Particle Concentration Distribution Research Articles

Effect of a high-gradient magnetic field on particle concentration distribution in a magnetic fluid seal: Rivalry of the diffusion and magnetophoresis

In this paper, the unsteady process of particle concentration distribution in a magnetic fluid is studied. Diffusion and the effect of a high-gradient magnetic field in a magnetic fluid seal (MFS) are taken into consideration. It is crucial to take into account how particle mobility and diffusion coefficient vary on particle concentration in order to determine the possibility and time of the formation of a close packing of particles. The Carnaghan-Starling approximation was employed. It is demonstrated numerically that the geometry of the MFS, namely its gap width and pole base width, as well as the magnitude of the magnetic field strength under the pole tooth of the MFS, both influence the time of the formation of a close packing of particles. This period can be regarded as the MFS's uptime. Depending on the design of the working gap, the uptime seal for magnetic fluid based on vacuum oil may require between two weeks and six months. The uptime seal also becomes shorter when the carrier fluid's viscosity decreases.

Evaluation of the spatial distribution of aerosols produced by various respiratory activities

This study investigated the dispersion and evaporation characteristics of droplets and droplet nuclei emitted during human respiratory activities. A specially designed wind tunnel was filled with purified air, wherein selected subjects performed various respiratory activities with their heads positioned inside. An optical particle sizer was used to collect particles with sizes of 0.3–10 μm at 63 points in front of the mouth. The dilution factors were analyzed to investigate the impact of combining the exhaled airflow with ambient air on droplet evaporation. At a distance of 0.01 m from the mouth opening, the volume concentration of the particles was the highest during breathing, followed by coughing and speaking. The volumetric concentration of particles decreased with an increase in the distance from the inlet for all activities. The spatial volume concentration distribution of particles showed that coughing tended to disperse the particles in the forward direction, whereas speaking tended to disperse them laterally. Utilizing these findings in CFD analysis can provide in-depth insights into dispersion and evaporation dynamics. This can contribute significantly to the development of preventive measures through the implementation of proactive HVAC systems to effectively remove infectious particles and control the spread of infectious diseases. Future studies should explore a wider range of particle sizes and advanced sampling techniques for a clear understanding of respiratory particle dynamics and infection control strategies.

Prediction model for vertical distribution of oil particles under thermal plume and displacement ventilation in a machining workshop

Oil particle concentrations exhibit an inhomogeneous distribution in large-space machining workshops with a displacement ventilation system. The inhomogeneous distribution can lead to variations in the required supply air volume used to control the indoor particle concentration at different heights. To rapidly calculate the particle concentration distribution in the vertical direction, this study established a zonal particle concentration prediction model based on the mass and energy balance by considering the interaction between the heat source thermal plume, wall thermal plume, and supply airflow. An experiment was conducted in a scaled chamber to validate the proposed prediction model. The result showed that the relative error between the prediction model and experiment ranged from −17% to 10%. A case study was performed to demonstrate the applicability of the prediction model to the control of a displacement ventilation system. Using the prediction model, the control system can maintain the particle concentration in the work area below 0.5 mg/m³with variable particle source emission rates and reduce the supply air volume by at least 24% and 55% compared with the variable and constant air volume systems, respectively, neither of which can address the inhomogeneous distribution of oil particle concentration. The prediction model can also be used for the design of displacement ventilation systems when the inhomogeneous particle concentration distribution is considerable.

The fluidization behavior of particles in supercritical water fluidized bed: A region-dependent analysis

The distribution and fluctuation of particle concentration in a supercritical water fluidized bed (SCWFB) are studied using a specially-designed capacitance probe measurement system. The measurement error of capacitance probe system is 2.48%. Results show that the particle concentration at the axial line fluctuates largely with time and the fluctuation is weakened when increasing the distance from axial line or decreasing particle diameter. At Uf/Umb=1.5, the largest difference between particle concentrations is 0.026, 0.04, 0.082 when the particles with a diameter of 0.124 mm, 0.198 mm, 0.235 mm are used, indicating a larger non-uniformity of larger particles. The probability density of local particle concentration mainly follows a unimodal distribution with the peak at right side. The main frequency of SCWFB ranges from 1.39 Hz to 2.73 Hz in this experiment and the main frequency decreases when larger particles are used.

