Evolution Of Particle Size Distribution Research Articles

Analysis and simulation of wet-granulation processes

BackgroundSize enlargement by wet-granulation is one of the most important unit operation in several industrial fields: pharmaceutics, food processing, animal nutrition, agronomics, and so on. A lot of techniques have been used in order to measure the particle size distributions (PSD) and a few different approaches are available to model the PSD evolution during the process, mainly based on population balance equations (PBE). However, difficulties in both the activities (reliable measurement and robust modeling) have hindered their diffusion in industrial practice, keeping the granulation closer to an art than to a science. MethodsIn this work, a fast and reliable method to measure PSD, based on dynamic image analysis (DIA) is presented and used in two case histories, one on a batch process on lab scale, and the other on a continuous process on plant scale. Significant findingsThe evolution of PSD was successfully described by models based on PBE, confirming the validity and the usefulness of the two approaches (experimental/modeling). The resulting model could be used as a basis for the process analysis and – to some extent – to predict the system's behavior in different conditions.

Modeling titanium dioxide (TiO2) nanoclusters using a 2D sectional method with molecular dynamics (MD) determined coagulation rates

Accurate prediction of the particle size distribution (PSD) evolution of growing nanometer scale particles is important in designing gas-phase synthesis reactors for the production of nanomaterials. Towards improved predictions of growth, we model the evolution of the PSD of 1-4 nm TiO2 particles from the decomposition of titanium tetraisoproxide (TTIP) using a two-dimensional (2D) sectional method, uniquely with coagulation rates derived from molecular dynamics (MD) trajectory calculations which account for detailed particle–particle interactions. The PSDs predicted by the 2D sectional method are compared to recent experimental measurements of PSDs in the 1-3 nm range in a flow tube reactor. The nucleation of particles is modeled based on prior mobility measurements of ions attributed to TTIP and their decomposition, with the specific nucleation rate here fitted as a fraction of base nucleation rate (k) derived from these prior measurements. In the 2D sectional model, we examine the influence of the initial (nucleated) particle charge distribution on the PSD, with different coagulation rate coefficients for neutral-charged and charged-charged particle collisions. With the MD-derived coagulation rate coefficients, we find that using nucleation rate coefficients between 0.005k and 0.03k leads to strong agreement between modeled PSD and measured PSD for a wide variety of experimental residence times, initial TTIP concentrations and temperatures. Increasing the charge fraction from 0% (uncharged) to 80% (bipolar) does not result in a significant change in the PSD, because the particles rapidly self-neutralize through coagulation based on the simulation results. The results with MD-derived coagulation rate coefficients are compared to those of the sectional method with classical kinetic theory of gases (KTG) rates with a constant enhancement factor to account for potential interactions. Through comparison, we find that the predictions from the classical KTG model consistently exhibit weaker coagulation rates than the MD-derived model during the PSD evolution.

A Novel PBM for Nanomilling of Drugs in a Recirculating Wet Stirred Media Mill: Impacts of Batch Size, Flow Rate, and Back-Mixing.

We examined the evolution of fenofibrate (FNB, drug) particle size distribution (PSD) during the production of nanosuspensions via wet stirred media milling (WSMM) with a cell-based population balance model (PBM). Our objective was to elucidate the potential impacts of batch size, suspension volumetric flow rate, and imperfect mixing in a recirculating WSMM. Various specific breakage rate functions were fitted to experimental PSD data at baseline conditions assuming perfect mixing. Then, the best function was used to simulate the PSD evolution at various batch sizes and flow rates to validate the model. A novel function, which is a product of power-law and logistic functions, fitted the evolution the best, signifying the existence of a transition particle size commensurate with a grinding limit. Although larger batches yielded coarser and wider PSDs, the suspensions had identical PSDs when milled for the same effective milling time. The flow rate had an insignificant influence on the PSD. Furthermore, the imperfect mixing in the mill chamber was simulated by considering more than one cell and different back-mixing flow ratios. The effects were weak and restricted to the first few turnovers. These insights contribute to our understanding of recirculating WSMM, providing valuable guidance for process development.

