Numerous publications have investigated new novel designs for structured packing over the years. Most of these publications considered designs that are derivatives of corrugated packing that were designed for specific purposes and evaluated the performance post-design stage. These studies have found that mass transfer performance can be enhanced by upwards of 70% compared to traditional corrugated structured packing [3], [4]. However, the designs of these packings were predetermined, so the performance of the packing subject to the design was not optimized. Other works considering optimization of the geometry of structured packing utilize computational fluid dynamics models, which are able to rate the performance with a high degree of accuracy utilizing physics-based approaches [5]. Due to the complexity of these models, a direct numerical optimization of the design becomes impossible, so genetic algorithms are developed to optimize the geometry, which becomes computationally expensive [6]. A drawback of this approach is the inability to apply these packing models in a flowsheet processor to evaluate and optimize not only the hydraulics of the packing but the mass transfer performance as well. There exist many different correlations in the literature that consider the characteristics of structured packing in the prediction of hydrodynamic conditions that, although not as accurate as CFD models, are suitable for modeling the scale up of a post-combustion capture absorption system and are commonly used [7], [8], [9]. But there is a gap in the literature which utilizes these correlations in process models to optimize the capture performance through optimizing the geometry of the packing. Additionally, as previously mentioned, corrugated packing has been typically used due to its ease of manufacture, but it can be difficult to embed a coolant in traditional corrugated packing, which addresses the issue of heat generation from CO2 absorption which reduces the efficiency of mass transfer. Based on improvements in 3D printing technology, a new design for intensified corrugated packing was developed that uses additive manufacturing to imbed separate channels into the wall of the packing in which a coolant can internally remove the heat of reaction, thus enabling continuous operation [10]. The potential of 3D printing for manufacturing structured packing could enable customization of unique designs that can optimize the performance of specific processes.
In this work, a topological model for intensified packing is developed that considers the geometric parameters of the packing to calculate the characteristics of the design, such as the specific area and wetted perimeter. A separate channel is included in the model to allow for the flow of cooling water to extract heat from the tower. Using the outputs of the topological model, correlations for hydrodynamics are utilized to rate the performance of mass transfer of CO2 in a counter-current flowing solvent-vapor system. The topological and hydrodynamic models are incorporated into a rate-based MEA solvent column flowsheet in the equation-oriented framework provided by Pyomo [11], enabling the implementation of numerical optimization algorithms that other flowsheet processors lack. The performance of the process is optimized with respect to the topological design of the packing type utilized, as well as other process decision variables and process constraints. Results of the optimization show that significant improvements in capture efficiency and capture costs can be made with optimal design of the packing and with heat extraction from the tower compared to fixed designs of standard corrugated structured packing.
Acknowledgement
The authors graciously acknowledge funding from the U.S. Department of Energy, Office of Fossil Energy and Carbon Management, through the Carbon Capture Program.
Disclaimer
This project was funded by the Department of Energy, National Energy Technology Laboratory an agency of the United States Government, in part, through a support contract. Neither the United States Government nor any agency thereof, nor any of its employees, nor the support contractor, nor any of their employees, makes any warranty, expressor implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof, or any of their contractors.
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