Fluidized Bed Drying Process Research Articles

Akışkan Yatak Kurutma Prosesi İçin Isı Pompalı Ön Isıtmanın Termoekonomik Analizi

Enerji verimliliği, küresel ısınma ve iklim değişikliği günümüzde üzerinde durulan en önemli konuların başında gelmektedir. Tüketilen enerjinin etkin ve verimli kullanımına ilişkin yeni tasarımlar yaparken de tasarımlarda kullanılacak yenilikçi ve verimli teknolojiler ekonomi ve çevresel olumsuz etkilerin azaltılmasına katkı sağlayacaktır. Bu çalışmada; tamamen gaz yakıcı bir cihazla çalışan döküm sektöründe kullanılan akışkan yataklı bir kum kurutma sistemine ısı pompası entegre edilerek doğalgaz tüketimi azaltılmaya ve bu sayede sistem kullanıcılarına doğrudan ve dolaylı kazanımlar yaratılmaya çalışılmıştır. Sudan suya çalışan ve çevre dostu R32 soğutucu akışkanı kullanılarak 20°C’deki ortam havasını 45°C’ye ön ısıtma yapacak şekilde tasarımı yapılan ısı pompası sisteminin performans katsayısı (COPIP) 3,88 olarak hesaplanmıştır. Isı pompası entegrasyonu sayesinde sistem yıllık 36.839,1 Nm3 doğalgaz tasarrufu gerçekleştirilecektir. Bu entegrasyon ile sistemin yıllık çalışma süresi, elektrik ve doğalgaz birim maliyetleri baz alınarak, işletmecisine 193.501,25 ₺/yıl mali tasarruf sağlayacağı öngörülmektedir. Sisteme entegre edilen ısı pompasının; ekipman ve kurulum fiyatı, güncel kur değeri ile yıllık mali tasarruf miktarı parametreleri dahilinde, sistemin amortisman süresi 1,50 yıl olarak hesaplanmıştır. Ayrıca sistemde kurulacak fotovoltaik paneller ile enerji üretilerek karbon emisyonunun azaltılabileceği ve yine fotovoltaik panellerin marifetiyle işletmeci firmaya ek bir gelir kalemi oluşturulabileceği de öngörülmektedir.

CFD-DEM investigation of the gas-solid flow characteristics in a fluidized bed dryer

Wet granules drying in a fluidized bed is a complex process and the process involves heat and mass transfer between gas and solid phases as well as the moisture changes in the granules. CFD-DEM model was employed to investigate the wet granule flow characteristics, the heat and mass transfer process in a fluidized bed drying process. The proposed model considered the liquid bridge force varying with granule moisture content and was validated by experimental data. Due to the computational capability restriction, pseudo 2D model simulations were first employed for the whole drying process and then 3D model simulations were performed at certain moisture contents to investigate the flow dynamics in more detail. The effects of granule number and the changing liquid bridge force on the drying process were further analyzed. Granule agglomeration was generated in the drying process at high moisture content due to the liquid bridge force, which affects the fluctuations of pressure and bed height. Moreover, the heat and mass exchange between the gas and solid phases mainly occurred in the interface of bubble phase and granule phase. With the increase of bed height, the granule volume fraction decreased and the transfer coefficients between these two phases decreased.

Experimental and computational study of fluidized-microwave drying process of shrinking parchment coffee and determination of quality attributes

Abstract This work presents the fluidized bed drying process combined with microwaves applied to Parchment coffee. In order to study different parameters that affect the quality of the grains, a mathematical model that describes energy and mass transfer during the drying process is presented and solved using Finite Elements Method (FEM) through COMSOL Multiphysics software. The model also considered the shrinkage of the grains due to water removal. Experiments were carried out in experimental prototype equipment obtaining the drying curves, which were utilized to validate the mathematical model. To study the impact of the operating conditions on the quality of the processed coffee, total polyphenolic content and antioxidant capacity were determined by Folin-Ciocalteau and free radical 2,2-diphenyl-1-picrylhydrazyl (DPPH) methods, respectively. Finally, nutritional parameters were related to operating conditions by the polynomial regression and desirability function methodology. Optimal operating conditions (1.4 m/s and 500 W) were found, which provides a product of excellent final quality.

