Bed Dynamics Research Articles

Improvement in an Analytical Approach for Modeling the Melting Process in Single-Screw Extruders

Most single-screw extruders used in the plastics processing industry are plasticizing extruders, designed to melt solid pellets or powders within the screw channel during processing. In many cases, the efficiency of the melting process acts as the primary throughput-limiting factor. If the material melts too late in the process, it may not be sufficiently mixed, resulting in substandard product quality. Accurate prediction of the melting process is therefore essential for efficient and cost-effective machine design. A practical method for engineers is the modeling of the melting process using mathematical–physical models that can be solved without complex numerical methods. These models enable rapid calculations while still providing sufficient predictive accuracy. This study revisits the modified Tadmor model by Potente, which describes the melting process and predicts the delay-zone length, extending from the hopper front edge to the point of melt pool formation. Based on extensive experimental investigations, this model is adapted by redefining the flow temperatures at the phase boundary and accounting for surface porosity at the beginning of the melting zone. Additionally, the effect of variable solid bed dynamics on model accuracy is examined. Significant model improvements were achieved by accounting for reduced heat flow into the solid bed due to the porous surface structure in the solid conveying zone, along with a new assumption for the flow temperature at the phase boundary between the solid bed and melt film.

Preliminary CFD simulations of a lab-scale novel design of a particle receiver for CSP applications

In the present work, a preliminary CFD analysis of a novel design of particle receiver for CSP applications was performed. The particle receiver is a new lab-scale prototype consisting in a thin fluidized bed in which the walls are made of glass to permit thermal radiation to pass through. The working fluid is air and the thermal performance has been studied for the case in which i) only gas flows through the receiver (no particles) and ii) particles are placed in the receiver. The addition of the particles enhances the heating process by increasing the heat transfer coefficient from the heated wall to both the bed of particles and the gas resulting in an increase of more than 55% in the air temperature at the outlet of the receiver. Then, the bed dynamics have been studied in detailed as a function of the superficial gas velocity and the static bed height of the system. The analysis comprises the time evolution of the temperature of the gas and solid phases, the position of the centre of mass (that can be increased by more than 25% during the heating process) and the bubble characteristics. It has been found that when the gas velocity is increased by 66% the average temperature of the solids is only decreased 10%; while, for the static bed height, when the number of particles is increased 3 times the average temperature of the particles is increased by 18%.

Unraveling the dynamics of bed and breakfast clusters development: A multiscale analysis

The growing Bed and Breakfast (B&B) industry has an increasing impact on tourism transition, but the understanding of dynamics of the B&B cluster is still unclear. This study utilizes Zhejiang Province as a case study to explore the characteristics and patterns of B&B clusters and conducts a multiscale analysis of the influencing mechanisms. The research finds that B&B clusters can be divided into four types: Scenic area dependent pattern, Coastal landscape dependent pattern, Ancient village dependent pattern, Traffic-led pattern, demonstrating environmental adaptability and regional differences. As B&B clusters transition from the free development stage to the brand alliance stage, the dominant factors shift gradually from tourism resources and transportation to policy support and innovation. The agglomeration of B&Bs benefits the increase in prices, while it is crucial to control the reception scale and adopt a boutique and personalized approach to gain a competitive advantage. These findings can enrich the understanding of B&B cluster development and provide valuable insights for the B&B industry.

