Optimization based synthesis of hybrid separation processes

Hybrid separation processes offer a great potential for the design of energy-efficient, sustainable separation processes through a combination of different separation techniques. However, the design of these highly integrated processes is challenging due to the multitude of structural and operative degrees of freedom. A lack of modeling experience and reliable synthesis methods has so far hindered the application of these promising designs in industry. It is the scope of this thesis to provide methodologies which facilitate an efficient and reliable conceptual design of hybrid separation processes. For this purpose, a synthesis framework for the optimization-based design of hybrid processes is proposed. Powerful shortcut and rigorous evaluation methods for distillation, heteroazeotropic distillation, extraction, crystallization and reactive distillation are developed. These methods are fully algorithmic and computationally efficient in order to allow an optimization-based design of large-scale hybrid processes. The proposed synthesis framework is validated by large-scale industrial case studies