A journey through space and time in the Godbert-Greenwald furnace: The evolution of a dust cloud particle size distribution

Minimum Ignition Temperature (MIT) characterizes the ignition sensibility of a dust cloud. This work assesses the role of a standard Godbert-Greenwald furnace in the agglomeration/deagglomeration and fragmentation phenomena. Several organic powders and different dispersion pressures were tested. The average residence time varied from 120 to 330 ms according to the amount of powder injected and the pulse pressure. Entanglement was observed for coarser cellulose particles, while surface cohesion forces characterised the agglomerates of finer cellulose, glucose and ascorbic acid. The latter was characterised by fragmentation, especially at 0.5 and 1 bar(g). Biot, Pyrolysis and Damköhler numbers were used to analyse the effects of cellulose agglomeration and deagglomeration. At 600 K, the pyrolysis is the rate-limiting step, but from 700 K, the external heat transfer becomes the rate-limiting step, which would not happen without agglomeration. Due to the particle size distribution evolution, but also to turbulence and residence time variation, MIT can vary by 50 °C.

Experimental and numerical investigation on soot formation and evolution of particle size distribution in laminar counterflow ethylene flames

A detailed investigation of the process of soot formation in ethylene-fueled laminar counterflow diffusion flames is conducted using dedicated experiments and numerical simulations. Two different strategies based on the Discrete Sectional Method (DSM) and the Split-based Quadrature Method of Moments (S-EQMOM) are considered to model the evolution of soot particle size distributions, and their comparative assessment is carried out for soot formation prediction and particle growth. A consistent chemical reaction mechanism describing the oxidation of hydrocarbon fuels and the prediction of soot precursors with the growth of polycyclic aromatic hydrocarbons (PAHs) up to pyrene ( ▪ ) is examined. Experiments for various strain rates and fuel compositions are performed to assess the sensitivity of soot production to these two parameters. The results show that both modeling strategies captured well the qualitative trends of soot volume fraction under variations in strain rate and mixture composition, with slight over-prediction of the peak values. For both soot models, a higher sensitivity of soot formation is noticed by changes in mixture composition compared to those of strain rate variation. Additionally, the soot models demonstrated promising performance in capturing the experimentally observed evolution of the soot particle size distribution (PSD).

Turning fly ash and waste gypsum into a resource for backfilling applications

Flue Gas Desulfurization Gypsum (FGDG), an industrial by-product generated by power plants, was thermally treated and incorporated in cement-free fly ash bricks. This study aimed to determine the effects of using a thermally treated FGDG as an additive to improve the mechanical and structural properties of cement-free fly ash bricks. FGDG was thermally treated for 2 h at different temperatures. The influence of varying amounts (10–50%) of thermally treated FGDG on the performance of cement-free bricks was analyzed through mechanical properties, micrography, durability, the evolution of particle size distribution and environmental characteristics experiments. The effect of curing temperatures and curing age on the strength development and microstructural properties was also investigated. A Toxicity Characteristic Leaching Procedure (TCLP) was carried out to determine the leachability of metals from the synthesized FA cement-free brick. The results showed that the FGDG had a high calcium oxide content. In contrast, FA is mainly composed of silica, and both materials carry cementitious properties making both good raw materials for this study. The FA cement-free bricks containing 30% of thermally treated FGDG, oven-cured at 60 ℃, yielded the highest unconfined compressive strength (UCS) of 7.14 MPa. However, curing at ambient temperature for 28 days yielded a better UCS of 7.37 MPa. The particle size distribution showed that particles transformed from fine particles at 7 days to larger particles at 28 days due to particle growth. Durability tests showed that the developed bricks could withstand 7 wet/dry cycles. The TCLP showed that the leachability concentrations of all metals are within the limit and, therefore, can be potentially used as a building material in backfilling. The synthesis of FA/FGDG composite will aid in reducing the generated waste gypsum in landfills consequently eradicating human health challenges and loss of biodiversity. This paper showed that developing FA/FGDG composites will reduce their environmental impact and make them a resource for other valuable products such as backfilling applications and green building bricks.

