Download 19 European Symposium on Computer Aided Process Engineering by Jacek Jezowski, Jan Thullie PDF

By Jacek Jezowski, Jan Thullie

The nineteenth eu Symposium on computing device Aided procedure Engineering includes papers awarded on the nineteenth ecu Symposium of machine Aided strategy Engineering (ESCAPE 19) held in Cracow, Poland, June 14-17, 2009.The get away sequence serves as a discussion board for scientists and engineers from academia and to debate growth accomplished within the region of CAPE. * CD-ROM that accompanies the booklet includes all study papers and contributions * foreign in scope with visitor speeches and keynote talks from leaders in technological know-how and * provides papers masking the newest examine, key most sensible components and advancements in computing device aided procedure engineering (CAPE)

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Keywords: process synthesis, process synthesizer, MIPSYN, synthesizer shell, MINLP. 1. Introduction Our global system is currently facing financial, production, social and environmental crisis. Globalization alone with increasing competition has thus proved to be insufficient for fostering steady economics. On the contrary, globalization based on unsustainable principles can only deepen and prolong the crisis. The community strives for sustainable development in general and sustainable chemical and bio-chemical industries in particular.

M. Daichendt and I. E. Grossmann, 1997, Integration of hierarchical decomposition and mathematical programming for the synthesis of process flowsheet, Computers Chem. Engng. vol. 22, pp. 147–175 M. A. Duran and I. E. Grossmann, 1986, An outer-approximation algorithm for a class of mixedinteger nonlinear programs, Mathematical Programming, vol. 36, pp. 307–339 I. E. Grossmann and L. T. Biegler, 2004, Part II. Future perspective on optimization, Comput. Chem. , vol. 28(8), pp. 1193-1218 I. E. Grossmann and Z.

An approach for the a-priori identification of critical points, either vertex or nonvertex, was developed for the synthesis of flexible flowsheets in order to overcome the problem of infeasibility caused by a large number of uncertain parameters. A set of critical points is determined by merging of critical values of uncertain parameters that are obtained by maximizing the design variables one-by-one, while simultaneously optimizing the economic objective function (Novak-Pintariþ and Kravanja, 2008).

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