Fine Particle Formation and Dependence of Wet Deposition on Precipitation Intensity in an Urban Area

ABSTRACT In order to understand the characteristics of the change of aerosol concentration in an urban area and the impact of meteorological conditions on aerosol concentration in urban areas, particle concentration and size distribution were measured using an aerosol particle counter and an aerosol spectrometer in Hefei, China in spring 2017. Meteorological data, such as temperature, relative humidity, wind speed, wind direction, and shortwave radiation, were measured on a meteorological tower. The concentration of coarse mode (d > 2.5 μm, d is particle diameter), accumulation mode (0.25 μm<d < 2.5 μm), and ultrafine (Aitken and nucleation mode, d < 0.25 μm) particles under different meteorological conditions were recorded. Results show that, approximately 10–20 min after the solar downward shortwave radiation decreases (rises), the ultrafine particles (UFPs) concentration decreases (rises). Diurnal change in radiation causes daily change in the concentration of UFPs, and when the relative humidity was low, UFP generation easily occurs. On wet deposition, the concentration of coarse mode particles is significantly reduced during precipitation, and the concentration of accumulation mode particles varies during heavy precipitation and slight precipitation. Because of the combined action of wet deposition and hygroscopic growth, the concentration of accumulation mode particles first increases and then decreases. And during the slight precipitation, the concentration only increases with the relative humidity.

Fluidization characteristics of iron ore powder in fluidized bed

The fluidization characteristics of iron powder were studied on a self-made cold fluidized bed in the laboratory. The pressure distributed in the axial inside the lifting pipe of a fluidized bed gradually decreases to a constant value from underbody to roof. As the gas flow rate in the fluidized bed increases, the pressure on each axial section first increases and then decreases. When the inflation numbers are fixed, as the operating gas speed increases, the pressure on the same height segment decreases. When the operating gas speed of a fluidized bed is constant, the pressure increases with the increase of inflation numbers. The pressure at different bed heights is affected differently by the operating air speed: at the underbody of the bed, the pressure rapidly decreases with increasing operating airspeed. As the cross-sectional height increases, the influence of operating gas speed on pressure gradually decreases. As the charge increases, the pressure at the underbody of the fluidized bed rises rapidly, while the pressure at the roof changes gently. When iron ore fine powder is fluidized, distribution in axes of particle concentration shows an uneven distribution of upper dilute and lower dense. Under a certain loading number, increasing the operating airspeed will reduce the average concentration of granules in each axial section of the entire bed, and the particle concentration distribution in that section will become uniform. As the number of charges increases, the average concentration of granules in the riser increases, and the difference in particle concentration between the underbody and roof parts of the riser decreases.

The research on the particle concentration distribution of directed airflow in cleanrooms for operators.

