Fluidized Bed Drying Process Research Articles

Drying kinetics and moisture diffusivity analysis of paddy in fluidised bed drying process

The drying kinetics and moisture diffusivity of paddy are studied in a fluidised bed dryer in this article. Different values of temperatures of drying air (T) at 45°C, 50°C and 55°C, velocities of drying air (V) at 2m/s, 2.5m/s and 3 m/s and paddy inventory (I) of 2 kg and 3 kg are used for drying paddy. The moisture content of paddy is reduced to a final value of around 12% (wb) from an initial value of around 28% (wb). Results showed that as the temperature and velocity of drying air increased, the drying rate also increased whereas, the drying rate decreased with an increase in paddy inventory. The moisture diffusivity is found to be increased as temperature and velocity of drying air increases, but it decreases with the inventory. A regression equation is obtained from linear regression analysis relating effective moisture diffusivity with all the drying process variables. With increase in drying air velocity and paddy inventory, the average activation energy decreases.

Drying kinetics and moisture diffusivity analysis of paddy in fluidised bed drying process

The drying kinetics and moisture diffusivity of paddy are studied in a fluidised bed dryer in this article. Different values of temperatures of drying air (T) at 45°C, 50°C and 55°C, velocities of drying air (V) at 2m/s, 2.5m/s and 3 m/s and paddy inventory (I) of 2 kg and 3 kg are used for drying paddy. The moisture content of paddy is reduced to a final value of around 12% (wb) from an initial value of around 28% (wb). Results showed that as the temperature and velocity of drying air increased, the drying rate also increased whereas, the drying rate decreased with an increase in paddy inventory. The moisture diffusivity is found to be increased as temperature and velocity of drying air increases, but it decreases with the inventory. A regression equation is obtained from linear regression analysis relating effective moisture diffusivity with all the drying process variables. With increase in drying air velocity and paddy inventory, the average activation energy decreases.

Online prediction of biomass moisture content in a fluidized bed dryer using electrostatic sensor arrays and the Random Forest method

The inherent moisture content in biomass needs to be dried before it is used for energy production. Fluidized bed dryers (FBD) are widely applied in drying biomass and the moisture content should be monitored continuously to maximise the efficiency of the drying process. In this paper, the moisture content of biomass in a FBD is predicted using electrostatic sensor arrays and a random forest (RF) based ensemble learning method. The features of electrostatic signals in the time and frequency domains, correlation velocity and the outlet temperature and humidity of exhaust air are chosen to be the input of the RF model. Model training is accomplished using the data taken from a lab-scale experimental platform and the hyper-parameters of the RF model are tuned based on the Bayesian optimization algorithm. Finally, comparisons between the online predicted and sampled values of biomass moisture content are conducted. The maximum relative error between the online predicted and reference values is less than 13%, indicating that the RF model provides a viable solution to the online monitoring of the fluidized bed drying process.

Accuracy Improvement of In-line Near-Infrared Spectroscopic Moisture Monitoring in a Fluidized Bed Drying Process.

An exploratory analysis of a large representative dataset obtained in a fluidized bed drying process of a pharmaceutical powder has revealed a significant correlation of spectral intensity with granulate humidity in the whole studied range of 1091.8–2106.5 nm. This effect was explained by the dependence of powder refractive properties, and hence light penetration depth, on the water content. The phenomenon exhibited a close spectral similarity to the well-known stochastic variation of spectral intensities caused by the process turbulence (the so-called “scatter effect”). Therefore, any traditional scatter-corrective preprocessing incidentally eliminates moisture-correlated variance from the data. To preserve this additional information for a more precise moisture calibration, a time-domain averaging of spectral variables has been suggested. Its application resulted in a distinct improvement of prediction accuracy, as compared to the scatter-corrected data. Further improvement of the model performance was achieved by the application of a dynamic focusing strategy when adjusting the model to a drying process stage. Probe fouling was shown to have a minor effect on prediction accuracy. The study resulted in a considerable reduction of the root-mean-square error of in-line moisture monitoring to 0.1%, which is close to the reference method's reproducibility and significantly better than previously reported results.

