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This work presents a Computer-Aided Molecular Design (CAMD) method for the synthesis and selection of binary working fluid mixtures used in Organic Rankine Cycles (ORC). The method consists of two stages, initially seeking optimum mixture performance targets by designing molecules acting as the first component of the binaries. The identified targets are subsequently approached by designing the required matching molecules and selecting the optimum mixture concentration. A multiobjective formulation of the CAMD-optimization problem enables the identification of numerous mixture candidates, evaluated using an ORC process model in the course of molecular mixture design. A nonlinear sensitivity analysis method is employed to address model-related uncertainties in the mixture selection procedure. The proposed approach remains generic and independent of the considered mixture design application. Mixtures of high performance are identified simultaneously with their sensitivity characteristics regardless of the employed property prediction method.

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The new approach for simulation and optimization of a continuous catalytic regenerative (CCR) reformer process is proposed. Typical CCR reforming processes consist of three to four reactors with recycle. The reaction patterns and reactors are typically modeled using a system of partial differential equations (PDEs). The numerical simulation solution of the entire model for a process system consisting of multiple reaction zones with recycle is extremely time-consuming and, thus, impractical in optimization studies. That is why we proposed a more efficient simulation and optimization scheme based on quasi-steady-state assumptions. We define criteria for reactor fragmentation to avoid the introduction of large errors in the quasi-steady-state calculations. The optimization problem is formulated with the objective of minimizing fuel consumption. The employed objective function constitutes a combined measure for economic and environmental performance. It is shown that the proposed approach identifies considerable improvements for the process.