Computational fluid dynamics configuration

The equations implemented are those defined in Sections 3.2-3.4, i.e. in a partial differential form, for each cell component. This approach is also referred to as Computational Fluid Dynamic (CFD). In order to illustrate the capabilities of the model, in terms of assessment of particular phenomena taking place within the fuel cell, one particular problem is analyzed for each geometry. In particular, for the disk-shaped cell, emphasis is put on the effect of the gas channel configuration on the gas distribution, and, ultimately, on the resulting performance. For the tubular geometry, three different options for the current collector layouts are analyzed. 

Another important modeling aspect is the simulation of catalytic process parameters and reactor configurations. Such models are typically associated with process engineering, and involve computational fluid dynamics and heat- and mass-transfer calculations. They are essential in the process planning and scale-up. However, as this book deals primarily with the chemical aspects of catalysis, the reader is referred to the literature on industrial catalysis and process simulations for further information [49,56]. 

For ease of fabrication and modular construction, tubular reactors are widely used in continuous processes in the chemical processing industry. Therefore, shell-and-tube membrane reactors will be adopted as the basic model geometry in this chapter. In real production situations, however, more complex geometries and flow configurations are encountered which may require three-dimensional numerical simulation of the complicated physicochemical hydrodynamics. With the advent of more powerful computers and more efficient computational fluid dynamics (CFD) codes, the solution to these complicated problems starts to become feasible. This is particularly true in view of the ongoing intensified interest in parallel computing as applied to CFD. 

In real production situations where geometric complexity and flow configurations warrant three-dimensional numerical simulations, computational fluid dynamic codes may be required to capture the complicated physicochemical hydrodynamics. This approach may begin to become feasible with the availability of powerful computers and efficient numerical algorithms. 

For the coarse estimation of extruder size and screw speed, simple mass and energy balances based on a fixed output rate can be used. For the more detailed design of a twin-screw extruder configuration it is necessary to combine implicit experience knowledge with simulation techniques. Theses simulation techniques cover a broad range from specialized programs based on very simple models up to detailed Computational Fluid Dynamics (CFD) driven by Finite Element Analysis (FEA) or Boundary Element Method (BEM). 

Hardt et al. [49] reached a similar conclusion, using computational fluid dynamics to study the effect of various fin configurations, as well as the effect of heat exchanger material conductivity on the overall performance of the microstructured equipment. 

Huang, L. X., Kumar, K., and Mujumdar, A. S. 2003. Use of computational fluid dynamics to evaluate alternative spray chamber configurations. Drying Technol. 21 385-412. 

The unexpected results of Sablani et al. [17] (i.e., less turbulence with smaller spacer thickness) may be best explained by an excellent paper by Schwinge et al. [82], The latter employed computational fluid dynamics (CFD) in a study of unsteady flow in narrow spacer-filled channels for spiral-wound membrane modules. The flow patterns were visualized for different filament configurations incorporating variations in mesh length and filament diameter and for channel Reynolds numbers, Re y, up to 1000. The simulated flow patterns revealed the dependence of the formation of... 

The conception, optimization, extrapolation or mastering of a GPTR necessitates first of all the elaboration of a reaction model, then its incorporatation into a code of Computational Fluid Dynamics (CFD) in order to carry out simulations of the phenomenon being studied under different operating conditions of composition, of pressure, of temperature, with different reactant loads, and for different reactor geometries. The analysis of the results of the simulations then allows the optimum reactant-reaction-reactor-product configuration to be determined or the phenomenon to be extrapolated. 

Computational fluid dynamics models were developed over the years that include the effects of leaflet motion and its interaction with the flowing blood (Bellhouse et al., 1973 Mazumdar, 1992). Several finite-element structural models for heart valves were also developed in which issues such as material and geometric nonlinearities, leaflet structural dynamics, stent deformation, and leaflet coaptation for closed valve configurations were effectively dealt with (Bluestein and Einav, 1993 1994). More recently, fluid-structure interaction models, based on the immersed boundary technique. 

Surface-Directed Capillaiy Row Systems, Rgure 1 Surface-directed microfluidic device fabricated via sol gel processing (a) with a demonstration of the configuration of device and (b) the implementafon of the device with colored fluid for visualization [9]. (c) Computational fluid dynamic representation of the fluid front of a device fabricated with a patterned bottom substrate and indiscriminately hydrophobic top substrate, (d) The implementation of the device with an unpatterned top substrate [ ]... 

Multiple impellers can be used as shown in Figure 22-12. The configuration shown in this computational fluid dynamics (CFD) simulation uses three high solidity, up-pumping axial flow impellers. The simulation shows the flow pattern by depicting the flow of neutral density particles (Weetman, 1998a). Other impeller types are discussed in Chapter 6. 

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