Bayesian estimation of parametric uncertainties, quantification and reduction using optimal design of experiments for CO2 adsorption on amine sorbents

•Bayesian estimation and quantification of CO2 adsorption isotherm parameters.•Parallel computation in uncertainty propagation and utility function evaluation.•Demonstrated optimal experimental design to reduce prediction uncertainty.•Integrated UQ framework developed in Python. Uncertainty quantifi...

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Veröffentlicht in:	Computers & chemical engineering 2015-10, Vol.81 (C), p.376-388
Hauptverfasser:	Kalyanaraman, Jayashree, Fan, Yanfang, Labreche, Ying, Lively, Ryan P., Kawajiri, Yoshiaki, Realff, Matthew J.
Format:	Artikel
Sprache:	eng
Schlagworte:	Adaptive metropolis Adsorption Bayesian inference Carbon dioxide CO2 adsorption Design engineering Mathematical models Optimal experimental design Parallel propagation Reduction Surface chemistry Uncertainty Utilities
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