A Comparative Study of Different CFD Codes for Fluidized Beds

Fluidized beds are pivotal in the process industry and chemical engineering, with Computational Fluid Dynamics (CFD) playing a crucial role in their design and optimization. Challenges in CFD modeling stem from the scarcity or inconsistency of experimental data for validation, along with the uncertainties introduced by numerous parameters and assumptions across different CFD codes. This study navigates these complexities by comparing simulation results from the open-source MFIX and OpenFOAM, and the commercial ANSYS FLUENT, against experimental data. Utilizing a Eulerian–Eulerian framework and the kinetic theory of granular flow (KTGF), the investigation focuses on solid-phase properties through the classical drag laws of Gidaspow and Syamlal–O’Brien across varied parameters. Findings indicate that ANSYS Fluent, MFiX, and OpenFOAM can achieve reasonable agreement with experimental benchmarks, each showcasing distinct strengths and weaknesses. The study also emphasizes that both the Syamlal–O’Brien and Gidaspow drag models exhibit reasonable agreement with experimental benchmarks across the examined CFD codes, suggesting a moderated sensitivity to the choice of drag model. Moreover, analyses were also carried out for 2D and 3D simulations, revealing that the dimensional approach impacts the predictive accuracy to a certain extent, with both models adapting well to the complexities of each simulation environment. The study highlights the significant influence of restitution coefficients on bed expansion due to their effect on particle–particle collisions, with a value of 0.9 deemed optimal for balancing simulation accuracy and computational efficiency. Conversely, the specularity coefficient, impacting particle–wall interactions, exhibits a more subtle effect on bed dynamics. This finding emphasizes the critical role of carefully choosing these coefficients to effectively simulate the nuanced behaviors of fluidized beds.

Predicting nitrous oxide contaminants in Cauvery basin using region-based convolutional neural network

Nitrous oxide (N2O) in riverbeds affects hydrological processes by contributing to the greenhouse effect, indicating poor water quality, disrupting biogeochemical cycling, and linking to eutrophication. Elevated N2O levels signal environmental issues, impacting aquatic life and necessitating precise forecasting for effective environmental management and reduced greenhouse gas emissions. Precisely forecasting nitrous oxide (N2O) emissions from riverbeds is paramount for effective environmental management, given its significant potency as a greenhouse gas. This study focuses on the difficulties related to spatial feature extraction and modeling accuracy in predicting N2O in riverbeds in Tamil Nadu. To address the obstacles, the research suggests utilizing the Deep Learning Based Prediction of Nitrous Oxide Contaminants (DL-PNOC), which studies the N2O contaminants in water using Region-based Convolutional Neural Network (RCNN) for spatial feature extraction, to predict nitrous oxide contaminants. The study is centered on the Cauvery River Basin located in Tamil Nadu, where the emission of N2O is a matter of environment. The outcomes encompass the specialized N2O contaminant model for riverbeds and the implementation of RCNN achieves precise N2O forecasting. The DL-PNOC approach combines a contaminant model with RCNN deep learning techniques to capture spatial characteristics and predict N2O pollutants accurately. Furthermore, using the River Bed Dynamics Simulator reinforces the dependability of the findings. The DL-PNOC approach has exhibited encouraging results, as evidenced by the following metrics: a high IoU of 88.66%, precision of 88.96%, recall of 90.03%, F1 score of 89.22%, and low RMSE and MAE values of 9.14% and 7.59%, respectively. The findings highlight the efficacy of the DL-PNOC approach in precisely forecasting N2O pollutants in river sediments.

Hyposalinity stress reduces mussel byssus secretion but does not cause detachment

Environmental stressors such as salinity fluctuations can significantly impact the ecological dynamics of mussel beds. The present study evaluated the influence of hyposalinity stress on the detachment and survival of attached mussels by simulating a mussel farming model in a laboratory setting. Byssus production and mechanical properties of thread in response to varying salinity levels were assessed, and histological sections of the mussel foot were analyzed to identify the changes in the byssus secretory gland area. The results showed that hyposalinity stress (20 and 15 psu) led to a significant decrease in mussel byssus secretion, delayed initiation of new byssus production, and reduced plaque adhesion strength and breaking force of byssal threads compared to the control (30 psu) (p < 0.05). The complete suppression of byssal thread secretion in mussels under salinity conditions of 10 and 5 psu, leading to lethality, indicates the presence of a blockade in byssus secretion when mussels are subjected to significant physiological stressors. Histological analysis further demonstrated a decrease in the percentage of foot secretory gland areas in mussels exposed to low salinities. However, contrary to expectations, the study found that mussels did not exhibit marked detachment from ropes in response to the reduced salinity levels during one week of exposure. Hyposalinity stress exposure reduced the byssal secretion capacity and the mechanical properties of threads, which could be a cause for the detachment of suspension-cultured mussels. These results highlight the vulnerability of mussels to hyposalinity stress, which significantly affects their byssus mechanical performance.

