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The application of a Grey-box Neural Model (GNM) in a nonlinear model predictive control scheme (NMPC) of a direct rotary dyer is presented in this work. The GNM, which is based on the combination of phenomenological models and empirical artificial neural network (ANN) models, was properly developed and validated by using experimental fish-meal rotary drying information. The GNM was created by combining the rotary dryer mass and energy balances and a feed forward neural network (FFNN), trained off-line to estimate the drying rate and the volumetric heat transfer coefficient. The GNM results allowed us to obtain the relation between the controlled variable (solid moisture content) and the manipulated variable (gas phase entrance temperature) used in the predictive control strategy. Two NMPC control strategies, one with a fixed extended prediction horizon and another with an extended range prediction horizon, were applied to a simulated industrial fish-meal drying process. The results showed that a correct ...

The residence time in a pilot-scale rotary dryer was determined experimentally for four types of solids (fish meal, sand, soy meal, and sawdust) while varying the solids flow rate, the slope of the dryer, the speed of rotation, and the flow rate of gas with the objective to develop a correlation to predict the mean residence time for inclined and horizontal rotating dryers and to compare the developed models to the experimental data. Three models, two based on the product of operating variables and a neural network, are presented and compared. Results show that all models provide good estimates of the mean residence time, with the neural network providing more accurate predictions.

Drying curves were determined in a mechanically agitated fluidized bed dryer, at temperatures between 70°C and 160°C, air velocities between 1.1 m/s and 2.2 m/s and stirring rates between 30 rpm and 70 rpm for batch drying of 3 kg lots of carrot slices, measuring the moisture content and shrinking of the particles in time. This was complemented by a study of the rate and degree of swelling of dried carrot particles in water between 20 and 75°C. Drying kinetics were modeled by Fick's second law, for which an optimal agreement with the experimental data was obtained when the effective diffusivity (D e ) was determined by a correlation based on the air velocity (v), the air temperature (T) and the dimensional moisture content of the carrot particles (X/X o ). Loss of carotenes is minimized when dehydration is carried out at about 130°C with a drying time below 12 min.

The solids mean residence time in a rotary dryer is influenced by several variables such as dryer dimensions and solids characteristics. One of these characteristics, usually not taken into account in correlations proposed to estimate the mean residence time, is the solids feed moisture content. Although it is well known that the solids moisture content has a major impact on the ability of the solids to move along the rotary dryer, it does not enter as a parameter in available correlations. In this investigation, numerous experiments were performed in a pilot-scale rotary dryer to study the influence of solids moisture content and drying gas temperature on the mean residence time. Sand employed in cement makeup was used to perform these experiments. Results show that the mean residence time for a moisture content in the range of 8% to 12% is four times higher than for dry solids. The moisture content and the drying gas temperature influence significantly the shape of the residence time distribution curve.

A batch-indirect rotary drier heated with steam was experimentally operated to obtain data of moisture content and temperature versus time for soy meal and fish meal. Operation conditions were as follow: steam pressure (1 to 4 bar), rotation speed (3.7 to 11.6 r.p.m.) and rate of vapor extraction (0.059 to 0.256 m/s). From experimental data the effective heat transfer coefficient between the hot surface and the bed of solids was determined. These data were correlated by means of dimensional analysis as a function of the drying process variables. The equation obtained for the effective Nusselt number predicts adequately the effective heat transfer coefficient, for both substrates, in the range of the operating variables studied.

The superficial and bound moisture removal from soya meal was studied in a pneumatic dryer. The effect of external condition over the effective diffusivity in drying kinetics prediction has been demonstrated and a model that considers time variable diffusion coefficient was developed and correlated with gas temperature and velocities. A simple experimental technique using a pulse injection of humected solid was utilized to determine real drying kinetics under steady state operation with solids recycling. The model fitted the experimental data well over a gas temperature range between 100° C and 300° C and gas velocities of 3.5 m/ s and 20 m/ s.

