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• W3205918215 endingPage "1863" @default.
• W3205918215 startingPage "1863" @default.
• W3205918215 abstract "Modeling of gas-solid fluidized systems has been a prevailing challenge over the last few decades. With different approaches and implementing different sub-models to capture the essential multiphase and multiscale phenomena in these systems, major advances have been achieved, even though most models are only subject to a practical validation of macroscopic parameters. The current description of fluidized beds through mathematical models relies on the inclusion of vast sub-models, leading to an unquantifiable degree of uncertainty on the models’ applicability for extrapolation studies. Furthermore, each closure and fitting parameter in the model represents a possible source of deviation, and their optimization, hence, becomes another major challenge. The recent advances in measurement techniques can enable us to troubleshoot and optimize the implemented models and sub-models based on local scale measurements. Local multiphase hydrodynamic information obtained by advanced measurement techniques can enable the validation of local predictions and optimization of the coupled sub-models, leading to the development of simplified and highly predictive models. Thus, pairing advanced experimental studies on these systems with insightful modeling approaches is required to advance the shortcoming and enhance the predictive quality of the models. In this work, an overview of the status of modeling and experimental measurement techniques for gas-solid fluidized beds is presented; then, an overview on pairing both experimental and modeling studies to improve the models’ local predictions for fluidized beds is presented." @default.
• W3205918215 created "2021-10-25" @default.
• W3205918215 creator A5081689066 @default.
• W3205918215 creator A5087985247 @default.
• W3205918215 date "2021-10-20" @default.
• W3205918215 modified "2023-10-06" @default.
• W3205918215 title "Pairing Experimental and Mathematical Modeling Studies on Fluidized Beds for Enhancement of Models Predictive Quality: A Current Status Overview" @default.
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