Efficient Dye Removal and Water Treatment Feasibility Assessment for Iraq's Industrial Sector: A Case Study on Terasil Blue Dye Treatment Using Inverse Fluidized Bed and Adsorption

In this study, we investigated Terasil blue dye absorption on modified rice husk through batch and continuous trials. In continuous mode includes experimental tests in an inverse fluidized bed teqnique at various times and under various operating conditions (bed height, initial concentration, and varying flow rate) were investigated. The effect of various factors like pH, contact time, agitation speed and particle size on the removal efficiency (%) the Terasil blue dye were thoroughly investigated. The maximum removal efficiency (%) was achieved up to pH 7.0. Removal efficiency (%) increased with increasing contact time. The maximum removal efficiency (%) was achieved @200 RPM (rate per minute). Increasing in the particle size caused decreased in the removal efficiency (%). In batch experiments the Freundlich, and Temkin models showed good agreement with R2 value while the Langmuir model had moderate agreement. The value of qe is 1.73 mg/g under specific conditions; the Langmuir model provides q-max of 0.0078 mg/g and K-L of 0.0801 L/mg.Ongoing tests conducted in an inverse fluidized bed offer valuable insights into the hydrodynamic behavior of the system. The collected data effectively demonstrates the variations in pressure drops and bed heights. There is a positive correlation between bed height and fluid velocity, suggesting a significant association within the dynamics of fluidized beds.

Exploring nearshore bed dynamics of a mixed beach using the depth of closure conceptual model

Mixed sediment beaches are globally commonplace, yet little is understood of the extent and behaviour of their nearshore zones, potentially underestimating total cross-shore change. This paper is the first study to investigate the lateral and vertical extent of the active zone of the gravel-rich mixed beach in Pevensey Bay, a study site on the South East UK coastline. Morphodynamic change in the nearshore zone was studied at a range of timescales (days, months, years) suggesting that the width of the active nearshore zone correlated with the magnitude of the peak morphological change, whilst the depth of closure was influenced by bed slope, grain size and local variation in wave conditions. A conceptual model detailing the physical parameters responsible for local variations in the depth of closure was used to help understand differences between the observed and predicted depths of closure. Finally, ongoing chronic loss of sediment from below Mean Sea Level (MSL) was examined, which was shown to be independent of the depth of closure, but closely linked to the wider geomorphic setting of the bay.

Remote sensing monitoring of seagrass bed dynamics using cross-temporal-spatial domain transfer learning in Yellow river Delta

ABSTRACT Seagrass beds play a vital ecological role by regulating climate, maintaining biodiversity, and sequestering carbon. Achieving accurate classification of seagrass beds across both time and space is of significant importance for efficient monitoring. This paper addresses the challenges of seagrass bed classification in remote sensing imagery and the difficulty of achieving temporal and spatial transferability of classification model. Leveraging a long-term Landsat satellite image time series spanning from 1976 to 2022 in the Yellow River Delta, we enhance the DeepLab V3+ network and propose a cross-temporal-spatial domain seagrass bed transfer learning classification approach. We utilize selectively chosen images from a few years in partial regions for training, introduce freeze-training and-unfreeze-training during the model training phase, and then transfer the model to achieve cross-temporal and cross-temporal-spatial domain classification on images from other years and regions. Additionally, we discuss the factors influencing the classification results. The research results indicate that: (1)The method we proposed has shown good results, achieving classification accuracy of 83.17% and 80.99% for seagrass beds in both cross-temporal and cross-temporal-spatial domains. (2) The classification results indicate that this method achieves an average classification accuracy higher by 16.18% compared to networks such as UNet, PSPNet, HRNet, UNet++, SegFormer, etc. under cross-temporal conditions and higher by 17.56% under cross-spatiotemporal conditions for seagrass bed classification. (3) Based on the classification results, it is observed that from 1973 to 1986, the overall area of seagrass beds in the Yellow River Delta had an initial growth trend, with the largest seagrass bed area recorded in 1986, reaching 4281.289 hectares. Subsequently, the seagrass beds showed an overall decreasing trend, and by 2019 they had almost completely disappeared. The cross-temporal-spatial domain seagrass bed transfer learning classification method proposed in this paper can provide valuable support for the monitoring, restoration, management, and utilization of seagrass ecosystems.

