(443d) A Process Intensification Synthesis Approach to Adsorption-Based Reactive Separation Systems

Adsorption-based reactive separation systems comprise an important category of process intensification applications which exploit the synergy between adsorption and reaction either using a single process unit (e.g., membrane reactor) or multi-column units operated in a periodic manner (e.g., simulated moving bed reactor) [1-2]. By integrating multiple tasks into a single modular unit (at different time scales), these technologies have been demonstrated to effectively shift the thermodynamic limitations to achieve high reaction conversions, reduce cost investment, and/or minimize process environmental impacts [3]. The computer-aided design and optimization of these processes rely mostly on unit-level rigorous models to directly solve large-scale partial differential algebraic equations (PDAE) or to fully discretize the PDAE spatial and temporal domains resulting in nonlinear programming problems [4-6]. Systematic synthesis approaches, which can efficiently incorporate the temporal domain and address the role of multifunctional materials in reactive adsorption, are still lacking.

In this work, we propose a systematic framework for the synthesis of intensified adsorption-based reactive separation systems based on the Generalized Modular Representation Framework (GMF) [7-8]. The reactive adsorption systems are represented as an aggregation of abstract phenomena-based mass- and/or heat- exchange building blocks leveraging a Gibbs free energy-based driving force constraints formulation to characterize the mass transfer feasibility via reaction, separation, and/or adsorption. The spatial distribution information in each modular building block, as well as the temporal dynamics, are extracted via Orthogonal/Radau Collocation on Finite Elements [9]. The proposed synthesis approach offers the advantages to: (i) synergize multi-functional phenomena without pre-postulation of equipment/flowsheet structures, (ii) find the optimal design parameters and operating strategies via a single mixed-integer nonlinear programming model, and (iii) provide a unified & computational efficient representation for evaluation of adsorption-based reactive separation systems. The applicability and versatility of the proposed framework will be showcased via two case studies: (i) a membrane reactor for water-shift reaction to demonstrate the spatial representation and efficient computational formulations using GMF, and (ii) a sorption-enhanced steam methane reforming reactor for hydrogen production to determine the optimal periodic operation strategy via superstructure optimization.

Reference

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