Fábio Bentes Freire

A Hybrid Lumped Parameter/Neural Network Model for Spouted Bed Drying of Pastes with Inert Particles

The current study analyzed the suitability of a hybrid CST/neural network model to describe the highly coupled heat and mass transfer during paste drying in a spouted bed. In the present approach, the main information was the moisture content predictions in the powder. The model was based on global energy and water mass balances in the liquid and the gaseous phases. In this model, the inter-phase coupling term r, which reflects both water evaporation and particle coating, was described by an artificial neural network. Artificial neural networks are efficient computing models which are extensively used whenever theoretical models fail to properly represent a given phenomena and reliable data basis of the main variables involved is available. Simulations were done in MatLab. The drying experiments for model verification were carried out in a conical semi-pilot scale spouted bed, from which measurements of gas and solid phase moisture were done. The good agreement between calculated and measured powder moisture content suggested that the well-mixed hypothesis could be applied for paste drying in a spouted bed. The robustness of the model with respect to changes in feed flow rates and other operating conditions showed the merits of using a trained neural network.

A Review on Paste Drying with Inert Particles as Support Medium

An overview of the contributions of the literature in the field of drying with inert particles is presented. Recent experimental studies developed in conventional spouted and fluidized beds aimed at describing and understanding the effects of the presence of a liquid or paste on the global behavior of these types of dryers are approached. Advances in numerical simulation of drying with inert particles are discussed. Several open research issues and future perspectives are addressed.

Transient Analysis of Pasty Material Drying in a Spouted Bed of Inert Particles

The aim of this work is analyzing experimentally the fluid dynamic, thermal, and mass transfer behavior during the transient period of paste drying process in spouted beds. The pasty materials used in this study were water, sewage sludge, skimmed milk, and calcium carbonate. Glass beads of 2.18 mm diameter and 2512.70 kg/m3 density were used as inert particle. Drying experiments were conducted with spouted beds under two different inlet air velocities, 15 and 30% higher than the minimum spouting velocity, and two ranges of temperature, 80 and 100°C. From these experiments, values of the bed pressure drop, spouting air velocity, particle bed temperature, exhaustion air temperature, and the humidity profile of gas and liquid phases during the transient period were obtained. The results indicate that the analysis of the transient drying period is an adequate and encouraging technique to obtain further information in order to understand the paste drying process in spouted beds.

Trends in Modeling and Sensing Approaches for Drying Control

A number of contributions have been made in the field of chemical process monitoring and control with applications ranging from simple flow and temperature control to highly complex inferential adaptive control systems in biochemical and polymer production. These technologies face difficulties when applied to drying equipment, due to the inherent complexity of the operation. This article shows some recent trends in monitoring and control of drying processes. This review is organized in sections according to the transport phenomena involved in the operation of a dryer. In each section, examples of recent trends in monitoring and control strategies of key variables directly related to these transport phenomena are discussed.

Industrial trials of paste drying in spouted beds under QDMC

Abstract Spouted bed has been extensively investigated by many authors for years, but the issue of controlling its operation still remains in basic developing stages. The present work consists of the application of an advanced control strategy (QDMC—Quadratic Dynamic Matrix Control) to automate the operation of a large-scale spouted bed dryer. The work on control strategies for spouted bed was motivated by the lack of references on this subject and the encouraging results obtained by Corrêa et al. (Corrêa, N.A.; Freire, J.T.; Corrêa, R.G. Improving operability of spouted beds using a simple optimizing control structure. Brazilian Journal of Chemical Engineering 1999 16 (4), 359–368; Corrêa N.A. Corrêa, R.G.; Freire, J.T. Adaptive control of paste drying in spouted bed using the GPC algorithm. Brazilian Journal of Chemical Engineering 2000 17 (4–7), 639–648; Corrêa, N.A.; Corrêa, R.G.; Freire, J.T. Self-tuning control of egg drying in spouted bed using the GPC algorithm. Drying Technology 2002 20 (4), 813–828.) for a laboratory-scale apparatus. The industrial-scale spouted bed dryer has a height of 4 m and a diameter of 66 cm. The same configuration of data acquisition unit, sensors, and interface developed for the laboratory-scale unit was employed. The dryer is capable of processing up to 20 L/h of pasty material. The powder moisture content (Ys), inferred from measurements of temperature at the exhaustion of the bed bulk, and the powder production rate (Pr), measured on-line by an electronic balance, are the controlled variables. The manipulated variables are: the paste inflow rate (W), regulated by an automatic pump, and the electrical power supply for air heating (P), regulated by a thyristor. The bed pressure drop, the airflow rate, and the information from the environment are monitored by means of an interfaced microcomputer. Experimental runs of drying up to 400 kg/day of an Al2O3 10% aqueous suspension were carried out. The results showed that the QDMC control is robust with respect to the main variables involved and is efficient in maintaining the operation of the bed under the constraints of the system. The major aim concerning the scale-up of spouted bed, which is the determination of the minimum amount of energy required to ensure spout stability, was accomplished by the constrained control strategy.

