Design of mixing systems

The following procedure may be adopted in the design of a mixing vessel for a given process. 

Mixer data sheet (procede. Eauipmettt No. (Tael  

TIME ACTUALLY MIXING CONTIN. DUTY INTERMIT. DUTY 1 1 6 

OF SETS OF BLADES PI RCTRICITV SUPPLY Volts phase Hz 26 

CRITICAL SPEED RECOMMENDED MOTOR POWER (UPi1 w ) 29 

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Doran, P. M. (1999). Design of mixing systems for plant cell suspensions in stirred reactors, Biotechnol. Prog. 15,319—335. 

Method of Adding Liquids When the addition of hquids may be desirable (see Dust Formation and Elec trostatic Charge ), this should be considered when designing the mixing system rather than hastily improvised. The purpose of the liquid shomd be considered, whether for (I) dust suppression, (2) product, or (3) heating and cooling. If a viscous hquid must be well distributed, this requirement should be considered when choosing the mixer. 

This is another common processing operation, usually for chemical reactions and neutralizations or other mass transfer functions. Pilot plant or research data are.needed to accomplish a proper design or scale-up. Therefore, generalizations can only assist in alerting the designer as to what type of mixing system to expect. 

An important aspect of studying metastable dissociation of these clusters is that the measurements enable a determination of the surface composition of mixed systems. This is important in designing experiments to study the heterogeneous chemistry of aqueous systems. For example, the loss channel of H20 is found to be open to all (H20)n(CH30H)mH+ except (H20)(CH3OH)mH+ for which the water loss is relatively small. For the water-rich composition mixed clusters, the results show that water molecules have a tendency to build a cage structure in the cluster size region m + n = 21, with 0 < m < 8. 

This chapter introduces the reader to elementary concepts of modeling, generic formulations for nonlinear and mixed integer optimization models, and provides some illustrative applications. Section 1.1 presents the definition and key elements of mathematical models and discusses the characteristics of optimization models. Section 1.2 outlines the mathematical structure of nonlinear and mixed integer optimization problems which represent the primary focus in this book. Section 1.3 illustrates applications of nonlinear and mixed integer optimization that arise in chemical process design of separation systems, batch process operations, and facility location/allocation problems of operations research. Finally, section 1.4 provides an outline of the three main parts of this book. 

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