Article ; Online: Bayesian predictive modeling for gas purification using breakthrough curves.
Journal of hazardous materials
2024 Volume 472, Page(s) 134311
Abstract: 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, ... ...
Abstract | 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 H |
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Language | English |
Publishing date | 2024-04-17 |
Publishing country | Netherlands |
Document type | Journal Article |
ZDB-ID | 1491302-1 |
ISSN | 1873-3336 ; 0304-3894 |
ISSN (online) | 1873-3336 |
ISSN | 0304-3894 |
DOI | 10.1016/j.jhazmat.2024.134311 |
Database | MEDical Literature Analysis and Retrieval System OnLINE |
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