Dissertation/Thesis Abstract

Concepts and Implementation of Collaborative Modeling in MOSAIC
by Kraus, Robert, Eng.D., Technische Universitaet Berlin (Germany), 2015, 187; 10699767
Abstract (Summary)

In process engineering a lot of resources are invested to improve existing and to develop new process concepts. Process unit models are derived and applied in simulations, which are the basis for further optimization work. Process data from the actual production plant, or the laboratory, can be used for the validation of the calculated results and as starting point for new developments. Due to the complexity, the work on large projects can only be realized in interdisciplinary collaboration with a team of specialists. In the scope of this work concepts are introduced and presented to meet the challenging demands for the collaborative process development. A database structure is generated for the integrated management of model and measurement data. The strict classification and area of application of process models is relaxed by the introduction of modularity approaches. A tool independence is achieved by moving several model specification features prior to the code generation of the target programming language. Models can be applied in simulation and optimization software and the specification of transformations for an automated discretization of ODE/DAE systems can be defined. This is achieved without altering the original equation system, which is thereby preserved in its original and well documented state. A structure analysis functionality offers decomposition concepts of equation systems and the automated development of solution routines. As a proof of concept, all the approaches are implemented in the online modeling environment MOSAIC.

Indexing (document details)
Advisor: Wozny, Günter
School: Technische Universitaet Berlin (Germany)
School Location: Germany
Source: DAI-C 81/1(E), Dissertation Abstracts International
Subjects: Operations research, Industrial engineering
Keywords: Process engineering
Publication Number: 10699767
ISBN: 9781392630464
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