(659e) Modular Process Intensification Synthesis for Membrane-Based Reactive Separation Systems Towards Sustainable Hydrogen Production

In a membrane-assisted reactive separation process, membrane separation is integrated with reaction operation to overcome reaction equilibrium by enhancing selective mass transfer. As a representative modular process intensification technology, membrane reactors have been demonstrated to effectively improve reaction conversions, achieve energy savings, and/or minimize environmental impacts [Drioli et al., 2011; Babi et al., 2014], and have been applied to various chemical/energy production systems particularly towards a hydrogen economy [Gallucci et al., 2009; Rodrigues et al., 2017]. Extensive studies have been performed on the modeling and simulation of membrane reactors, most of which leverage high fidelity process models resulting in large-scale partial differential algebraic equations [Tian et al., 2018]. While several works have been proposed recently for the conceptual design of such systems [Esche et al., 2014; Bishop and Lima, 2021; Monjur et al., 2021], a systematic approach is still lacking for rapid screening and design optimization of generalized membrane-assisted reactive separation systems and simultaneously benchmark with other intensified or conventional process alternatives under a unified synthesis framework.

To address these challenges, we propose a process synthesis framework for membrane-assisted reactive separation systems based on the Generalized Modular Representation Framework (GMF) [Papalexandri and Pistikopoulos, 1996; Tian and Pistikopoulos, 2018]. GMF features a bottom-up representation approach to capture chemical process systems using two types of phenomenological building blocks, namely a mass/heat exchange module and a pure heat exchange module. In our previous works, Gibbs free energy-based driving force constraints have been developed to intensify the generalized mass and heat transfer performance towards the ultimate thermodynamic bounds (with applications to reactive distillation, reactive absorption, gas phase reaction systems, etc.), formulated as a function of the multi-phase chemical potentials [Tian et al., 2020]. The mass transfer driving forces in a membrane-assisted system, which are determined by the differences between the chemical potentials of the permeate stream and the rentate stream, can thus be encapsulated under a unified driving force constraints formulation. To facilitate the representation, binary variables are added to dictate the selection (or not) of the membrane and to activate (or not) the unidirectional mass transfer pattern across the membrane. Therefore, each GMF modular building block can be automatically identified as a membrane-assisted (reactive) separation task or a phase equilibrium-driven reaction and/or separation task without pre-postulation. The impact of membrane on process feasibility are further correlated with material parameters such as permeability. To extract the spatial distribution information and to estimate modular design sizing parameters (e.g., module diameter, number of aggregated modules), Orthogonal Collocation on Finite Elements is applied to discretize each GMF building block while maintaining computationally compact in the combinatorial space [Stewart et al., 1985; Algusane et al., 2006].

In this way, GMF provides a systematic approach to: (i) identify the ultimate performance limits of membrane-assisted reactive separation systems, (ii) automatically generate the optimal process solutions, including but not limited to membrane-assisted configurations, using a unified synthesis representation, and (iii) incorporate the considerations of scaling up vs. numbering up. The overall GMF synthesis problem is formulated as a superstructure optimization problem to solve with mixed-integer nonlinear programming algorithms. We will showcase the proposed approach to synthesize membrane-assisted reactive separation systems for high-efficiency hydrogen production from steam methane reforming. The integration of life cycle inventory analysis and global warming potential metrics with GMF will also be disucssed to generate multiple hydrogen production process designs (convnetional and intensified) to elucidate the trade-off between sustainability, cost, and productivity.

References

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