Fast synthesis of optimal chemical reactor networks based on a universal system representation

Xie M, Freund H (2018)


Publication Status: Published

Publication Type: Journal article

Publication year: 2018

Journal

Publisher: ELSEVIER SCIENCE SA

Book Volume: 123

Pages Range: 280-290

DOI: 10.1016/j.cep.2017.11.011

Abstract

We propose a new approach for the synthesis of optimal chemical reactor networks based on the concept of elementary process functions [1] and dynamic optimization. This approach is capable of incorporating process intensification options at an early design stage. Only one single differential equation is required to describe the mass balance of the whole reactor system along the reaction route. This equation contains terms describing mass fluxes from outside the reactor system and mass fluxes which flow between different positions of the reaction route. We demonstrate that different reactor types and different reactor connections can be represented by such a formulation. After solving an optimization problem using such a model, optimal profiles of state variables and fluxes are obtained. Based on these profiles, the optimal reactor system is determined. After the presentation of the theoretical background and the derivation of the new approach, it is illustrated in case studies and validated by comparison with literature results. The advantages of this new approach presented in our contribution are its simplicity in description and implementation, universality in representing different reactor types and networks, and the potential to consider different intensification and integration options at an early design stage.

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APA:

Xie, M., & Freund, H. (2018). Fast synthesis of optimal chemical reactor networks based on a universal system representation. Chemical Engineering and Processing, 123, 280-290. https://doi.org/10.1016/j.cep.2017.11.011

MLA:

Xie, Mingquan, and Hannsjörg Freund. "Fast synthesis of optimal chemical reactor networks based on a universal system representation." Chemical Engineering and Processing 123 (2018): 280-290.

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