(588d) A Hierarchical Modeling Approach to Process Design and Simulation | AIChE

(588d) A Hierarchical Modeling Approach to Process Design and Simulation

Authors 

Kraus, R. - Presenter, Berlin Institute of Technology
Arellano-Garcia, H. - Presenter, Berlin Institute of Technology
Wozny, G. - Presenter, Berlin Institute of Technology


In this work, we propose a hierarchical modeling approach embedded in a developed tool called MOSAIC (Modeling, Simulation, Application and Interaction of Chemical processes), which is a web-based modeling- and simulation platform developed at our group at the Berlin Institute of Technology. It has basically been designed for the collaboration of different workgroups, independent of their location. Single models are entered as equations and saved on the server. The created systems can then be exported to common simulation programs and programming languages such as Aspen, Chemcad, gPROMs, Matlab and C. The model library of MOSAIC contains equation systems, which describe basic process system units and several packages with implemented models from different publications.

Generally, a process can be divided in different units, which consist of a combination of different phenomena's described by different more or less complex rigorous models. The selection of these elementary models is mostly done without the knowledge of which combination of all models is able to describe the whole unit in the best possible way. It can happen that the selected models explain the single phenomena's very well, but when they are combined to describe the whole unit they may fail. Furthermore, it is not known then if a combination of less complex and more robust models will be able to describe the unit with the same accuracy and less effort. The structure and working principle of the developed environment MOSAIC makes it possible to exchange single equations and to create different model combinations. These are rated with the aid of different indicators e.g. speed of convergence, robustness, physical relevance, and the applicability for optimization algorithms.

Acknowledgement: The authors acknowledge the support from the Collaborative Research Center SFB/TR 63 InPROMPT ?Integrated Chemical Processes in Liquid Multiphase Systems? coordinated by the Berlin Institute of Technology and funded by the German Research Foundation.