Artikel ; Online: Bayesian predictive modeling for gas purification using breakthrough curves.
Journal of hazardous materials
2024 Band 472, Seite(n) 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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| Sprache | Englisch |
| Erscheinungsdatum | 2024-04-17 |
| Erscheinungsland | Netherlands |
| Dokumenttyp | 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 |
| Datenquelle | MEDical Literature Analysis and Retrieval System OnLINE |
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