Existing research of non-unidirectional cleanrooms generally suggests that lower-side return air outlets provide better control effect on indoor particle concentration. As a result, there has been relatively less focus on return air outlets. However, installing return air outlets oriented towards operators as particle emission sources can reduce the impact on process layout and improve space utilization, while also provide less impact from upper particle emission sources on the workbench area. To investigate the characteristics of return air outlet for operators (abbreviated as H), this study compared the particle concentration distribution, non-uniformity, and purification efficiency of return air oultet H and the traditional lower-side (abbreviated as L) return air outlets by experiments and CFD simulations. Based on the theory of mass conservation, the expression of required air supply volume under equivalent cleanroom conditions was derived. Under corresponding experimental and simulation conditions, the particle concentration differences range from 2.0% to 12.7% for return air outlet H and from 12.4% to 33.2% for return air outlet L, and these differences gradually decrease with the air exchange rate (ACH) increases. The results show that ACH = 20 is sufficient for cleanliness requirements with return air outlet H when there is one person in the cleanroom, while a higher rate of ACH = 35 is needed when there are two persons. Although lower-side return air outlets have certain potential for reducing particle concentration in the cleanroom, increasing the air exchange rate remains the most effective method to control indoor particle concentration. Compared to the traditional lower-side return air outlet L, the ranges of the non-uniformity coefficients for return air outlet H and L are 0.50 to 0.67 and 0.45 to 0.53, respectively. The average non-uniformity coefficient differs by 11.9%, and there is not a significant difference in uniformity with more than 20 air changes per hour. The use of return air outlets H only requires an additional 11% of air supply volume to achieve the same cleanliness, demonstrating its effectiveness in controlling particle concentration. It is suitable for cleanrooms with higher requirements for workbenches and for cleanrooms with restricted floor usage or requiring flexible layouts. The study also explores the impact of width of return air outlet oriented towards operators as particle emission sources, the results show that the larger-sized outlets facilitate the particle discharge and control the particle distribution inside the room.

Efficient super-resolution image reconstruction of electrical capacitance tomography for gas–solid fluidized bed measurement

Electrical capacitance tomography (ECT) has been widely used to investigate the flow dynamics of the gas–solid fluidized bed. Deep learning-based tomographic imaging of ECT is of great potential to reconstruct the particle concentration distribution with compatible image quality and reconstruction speed. However, it suffers from low model construction efficiency as numerous data samples need to be collected for training the deep neural network. Here a super-resolution (SR) imaging model based on a two-stage imaging network is proposed to improve the model construction efficiency. A low-resolution (LR) imaging network is used to reconstruct the LR image with the measured capacitance matrix while a subsequent high-resolution (HR) network calculates the HR image with the reconstructed LR image. The imaging performance, construction efficiency, and generalization ability of the trained SR imaging model are evaluated by reconstructing the samples in the test set and the unseen typical flow patterns. Considering the training set includes 100,000 data samples, the time consumption of numerically collecting the dataset for training the SR imaging model is 2.70 h, 2.2 % of that for a conventional deep learning-based imaging model of ECT, and the overall model construction time is only 4.44 h when the grid numbers of the LR and HR images are 246 and 8053, respectively. Experimental measurements are further carried out on a fluidized bed and the preliminary results show good prediction and generality of the trained model for reconstructing the particle concentration distribution.

A combined CFD-based simulation and experimental study of particle dispersion in a high-concentration airtight space under unorganized airflow

It is significant to obtain the particle distribution data for workpiece processing and industrial protection strategies. To simulate the particle dispersion in a high-concentration airtight space under unorganized airflow, a CFD-based simulation and experimental were utilized in this study. The proposed method works in three steps. The first step is to use Stokes-MRF-Fan-CFD model to simplify the distribution of high-concentration particles calculation to the dispersion state of the gas components. The second step is to compute the airflow patterns and dispersion of particles. The third step is to prove the feasibility of Stokes-MRF-Fan-CFD model. The results of this model in particle dispersion show ±200 mg·m−3 of absolute error, ±20% of relative error, and 88.5747 grade of simulation accuracy. And the results of particle concentration distribution can be mutually confirmed with the streamline and velocity vector distribution in the airtight space, providing a promising and innovative model for the particle dispersion in a high-concentration airtight space under unorganized airflow.

Approaching Effective Differential Centrifugal Fractionation by Combining Image Analysis with Analytical Ultracentrifugation.

