In the context of attempts to improve the protection of the environment, a novel process where the carbon dioxide reacts rapidly with almost 100 % conversion under mild conditions, is proposed. The chemisorptive process takes place in a slurry bubble column which operates with countercurrent flow, utilizing special solutions of primary long chain amines in a nonaqueous media. The product obtained is insoluble and separated by filtration. Because of its molecular structure, this product possesses tenside properties and can be used as an industrial additive. Typically the liquid phase consists of a mixture of hexadecylamine (C 16 H 33 NH 2 ) or dodecylamine (C 12 H 25 NH 2 ) in various concentrations with methanol or other alcohols as the solvent. Numerous parameters have been studied including different column heights, gas inlet compositions, gas flow rates and solvent type. Efficiencies of up to 99 % are achievable for CO 2 absorption with methanol as the solvent. The second solvent examined, isopropanol, shows lower CO 2 conversion rates. This can be attributed to its physical properties, mainly higher viscosity and hence, smaller mass transfer coefficient. In order to simulate real gas conditions, the influence of other sour gases, e.g., SO 2 was also investigated experimentally. Because of coabsorption of the two gases, the CO 2 efficiency was lower in this instance. In both solvents, the absorption efficiency with respect to SO 2 is more than 99 % due to its high solubility and reactivity. A complex mathematical model has been developed and applied to describe the mass and enthalpy transport in the reactive bubble column.

No abstract

No abstracts.

The ProblemCompared with the conventional configuration, complex distillation columns make for a marked reduction of the energy requirements of multi-component rectification systems. In the case of the particularly interesting dividing-wall column, i.e., of the special Petlyuk arrangement [1] in a column shell described by Kaibel [2], the following savings can be achieved in individual cases [3,4]: ± Investment costs:± 25 % ± Operating costs:± 35 % ± Space requirements: ± 40 % In the past, the problems encountered with complex rectification systems were the relatively difficult design and control. Whereas the control problems have, on the whole, been resolved, the ability to find the process-technological optimum of a complex distillation system within a short space of time still presents difficulties. The solution can frequently be found only with a high degree of mathematical effort on the basis of independent systems without using existing standard software [5,6].The aim of this paper is, therefore, to reduce the time required for finding the optimum design with the aid of commercial standard software. Fig. 1 illustrates the complexity of the problem of designing a dividing-wall column. The definition of the geometrical and operational degree of freedom [7] shows that the steady-state design of a dividing-wall column is more difficult than dynamic control, because considerably more free variables exist during the design phase (number of theoretical stages). Description of the SystemTo obtain a first estimate of the design of a dividing-wall column, a short-cut model is used, which is also capable of calculating the annual overall costs of the other distillation systems shown in Fig. 2. Such a rough estimate is followed by a rigorous calculation. Overall Cost Optimization ± GeneralIn order to achieve the best possible compatibility with simulations of already existing processes at Messrs UHDE, it was decided at the commencement of work to use the Aspen Plus software. This also permits access to the extensive Aspen properties data base.One of the problems of optimizing with the aid of Aspen Plus is the existence of both integer and real variables. The number of theoretical stages in the segments of the distillation column cannot be varied in the rigorous simulation using the optimization algorithms integrated in Aspen Plus. CommunicationsOne method used was, therefore, a short-cut method, which yields the number of theoretical stages. Moreover, this method is characterized by good convergence behavior and short computing times. However, it is not suitable for highly non-ideal material systems [8].The second method is the rigorous calculation, in which the integer and real variables are provided by a modern type of evolutionary algorithm (EA), of the Institute for Neurocomputing of the Ruhr University Bochum. The result obtained is a precise optimum design for all systems, including non-ideal systems [9]. Optimization ProcedureThe following optimization procedure is used for both methods:i. System initialization...

No abstract