Bayesian predictive modeling for gas purification using breakthrough curves

This study proposes a predictive model for assessing adsorber performance in gas purification processes, specifically targeting the removal of chemical warfare agents (CWAs) using breakthrough curve analysis. Conventional parameter estimation methods, such as Brunauer-Emmett-Teller analysis, encount...

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Bibliographic Details
Published in:Journal of hazardous materials 2024-07, Vol.472, p.134311-134311, Article 134311
Main Authors: Hyun, Yesol, Oh, Geunwoo, Lee, Jaeheon, Jung, Heesoo, Kim, Min-Kun, Choi, Jung-Il
Format: Article
Language:English
Subjects:
Adsorption dynamics
Chemical warfare agents
Filter performance
Gas adsorption
Parameter identification
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Summary:This study proposes a predictive model for assessing adsorber performance in gas purification processes, specifically targeting the removal of chemical warfare agents (CWAs) using breakthrough curve analysis. Conventional parameter estimation methods, such as Brunauer-Emmett-Teller analysis, encounter challenges due to the limited availability of kinetic and equilibrium data for CWAs. To overcome these challenges, we implement a Bayesian parametric inference method, facilitating direct parameter estimation from breakthrough curves. The model’s efficacy is confirmed by applying it to H2S purification in a fixed-bed setup, where predicted breakthrough curves aligned closely with previous experimental and numerical studies. Furthermore, the model is applied to sarin with ASZM-TEDA carbon, estimating key parameters that could not be assessed through conventional experimental techniques. The reconstructed breakthrough curves closely match actual measurements, highlighting the model’s accuracy and robustness. This study not only enhances filter performance prediction for CWAs but also offers a streamlined approach for evaluating gas purification technologies under limited experimental data conditions. [Display omitted] •This study introduces a novel Bayesian model to analyze the gas purification process.•The model accurately estimates elusive adsorption parameters for toxic gas.•The model enables a single-step adsorption analysis using breakthrough curves.•The model’s validity is confirmed through a successful application to sarin gas.
ISSN:0304-3894
1873-3336
DOI:10.1016/j.jhazmat.2024.134311