<b>Adjustment of non-linear models for drying in thin layer by bayesian inference<b>

Autores

  • Ricardo Cardoso de Oliveira Universidade Estadual de Maringá
  • Robson Marcelo Rossi Universidade Estadual de Maringá
  • Marcelino Luiz Gimenes Universidade Estadual de Maringá
  • Sueli Teresa Davantel de Barros Universidade Estadual de Maringá

DOI:

https://doi.org/10.4025/actascitechnol.v36i2.15197

Palavras-chave:

passiflora, drying characteristics, Bayesian inference|

Resumo

Thin layer air-drying experiments on passion fruit seeds were conducted and the effects of temperature and air-drying speed were investigated in a pilot air-dryer. Drying characteristics of passion fruit seeds were examined by heated ambient air at 40 and 60ºC and air-flow speed at 0.4 and 0.6 ms-1. Analysis of variance showed that the main effects were statistically significant for temperature (p < 5%) and for the interaction between air-speed and temperature (p < 5%). Diffusivity coefficient dependence with temperature was described by an Arrhenius-type equation. Diffusivity coefficient rates were 1.19 x 10-10 m2 s-1, at 0.9 m s-1 and 40ºC, to 1.55 x 10-10 m2 s-1 at 0.6 m s-1 and 60ºC. Activation energies were 13.3 and 14.2 kJ mol-1 for speeds 0.6 and 0.9 m s-1, respectively.

 

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Biografia do Autor

Robson Marcelo Rossi, Universidade Estadual de Maringá

Universidade Estadual de Maringá - Departamento de Estatí­stica - Avenida Colombo 5790, Bloco F67, CEP 87020-900, Maringá - PR, Brasil.

Marcelino Luiz Gimenes, Universidade Estadual de Maringá

Universidade Estadual de Maringá - Departamento de Engenharia Quí­mica - Avenida Colombo 5790, Bloco D90, CEP 87020-900, Maringá - PR, Brasil.

Sueli Teresa Davantel de Barros, Universidade Estadual de Maringá

Universidade Estadual de Maringá - Departamento de Engenharia Quí­mica - Avenida Colombo 5790, Bloco D90, CEP 87020-900, Maringá - PR, Brasil.

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Publicado

2014-04-04

Como Citar

Oliveira, R. C. de, Rossi, R. M., Gimenes, M. L., & Barros, S. T. D. de. (2014). <b>Adjustment of non-linear models for drying in thin layer by bayesian inference<b>. Acta Scientiarum. Technology, 36(2), 263–269. https://doi.org/10.4025/actascitechnol.v36i2.15197

Edição

Seção

Engenharia Quí­mica

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