Investigation of near-wall particle statistics in CFD-DEM simulations of dense fluidised beds and derivation of an Eulerian particle dynamic wall boundary condition

In two-fluid simulations of gas–solid fluidised beds, the gaseous phase and the particulate phase are modelled as continuous media. The stress exerted by the particulate medium on the container walls should be modelled to predict accurately the bed dynamics. This paper addresses the modelling of sliding particle–wall contacts in two-fluid simulations, based on reference simulations coupling computational fluid dynamics with the discrete element method (CFD-DEM), in which the individual movement of the particles is tracked. The analysis of the CFD-DEM highlights the complex near-wall behaviour of the particles, which is not reproduced by two-fluid models. Nevertheless, the particle–wall shear stress can be expressed based on the total granular pressure within the first cell off the wall. The model is validated for the two-fluid simulation of a bubbling gas–solid fluidised bed of olefin particles in the dense-fluidisation regime.

ANALYSIS OF THE CURRENT STATE AND DEVELOPMENT TRENDS OF THE HOTEL INDUSTRY IN EU COUNTRIES

Objective. The objective of the article is to analyze the main indicators of the functioning of the hotel industry in the EU countries and determine the current development trends. Methods. In order to achieve the set goals and objectives, the following research methods are used: analysis and synthesis (to determine indicators of the development of the hospitality industry of EU countries suitable for further analysis), statistical research, namely the construction and analysis of dynamic series (to determine and evaluate trends and regularities development of the hospitality industry of the EU countries), comparative analysis (for a country comparison of the EU countries hotel industry development indicators), cartographic method (for a visual demonstration of the spatial location of hotels and similar accommodation facilities in the EU countries), graphic and tabular methods (for a visual representation of statistical material ). Results. A study of the hotel industry development in EU countries is carried out based on the analysis of the main indicators of its functioning over the period 2012-2022, namely: the number of hotels and similar accommodation establishments; number of beds in hotels and similar accommodation establishments; the number of persons staying in accommodation establishments; number of overnight stays in accommodation establishments. The analysis of the main indicators of the EU countries hotel industry development in 2012-2022 allows us to identify the following trends: 1) constant growth in the number of hotels and similar accommodation facilities with an average growth rate of 2.19% and a negative growth of 3.8% in each of 2020; 2) significant national disparity in the number of hotels and similar accommodation facilities, as well as the rates of their positive and negative growth. Thus, the highest rates of growth were observed in Croatia, Romania, Slovenia, Portugal, Lithuania and Malta, while negative growth was recorded in Germany, Greece, Hungary, Finland, Luxembourg; 3) a significant difference in the number and dynamics of beds in hotels and similar accommodation facilities by EU countries. Thus, the largest increase in hotel capacity occurred in Croatia, Portugal, Slovenia and Lithuania, while the most significant negative increase was recorded in Hungary and Luxembourg; 4) a gradual steady increase in the number of arrivals at tourist accommodation establishments in the period 2012-2019 and a sharp decrease in 2020 by 53.28% under the influence of the Covid-19 pandemic and quarantine restrictions; 5) a gradual steady increase in the number of overnight stays in accommodation facilities of EU countries, their rapid reduction due to the impact of Covid-19 in 2020 (-50.54%) and the restoration of a positive trend in 2021 due to the relaxation of quarantine restrictions and the introduction of vaccination ( +28.8%).