Comparative study on the real-time monitoring of a fluid bed drying process of extruded granules using near-infrared spectroscopy and audible acoustic emission

The process of fluidized bed drying of granules was comparatively evaluated by on-line real-time measurements of granule moisture content (MC) using near-infrared spectroscopy (NIR) and audible acoustic emission (AAE). The extruded granules were prepared by kneading a powder blend containing lactose, starch, crystalline cellulose, and riboflavin, with water. The MC of the granules (while they were dried at 35 °C in a fluidized bed dryer) was monitored simultaneously with NIR and AAE. The prediction accuracy of the NIR and AAE using partial least squares (PLS) was verified by measuring MC of the granules. The best calibration models following NIR and AAE evaluations consisted of five latent variables with correlation coefficients of 1.000 and 0.998 and root mean square error of 0.259 and 0.615, respectively. As a result of external verification, the accuracy of MC analysis by AAE was slightly lower than that of NIR; however, it was still applicable in practice. Furthermore, the end point of fluidized bed drying process was automatically determined using the PLS discriminant analysis. From the above results, it can be concluded that the AAE-mediated granule drying process can be monitored with sufficient accuracy (compared with NIR).

Synchronization-Free Multivariate Statistical Process Control for Online Monitoring of Batch Process Evolution

Synchronization of variable trajectories from batch process data is a delicate operation that can induce artifacts in the definition of multivariate statistical process control (MSPC) models for real-time monitoring of batch processes. The current paper introduces a new synchronization-free approach for online batch MSPC. This approach is based on the use of local MSPC models that cover a normal operating conditions (NOC) trajectory defined from principal component analysis (PCA) modeling of non-synchronized historical batches. The rationale behind is that, although non-synchronized NOC batches are used, an overall NOC trajectory with a consistent evolution pattern can be described, even if batch-to-batch natural delays and differences between process starting and end points exist. Afterwards, the local MSPC models are used to monitor the evolution of new batches and derive the related MSPC chart. During the real-time monitoring of a new batch, this strategy allows testing whether every new observation is following or not the NOC trajectory. For a NOC observation, an additional indication of the batch process progress is provided based on the identification of the local MSPC model that provides the lowest residuals. When an observation deviates from the NOC behavior, contribution plots based on the projection of the observation to the best local MSPC model identified in the last NOC observation are used to diagnose the variables related to the fault. This methodology is illustrated using two real examples of NIR-monitored batch processes: a fluidized bed drying process and a batch distillation of gasoline blends with ethanol.

Variational PLS-Based Calibration Model Building With Semi-Supervised Learning for Moisture Measurement During Fluidized Bed Drying by NIR Spectroscopy

To measure the moisture content of granules during the industrial fluidized bed drying (FBD) process, a semi-supervised calibration model is proposed for using the near-infrared (NIR) spectroscopy to conduct in-situ measurement. To solve the dilemma of lacking sufficiently labeled samples as often encountered in various batch FBD processes, a semi-supervised variational inference PLS method is proposed to use up all the labeled and unlabeled spectra measured for calibration model building. Moreover, an adaptive Gamma distribution based sparsing algorithm is established to select the spectral variables for modeling, in order to overcome the high-dimensional input collinearity. Owing to the use of a variational inference learning approach, the constructed model can ensure not only prediction accuracy but also credibility. A numerical example and experiments on batch FBD processes of silica gel granules are shown to demonstrate the effectiveness and merit of the proposed method.

The Influence of Equipment Design and Process Parameters on Granule Breakage in a Semi-Continuous Fluid Bed Dryer after Continuous Twin-Screw Wet Granulation.

