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Figure 2.6 Pressure maps within PBR reactors obtained using CFD simulations to shed light on the pressure distribution of three geometric configurations: (a) fractal‐inspired shape, (b) multi‐tubular, and (c) serpentine.

      Source: Adapted from Tao et al. (2019).

There have been several efforts in different fields of engineering to integrate CFD and process simulations. Proof of this is the recent development a co‐simulation software framework at the DOE National Energy Technology Laboratory in the United States, which was applied to fossil energy systems with carbon capture. This tool is called APECS (advanced process engineering co‐simulator) and allows the design and optimization of the overall plant performance based on detailed high‐fidelity fluid dynamic models (CFD). Other instances of co‐simulation strategies applied to CCSU technologies are the work of Zitney [67], where an integrated gasification combined cycle (IGCC) power and hydrogen coproduction plant with carbon capture was analyzed by feeding data from CFD models into Aspen Plus. The results of the integration showed that the overall plant performance is affected by complex thermal and fluid flow phenomena that can only be analyzed at the CFD level; otherwise, process simulations miss those details. Another example of the intertwining between CFD and process simulations can be found in the work of Fei et al. [55], where the link between CFD and process simulations was accomplished by developing reduced order models (ROM) with the CFD data and introducing them into the process model. Edge et al. [54] on the other hand obtained temperature contours, velocities, and mole fraction maps of different species involved by using CFD and introduced the data into the process simulation tool gPROMS to assess the retrofitting of a coal‐fired power plant into an oxy‐fuel plant. Their approach resulted in guidelines as for the conditions where the system results in the same efficiency as air‐firing. Also, similar to Fei et al. [55], Lang et al. [68] presented a co‐simulation approach for an IGCC by developing an ROM via CFD in order to reduce the computational time and then optimize the plant by using process simulations. The efficiency of the process was increased by 7%, compared to the conventional configuration.

      The above examples show the benefits of the co‐simulation approach, in allowing the detailed interactions between fluid mechanics, heat transfer, reaction, and control strategy to be examined, and give valuable outputs to the design and operational model. The aforementioned examples also show that there is a lot to be done, given the scarcity of CFD process co‐simulation studies published in the literature. For instance, and to the best of the author's knowledge, no co‐simulation study has been reported regarding carbon utilization. As previously mentioned however, the combination of CFD and process simulations will certainly lead to significant research outcomes, especially in cases with CO₂ utilization where new catalysts (CFD) need to be tested in a reactor (part of a bigger process simulation) in which steady‐state performance, dynamics, and control strategy depend on mixing and fluid flow behavior. More specifically, in the area of methanation, there are two different aspects that need to be combined: the methanation reactor configuration and the catalysts. Not only is the reactor design clearly influenced by the catalyst applied, its activity, and selectivity, but also are up‐ and downstream processes [69]. A tight interfacing between CFD calculations for the performance assessment of a given catalyst and process simulation tools for the reactor design will open the possibility for process modeling on a detailed and optimized approach.

      It is evident from the aforementioned examples that the combination of process simulations and CFD will lead to a future with improved and optimized CCSU technologies. Also, the combination and implementation of different control strategies shall also provide an extra benefit.

References