Dynamic coassembly of nanodiamonds and block copolymers in organic solvents

Nonaqueous suspensions of nanoparticles have potential value in a wide range of applications, from coatings to environmental remediation. However, organic solvents often lead to nanoparticle agglomeration, and few methods developed to counteract this phenomenon. We present a novel approach to achieve stable nanoparticle suspensions in both nonpolar and polar aprotic solvents. Our method utilizes nanodiamonds (NDs) as a model system, due to the rich nature of their surface chemistry. This technique involves three key steps: (1) ultrasonication of air-oxidized NDs (OXNDs) in dimethylacetamide (DMAc), (2) the introduction of amphiphilic dispersants primarily composed of PVA-b-PMMA block copolymers (BCPs), and (3) exchanging DMAc with organic solvents to promote composite micelle formation, where BCP forms the micelle corona encapsulating OXND as the micelle core. Our method yields stable suspensions with particle sizes strongly influenced by thermokinetic interactions between OXND, BCP, and the solvent. Dynamic light scattering measurements of OXND–PVA-b-PMMA suspensions demonstrate that stabilization in toluene is governed by steric hindrance, while in THF or CHCl3 both electrostatic repulsion and steric hindrance contribute to particle stabilization. Characterization through electron microscopy and AFM reveals the efficacy of our coassembly method for producing uniformly-sized composite micelles. We identify a critical BCP:OXND weight ratio, analogous to the critical micelle concentration in surfactant-stabilized suspensions, crucial for effective particle stabilization. By analyzing the evolution of particle size distribution with varying solvent composition, we propose a dynamic coassembly mechanism between OXND and BCP, wherein OXND particles and encapsulating BCP chains dynamically rearrange to reach an equilibrium structure as the thermodynamic quantities of the surrounding medium change. Furthermore, BCP micellization is shown to play a vital role in preventing OXND aggregation during solvent exchange, resulting in uniformly sized particles. This enhanced understanding of the OXND–BCP coassembly mechanism in organic solvents holds promise for the development of novel functional materials. Our study provides insights into fabricating stable nanoparticle suspensions with diverse applications to coatings, lubricants, drug delivery, nanocomposite materials, biosensing, medical imaging, and environmental remediation.

Precise Modeling of the Particle Size Distribution in Emulsion Polymerization: Numerical and Experimental Studies for Model Validation under Ab Initio Conditions.

The particle size distribution (PSD) in emulsion polymerization (EP) has been modeled in the past using either the pseudo bulk (PB) or the 0-1/0-1-2 approaches. There is some controversy on the proper type of model to be used to simulate the experimental PSDs, which are apparently broader than the theoretical ones. Additionally, the numerical technique employed to solve the model equations, involving hyperbolic partial differential equations (PDEs) with moving and possibly steep fronts, has to be precise and robust, which is not a trivial matter. A deterministic kinetic model for the PSD evolution of ab initio EP of vinyl monomers was developed to investigate these issues. The model considers three phases, micellar nucleation, and particles that can contain n≥0 radicals. Finite volume (FV) and weighted-residual methods are used to solve the system of PDEs and compared; their limitations are also identified. The model was validated by comparing predictions with data of monomer conversion and PSD for the batch emulsion homopolymerization of styrene (Sty) and methyl methacrylate (MMA) using sodium dodecyl sulfate (SDS)/potassium persulfate (KPS) at 60 °C, as well as the copolymerization of Sty-MMA (50/50; mol/mol) at 50 and 60 °C. It is concluded that the PB model has a structural problem when attempting to adequately represent PSDs with steep fronts, so its use is discouraged. On the other hand, there is no generalized evidence of the need to add a stochastic term to enhance the PSD prediction of EP deterministic models.