The drying unit of a continuous from-powder-to-tablet manufacturing line based on twin-screw granulation (TSG) is a crucial intermediate process step to achieve the desired tablet quality. Understanding the size reduction of pharmaceutical granules before, during, and after the fluid bed drying process is, however, still lacking. A first major goal was to investigate the breakage and attrition phenomena during transport of wet and dry granules, the filling phase, and drying phase on a ConsiGma-25 system (C25). Pneumatic transport of the wet granules after TSG towards the dryer induced extensive breakage, whereas the turbulent filling and drying phase of the drying cells caused rather moderate breakage and attrition. Subsequently, the dry transfer line was responsible for additional extensive breakage and attrition. The second major goal was to compare the influence of drying air temperature and drying time on granule size and moisture content for granules processed with a commercial-scale ConsiGma-25 system and with the R&D-scale ConsiGma-1 (C1) system. Generally, the granule quality obtained after drying with C1 was not predictive for the C25, making it challenging during process development with the C1 to obtain representative granules for the C25.

An experimental research to determine the fluidized bed regime of pepper in the fluidized bed drying process

This is an experimental study to determine that the minimum fluidization velocity, the fluidized bed height, and the pressure loss through the grain layer depend on the thickness of grain layers and moisture content of materials. The drying materials used in this study are fresh pepper and dried pepper of which moisture content is 54.2% and 12%, respectively. All the experiments are conducted with the thickness of the pepper layer ranging from 4mm to 44mm while the wind speed ranging from 5 m/s to 11m/s. From the result of experimental analysis, it can be seen that the minimum fluidization velocity of an air stream through fresh pepper ranges from 5.2m/s to 6,5m/s. The pressure drop of air stream through the fresh pepper is 225Pa while 147Pa for dry pepper, corresponding to the grain thickness of 37mm layer. By comparing the results determined from these experiments with computational models and some available correlations, the computational models of Fedorov, Baeyens-Geldart and Leva all match the experimental data collected from the pepper material. The correlation between the calculated and experimental results has a negligible error, the tendency to increase pressure loss depends on the thickness of grain layer is also quite similar. From the experimental data results obtained by determining the pressure drop through the pepper layers which depends on the thickness of both fresh pepper and dried pepper, the linear equations of the first order are established with high credibility.

Monitoring of high-moisture content particle drying in a fluidized bed by microwave and capacitance tomographic sensors

Particle drying in fluidized beds is a common and important process in food and pharmaceutical industry. However, the fluidization characteristic is complex due to the moisture content change in the process and it is a challenge to monitor the flow characteristics by conventional measurement approach, likes pressure and thermal probes. In this research, process tomography including capacitance and microwave tomographic systems are used to investigate the flow characteristics in a fluidized bed dryer with high-moisture content particles. Static tests were firstly carried out to investigate the image characteristics based on microwave tomography (MWT) and electrical capacitance tomography (ECT). The imaging ability was compared between MWT and ECT. In the dynamic tests, the drying process for particles with high-moisture content was monitored on-line by MWT and ECT separately. The static test results show that the high calibration for ECT is critical and particles with low moisture content should be used for high calibration of an ECT system to achieve high quality images for the dynamic tests. For the high calibration of ECT, there is an upper limit for the moisture content. With a fixed calibration background, the moisture content of particles should not exceed this upper limit value. MWT basically has no limitation on the moisture content both for high calibration and measurement. Dynamic test results illustrate that MWT is a good option to monitor high-moisture content particles drying in a fluidized bed and it is possible to combine ECT together to identify the gas–solids flow regime transit and to determine the moisture content by MWT in a fluidized bed drying process.

Linear Identification and Design of Optimal Controller for Multistage Fluidized Bed Dryer

In many particulate industries, one of the major unit operations used is fluidized bed drying process. In industries, which process large amount of solids, continuous dryers play significant role. The multistage fluidized bed dryer is adapted in research to improve the drying efficiency of final product. The moisture content is an important controlled variable in any drying process. In the present study, identification of three stage fluidized bed dryer by linear time-series models from experimental data has been done. The transfer functions and step response of three stages were identified. Based on state space model, linear quadratic controller was implemented for the identified model of multistage fluidized bed dryer in simulations. The controller was not implemented on the experimental setup.

Continuous twin screw granulation and fluid bed drying: A mechanistic scaling approach focusing optimal tablet properties.