Data driven reduced modeling for fluidized bed with immersed tubes based on PCA and Bi-LSTM neural networks

The fast and accurate reduced-order modeling of fluidized beds is a challenging task in the field of fluid dynamics, owing to their high dimensionality and nonlinear dynamic behavior. In this study, a nonintrusive reduced order modeling method, the reduced order model based on principal component analysis and bidirectional long short-term memory networks (PBLSTM ROM), was developed to capture complex spatio-temporal dynamics of fluidized beds. By combining principal component analysis and Bidirectional long- short-term memory networks, the PBLSTM ROM effectively extracted dynamic evolution information without any prior knowledge of governing equations, enabling reduced-order modeling of unsteady flow fields. The PBLSTM ROM was validated using the solid volume fraction and gas velocity flow fields of a fluidized bed with immersed tubes, showing superior performance over both the PLSTM and PANN ROMs in accurately capturing temporal changes in the fluidization fields, especially in the region near immersed tubes where severe fluctuations appear. Moreover, the PBLSTM ROM improved the simulation speed by five orders of magnitude compared to traditional computational fluid dynamics simulations. These findings suggest that the PBLSTM ROM presents a promising approach for analyzing the complex fluid flows in engineering practice.

Analysis of mesoscopic mechanical dynamic characteristics of ballast bed with under sleeper pads

The meso-dynamical behaviour of a high-speed rail ballast bed with under sleeper pads (USPs) was studied. The geometrically irregular refined discrete element model of the ballast particles was constructed using 3D scanning techniques, and the 3D dynamic model of the rail–sleeper–ballast bed was constructed using the coupled discrete element method–multi-flexible-body dynamics (DEM–MFBD) approach. We analyse the meso-mechanical dynamics of the ballast bed with USPs under dynamic load on a train and verify the correctness of the model in laboratory tests. It is shown that the deformation of the USPs increases the contact area between the sleeper and the ballast particles, and subsequently the number of contacts between them. As the depth of the granular ballast bed increases, the contact area becomes larger, and the contact force between the ballast particles gradually decreases. Under the action of the elastic USPs, the contact forces between ballast particles are reduced and the overall vibration level of the ballast bed can be reduced. The settlement of the granular ballast bed occurs mainly at the shallow position of the sleeper bottom, and the installation of the elastic USPs can be effective in reducing the stress on the ballast particles and the settlement of the ballast bed.

Crystallization and refluidization in very-narrow fluidized beds

Fluidization of solid particles by an ascending fluid is frequent in industry because of the high rates of mass and heat transfers achieved. However, in some cases, blockages occur and hinder the correct functioning of the fluidized bed. In this paper, we investigate the crystallization (defluidization) and refluidization that take place in very-narrow solid–liquid fluidized beds under steady flow conditions. For that, we carried out experiments where either monodisperse or bidisperse beds were immersed in water flows whose velocities were above those necessary for fluidization, and the ratio between the tube and grain diameters was smaller than 6. For monodisperse beds consisting of regular spheres, we observed that crystallization and refluidization alternate successively along time, which we quantify in terms of macroscopic structures and agitation of individual grains. We found the characteristic times for crystallization and propose a new macroscopic parameter quantifying the degree of bed agitation. The bidisperse beds consisted of less regular spheres placed on the bottom of a layer of regular spheres (the latter was identical to the monodisperse beds tested). We measured the changes that macroscopic structures and agitation of grains undergo and show that the higher agitation in the bottom-layer hinders crystallization of the top layer. Our results bring new insights into the dynamics of very-narrow beds, in addition to proposing a way of mitigating defluidization.

