Computational fluid dynamics case studies

A numerical study of the effect of area ratio on the flow distribution in parallel flow manifolds used in a Hquid cooling module for electronic packaging demonstrate the useflilness of such a computational fluid dynamic code. The manifolds have rectangular headers and channels divided with thin baffles, as shown in Figure 12. Because the flow is laminar in small heat exchangers designed for electronic packaging or biochemical process, the inlet Reynolds numbers of 5, 50, and 250 were used for three different area ratio cases, ie, AR = 4, 8, and 16. 

Alamdari, F., Edwards, S. C., and Hammond, S. P., Microclimate performance of an open atrium office building A case study in thermo-fluid modeling. In Computational Fluid Dynamics for the Environmental and Building Services Engineer—Tool or Toy , The Institution of Mechanical Engineers, London, 1991, p- 81. 

Computational fluid dynamics (CFD) approach has become a standard tool for analyzing various situations where fluid flow has an effect on the studied processes. Numerous studies using CFD for chemical process industry have also been reported. Mostly, they have been simple cases as the system is non-reacting, contains only one phase (liquid or gas), or physical properties are assumed constant. When we are dealing with multiphase systems like gas-liquid or liquid-liquid systems we must take into account some phenomena which are not of importance for one-phase systems. The vapor-liquid or liquid-liquid equilibrium is one of these that are needed in order to model the system. In addition to that, mass and heat transfer between the phases must generally be taken into account. Also, the two-phase characteristics of fluid flow need to be taken into consideration in the CFD models. 

The case study presented here shows that computational fluid dynamics and process simulation technologies are highly complementary, and that fliere are clear benefits to be gained from a close integration of the two. 

Various techniques determining loading from explosions (TNT equivalent, multienergy methods, Baker-Strehlow method and computational fluid dynamics) are available, mainly developed for hazard studies for chemical plants [24]. In the case of solid detonation, the TNT equivalent technique is the most widely used approach. In the case of a gas or vapour cloud, the elevation of the explosion and the reaction characteristics may suggest other approaches. 

Now, from its essential notion, we have the feedback interconnection implies that a portion of the information from a given system returns back into the system. In this chapter, two processes are discussed in context of the feedback interconnection. The former is a typical feedback control systems, and consists in a bioreactor for waste water treatment. The bioreactor is controlled by robust asymptotic approach [33], [34]. The first study case in this chapter is focused in the bioreactor temperature. A heat exchanger is interconnected with the bioreactor in order to lead temperature into the digester around a constant value for avoiding stress in bacteria. The latter process is a fluid mechanics one, and has feedforward control structure. The process was constructed to study kinetics and dynamics of the gas-liquid flow in vertical column. In this second system, the interconnection is related to recycling liquid flow. The experiment comprises several superficial gas velocity. Thus, the control acting on the gas-liquid column can be seen as an open-loop system where the control variable is the velocity of the gas entering into the column. There is no measurements of the gas velocity to compute a fluid dynamics... 

The radial distribution function plays an important role in the study of liquid systems. In the first place, g(r) is a physical quantity that can be determined experimentally by a number of techniques, for instance X-ray and neutron scattering (for atomic and molecular fluids), light scattering and imaging techniques (in the case of colloidal liquids and other complex fluids). Second, g(r) can also be determined from theoretical approximations and from computer simulations if the pair interparticle potential is known. Third, from the knowledge of g(r) and of the interparticle interactions, the thermodynamic properties of the system can be obtained. These three aspects are discussed in more detail in the following sections. In addition, let us mention that the static structure is also important in determining physical quantities such as the dynamic an other transport properties. Some theoretical approaches for those quantities use as an input precisely this structural information of the system [15-17,30,31]. 

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