This study provides the results of investigation on scaling approaches for three differently-sized continuous granulation lines, each consisting of a twin screw wet granulation process and a continuous fluid bed drying process. To check the initial scaling approach with regard to granule and tablet properties, a process parameter Design of experiment (DoE) was performed on each of the three equipment scales. The processed formulation did not contain cellulose to allow a high overall flowrate through the directly connected granulation and drying sections. Enhanced scaling aspects showed the influence of Froude number [-] at different twin screw granulator scales and screw speeds on the overgranulated particle fraction [% (V/V] as well as on the scale-dependent drying performance of the continuous fluid bed dryers. Scale-independent, specification limits of the two granule material attributes particle fine fraction [%] and residual water content [%] could be defined, resulting in high tableting performance in terms of tabletability and compressibility. Based on these specification limits and the statistical evaluation of the process parameter DoE, a process design space for the continuous granulation and drying process for each scale was calculated. It came up, that this process design space was decreasing in range with increasing equipment scale. The applicability of the presented scaling approach in terms of granule and tablet properties could successfully be demonstrated by three control experiments performed on the different equipment scales. In sum, this work delivers a basis for a smooth transition of scales within process development on the investigated continuous twin screw granulation and drying lines.

Wavelet based calibration model building of NIR spectroscopy for in-situ measurement of granule moisture content during fluidized bed drying

For in-situ measurement of the granule moisture content (MC) during a fluidized bed drying (FBD) process by using the near-infrared (NIR) spectroscopy, a novel spectral calibration model building method is proposed in this paper for improving the real-time measurement accuracy. To tackle the serious high-dimensional parameter estimation problem arising from a large number of NIR spectral variables in the wavelength range for measurement, a small number of wavelet functions are constructed to closely approximate the measured NIR spectral curve for each sample, such that a functional regression model is established based on these wavelet functions, which facilitates reducing the model parameters for output prediction while the spectral nonlinearity can be conveniently addressed. An active learning strategy is given to choose these wavelet basis functions with respect to a user specified fitting accuracy. Owing to the orthogonal property of wavelet basis functions, the established calibration model can be efficiently used for real-time measurement. Numerical studies and experimental results on in-situ measurement of the silica gel granule moisture under different FBD operating conditions well demonstrate the effectiveness of the proposed method.

Simulation and Analysis of Plug Flow Fluidized Bed Dryer

Today many industries now use the dryer as a part of grain-drying process even during wet and dry seasons. This helps in reducing spoilage and wastage of paddy. Mostly the available industrial dryers are expensive to purchase and to maintain its smooth functioning. This study therefore is a step to design a simple Plug flow fluidized dryer that can lead to introduce small scale dryers to paddy process industry. The Plug flow fluidized bed dryers are designed and fabricated in this study consists of the drying chamber, hot air distributer plate, hot air inlet and exit system, paddy entry and exit system, fluidization chamber unit with temperature control unit and the centrifugal fan. The evaluation of dryer is based on drying time and reduction in moisture content and outlet temperature of paddy on quality parameters. Dryer dimensions are very important to analyze heat and mass transfer analysis of the Plug flow fluidized bed drying process of paddy grains. It was found d that heat and mass transfer properties of paddy grains in fluidized bed dryer was decreases as the time of drying passes and very rapid at the start of drying. The model present here predicts about dryer dimensions along safe zone of rough rice moisture content with other parameters. Simulation results show a good agreement between the simulation model and the existing simulation models.

Data fusion strategies to combine sensor and multivariate model outputs for multivariate statistical process control.

Process analytical technologies (PAT) applied to process monitoring and control generally provide multiple outputs that can come from different sensors or from different model outputs generated from a single multivariate sensor. This paper provides a contribution to current data fusion strategies for the combination of sensor and/or model outputs in the development of multivariate statistical process control (MSPC) models. Data fusion is explored through three real process examples combining output from multivariate models coming from the same sensor uniquely (in the near-infrared (NIR)-based end point detection of a two-stage polyester production process) or the combination of these outputs with other process variable sensors (using NIR-based model outputs and temperature values in the end point detection of a fluidized bed drying process and in the on-line control of a distillation process). The three examples studied show clearly the flexibility in the choice of model outputs (e.g. key properties prediction by multivariate calibration, process profiles issued from a multivariate resolution method) and the benefit of using MSPC models based on fused information including model outputs towards those based on raw single sensor outputs for both process control and diagnostic and interpretation of abnormal process situations. The data fusion strategy proposed is of general applicability for any analytical or bioanalytical process that produces several sensor and/or model outputs. Graphical abstract.

