(710f) Mosaic: An Online Platform for Combined Process Model and Measurement Data Management

Authors: 
Esche, E., Technische Universität Berlin
Müller, D., Berlin University of Technology
Kraus, R., Berlin University of Technology
Fillinger, S., Berlin University of Technology
Wozny, G., Berlin Institute of Technology



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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