Packed beds dynamic fluid

Solid Desiccants. The sohd desiccants used in dynamic appHcations fad into a class caded adsorbents (see Adsorption). Because they are used in large packed beds through which the gas or Hquid to be treated is passed, the adsorbents are formed into soHd shapes that adow them to withstand the static (fluid plus sohd head) and dynamic (pressure drop) forces imposed on them. The most common shapes are granules, extmded pedets, and beads. 

Equation 6-108 is also a good approximation for a fluidized bed reactor up to the minimum fluidizing condition. However, beyond this range, fluid dynamic factors are more complex than for the packed bed reactor. Among the parameters that influence the AP in a fluidized bed reactor are the different types of two-phase flow, smooth fluidization, slugging or channeling, the particle size distribution, and the... 

Three-dimensional electrodes are configured as static or solid electrodes (porous or packed bed), or as dynamic or fluid bed electrodes (fluidized bed and moving bed), cf. Table 6. 

Appendix B consists of a systematic classification and review of conceptual models (physical models) in the context of PBC technology and the three-step model. The overall aim is to present a systematic overview of the complex and the interdisciplinary physical models in the field of PBC. A second objective is to point out the practicability of developing an all-round bed model or CFSD (computational fluid-solid dynamics) code that can simulate thermochemical conversion process of an arbitrary conversion system. The idea of a CFSD code is analogue to the user-friendly CFD (computational fluid dynamics) codes on the market, which are very all-round and successful in simulating different kinds of fluid mechanic processes. A third objective of this appendix is to present interesting research topics in the field of packed-bed combustion in general and thermochemical conversion of biofuels in particular. 

The combustion system and the boiler system of a PBC system, according to the three-step model, can be modelled by means of CFD codes [4,5]. However, an allround bed model [6,7] to simulate the thermochemical conversion of the solid fuel inside the conversion system does not yet exist. Bed models of the conversion system will herein also be referred to as CFSD code computational fluid-solid dynamics), analogue to the CFD code. From the three-step model point of view, it is clear that without a CFSD code simulating the thermochemical conversion of the packed bed in the conversion system, simulation of the whole PBC system can never be completely successful. 

The long-term goal in the science of thermochemical conversion of a solid fuel is to develop comprehensive computer codes, herein referred to as a bed model or CFSD (computational fluid-solid dynamics). Firstly, this CFSD code must be able to simulate basic conversion concepts, with respect to the mode, movement, composition and configuration of the fuel bed. The conversion concept has a great effect on the behaviour of the thermochemical conversion process variables, such as the molecular composition and mass flow of conversion gas. Secondly, the bed model must also consider the fuel-bed structure on both micro- and macro-scale. This classification refers to three structures, namely interstitial gas phase, intraparticle gas phase, and intraparticle solid phase. Commonly, a packed bed is referred to as a two-phase system. 

The up-scaling from microreactor to small monoliths principally deals with the change of geometry (from powdered to honeycomb catalyst) and fluid dynamics (from turbulent flow in packed-bed to laminar flow in monolith channels). In this respect, it involves therefore moving closer to the conditions prevailing in the real full-scale monolithic converter, while still operating, however, under well controlled laboratory conditions, involving, e.g. the use of synthetic gas mixtures. 

In most adsorption processes the adsorbent is contacted with fluid in a packed bed. An understanding of the dynamic behavior of such systems is therefore needed for rational process design and optimization. What is required is a mathematical model which allows the effluent concentration to be predicted for any defined change in the feed concentration or flow rate to the bed. The flow pattern can generally be represented adequately by the axial dispersed plug-flow model, according to which a mass balance for an element of the column yields, for the basic differential equation governing llie dynamic behavior,... 

To consolidate the experimental screening data quantitatively it is desirable to obtain information on the fluid mechanics of the reactant flow in the reactor. Experimental data are difficult to evaluate if the experimental conditions and, especially, the fluid dynamic behavior of the reactants flow are not known. This is, for example, the case in a typical tubular reactor filled with a packed bed of porous beads. The porosity of the beads in combination with the unknown flow of the reactants around the beads makes it difficult to describe the flow close to the catalyst surface. A way to achieve a well-described flow in the reactor is to reduce its dimensions. This reduces the Reynolds number to a region of laminar flow conditions, which can be described analytically. 

In adiabatically operated industrial hydrogenation reactors temperature hot spots have been observed under steady-state conditions. They are attributed to the formation of areas with different fluid residence time due to obstructions in the packed bed. It is shown that in addition to these steady-state effects dynamic instabilities may arise which lead to the temporary formation of excess temperatures well above the steady-state limit if a sudden local reduction of the flow rate occurs. An example of such a runaway in an industrial hydrogenation reactor is presented together with model calculations which reveal details of the onset and course of the reaction runaway. 

The holdup of a phase is usually defined as the volume of the phase per unit reactor volume. However, for a fixed-bed reactor, the gas and liquid holdups are often defined on the basis of void volume of the reactor. In a fixed-bed reactor, the liquid and sometimes gas holdups are divided into two parts dynamic holdup, which depends largely on the gas and liquid flow rates and the properties of the fluids and the packing material, and static holdup, which depends to a major extent on the nature of the packing (e.g., porosity of the packing) and the fluids properties. The relationships between the holdups of various phases and the system variables for a variety of three-phase reactors are discussed in Chaps. 6 through 9. 

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. 

Cells with three-dimensional electrodes providing enlarged specific electrode area and improved mass transport due to the specific fluid dynamics inside the three-dimensional structure are, for example, the porous flow-through cell [68], the RETEC (RETEC is a trademark of ELTECH Systems Inc., Cardon, Ohio) cell [15], the packed-bed cell [69-71],... 

A chromatogram is influenced by several factors, such as the fluid dynamics inside the packed bed, mass transfer phenomena and, most importantly, the equilibrium of the adsorption at the temperature of the system. 

Microscopic fluid distribution non-ideality is caused by fluid dynamic adhesion between the fluid and the adsorbent particle inside the microscopic channels of the packed bed. Adhesion results in a higher fluid velocity in the middle of the channel than at the channel walls (Fig. 2.9a). Solute molecules in the middle of the channel thus have a shorter retention time than those at the channel walls. 

In laminar flow and for a given fluid with constant dynamic viscosity, rj, and density, the pressure drop is inversely proportional to the square of the particle diameter dp and increases linearly with the length of the packed bed, Lbed, and the superficial velocity of the flowing fluid, u. The porosity, e, in packed beds depends on the particle shape and the particle size distribution, and is typically e 0.5. 

The third major factor in dynamics is packed bed flow behavior. The pressure drop in the adsorbent media is caused by drag due to fluid flowing through the interstices. For slow flow, the pressure drop, AP, across a bed of length Az and superflcial velocity v, can be represented by Darcy s equation ... 

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