Scale-up of fluidized bed drying: Impact of process and design parameters

The fluidized bed drying unit operation is extensively used in the pharmaceutical industry. However, there are still many unanswered questions with respect to scaling up fluidized bed drying operations. In this study, a scaling method for the fluidized bed drying process was investigated to predict drying under new operating conditions based on existing experimental data. A normalization scaling factor was implemented based on the ratio of operating conditions – heating air temperature, air flow rate and the loading. The scaling method was examined experimentally using a small-scale MiniGlatt and a medium-scale Glatt GPCG-1 fluidized bed dryer. The predictions showed good agreement for variations in air temperature and flowrate, but predictions for variations in loading did not show as good agreement with the experimental data. We investigated the reason for the poor predictions and found that the air distributor area should be chosen as the bed area in the scaling model. Modifying the cross-sectional area available for drying by taking into account the physics of drying in the fluidized bed improves the agreement of the predictions with the experimental data for different loadings. Lastly, we examined scale-up predictions for the GPCG-1 drying performance based on the MiniGlatt experimental data.

Process monitoring and evaluation of a continuous pharmaceutical twin-screw granulation and drying process using multivariate data analysis

The present study aims at acquiring an in-depth process knowledge about a twin-screw granulation and fluid bed drying process performed on the commercially available continuous line. Batch Statistical Process Monitoring (BSPM) principles are used to describe and monitor the variables with a relevant time-related trajectory. The continuous granulator operates in a truly continuous manner and variables logged by this unit do not present time-relevant features. On the other hand, the fluid bed dryer is divided in six identical cells, which are sequentially filled and discharged, ensuring a continuous flow of material. Multiple variables logged at the dryer and subsequent product control unit, present time-relevant features. A profound analysis of these variables logged during normal operation, as well as an in-depth description of the startup period of the different units, were achieved.The BSPM concepts allows to monitor the time relevant variables of this continuous manufacturing line, to detect and diagnose deviations from normal operation and assign possible causes for the disturbances.

Experimental Design Approach for Optimization of Sucrose Fluid Bed Drying Process Conditions

Experimental Design Approach for Optimization of Sucrose Fluid Bed Drying Process Conditions

Discrete particle simulation of food grain drying in a fluidised bed

Drying is a common practice for post-harvest processing of food grains. Fluidised beds are often adopted for this purpose. It is of importance to understand the fluidised bed drying process for improving its energy efficiency. This work establishes a numerical drying model based on the combined approach of computational fluid dynamics and discrete element method for describing heat and mass transfer in the gas-solid flow system. Water evaporation is modelled in resemblance to a chemical reaction, thereby requiring fewer model parameters. The model is first described in detail. Then it is tested by comparing model predictions with those experimental data of corn kernel from the literature. General drying characteristics including grain and air moisture contents are reproduced qualitatively. The predicted drying rate curves are quantitatively comparable with those of experimental data. Finally, the effects of inlet air velocity and temperature are examined. The model predictions confirm that the drying rate increases with both the inlet air velocity and temperature. However, the drying product quality, here represented by the standard deviation of grain moisture distribution, increases with increasing air velocity or decreasing air temperature. This grain scale model would be useful to the design and control of the drying process.

Numerical Simulation on Superheated Steam Fluidized Bed Drying at Different Operating Pressures

Abstract During superheated steam fluidized bed drying process, the operating pressure has an important influence on heat and mass transfer characteristics and the vapor-solid two-phase flow characteristics. Based on the two-dimensional unsteady model of rapeseeds drying process, the influence of operating pressure on the superheated steam fluidized bed drying kinetics was revealed by computer numerical simulation. The quantitative analysis of relationship between operating pressure and maximum drying rate was conducted under negative pressure, near atmospheric pressure and high pressure environment, respectively. The optimum operating pressure values for superheated steam fluidized bed drying were obtained with the imported superheated steam temperature and superficial velocity. The simulation results provide a theoretical reference for superheated steam fluidized bed drying technology applying to agro-processing projects.