LES investigation of soot formation in a turbulent non-premixed jet flame with sectional method and FGM chemistry

This study proposes a detailed soot modeling framework for large-eddy simulation (LES) to accurately predict soot formation and particle size distributions (PSD) in turbulent reacting flows. The framework incorporates Flamelet Generated Manifold (FGM) chemistry and a soot model based on the discrete sectional method (DSM) to predict both qualitative and quantitative sooting behavior while keeping the computational cost affordable. Two elementary modeling strategies are considered in the LES formalism for describing soot formation rates. These strategies rely on an a-priori tabulation of soot formation rates and their run-time computation. The LES formalism is applied to the simulations of a well-characterized, non-premixed, turbulent jet flame. A comparative analysis of strategies employed for filtered soot source term treatment is conducted to investigate their impact on the prediction of soot quantities and the evolution of soot PSDs. The LES results for the gas phase and soot phase are compared against the available experimental data. A good prediction of soot evolution is achieved with the two methodologies. The tabulation of soot formation rates leads to a significant reduction in computational cost compared to the model based on their explicit runtime computation. The LES results reveal that the modeling of filtered soot source terms has a significant impact on the quantitative prediction of soot formation. The possible reasons for the observed differences in the soot prediction are discussed. The run-time computation-based model provides a more consistent treatment of the non-linear interactions between the gas and soot phases in soot source terms compared to the tabulated soot chemistry approach. On the other hand, the tabulated soot chemistry model is an interesting and efficient modeling approach for predicting soot formation in turbulent conditions. Overall, both approaches have their strengths and limitations, and the choice of approach may depend on the specific needs of the application.

Nonequilibrium Behavior in Isoprene Secondary Organic Aerosol.

Recent studies have shown that instantaneous gas-particle equilibrium partitioning assumptions fail to predict SOA formation, even at high relative humidity (∼85%), and photochemical aging seems to be one driving factor. In this study, we probe the minimum aging time scale required to observe nonequilibrium partitioning of semivolatile organic compounds (SVOCs) between the gas and aerosol phase at ∼50% RH. Seed isoprene SOA is generated by photo-oxidation in the presence of effloresced ammonium sulfate seeds at <1 ppbv NOx, aged photochemically or in the dark for 0.3-6 h, and subsequently exposed to fresh isoprene SVOCs. Our results show that the equilibrium partitioning assumption is accurate for fresh isoprene SOA but breaks down after isoprene SOA has been aged for as short as 20 min even in the dark. Modeling results show that a semisolid SOA phase state is necessary to reproduce the observed particle size distribution evolution. The observed nonequilibrium partitioning behavior and inferred semisolid phase state are corroborated by offline mass spectrometric analysis on the bulk aerosol particles showing the formation of organosulfates and oligomers. The unexpected short time scale for the phase transition within isoprene SOA has important implications for the growth of atmospheric ultrafine particles to climate-relevant sizes.

Langevin dynamics simulation and collision frequency modification in population balance model of nanoparticle coagulation during simultaneous agglomeration and sintering

Coagulation of nanoparticles from the free-molecular to the transition regime under a high-temperature environment is investigated by coupling Langevin Dynamics (LD) model with agglomeration and finite-rate sintering. The effect of temperature on the evolution of particle size and structure is investigated, variations in agglomeration-sintering dynamics are obtained. The fractal dimension of agglomerates at different temperatures can be expressed as a function of the ratio between the characteristic collision time and sintering time. The overall collision frequency (β) is enhanced by the polydispersity and fractal properties of agglomerates compared to the monodisperse collision kernel functions. Finally, the classic function of β is modified based on the LD simulations and used in a one-dimensional population balance equation, which reproduces a better prediction of the evolution of particle size distribution during particle coagulation with agglomeration and sintering.

