(130b) Design Space Analysis: Flexibility Quantification for Carbon Capture Adsorbent Screening

Pressure-vacuum swing adsorption (PVSA) is an established technology used to capture carbon dioxide (CO₂) from post-combustion flue gas, representing a key step towards achieving a sustainable energy system on a global scale. The status-quo for PVSA design involves solving a constrained multi-objective optimization problem [1], which seeks to maximize productivity while minimizing energy consumption subject to purity and recovery constraints mandated by regulatory bodies [2]. Similarly, for adsorbent screening , the emphasis is typically placed on minimizing the parasitic energy of the adsorbent [3]. While this approach leads to highly efficient designs, they may be constrained to operate within a narrow parameter space that ensures optimal performance. Therefore, assessing process flexibility is essential to ensure robustness and controllability of the process, especially when regulatory purity requirements are stringent.

In this study, we propose a model-based framework to facilitate an integrated assessment of process flexibility and performance. Specifically, we deploy the proposed framework to screen adsorbent materials suitable for a PVSA process. Contrary to previous studies, flexibility is added as the metric to evaluate process controllability. The framework consists of three main steps: (1) model development and problem formulation, (2) design space identification, and (3) design space analysis. Firstly, a mathematical model of the process is developed and experimentally validated, providing the basis for subsequent analysis. The problem is then defined by selecting the design inputs (DIs), key performance indicators (KPIs), and process constraints. Quasi-random Sobol sampling is employed to explore the process efficiently with low discrepancy. Based on the sampled data set, an artificial neural network is trained and used to enhance the design space identification using alpha shapes. Once the design space boundary is quantified, design space analysis is performed to identify acceptable ranges and KPI distributions in an integrated manner.

The proposed framework is implemented to screen adsorbents for post-combustion carbon capture via PVSA. The model consists of partial differential equations and has been experimentally validated as presented by Ward and Pini [4]. A techno-economic assessment framework is coupled to the process model to enable the quantification of capture cost. The assessment of the adsorbent is integrated within the evaluation of process flexibility. The design inputs of the problem are the process intermediate pressure, high pressure, and feed velocity. While the KPIs recorded are purity, recovery, energy consumption, productivity, and capture cost. Constraints with respect to regulations are implemented [1-3] and design spaces are identified for all adsorbents. Integrated quantitative analysis between adsorbents and design cases are carried out. The most flexible designs are identified, acceptable parameter ranges are quantified, and KPI distributions are examined for each adsorbent.

We demonstrate how the proposed framework can be utilized for adsorbent screening of a PVSA process. In contrary to the status-quo approach for PVSA design and adsorbent screening, our methodology is capable of performing integrated assessment between performance and flexibility of the adsorbent-design combination with respect to industrially relevant constraints.

References

[1] R. Haghpanah et al., "Multiobjective Optimization of a Four-Step Adsorption Process for Postcombustion CO₂ Capture Via Finite Volume Simulation," Industrial & Engineering Chemistry Research, vol. 52, no. 11, pp. 4249-4265, 2013, doi: 10.1021/ie302658y.

[2] R. T. Maruyama, K. N. Pai, S. G. Subraveti, and A. Rajendran, "Improving the performance of vacuum swing adsorption based CO₂ capture under reduced recovery requirements," International Journal of Greenhouse Gas Control, vol. 93, 2020, doi: 10.1016/j.ijggc.2019.102902.

[3] V. Subramanian Balashankar and A. Rajendran, "Process Optimization-Based Screening of Zeolites for Post-Combustion CO₂ Capture by Vacuum Swing Adsorption," ACS Sustainable Chemistry & Engineering, vol. 7, no. 21, pp. 17747-17755, 2019, doi: 10.1021/acssuschemeng.9b04124.

[4] A. Ward and R. Pini, "Efficient Bayesian Optimization of Industrial-Scale Pressure-Vacuum Swing Adsorption Processes for CO₂ Capture," Industrial & Engineering Chemistry Research, vol. 61, no. 36, pp. 13650-13668, 2022, doi: 10.1021/acs.iecr.2c02313.