Multivariate statistical process control of a continuous pharmaceutical twin-screw granulation and fluid bed drying process

A multivariate statistical process control (MSPC) strategy was developed for the monitoring of the ConsiGma™-25 continuous tablet manufacturing line. Thirty-five logged variables encompassing three major units, being a twin screw high shear granulator, a fluid bed dryer and a product control unit, were used to monitor the process. The MSPC strategy was based on principal component analysis of data acquired under normal operating conditions using a series of four process runs. Runs with imposed disturbances in the dryer air flow and temperature, in the granulator barrel temperature, speed and liquid mass flow and in the powder dosing unit mass flow were utilized to evaluate the model’s monitoring performance. The impact of the imposed deviations to the process continuity was also evaluated using Hotelling’s T2 and Q residuals statistics control charts. The influence of the individual process variables was assessed by analyzing contribution plots at specific time points. Results show that the imposed disturbances were all detected in both control charts. Overall, the MSPC strategy was successfully developed and applied. Additionally, deviations not associated with the imposed changes were detected, mainly in the granulator barrel temperature control.

Application of Mathematical Models Using Volumetric Transfer Coefficients in Fluidized Bed Dryers

Fluidized bed dryers are often used in several industrial processes to dry wet granular solids with high moisture contents. During the drying process, simultaneous heat- and mass transfer occurs between the material and drying gas. Drying is an extremely energy intensive process, therefore the invested energy should be mitigated during planning the operation, granting optimal geometric and operational parameters of the device. During the planning, sufficiently accurate thermal models provide an opportunity to increase the effectiveness of dryers. The purpose of our work is to develop mathematical model to investigate the influence of operating parameters describing the simultaneous heat- and mass transfer in a fluidized bed dryer. The input parameters of the model are the volumetric transfer coefficients between the drying gas and the granules, due the uncertain heat- and mass transfer surface. A pilot plant fluidized bed dryer device is developed to determine the volumetric transfer coefficients and to study the heat- and mass transfer phenomena during the drying processes. The goal of our work is to model the fluidized bed drying process more accurately using volumetric transfer coefficients.

FLUIDIZED BED DRYING OF A GRANULATED PROTOTYPE BASED ON A POTENTIAL PROBIOTIC YEAST Meyerozyma guilliermondii: SELECTION OF PROCESS PARAMETERS AND DRYING PROTECTANT

Meyerozyma guilliermondii strain Lv196 has been identified as a native Colombian yeast with a high probiotic potential increasing rumen microbial efficiency at in vitro assays when a ruminant digestion system is simulated. Often, these types of products are supplied in a granulated form to facilitate its dosage to ruminants as cows, sheep, among others. To produce granulated bioproducts based on microorganisms, it is required to select suitable drying conditions, protectants and the adequate drying operation, decisive factors to guarantee cell viability and stability during storage. Most granulated products are dried through fluidized bed drying process reducing investment and maintenance costs, and improving mass and heat transfer decreasing operation time and the risk of product overheating. Therefore, in this work a selection ofdrying protectants through decision matrix was conducted based on parameters as compatibility with Lv196 and cost of protectants. The best two drying protectants were used as functional coadjuvants in the formulation of two granulated prototypes. Drying temperature, chamber pressure and the two prototypes were evaluated in an experimental design to select adequate conditions for a fluidized bed drying process. Finally, the stability of two dried granulated prototypes using selected conditions was determined. Prototype PF2 dried at 45oC and 0.5 bar during 30 min had a final moisture of 7.84 ± 0.01% and operation yield of 98.54 ± 0.11% guaranteeing a los of viability lower tan 2.09 ± 0.01% after 15 months of storage at room temperature.