Compaction-deformation behaviors and breakage characteristics of loose broken coal under various stress–temperature coupling loads

This study probed the compaction-deformation and breakage characteristics of loose broken coal under stress–temperature coupling loads. The constitutive model of loose broken coal under stress–temperature coupling loads was first constructed. Then, we quantificationally investigated the particle size distribution (PSD) evolution for the compacted loose coal using the fractal and Weibull functions. In addition, the relative breakage rate, energy evolution, and particle breakage degree of the loose coal compacted were quantificationally evaluated. Results suggest that stress is the prominent factor leading to the breakage of loose broken coal, while increased temperature exacerbates the particle breakage process in combination with the axial stress. Changes in temperature have a distinctive influence on particle breakage for loose broken coal under low-stress conditions, whereas less conspicuous under high-stress conditions. Finally, the evolution of PSDs and related breakage parameters for the entire loose broken coal compaction process were mathematically predicted utilizing the grey model.

Mechanical approach for the evaluation of the crispiness of food granular products.

Crispiness of food products is a key parameter for consumer acceptance. Available methods to evaluate this attribute are subjective and have limitations. They are particularly difficult to implement when granular products are considered. The present study aims to provide a physical characterization of the crispiness of food granular products (gari and grinded corn flakes) based on the compression cycle modeling and the determination of the Py (yield pressure) parameter of the Heckel model. High Py values attributed to the brittle behavior, are indicative of product crispiness. Furthermore, Py parameter showed sensitivity to the plasticizing effect of water. This developed physical method was validated through sensory analysis and acoustic measurements which are both considered as reference methods for crispiness evaluation. The brittle/plastic behavior attributed to crispy/non crispy products respectively was confirmed through image analysis using X-ray microcomputed tomography. The latter made it possible to distinguish the brittle from the plastic behavior through the particle size distribution evolution. This work suggests that the Py value is a relevant indicator for the crispiness evaluation of granular products. This physical characterization is expected to contribute in food engineering as an alternative method for granular products crispiness in a simpler and a more objective way.

Analysis of the evolution of ultra-filtered water quality in a drinking water distribution system by particle size distribution: Influence of pre-ozonation.

An experimental drinking water distribution system (DWDS) was used to evaluate the evolution of particle size distribution (PSD) and basic quality parameters of ultrafiltered water with or without pre-ozonation. An ultrafiltration (UF) module was set up, associated with a pre-ozonation system (3.7g O3 /m3 ). The permeate was circulated in the DWDS (300 m; 0.9m/s) with 0.4mg/L of chlorine, and the analysis of the PSD was performed using a β-variable mathematical model. A better control of membrane fouling was obtained with pre-ozonation, and PSD was necessary to observe water quality differences between permeates and in the DWDS. A decrease in particle concentration of 1.8 logarithms was obtained with the application of UF membranes, while a decrease of only 1.2 logarithms was obtained with pre-ozonation. The system without pre-ozonation showed a higher efficiency at removing smaller particles (around 2μm), with the absence of particles larger than 23 μm during both stages. The PSD revealed a worsening of water quality in the DWDS with an increase of particles smaller than 5μm during the application of UF membranes, while with pre-ozonation, all particle sizes analyzed increased their concentration. PRACTITIONER POINTS: Pre-ozonation led to a better control of membrane fouling, but a worsening of permeate quality according to particle size distribution. Pre-ozonation does not improve the turbidity, dissolved organic carbon or UV254 removal capacity of ultrafiltration during drinking water treatment. Particles size distribution reveals the deterioration of water quality in a drinking water distribution system better than turbidity or DOC. Ozone prior to ultrafiltration membranes led to a worsening of permeate quality, more significant in the drinking water distribution system.