Unsteady behaviour of bubble column in homogeneous flow regime: Startup and shutdown

The startup (engagement, EN) and shutdown (disengagement, DE) processes in the bubble column are investigated both experimentally and theoretically. Two horizontal interfaces, top and bottom, characterize the evolving bubble bed. Their motion is explored by measurements in a laboratory air–water bubble column operated in the homogeneous flow regime (HoR). The effect of two control parameters is determined: clear liquid height L and gas superficial velocity q. The following results are obtained: the trajectories of the top and bottom interfaces, the duration of the early and late stages of EN, the coordinate points of the typical events of the bubble bed dynamics, the bubble swarm velocities related to the interfaces, the characteristic time scales, the symmetry features of EN and DE processes, the parametric dependence on L and q. A simple mathematical model is suggested to describe and interpret the experimental data.

ANALIZA ZMIAN PARAMETRÓW HYDRAULICZNYCH W RZECE NIZINNEJ PRZY ZASTOSOWANIU MODELOWANIA NUMERYCZNEGO

Aim of the study: River channels are dynamic structures in which fluvial processes leading to equilibrium state between energy of flowing water and the stability of the bed material. The changes of river morphology is difficult to capture using the monitoring tools, however, physical or numerical modeling can be used instead to reflect these natural processes. Objective of the study is to analyze the variability of hydraulic parameters and their impact on morphological changes using numerical modeling of a regulated section of the Nida River. Material and methods: On the basis of field measurements, numerical model of the river was built. In this section, the channel has been strengthened, which enables the process of its restoration. Numerical modeling was carried out for a range of flows from low to an overbank one. Bankfull discharge was determined using the Riley method. Calculations based of modeled parameters made it possible to analyze their impact on the bed dynamics. Results and conclusions: The numerical modeling resutls (average velocity, shear stresses, and water depth) was used to calculate shear velocity, Reynolds Number, Grain Reynolds Number and settling velocity. The lack of clear trends of changes in individual parameters with increasing flows proves the existence of irregular connections between flowing water and riverbed. Changing discharge in the river affects not only the intensity of fluvial processes, but also their location. The bottom morphology created during low flows is completely changed at the passage of high water, as indicated by measurements and simulations of the examined section of the Nida River.

A comparison and coupling of two novel sensors for intertidal bed‐level dynamics observation

AbstractPrevious studies have revealed the importance of short‐term bed‐level change on the long‐term development of intertidal ecosystems. One of the recent advancements in the short‐term bed dynamics observation is the developments of laser‐based surface elevation dynamics (LSED) and acoustic surface elevation dynamics (ASED) sensors. These two sensors are developed to automatically monitor tidally induced bed‐level changes, and their measuring windows are during emergent and submerged periods, respectively. So far, there is no direct comparison or joint application of these two sensors. Therefore, in the current study, we first compare their observation precision in both laboratory and field conditions. Results show that both sensors' measurements are in good agreement with the manual measurements in the flume (R2 &gt; 0.99) and field (R2 ≈ 0.70), indicating the applicability of each sensor in natural environment. Finally, a coupled system (i.e., combining LSED and ASED) is established in a mangrove wetland and both sensors show good agreement with each other (R2 = 0.69). Results also demonstrate that the coupled observation system can well capture the bed‐level change during emergent and submerged conditions, which provides detailed continuous data sets to study the bed‐level dynamics within a tidal cycle. Furthermore, large‐scale monitoring systems can also be established via mobile network module embedded in the sensor, providing real‐time monitoring for bed‐level changes, which is valuable to coastal morphological research and vital for detecting deterioration of coastal ecosystems and the services they provide to be able to apply adaptive management.