Development of a two stage batch fluid bed drying process to minimise impact of entrainment on product quality and drying endpoint determination

Control over batch fluid bed drying processes is important to assure product of uniform moisture content as the level of residual moisture can impact further processing and final product performance and stability. Entrainment during batch fluidised bed drying can potentially result in non-uniformity of the product moisture content and impact reliability of the process endpoint. A two stage inlet air flow batch drying process was defined to minimise the impact of entrainment on product uniformity. The two stage batch fluid bed drying process reduced the level of entrainment observed. This enables the implementation of a relatively straightforward differential temperature technique based on a temperature sensor only to reliably indicate drying endpoint.

流動層乾燥プロセスにおける水分量のリアルタイムモニタリング

近赤外分光法（Near-Infrared Spectroscopy; NIRS）によるインライン水分量測定を，流動層乾燥法を用いたラクチュロースの三水和物結晶粉から無水物結晶粉への変換プロセスに適用して，ラクチュロース結晶粉の水分量変化をリアルタイムにモニタリングした．そのために，流動層乾燥中のラクチュロース結晶粉のNIRスペクトルを測定し，スペクトル前処理としてMSC（Multiplicative Scatter Correction; 乗算的散乱補正）を適用してリファレンス水分量とPLS回帰分析を行い，検量モデルを作成した．NIRスペクトルは乾燥用空気の温度依存性，および三水和物結晶粉で粒子径依存性を示したが，検量モデルではその影響は除去できた．この検量モデルの妥当性検証のため，バリデーション用に別途用意したテストセットのラクチュロース三水和物結晶粉の原料を使用してラクチュロース三水和物結晶粉から無水物結晶粉に変換する流動層乾燥を行い，検量モデルによる予測水分量とリファレンス水分量がよく一致することを確認した．このことから，NIRSによるインライン測定で流動層乾燥プロセス中のラクチュロース結晶粉の水分量変化，および乾燥終点をリアルタイムでモニタリングすることが可能であることが確認できた．

Drying performance analysis of a batch type fluidized bed drying process for corn and unshelled pistachio nut regarding to energetic and exergetic efficiencies

A batch type fluidized bed dryer is designed and constructed in order to investigate drying performance of a batch type fluidized bed drying process of corn and unshelled pistachio nut regarding to energetic and exergetic efficiencies. A series of experiments is carried out for the purpose in the covered range of 100g⩽mp⩽300g, 50°C⩽T⩽75°C, 6.87m/s⩽Um⩽10.86m/s and 47632⩽Re⩽75296. An increase in particle mass is found to cause an increase of drying time. On the other hand, an increase in drying air temperature and drying air velocity result in a decrease of drying time. The experimental results in terms of energetic and exergetic efficiencies are compared with the available ones in the literature by means of the previously proposed model of the authors. There is a good conformity between the present data and available data in the literature with a mean deviation of ±14% for energetic efficiency during drying process of corn. However, the deviation is raised to ±37% for energetic efficiency during drying process of unshelled pistachio nut, diverging from Eq. (9) which was previously proposed for corn drying. It can be deduced that both energetic and exergetic efficiencies are strongly dependent on air mass flow rate, particle mass and moisture content of particle to be dried and also ambient temperature.