Investigation and analysis of a fluidized bed dryer by process tomography sensor

In the pharmaceutical industry, fluidized beds are typically used for pellets drying, coating and granulation. The gas–solids flow characteristic in the process plays an important role to control the heat and mass transfer as well as the end-point product quality. Therefore, it is necessary to investigate the flow characteristics based on advanced measurement technologies. In this research, electrical capacitance tomography (ECT) sensor with eight electrodes was used to investigate the pharmaceutical fluidized bed drying process with different operation conditions. Key process parameters including solids concentration, particle moisture and capacitance signals in the process are given and analysed based on the ECT sensor. In addition, the fluidized bed process with Wurster tube is also investigated based on this ECT sensor. The effect of Wurster tube on the hydrodynamic behaviour and the dominant frequency spectrum distribution in the chamber were analysed based on fast Fourier transform. Test results reveal that process moisture change can be addressed from the raw capacitance of adjacent electrode pair combined with calibration model. Experimental result also indicates that ECT technology can provide useful information for process monitor in a fluidized bed dryer.

Energetic and exergetic analyses of Barnyard millet drying using continuous multistage fluidized bed dryer

AbstractMost of the exergy studies reported were in batch fluidized bed drying process. The continuous dryer plays a pivotal role in industrial usage. In this study, exergy and energy analyses of multistage fluidized bed drying of Barnyard millet with stages connected externally were examined. The dryer was operated by changing wall temperature of stages (313–328 K), air inlet velocity (1.01–1.3 m/s), downcomer height (50–70 mm), and flow rate of solids (5–10 kg/h). Drying characteristics of Barnyard millet by changing process operating conditions of the dryer, were reported and the energy utilization ratio, exergy loss and exergy efficiency of dryer were also reported. The EUR of dryer at steady state has been found to be in the range of 0.25–0.46 and the maximum exergy efficiency of dryer was observed as 0.64 and lowest as 0.371 in the continuous drying process.Practical ApplicationsFluidized beds offer many distinct features and advantages for processing of particulate food materials. To decrease the drying time than that for single stage dryers, continuous multistage fluidized bed dryer was introduced. Reducing moisture content from feed materials in continuous dryers while discharging continuously, helps to process large quantity of solid materials with good quality of product. Several dryers with different modifications and designs have been suggested by many earlier investigators but continuous dryers play significant role in particulate industry. The multistage dryer is designed by connecting two or more fluidized beds internally or externally, where each bed is termed as a stage. Advantages of the multistage dryer are improvement in gas–solid axial mixing, which results in good quality of product. Due to stage‐wise contact of solids with gas, dried product with uniform moisture content can be obtained.

110th Anniversary: Real-Time End Point Detection of Fluidized Bed Drying Process Based on a Switching Model of Near-Infrared Spectroscopy

For timely detection of the drying end point of a fluidized bed drying (FBD) process, a switching model based monitoring method is proposed based on in situ measurement of granule moisture content via near-infrared (NIR) spectroscopy. The least-squares support vector classification (LSSVC) method is adopted to build a global model for monitoring the initial underdrying phase with relatively higher granule moisture content. Subsequently, the instance based learning (IBL) strategy is used to select similar samples from historical batches for building up a local model to check on each query sample in the current process, in order to detect whether the real drying end point is reached. To solve the problem of selecting similar samples in high-dimensional NIR spectral space, the t-distributed stochastic neighbor embedding (t-SNE) strategy is introduced into the IBL model building method to ensure efficiency of dimension reduction. For online monitoring of an FBD process, a model switch strategy is proposed bet...

