Reference : A discrete-continuous approach to describe CaCO3 decarbonation in non-steady thermal ...
Scientific journals : Article
Engineering, computing & technology : Materials science & engineering
Computational Sciences
http://hdl.handle.net/10993/20664
A discrete-continuous approach to describe CaCO3 decarbonation in non-steady thermal conditions
English
Estupinan Donoso, Alvaro Antonio mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit >]
Peters, Bernhard mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit >]
Copertaro, Edoardo mailto []
Chiariotti, Paolo mailto []
Paone, Nicola mailto []
Revel, Gian Marco mailto []
May-2015
Powder Technology
Elsevier Science
275
131-138
Yes (verified by ORBilu)
0032-5910
Lausanne
Switzerland
[en] Computational Fluid Dynamics ; CFD ; Extended Discrete Element Method ; XDEM ; Soft sensors ; thermal engineering
[en] In cement production, direct measurements of thermal and chemical variables are often unfeasible as a consequence of aggressive environments, moving parts and physical inaccessibility, and therefore prediction models are essential tools in these types of industrial applications. This article addresses the problem of the numerical prediction of the CaCO3 calcination process, which is the first and the most energy expensive process in clinker production.

This study was conducted using the Extended Discrete Element Method (XDEM), a framework which allows a Eulerian approach for the gas phase to be combined with a Lagrange one for the powder phase.

A detailed validation of the numerical model was performed by comparison to non-isothermal TG curves for mass loss during the CaCO3 decarbonation process. The complex three-dimensional predictions for solid and gas phases are believed to represent a first step towards a new insight into the cement production process.

Thus, the high accuracy and detailed description of the problem addressed, serve as a basis to assess the uncertainty of more simplified models such as those used in soft sensors.
http://hdl.handle.net/10993/20664

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