Implementation of digitalization methods which are already established in the IT sector, but are only occasionally used in the field of process engineering, for the holistic modeling of industrial energy systems. Such methods enable the creation of non-linear models that perform fast and robust calculations and enable the linking of individual plants to holistic models of entire production plants including energy systems. Such holistic models make it possible to (i) make visible previously hidden energetic and production synergy effects which lead to new optimum process control in terms of energy efficiency and productivity, and (ii) make these optima available in near real time, so that the energy system can always be operated at its economic optimum.
Current topics include the:
Discrete modeling is an approach to establish thermodynamics on discrete states of molecules within the context of their interacting neighbors. The novelty of the approach is that it a priori accounts for the geometrical information about the possible arrangements of molecules in condensed phases by considering clusters of molecules as modeling basis. In this way, in particular compared to most state-of-the-art quasichemical-based approaches, the usual decoupling of interacting surface segments from geometric restrictions is avoided and only geometrically feasible arrangements of molecules are considered, which in particular enables the distinction between isomeric configurations.
Application and further development of a Gibbs-Ensemble Monte-Carlo algorithm, implemented in the Wolfram Language and optimized for parallelization on a scientific computer cluster. Application to the:
Institut für Chemische Verfahrenstechnik und Umwelttechnik