Fluidized Bed Dryers — Recent Advances

Daud, Wan Ramli Wan

doi:10.1163/156855208x336675

Cited by 21 publications

(4 citation statements)

References 58 publications

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“…Thus, higher inlet temperatures of drying air should be met, which leads to shorter drying times. However, the product quality considerations limit the applicable rise to the air temperature (Mujumdar, 1995;Daud, 2008). Excessive hot air can almost completely dehydrate the sago bagasse surface, making its pores shrink and almost close, leading to crust formation or "case hardening", which is usually undesirable.…”

Section: Resultsmentioning

confidence: 99%

Development of a Fluidized Bed Dryer for Drying of a Sago Bagasse

Othman¹,

Harry²

2021

JST

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Sago is an essential source of starch for some regions in the third and developing world. However, the sago processing industry has been producing a large amount of sago waste, and the untreated waste is usually disposed to the nearest river. It not only leads to the environmental problem, but it is illegal under the Environmental Quality Act 1974. Since the sago waste still has high starch content, which is 58%, it can be converted to high value-added products such as poultry feed. However, before being converted to other products, the sago must be dried to remove the moisture content to prevent any bacteria growth and ensure safety health issues have been observed. Recently, drying of sago bagasse using a fluidized bed dryer (FBD) has gained attention since the dry rate of the material is considerably faster compared to other methods. Due to that reason, the drying of the sago bagasse in the FBD is studied using computational fluid dynamic as it can be executed in a short period of time compared to the experimental approach. The FBD model was developed using ANSYS© Fluent academic version 19.2. The effect of the hot air feed temperature; T=50, 60, 70, and 80°C and velocity of hot air feed; v=1-4 m/s on the sago’s behavior and performance of fluidization profile were studied. The simulation results showed that the high temperature and air feed velocity would result in a rapid drying rate. Besides, the optimum drying rate was at T=60°C with the v=4 m/s as these conditions give a shorter drying time to achieve of final 10% moisture content. It also has the added advantages of reducing the power energy and cost supply. These optimal conditions are very crucial and should be consider as the dried sago bagasse tend to be retrograded when a higher temperature is applied.

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Section: Resultsmentioning

confidence: 99%

Development of a Fluidized Bed Dryer for Drying of a Sago Bagasse

Othman¹,

Harry²

2021

JST

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“…Various energy-consuming methods are applied for the disperse material drying [2]. Even though energy-consumption in convection drying is not the lowest, the convection dryers are often used for the disperse materials due to numerous advantages [3,4]. An active hydrodynamic regime used in such dryers contributes to the intensification of the process without reducing its cost efficiency, and it has the following advantages [5,6]: -the hydrodynamic sustainability of the process; -an increase in the relative velocity of the interacting phases motion; -a developed surface of the contacting phases interaction; -the approximation of a hydrodynamic model of flows in the apparatus to an ideal displacement model; -the reduced energy-consumption of the process and a lower specific amount of metal in apparatuses.…”

Section: Introductionmentioning

confidence: 99%

Investigation of the Convection Drying Process in a Multistage Apparatus with a Differential Thermal Regime

Krmela¹,

Аrtyukhova²,

Аrtyukhov³

2020

Manufacturing Technology

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This paper describes a search for an optimal organization of the drying agent motion in the convection dryers. An overview of the main methods on how to reduce the energy consumption for the convection drying of the disperse materials is presented. The use of the multistage shelf apparatuses with a differential thermal regime for the convection drying of the disperse materials is justified. The work contains the results of a computer modeling on determining the drying temperature and moisture characteristics with the use of various methods of the organization of the drying agent motion. The model is realized implementing the author's software product Multistage Fluidizer®. The software product enables to automatize calculation simultaneously by several optimization criteria and to visualize calculation results in the form of 3D images. The engineering computation of sectioning devices methodology with fluidized bed of particles is based on the calculation results. The automated calculations results give a base to design industrial drying device with a differential thermal regime.

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“…Fluidized bed drying is a novel and efficient method which makes it feasible to dry food products in continuous and moderate conditions. High rate of heat transfer makes drying a thrifty process; on the other hand, no need for various mechanical parts for drying reduces maintaining costs (Wan Daud ). It is very difficult to develop a complete mathematical model for predicting dependent variables of a process considering all independent variables.…”

Section: Introductionmentioning

confidence: 99%

Modeling the Drying Kinetics of Green Bell Pepper in a Heat Pump Assisted Fluidized Bed Dryer

Jafari

Ghanbari

Ganje

et al. 2015

Journal of Food Quality

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In this research, green bell pepper was dried in a pilot plant fluidized bed dryer equipped with a heat pump humidifier using three temperatures of 40, 50 and 60C and two airflow velocities of 2 and 3 m/s in constant air moisture. Three modeling methods including nonlinear regression technique, Fuzzy Logic and Artificial Neural Networks were applied to investigate drying kinetics for the sample. Among the mathematical models, Midilli model with R = 0.9998 and root mean square error (RMSE) = 0.00451 showed the best fit with experimental data. Feed‐Forward‐Back‐Propagation network with Levenberg–Marquardt training algorithm, hyperbolic tangent sigmoid transfer function, training cycle of 1,000 epoch and 2‐5‐1 topology, deserving R = 0.99828 and mean square error (MSE) = 5.5E‐05, was determined as the best neural model. Overall, Neural Networks method was much more precise than two other methods in prediction of drying kinetics and control of drying parameters for green bell pepper. Practical Applications This article deals with different modeling approaches and their effectiveness and accuracy for predicting changes in the moisture ratio of green bell pepper enduring fluidized bed drying, which is one of the most concerning issues in food factories involved in drying fruits and vegetables. This research indicates that although efficiency of mathematical modeling, Fuzzy Logic controls and Artificial Neural Networks (ANNs) were all acceptable, the modern prediction methods of Fuzzy Logic and especially ANNs were more productive and precise. Besides, this report compares our findings with previous ones carried out with the view of predicting moisture quotients of other food crops during miscellaneous drying procedures.

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Fluidized Bed Dryers — Recent Advances

Cited by 21 publications

References 58 publications

Development of a Fluidized Bed Dryer for Drying of a Sago Bagasse

Development of a Fluidized Bed Dryer for Drying of a Sago Bagasse

Investigation of the Convection Drying Process in a Multistage Apparatus with a Differential Thermal Regime

Modeling the Drying Kinetics of Green Bell Pepper in a Heat Pump Assisted Fluidized Bed Dryer

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