The work considers the application of the flash drying to the moisture removal of fishmeal using superheated steam as transport medium. Heat, momentum and mass transfer equations were applied and an algorithm based on these equations was developed and solved. The model was validated using experimental data obtained in a pilot pneumatic dryer ( total length 60 m) provided with a steam jacket to maintain the superheated steam at a constant temperature. The drying time was less than 10 s to decrease the fish meals moisture content from 53.5% to 28% d.b. and in a second pass by the dryer the moisture down to 16.9% using superheated steam at It 1 ° C and 130 ° C in the jacket. The computational results are in agreement with the experimental data.

Adaptive and conventional control of a direct rotary dryer has been assessed through simulations. A dynamic model of the process was developed specifically for this purpose. The model is based on mass and energy balances and includes a drying kinetic derived from mass transfer principles. In the modelling process, ten discrete perfectly mixed elements were considered for the dryer with each containing four differential equations. A well tuned discrete PID and an adaptive algorithm were used to control the outlet solid humidity. Both controllers can regulate the controlled variable for different disturbances, although the adaptive controller is more effective.

In this work, a general framework for modelling and simulation of particulate solid drying processes is presented, based on fundamental conservation laws associated with a neural network, for model uncertain parameter estimation. The modeling approach, which leads to a hybrid-neural model, is applied in order to describe the dynamic behavior of two important drying systems: a direct flow rotary dryer and a batch fluidized bed dryer. Both models are built using simple mass and energy balances, where heat and mass transfer parameters are estimated with neural networks. Model behavior was evaluated by comparing experimental and simulation data. It is concluded that the hybrid-neural modeling approach is better for adaptation and prediction than its black box type counterpart.

The objetive of this work, was to demonstrate the validity of empirical relationships for computing the volumetric heat transfer coefficient Ua in a pilot direct contact rotary dryer. It was also studied the effect of the operation conditions on the volumetric heat transfer coefficient. Relationships were proposed to compute the volumetric heat transfer coefficient. The methods used to obtain these relationships were based on mass and heat balances. The solids used in this work were soya meal, sawdust and sand.

This article presents the modeling and simulation of a batch pilot-scale vibrofluidized bed dryer. The model considers the effect of back-mixing by establishing interconnected drying zones. The model's equations consist of the mass and energy balances for each zone in the solid phase, while a complete mixing is assumed in the gas phase. The drying and heat transfer parameters are correlated with the operating conditions by means of three neural networks that have been adapted from data obtained experimentally. The system of algebraic-differential equations provides the solid's moisture content and temperature profiles as a function of time. The model was validated by experiments with turnip seeds. Good fit was obtained using only four drying zones.

The utilization of superheated steam for pneumatic drying of solid particles makes it possible to operate with high particle concentration without the problem of phase saturation which tends to occur when hot air is utilized for drying. Normally, the operation of pneumatic dryers is analyzed through variations of unidirectional flows. For highly diluted transport conditions this is a correct assumption, but when the solid concentration is too high, the fluid dynamics is highly modified and the gas and solid velocities are distorted by solid–solid and Solid–Wall -interactions. These conditions affect the temperature distribution along the axial and the radial coordinates, which makes a bi-dimensional model analysis very important. Mathematical models have been developed for the bi-dimensional fluid dynamics of pneumatic transport. The present work applies one of these models to describe the axial and radial variation of velocities in a gas and particulate phase flow.

In this paper, the usefulness of a mathematical model based on equations describing the diffusional phenomena which are variable with time, is developed and discussed in relation to serve as a model for experimental data of drying of Thompson seedless grapes. This model represents more closely the drying curves tested, than the classic diffusion model normally utilized to analize drying processes

A mathematical model able to predict solid and drying gas temperature and moisture content axial profiles along a direct contact rotary dryer was developed. The study was focused on the drying kinetics based on phenomenological models. Two different drying mechanisms in the decreasing drying rate period were tested: proponional to the unbound moisture content and moisture diffusion inside the particle. Experimental data collected in a pilot-scale direct contact rotary dryer was used to validate the model. Soya and fish meals were used as drying material.