324478 Mosaic: An Online Platform for Combined Process Model and Measurement Data Management

Thursday, November 7, 2013: 4:50 PM
Continental 7 (Hilton)
Erik Esche, David Müller, Robert Kraus, Sandra Fillinger, Victor Alejandro Merchan Restrepo and Günter Wozny, Chair of Process Dynamics and Operation, Berlin University of Technology, Berlin, Germany

The development, validation, and subsequent management of process models are some of the most challenging tasks in process systems engineering. Due to insufficient knowledge on chemistry and physics standard models usually do not suffice to accurately describe the performance of a chemical plant. Individual solutions in the form of validated process models are often preferred. Most of all, this implies a continuous adjustment of process models and their parameters to updated experimental data. This calls for a platform which allows for the collaboration of experimenters and modelers, who work in same or varying programming languages, to manage the process models, store measurement data, and facilitate the fitting of model parameters. For this purpose the online modeling environment “MOSAIC” [1] has been extended.

MOSAIC enables mathematical modeling on the documentation level, wherein anything from single phenomena to whole process superstructures (hierarchical modeling) can be developed. The platform is able to support multiple contributors, allows for code export to numerous programming languages (Aspen Custom Modeler®, gPROMS, AMPL, GAMS, MATLAB®, …), and model analysis based on the Dulmage–Mendelsohn decomposition. Furthermore, interfaces to simulation and optimization tools are available. To include the measurement data the documentation level is expanded as shown in Figure 1. Each process model now consists of meta data, the model documentation, the data documentation, and versioning information to track model and plant changes.

For each measurement data set there is a documentation of the measurement device, a graphical representation of where, how and by whom it was taken and how it relates to the process model. Consequently, each fitted model parameter holds information which data was used for the fitting and where in turn those stem from. In addition, MOSAIC now has frontends for filing measurement data, for exporting optimization problems, e.g. for the parameter identification or fitting, and for experimental design to obtain more helpful measurements.

Figure 1: Overview of MOSAIC's capabilities and the new implementation for combining experimental measurement data with process models.

In this contribution, the modeling environment MOSAIC is discussed focusing on details on the implementation as well as the modeling capabilities. Moreover, a brief example is presented on how the collaboration of modelers and experimenters is facilitated.

Acknowledgements

This work is part of the Collaborative Research Centre "Integrated Chemical Processes in Liquid Multiphase Systems" (TRR 63) and the Cluster of Excellence „Unifying Concepts in Catalysis" coordinated by the Technische Universität Berlin. The financial support by the German Research Foundation (Deutsche Forschungsgemeinschaft, DFG) is gratefully acknowledged.

References

[1]           Kuntsche, S., Arellano-Garcia, H., and Wozny, G. (2011) MOSAIC, an environment for web-based modeling in the documentation level, Computer Aided Chemical Engineering 29, 1140-1144 ISBN 978-0-444-54-298-4.

 


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