Thermal Treatment of Solid Wastes Using Drying Technologies: A Review

ABSTRACT The proper treatment of organic or inorganic solid wastes is necessary for economic and environmental interests. Added-value by-products of market interest can be obtained through the recovery, reuse, and treatment of solid wastes, which are otherwise discarded inappropriately in large quantities into the environment. In this review, the drying process is presented as an alternative environmental technology for the thermal treatment of residues of different natures from different origins. The main techniques applied to solid waste drying are described and, in parallel, the most relevant studies found in the literature for this theme are analyzed. Moreover, the main dryers currently used are presented, as well as their most important characteristics. Some general aspects of the thermal and energetic performance of these dryers fundamental for process feasibility analysis are also discussed in this review. Essential aspects of the solid waste drying process are primarily presented with the purpose of showing the particularities that this approach offers when it comes to putting the theory into practice.

Moisture Prediction During Paste Drying in a Spouted Bed

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.

Thin-Layer Drying of Mate Leaves (Ilex paraguariensis) in a Conveyor-Belt Dryer: A Semi-Automatic Control Strategy Based on a Dynamic Model

A feedback strategy of drying control of mate leaves in a thin-layer conveyor-belt dryer was experimentally evaluated. Moisture content in the discharge of the continuous dryer was controlled by manually adjusting the speed of the moving belt between 3.7 × 10−4 and 15.2 × 10−4 m s−1 for approximately 7200 s in 120 s time steps. The sets of PID controller parameters and manipulated conveyor velocities were computed with a dynamic drying model at conditions identical to those found in the closed-loop experiments. The model is represented by a system of two partial differential equations built by energy and solute mass balances in the solid phase of the dryer. A large set of experimental drying curves and temperature of mate leaves as a function of drying time, in the temperature range from 55 to 130°C, confirmed the reliability of the considered model. Experimental closed-loop responses of discharge moisture content in the presence of disturbances in the feed moisture content (≈ 0.5 − 1.7 dry basis) and variations in set-point (≈ 0.1 − 1.0 dry basis) validated the suggested control scheme.

Control of the Moisture Content of Milk Powder Produced in a Spouted Bed Dryer Using a Grey-Box Inferential Controller

Although the moisture content of dried products is an important variable in industrial dryers, it is often not measured directly for control purposes. Alternative and simpler meters might provide information to be used in a physical-mathematical model to estimate the moisture content. When this procedure is applied to a control strategy, an inferential controller is developed. In this article, a physical-mathematical model was used to infer the moisture content of milk powder produced in a spouted bed dryer. Afterwards, simulations of an inferential proportional-integral controller were carried out using the inlet air heating rate as the manipulated variable. The physical-mathematical model used in the procedure was a hybrid model, which considers mass and energy balances and one term which is estimated by an artificial neural network. The controller parameters (controller gain and integral time) were tuned by trial and error. Even though the procedure was quite simple, it was proven to be effective in yielding a stable closed-loop response for both servo and regulatory control of the (inferred) powder moisture content.

Prediction of Residence Time Distribution of Solid Wastes in a Rotary Dryer

The residence time distribution (RTD) of heterogeneous citrus waste particles was determined in a semi-pilot-scale rotary dryer with concurrent flow under several operational conditions. The experimental methodology was based on the stimulus-response technique, which consisted of injecting pulse-like tracers in the dryer feed stream. Measurements of RTD were performed to build up experimental curves that were numerically integrated to provide the mean residence time. A perfectly-stirred-tank in series model and a neural network model were derived. In addition, empirical and semi-empirical correlations from the literature were used to estimate residence time and the influence of operating conditions on this variable was investigated.