Quantifying Particle Breakage and Its Evolution Using Breakage Indices and Grading Entropy Coordinates

Particle breakage in soils is a well-recognised behaviour. Conventional methods for quantifying the breakage process rely on calculating the area between the particle size distribution (PSD) curves produced before and after crushing. A key aspect of breakage is understanding the process across the different size/sieve fractions. Grading entropy coordinates allow for the representation of any PSD to be shown as a single point on a Cartesian plane and are able to track grading evolution with relative ease. In this study, grading entropy coordinates are compared to three commonly used breakage indices (Br, Br* and IG). It is shown that grading entropy coordinates are advantageous over the traditional indices in quantifying subtle changes in the PSD evolution and directly provide further insight with regards to the individual fraction sizes. It is also discussed that conventional breakage indices rely on relative measures and are dependent on assumptions of an initial and/or final PSD. In contrast, grading entropy coordinates depend only on the characteristics of the (current) PSD curve. It was also observed that the breakage evolution captured by the entropy coordinates is able to determine the rate at which differently sized particles break as differently sized particles take on stress. Moreover, it is suggested that entropy coordinates may also stress path dependency, a feature not present in conventional indices.

Effect of phospholipid matrix on emulsion stability, microstructure, proteolysis, and in vitro digestibility in model infant formula emulsion

The effects of adding different phospholipid (PL) matrices [milk sphingomyelin (SM) vs soy phosphatidylcholine (PC)] on emulsion stability, microstructure, and in vitro simulated lipid digestion were examined using a Model Infant Formula Emulsion (MIFE). The emulsion stability of MIFE increased significantly with PL addition (0.1 and 0.2 %). Compared to sole MIFE or MIFE + PC, the incorporation of SM resulted in increased emulsion stability (p < 0.05) and a greater amount of free fatty acid release (p < 0.05) during in vitro simulated digestion. This was mainly due to the reduction of intensive droplet aggregation, thus providing a large surface area and improved digestibility. This is further experimentally supported by the evolution of particle size distribution, zeta-potential, and microstructure analysis using confocal laser scanning microscopy. The incorporation of SM in the emulsion formation significantly delayed digestion of β-lactoglobulin during in vitro digestion. Lipid digestibility in MIFE was altered depending on the type of PL matrix, and SM displayed a superior effect to PC. Thus, the creation of a novel emulsion interface by the appropriate selection of emulsifiers can be used to improve lipid digestion in infants and obtain desirable nutritional consequences.

Radial Basis Function Method for Predicting the Evolution of Aerosol Size Distributions for Coagulation Problems

The dynamic evolution of particle size distributions (PSDs) during coagulation is of great importance in many atmospheric and engineering applications. To date, various numerical methods have been developed for solving the general dynamic equation under different scenarios. In this study, a radial basis function (RBF) method was proposed to solve particle coagulation evolution. This method uses a Gaussian function as the basis function to approximate the size distribution function. The original governing equation was then converted to ordinary differential equations (ODEs), along with numerical quadratures. The RBF method was compared with the analytical solutions and sectional method to validate its accuracy. The comparison results showed that the RBF method provided almost accurate predictions of the PSDs for different coagulation kernels. This method was also verified to be reliable in predicting the self-preserving distributions reached over long periods and for describing the temporal evolution of moments. For multimodal coagulation, the RBF method also accurately predicted the temporal evolution of a bimodal distribution owing to scavenging effects. Moreover, the computational times of the RBF method for these cases were usually of the order of seconds. Thus, the RBF method is verified as a reliable and efficient tool for predicting PSD evolution during coagulation.

