2022
DOI: 10.1021/acs.iecr.2c00106
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Parameter Identification in Population Balance Models Using Uncertainty and Sensitivity Analysis

Abstract: The accurate estimation of sensitive parameters in a mathematical model predicting the outcome of a real experiment is of great importance in studying a complex physical phenomenon. A systematic methodology based on the uncertainty and sensitivity analysis framework is proposed for precise estimation of model parameters. The nonintrusive polynomial chaos expansion and the Sobol'-based sensitivity indices are used to quantify the uncertainties in the model prediction due to parameter uncertainties, and the Mont… Show more

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Cited by 4 publications
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