CFD simulations to study bed characteristics in gas–Solid fluidized beds with binary mixtures of Geldart-B particles: A qualitative analysis

The bed dynamics of unary and binary fluidized beds play a key role in understanding the pressure drop and hence provides an opportunity for performance improvement of the beds. In the present work, characteristics of fluidized beds with binary mixtures of Geldart-B particles were investigated using CFD simulations. The phenomena of segregation and mixing using simulations were studied, both qualitatively and quantitatively, at a range of superficial gas velocities (0.3–0.6 m/s) and two different bed heights. The study was divided into two parts. In Part I, the current study, a qualitative analysis of flow patterns for seven different binary mixtures, is presented. The quantitative analysis, including particle and gas velocity profiles, particle volume fraction profiles, and correlations for minimum fluidization velocity and pressure drop, will be presented in Part II of this work. A mathematical model consisting of an Eulerian-Eulerian model with RNG k-ε model and KTGF model to capture the bubble dynamics was used. The standardized values of coefficients and plastic stresses have been used for all simulations. The CFD model was validated using experimental data from the literature. Qualitative predictions of volume fraction profiles of small-sized particles showed that, for mixtures within a range of 40%–60% Geldart-B type large particles, the bubble and solid particle dynamics were different from those of single particles of the superficial gas velocities considered. In contrast to the single particles in the given superficial gas velocity range that were in bubbling regime, the binary particles showed a transition from bubbling to slugging to turbulent regime, as demonstrated by qualitative analysis. A homogeneous regime was observed for lower superficial gas velocities for mixtures consisting of 0%–20% large particles.

Effect of Inlet Flow Strategies on the Dynamics of Pulsed Fluidized Bed of Nanopowder.

The use of fluidization assistance can greatly enhance the fluidization hydrodynamics of powders that exhibit poor fluidization behavior. Compared to other assistance techniques, pulsed flow assistance is a promising technique for improving conventional fluidization because of its energy efficiency and ease of process implementation. However, the inlet flow configuration of pulsed flow can significantly affect the bed hydrodynamics. In this study, the conventional single drainage (SD) flow strategy was modified to purge the primary flow during the non-flow period of the pulse to eliminate pressure buildup in the inlet flow line while providing a second drainage path to the residual gas. The bed dynamics for both cases, namely, single drainage (SD) and modified double drainage (MDD), were carefully monitored by recording the overall and local pressure drop transients in different bed regions at two widely different pulsation frequencies of 0.05 and 0.25 Hz. The MDD strategy led to substantially faster bed dynamics and greater frictional pressure drop in lower bed regions with significantly mitigated segregation behavior. The spectral analysis of the local and global pressure transient data in the frequency domain revealed a pronounced difference between the two flow strategies. The application of the MDD inlet flow strategy eliminated the disturbances from the pulsed fluidized bed irrespective of the pulsation frequency.

Powder bed dynamics of a single-tablet-scale vibratory mixing process

Vibratory mixing is a promising technique for the blending of pharmaceutical powders to produce solid dosage forms. In this study we evaluate the particle dynamics inside a single-tablet-scale vibratory mixing device, to gain insight on the contributions of diffusive and convective mixing on the blending performance. To investigate the influence of vibration parameters, the frequency of vibration is varied from 100 to 300 Hz keeping similar acceleration amplitudes. Particle-dynamics evaluation is realized using high-speed video recordings and PIV-analysis. The experiments showed faster onset of agitation, higher average velocity magnitudes, and higher apparent granular temperatures for lower vibration frequencies. The size of the dilute zones, predominately responsible for rapid mixing, decreased with increasing frequency. Comparison with studies on the mixing performance from literature revealed a good correlation between the observed dispersion coefficient and the mixing speed, indicating that diffusive mixing mechanisms are the major driving factor in this single-tablet-scale blending process. • Diffusion is the dominant mechanism in vibratory mixing on single-tablet-scale. • Velocity and dispersion coefficient decrease with vibration frequency. • Rapid mixing happens inside active dilute regions in the agitated powder bed. • The position and size of active dilute zones strongly impact the mixing efficacy. • The size of active dilute zones increases for decreasing frequencies.