Roger Böttcher

Open chemasimTM: Breaking paradigms in process simulation

Abstract Since September 2005 OPEN CHEMASIM™, a process simulator with features similar to commercial programs is available to the academic community as an Open Source Code. The code was developed by BASF for over 30 years as an in-house tool, and has now been transformed into an Open Source Code for academic use. For the distribution, the internet platform http://chemasim.itt.uni-stuttgart.de was set up at ITT, University of Stuttgart. Academic institutions may use OPEN CHEMASIM™ freely for teaching and in research as long as the results are published unrestrictedly. The code can be distributed to students, e.g., for project work. The present paper reports on this unprecedented project in process simulation. Features of the OPEN CHEMASIM™ program are briefly described and it is explained how the OPEN CHEMASIM™ as an acaedemic non-commercial project works.

Decision Support by Multicriteria Optimization in Process Development: An Integrated Approach for Robust Planning and Design of Plant Experiments

Abstract In simulation-based process design, model parameters, like thermodynamic data, are affected by uncertainties. Optimized process designs should, among different other objectives, also be robust to uncertainties of the model parameters. In industrial practise, it is important to know the trade-off between an increase in robustness and the other objectives – like minimizing costs or maximizing product purities. This contribution describes a practical procedure how to incorporate robustness as an objective into a multicriteria optimization framework. The general procedure is illustrated by a concrete example. Finally, we argue that the same approach is useable for an optimal design of plant experiments.

Graybox Models - New Opportunities for the Optimization of Entire Processes

Abstract The use of process optimization is often limited due to missing models for certain process steps. The systematic combination of available operating data with previous knowledge in so called graybox models helps to bridge this gap. Following the concept of incremental model identification it will be shown how the workflow has been integrated into a simulation software environment. It will be applied to a cumene process.

INES – Interface between Experiments and Simulation

Abstract The development of chemical processes is usually based on both experiments (often in pilot plants), and process simulation. Design of experiments, data evaluation and reconciliation, model development and validation are essential steps in this procedure. Different tools and approaches are available for each of these tasks but in the process developer’s workflow, they are usually not supported in an integrated way. Therefore, in the project INES, on which this paper reports, a new interface between experiments and simulation for process design was created, and integrated in a tool box which comprehensively supports process design. It contains modules for data selection and reconciliation, sensitivity analysis, and model validation and -adjustment. Methods from the literature are suitably combined to support the overall goal. The chosen methods, their combination and implementation are described and examples are given which demonstrate the benefits of the new interactive tool in the process development workflow.

Model-based Design of Experiments Using a Flowsheet-Simulator

Abstract The quality of process optimization depends on model parameters. The use of operating data from mini-, pilot or production plants can help to improve model agreement with operation. To support the design of experiments (DoE) in plants with many operability limitations a model-based DoE was implemented into a flowsheet simulator. In this contribution, the implementation of the method is described and its use for the identification of kinetics is demonstrated for a cumene process.