STIRRED FLUIDIZED-BED DRYER OF REGENERATED ION EXCHANGER PARTICLES

<p class="TextCxSpFirst">This article describes intensification of the fluidized-bed drying process for regenerated spherical-shape ion exchanger particles in the batch mode, achieved by a mechanical stirrer in the fluidized bed layer of the dried particles. The effect of the mechanical stirring system on the drying process was examined.</p> <p class="TextCxSpLast">Calculations as well as results of comparison measurements provide evidence of a favourable effect of stirring on the total drying time as compared to the initial unstirred system. The regenerated ion exchanger particles pass to the fluid state in a shorter time and the ultimate total drying time is thus more than 60% shorter.</p>

Numerical simulation and experimental investigation of plug-flow fluidized bed drying under dynamic conditions

In this study, a mathematical model was presented for prediction of the plug-flow fluidized bed drying process under dynamic conditions resulted from the transient of inlet dry solids mass flow rate. The model previously developed and successfully validated for plug-flow fluidized bed drying process under steady-state condition was the starting point of this study. This model was extended in order to account for the mass and energy transfers between solids and gas phases at dynamic conditions. Additionally, a mass balance equation of dry-based solid holdup and a mass flow rate relationship for outlet solids were developed to predict the transient response of outlet dry solids mass flow rate. The model equations were solved numerically using the finite difference method. To validate the model, drying of rough rice in a laboratory-scale plug-flow fluidized bed dryer was investigated under dynamic conditions. A very satisfactory agreement between simulated and measured results was achieved.

Simulation of energetic- and exergetic performance of microwave-assisted fluidized bed drying of soybeans

The performance of microwave-assisted fluidized bed drying of soybeans was simulated (using a previously validated mathematical model) and analyzed based on the first- and second law of thermodynamics. The energy and exergy analysis were carried out for several drying conditions. The effects of inlet air temperature, microwave power density, bed thickness and inlet air velocity on the efficiencies and inefficiencies of drying process have been simulated and discussed. Generally, application of microwave energy during fluidized bed drying enhanced the exergy efficiency of drying process. However, the results showed that it was more efficient not to apply microwave energy at the first stage of fluidized bed drying process. The application of higher levels of drying air temperature led in higher exergy efficiencies. The values of mean relative deviations for the predictions of efficiencies and inefficiencies of drying process were less than 14%, compared with those calculated using experimental data.

Acoustic chemometrics for on-line monitoring and end-point determination of fluidised bed drying

An emerging process analytical technology (PAT) technique, acoustic chemometrics, was applied for monitoring of heated fluidised bed drying process. The feasibility of quantitative on-line monitoring of the drying progress and end-point determination of silica gel dried in a heated fluidised bed was investigated. Silica gel was used owing to its high water adsorption property and stability to heat. Acoustic signals were acquired using four accelerometers mounted at different locations on the wall of the fluidised bed. The accelerometer located close to the base was the best based results from this study. Prediction models validated with independent acoustic data (test set validation) were developed using partial least square regression, PLS-R. Some data pre-preprocessing techniques were applied to improve the developed prediction model. The final prediction results were satisfactory for monitoring of the drying progress and end point determination. The prediction results based on the independent data indicated a slope=0.97, correlation coefficient, R2=0.99 and the root mean square error of prediction was 1.71 water %, within the range 0–35.69 water % of sampled reference. It was concluded that the results from this feasibility study show that acoustic chemometrics is a viable on-line technique for monitoring the drying progress and for determining the end-point during drying of particulate matter. This on-line monitoring technique for the drying process developed in this study can be applied in many relevant industries in order to improve the overall economics of material drying by optimising fluidised bed drying technology using this decisive end-point determination approach.

Exergetic performance assessment of plug flow fluidised bed drying process of rough rice

Exergy analysis of rough rice drying process in laboratory–scale plug flow fluidised bed dryer was carried out. The drying experiments were conducted to assess the effects of inlet drying air temperature, feed mass flow rate and weir height on energy efficiency, exergy destruction, exergy efficiency, entropy generation, improvement potential rate and sustainability index. The energy and exergy efficiency values were found to be in the ranges of 7.97-31.32% and 4.18-12.00%, respectively. Results showed that the magnitude of exergetic parameters strongly depend on the drying variables. It was also confirmed that exergy analysis presented in this study could be applied to minimise the irreversibilities and losses occurring in the industrial fluidised bed drying systems and enhance the sustainability of fluidised bed drying processes.