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On the Influence of Particles Characteristics on Moisture Diffusivity during Drying of Granular Porous Media

Advances in Chemical Engineering and Science 2014年第1期4卷 7-16页

作者： JoséTeixeira freire fábio bentes freire Hugo Perazzini Department of Chemical Engineering Federal University of Sao CarlosSao CarlosBrazil

The objective of this work was to study the diffusive mechanisms of mass transfer predominant in the drying of cylindrical unconsolidated granular porous media of different diameters of porous spherical particles. The experimental study was based on determining the drying kinetics of the porous media evaluated and on obtaining the physical properties regarding the particles that constitute them. Moisture data as a function of time were obtained by subjecting the porous media to an upward single-phase flow of heated air at a specific condition of temperature, velocity and absolute humidity of the drying air. The theoretical study regarded the determination of the overall effective diffusion coefficient based on mass transfer foundations. from the results obtained, it was verified that the drying kinetics, for a given operational condition applied, is influenced by particle diameter, and the effective superficial liquid diffusivity is the mechanism that limits the drying process.

关键词： Adsorption Desorption Diffusion fick Knudsen Mass Transfer

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Influence of Bed Geometry on the Drying of Skimmed Milk in a Spouted Bed

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Advances in Chemical Engineering and Science 2015年第4期5卷 447-460页

作者： Maisa Tonon Bitti Perazzini fábio bentes freire José Teixeira freire Department of Chemical Engineering Federal University of S&atildeo Carlos S&atildeo Carlos Brazil

In this present work, the fluidynamic and drying process of skimmed milk in conical and conical-cylindrical spouted bed was analyzed as a function of different bed geometry and operating conditions. It used three internal cone angles (45°, 60° and 75°), different loads of inert particles (1.50, 3.00 and 4.50 kg) and a fixed static bed height (20.50 cm). Polyethylene particles of 4.38 mm of diameter and 930.50 ± 0.3 kg/m3 of specific mass were used as inert particles. An artificial neural network model was trained to predict the peak pressure drop and the minimum spout velocity from an experimental data bank. The experimental results showed a significant effect of geometric characteristics of the bed on fluidynamics parameters. It was also observed for the operating conditions that conical spouted bed and cone angle of 45° were more suitable for drying skimmed milk. The neural network provided predictions in good agreement with experimental data.

关键词： Cone Angle Bed Geometry Bed Configuration Inert Particles Neural Network

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A Neural Based Modeling Approach for Drying Kinetics Analysis of Mint Branches and Their fractions (Leaves and Stems)

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Advances in Chemical Engineering and Science 2017年第2期7卷 154-174页

作者： Aline de Holanda Rosanova Gustavo Dias Maia fábio bentes freire Maria do Carmo ferreira Graduate Program of Chemical Engineering Federal University of S&atilde o Carlos S&atilde o Carlos Brazil Chemical Engineering Department Federal University of S&atilde o Carlos S&atilde o Carlos Brazil

This work is aimed at investigating regular mint (Mentha × villosa) drying behavior and assessing how the heterogeneous composition of plants affects their drying kinetics. Drying kinetics and sorption isotherms were evaluated for whole branches and their fractions (leaves and stems). Stems and leaves were characterized by measurement of dimensions, apparent density and initial moisture content. The moisture sorption isotherms were obtained under temperatures of 30°C, 40°C and 50°C for branches, stems and leaves and the data were fitted to the GAB model. Mint branches and their fractions were oven dried at temperatures from 40°C to 70°C?and were obtained kinetic curves for each part. Water sorption patterns were similar for leaves and stems and the GAB model described well the sorption behavior of both materials. At a constant temperature, the drying rates were higher for leaves in comparison to stems and the differences increased as the temperature was raised. Therefore, depending on drying conditions, the moisture distribution in dried branches might be significantly different. Since the leaves constitute the major fraction in branches, the drying rates of branches were closer to those of leaves. The kinetic curves were fitted to a diffusion model based on an analytical solution of fick’s second diffusion law and to an empirical model based on artificial neural network (ANN). The results showed that the model based on the ANN predicted the drying kinetics of the different parts better than the diffusive model. A single network was built to describe the kinetic behavior of branches and fractions in the whole range of temperatures investigated. The diffusive model based on fitting effective diffusivity did not provide good predictions of moisture content, probably because neither the dependence of effective diffusivity on the moisture content nor the heterogeneity and shrinking of static beds were considered.

关键词： Aromatic Herbs Regular Mint Branches Stems Sorption Isotherms Oven Drying Artificial Neural Network

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