Jump label

Service navigation

Main navigation

You are here:

Main content

Doctoral degree awarded to the former DYN researcher, Corina Nentwich

On May 19, 2021, Corina Nentwich who had been supervised by Prof. Engell, finished the procedures for her doctoral degree with the oral examination at TU Dortmund.

Corina Nentwich, a former member of the DYN group at TU Dortmund and currently employed at the Evonik Technology & Infrastructure GmbH obtained the Dr.-Ing degree for her dissertation “Surrogate modeling of phase equilibrium calculations using adaptive sampling”, with the following brief abstract:

The choice of thermodynamic models for phase equilibrium calculations plays a central role in the context of process simulation. For highly non-ideal systems, equations of state as the Perturbed-Chain Statistical Associating Fluid Theory (PC-SAFT) model are preferred for an accurate description of phase equilibria in a chemical process simulation. In order to implement such complex models, the thermodynamic model either is directly implemented into the process simulation software or it is outsourced into an external library, which is called by the process simulator. For PC-SAFT models, due to the iterative solution process, both options can lead to a high computational effort for the process simulation and optimization.

This thesis suggests to use surrogate modeling – replacing a complex model by a more simple black box model – in order to reduce the computational effort for complex phase equilibrium calculations. Two methods are

proposed: the indirect method applies surrogate models within explicit formulation of the phase equilibrium to efficiently solve the phase calculations during process simulation, while the direct method applies surrogate models to directly determine phase compositions. Prior to training the surrogate models, samples using original model calculations are drawn.

In order to reduce the computational effort for sampling, an adaptive sampling method is proposed, which combines sampling and training of the models in an iterative manner. This method provides superior surrogate models for the same number of samples compared to a conventional space-filling sampling design, which is shown for different surrogate model types.

The training and the use of the surrogate models are demonstrated for different systems: a ternary and a quaternary liquid-liquid equilibrium, a senary gas-liquid equilibrium, and a quinary vapor-liquid equilibrium. The surrogate models are applied to the simulation and optimization of hydroformylation process of 1-dodecene and the results are compared to simulations using the original PC-SAFT model.

The special conditions in the lockdown were successfully solved at the Faculty of Bio- and Chemical Engineering at the TU Dortmund University by a hybrid examination concept. Thanks again to Prof. Sebastian Engell for supervising, Prof. Michael Bortz for reviewing, Prof. Gabriele Sadowski and Prof. Dieter Vogt for taking the role of examiners and Dr.-Ing. Kerstin Wohlgemuth for moderating. Congratulations to Corina Nentwich!