Collaborative Research Center/Transregio 63
"Integrated Chemical Processes in Liquid Multiphase Systems"
The project area Systems Engineering is focused on the development of systematic methods and tools for the design and optimization of integrated multi-phase processes. Consequently, the objectives of the more general approaches followed in this project area are tailored to the practical needs of project areas A and B.
The goal of project C1 is to develop systematic methods to support the development of chemical processes from laboratory experiments to the optimization of the whole process. The focus lies on the data- and model-driven decision support during the early phases of the process design where only limited experimental data and models of different depth and accuracy of the possible processing steps are available.
Project C2 E developed a new modeling and simulation environment for the hierarchical modeling of integrated processes, which combines concepts such as equation-based modeling, use of symbolic mathematic language, and code generation. Starting from the collection of a number of partial models and experimental data, the best model combination for plant-wide models was determined by model discrimination and optimization methods.
In project C3 new mathematical approaches for the global optimization of integrated liquid multiphase systems are developed. The modelling of such systems usually gives rise to mixed-integer, nonlinear optimization problems, which can not be solved for guaranteed global optimality by local or stochastic algorithms. The new methods are developed cooperatively by mathematicians and engineers to solve problems originating from other subprojects of the Collaborative Research Center/Transregio.
Within project C4 methods for optimal operation of multi-phase liquid processes are being developed and applied to support the operation of the mini-plants at TU Dortmund (B5) and TU Berlin (B4). The focus lies on quickly achieving the start-up of each mini-plant, to sustain stable operation conditions, and to perform online optimization of the operation conditions under economic constraints. This entails the formulation of steady-state and dynamic models for both process concepts, parameter estimation, online state estimation based on the miniplants’ measurement data, and the actual model- and data-based optimization.