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Hybrid mechanistic data-driven modeling for the deterministic global optimization of a transcritical organic Rankine cycle

Global optimization is desirable for the design of chemical and energy processes as design decisions have a significant influence on the economics. A relevant challenge for global flowsheet optimization is the incorporation of accurate thermodynamic …

Modelling circular structures in reaction networks: Petri nets and reaction network flux analysis

Optimal reaction pathways for the conversion of renewable feedstocks are often examined by reaction network flux analysis. An alternative modelling approach for reaction networks is a Petri net. These explicitly take the reaction sequence into …

Deterministic global nonlinear model predictive control with neural networks embedded

Nonlinear model predictive control requires the solution of nonlinear programs with potentially multiple local solutions. Here, deterministic global optimization can guarantee to find a global optimum. However, its application is currently severely …

Impact of accurate working fluid properties on the globally optimal design of an organic Rankine cycle

Deterministic global optimization of process flowsheets has so far mostly been limited to simplified thermodynamic models. Herein, we demonstrate a way to integrate accurate thermodynamic models for the optimal process design of an organic Rankine …

Deterministic global process optimization: Flash calculations via artificial neural networks

We recently demonstrated the potential of deterministic global optimization in a reduced-space formulation for flowsheet optimization. However, the consideration of implicit unit operations such as flash calculations is still challenging and the …