with conventional methods. [Pg.101]

This contribution outlines a multiscale simulation approach for analysis of a Wurster coating process occurring in a fluidized bed. The processes occurring in the apparatus are described on four different time and length scales The Discrete Element Method coupled with Computational Fluid Dynamics, where each particle is considered as a separate entity and its motion in fluid field is calculated, play a central role in the modeling framework. On the macroscale, the Population Balance Model describes the particle... [Pg.83]

Van Vlimmeren, B.A.C., Fraaije, J.G.E.M. Calculation of noise distribution in mesoscopic dynamics models for phase-separation of multicomponent complex fluids. Comput. Phys. Comm. 99 (1996) 21-28. [Pg.36]


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