The objective of this work was to derive and experimentally verify a hybrid CST/neural network model to determine the moisture content of the powders produced during paste drying in a spouted bed and describe the highly coupled heat and the mass transfer. The model was derived from overall energy and mass balances with effective drying kinetics given by a neural network. Simulations were performed in MatLab and drying experiments for model verification were carried out for different pastes in a conical, semi-pilot-scale spouted bed.
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Univ Sao Paulo, Fac Ciencias Farmaceut Ribeirao Preto, BR-14040903 Ribeirao Preto, SP, BrazilUniv Sao Paulo, Fac Ciencias Farmaceut Ribeirao Preto, BR-14040903 Ribeirao Preto, SP, Brazil
Benelli, Lucimara
Souza, Claudia Regina F.
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Univ Sao Paulo, Fac Ciencias Farmaceut Ribeirao Preto, BR-14040903 Ribeirao Preto, SP, BrazilUniv Sao Paulo, Fac Ciencias Farmaceut Ribeirao Preto, BR-14040903 Ribeirao Preto, SP, Brazil
Souza, Claudia Regina F.
Oliveira, Wanderley Pereira
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Univ Sao Paulo, Fac Ciencias Farmaceut Ribeirao Preto, BR-14040903 Ribeirao Preto, SP, BrazilUniv Sao Paulo, Fac Ciencias Farmaceut Ribeirao Preto, BR-14040903 Ribeirao Preto, SP, Brazil