Production of Functional Non-dairy Creamer using Nigella sativa oil Via Fluidized Bed Coating Technology

Nigella sativa oil has a high potential to be developed into bioactive food ingredients. The aim of this study is to produce a low-fat, non-dairy creamer (NDC) from Nigella sativa oil (NSO) that is extracted by a supercritical fluid technique. The emulsion was processed with total solids of 40% and the drying process was performed using a spray dry technique at 160 °C inlet air temperature to obtain the microencapsulated oil. The agglomeration conditions (fluidizing time, fluid air temperature, and feed flow rate), were optimized using a response surface methodology (RSM) with a central composite design. The microencapsulated oil demonstrated low moisture content, high water solubility, strong antioxidant activity and high thymoquinone content in the developed creamer. The optimum conditions of the fluidized bed drying process were inlet air temperature (50 °C), drying time (25 min), and feed flow rate (1 mL/min). The sensory evaluation revealed that consumers’ acceptability is high for the developed coffee creamer. The findings indicated the high potential of the microencapsulated oil for applications to mass produce and commercialize functional non-dairy creamer.

Application of a mechanistic model of batch fluidized bed drying at laboratory and pilot scale

The aim of this work was to test the feasibility of reducing experimentation during the development of the fluid bed drying process of a pharmaceutical product, by conducting experimentation at laboratory scale and by using a mechanistic model calibrated on the laboratory scale data to simulate the process at pilot scale. The advantage of this approach with respect to a fully empirical approach, is that a limited number of experiments are run at pilot scale with the purpose of scale verification, instead of an extensive experimental campaign. Batch fluidized bed drying experiments were run with two different formulations containing the same active pharmaceutical ingredient (API) at laboratory and pilot scales. A mechanistic model was calibrated at laboratory scale, and then the same parameters describing drying behavior were used in simulations of the drying process at the pilot scale. The setup of the model differed for the two formulations; in particular, for the more hygroscopic formulation, the model needs to account for a higher influence of the material on drying. The simulated product temperature and moisture content in granules were compared with experimental data. Model accuracy is good at steady state for granule moisture content and for product temperature, in particular for the more hygroscopic formulation. During dynamic phases the product temperature prediction is less accurate: this effect is more visible for the less hygroscopic formulation. Finally, the mechanistic model calibrated at laboratory scale was used to simulate experimental results obtained at pilot scale. Good agreement between simulations and experiments could be observed, confirming that the suggested approach could be used in order to considerably decrease experimental effort during process development with respect to a fully empirical approach.

Real-time monitoring of particle size distribution in a continuous granulation and drying process by near infrared spectroscopy

In continuous granulation, it can be important to control granules particle size distribution (PSD), as it may affect final product quality. Near infrared spectroscopy (NIRS) is already a routine analytical procedure within pharmaceutical continuous manufacturing for the in-line analysis of chemical material-characteristics. Consequently, the extraction of additional information related to granules’ physical properties like particle size distribution is tempting, as it would enhance process knowledge without the need for new capital investments.Three in-line NIRS methods were developed via partial least squares regression, to predict dried granules PSD-fractions X10, X50, and X90 within a GMP-qualified continuous twin-screw wet granulation and fluid-bed drying process. Methods were developed for the size range of 20–234 µm (X10), 98–1017 µm (X50), and 748–2297 µm (X90) and assessed with one internal and three external validation datasets in agreement with current guidelines on NIRS. Internal validation indicated root mean square error of predictions (RMSEPs) of 17 µm, 97 µm, and 174 µm, for PSD X10, X50, and X90 respectively, with acceptable linearity, slope, and bias. Furthermore, the ratio of prediction to deviation (RPD), the ratio of prediction error to laboratory error (PRL), and the range error ratio (RER) were evaluated, with all values within the acceptance range for adequate to good NIR methods (1.75 > RPD < 3, PRL ≤ 2, RER ≥ 10). Methods applicability to in-line processes and their robustness towards water content and active pharmaceutical ingredient content was further demonstrated with three independent in-line datasets in real-time, showing good agreement between predicted and reference values. In summary, methods demonstrated to be sufficient for their intended purpose to monitor trends and sudden changes in dried granules PSD during continuous granulation and drying. Because of their fast response time, they are unique tools to characterize the dynamic behavior and navigate the agglomeration state of the material in static and transient process conditions during continuous granulation and drying.