Combining density functional theory and CFD-PBM model to predict TiO2 nanoparticle evolution during chemical vapor deposition

Preparation of TiO2 nanoparticles by TiCl4 hydrolysis during chemical vapor deposition (CVD) is one of the effective techniques for producing TiO2 nanoparticles, while the mechanisms of TiO2 nanoparticle evolution are not well understood. This paper uses computational fluid dynamics (CFD) population balance model (PBM) to predict particle size distribution during CVD, and density functional theory (DFT) calculations to explore reaction mechanisms. DFT calculations reveal that the gas phase hydrolysis reaction can be simplified into two processes, the hydrolysis of TiCl4 to form TiO(OH)2 and the decomposition of TiO(OH)2 to TiO2. During the surface reactions, the energy barriers of TiO(OH)2 decomposition reactions on the surfaces of (TiO2)n nanoclusters (n = 1–8) are generally lower than those in the gas phase reactions, and the largest energy barrier of the surface reaction occurs on the surface of (TiO2)6 nanoclusters. Simulations using a perfect stirred reaction model indicate that Ti(OH)4 is the dominant hydrolysis products when the temperature is lower than 548 K, while TiO2 production starts at ∼610 K, indicating reaction temperature is a crucial factor that governs the products of TiCl4 hydrolysis. CFD-PBM model predict the evolution of Particle Size Distribution (PSD) of nanoparticles in a CVD reactor, which is agreed with experimental measurements in the literature. Increasing the reaction temperature results in an increase of the peak of the PSD of nanoparticles in the reactor. This study provides atomic insights into the nanoparticle evolution and a practical model to predict the nanoparticle evolution during the CVD process.

Soot nanoparticle sizing in counterflow flames using in-situ particle sampling and differential mobility analysis verified with two-colour time-resolved laser-induced incandescence

The emphasis of this work is on the development of an intrusive particle sampling system to track the evolution of soot nanoparticles in ethylene counterflow diffusion flames. The overarching objective is to determine the mobility size distributions in a spatially resolved manner using the developed probe system coupled with differential mobility analysis, i.e., a scanning mobility particle sizer (SMPS). The probe system involves a tailor-made quartz probe, gas supply, pressure control periphery, and a traverse system enabling a precise positioning along the flame axis. In preliminary experiments, the dilution ratio of the quartz probe as function of boundary conditions as well as particle losses during intrusive particle sampling are studied. To demonstrate the capability of the developed particle sampling system, results from ethylene counterflow diffusion flames with different fuel mass fractions and strain rates are presented and compared with results derived by non-intrusive laser-based diagnostics, i.e., two-colour time-resolved laser induced incandescence (2C-TiRe-LII). Results of these experiments indicate that the particle sampling system is capable of tracking the development of particle size distributions – independent of the distribution function, i.e., mono-, bi- or multimodal shape – in counterflow flames. Likewise, the agreement between soot volume fractions and particle size distributions measured via intrusive particle sampling coupled with differential mobility analysis and non-intrusive laser-based 2C-TiRe-LII is excellent at varying the fuel mass fractions and strain rates of the ethylene counterflow flames.

Influence of cycle time distribution on coating uniformity of particles in a spray fluidized bed by using CFD-DEM simulations

Cycle Time Distribution (CTD) plays a critical role for determining uniformity of particle coating in spray fluidized beds. However, the CTD is influenced by both geometrical structure and operating conditions of fluidized bed. In this study, a spray fluidized bed of coating process is simulated by a comprehensive Computational Fluid Dynamics-Discrete Element Model (CFD-DEM). To achieve different behaviors of CTD, some modifications are designed on a pseudo-2D internally circulating fluidized bed, which traditionally composes of a high-velocity upward bed and low-velocity downward bed. These modifications include making the air distributor slope and/or laying a baffle in the downward bed. First, the CTD and evolution of particle size distribution under different bed structures are compared. The CTD directly influences the coating uniformity. By making the particles flowing along a parallel direction in the downward bed through the geometrical modifications, the CTD becomes narrower and the coating uniformity is significantly improved. Second, under the optimized bed structure, the influence of operating conditions on the coating uniformity is studied. Properly increasing the fluidization gas velocity and the fluidization gas temperature and reducing the liquid spray rate can improve the coating uniformity.