Centrifugation is one of the most commonly used methods for separation in biology and chemistry. However, effective fractionation is not always easy to obtain, as preparative centrifuge experiments are mostly conducted in an empirical way, even when it is guided by the quantitative results from analytical ultracentrifuge (AUC). Very few works have been performed to enhance the fractionation resolution of the differential centrifugation method in a swing-out rotor. This is primarily due to the absence of a characterization tool for sedimentation in the preparative centrifuge. In this study, we utilized image analysis to map the particle concentration distribution throughout the preparative centrifuge tube, revealing an unexpected and abnormal sedimentation process. By characterizing the sedimentation coefficient distributions of the fractionated product via AUC, we demonstrated that the overall sedimentation efficiency in a swing-out preparative centrifuge was significantly reduced. Furthermore, effective fractionation was confined to the intermediate phase of the entire sedimentation process. We propose that the mechanism here is a combination of the inverse Boycott effect and droplet sedimentation. The actual sedimentation process within a preparative centrifuge can be described by modifying the Lamm equation phenomenologically, which simply results in an effective sedimentation coefficient. Our work builds a foundation for determining the optimal preparative centrifugation conditions for various systems.

Atmospheric Air Dust Concentration, Composition And Size Distribution Data At Breathing Heights In Yekaterinburg.

Accurate information on air quality serves as the foundation for making regulatory and legal decisions aimed at reducing air pollution. This study investigates the vertical distribution of dust particle concentration, their elemental composition, and size distribution in the atmospheric surface layer in Yekaterinburg. Over eight days in April 2021, 64 dust samples were collected on filters at heights ranging from 0.5 m to 10 m at a single site using a mobile post. The mass concentration of the dust, characterized by heterogeneous data with a coefficient of variation exceeding 30%, exhibited a weak tendency to decrease with height. The proportion of particles smaller than 1 µm decreased with increasing altitude, except for 10 m, where their proportion increased. Conversely, the concentration of p articles ranging from one to two microns decreased closer to the surface. Dust grains of other sizes were nearly evenly distributed at various heights. Dust particles smaller than PM2.5 accounted for approximately 45% of the total particles. X-ray fluorescence analysis identified 12 elements in dust particles, with S, Ca, and Fe showing the most substantial content. The proportion of most metals and Ca in solid particles decreased with height, while the content of S and As increased. The Cu, Zn, and Sb content in dust particles remained constant at all measured heights.

Effect of Heating Emissions on the Fractal Size Distribution of Atmospheric Particle Concentrations

Excessive particle concentrations during heating periods, which greatly affect people’s physical and mental health and their normal lives, continue to be a concern. It is more practical to understand and analyze the relationship between the fractal dimension and particle size concentration distribution of atmospheric particulate matter before and after adjusting heating energy consumption types. The data discussed and analyzed in this paper were collected by monitoring stations and measured from 2016 to 2018 in Xi’an. The data include fractal dimension and particle size concentration changes in the atmospheric particulate matter before and after adjusting the heating energy consumption types. The results indicate that adjusting the heating energy consumption types has a significant impact on particulate matter. The average concentration of PM2.5 decreased by 26.4 μg/m3. The average concentration of PM10 decreased by 31.8 μg/m3. At the same time, the different particle sizes showed a downward trend. The particles ranging from 0.265 to 0.475 μm demonstrated the maximum decrease, which was 8.80%. The heating period in Xi’an mainly involves particles ranging from 0 to 0.475 μm. The fractal dimensions of the atmospheric particulate matter before and after adjusting the heating energy consumption types were 4.809 and 3.397, respectively. After adjusting the heating energy consumption types, the fractal dimension decreased by 1.412. At that time, the proportions of particle sizes that were less than 1.0 μm, 2.0 μm, and 2.5 μm decreased by 1.467%, 0.604%, and 0.424%, respectively. This paper provides new methods and a reference value for the distribution and effective control of atmospheric particulate matter by adjusting heating energy consumption types.

Improved multivariable algorithms for estimating oceanic particulate organic carbon concentration from optical backscattering and chlorophyll-a measurements

The capability to estimate the oceanic particulate organic carbon concentration (POC) from optical measurements is crucial for assessing the dynamics of this carbon reservoir and the capacity of the biological pump to sequester atmospheric carbon dioxide in the deep ocean. Optical approaches are routinely used to estimate oceanic POC from the spectral particulate backscattering coefficient bbp, either directly (e.g., with backscattering sensors on underwater platforms like BGC-Argo floats) or indirectly (e.g., with satellite remote sensing). However, the reliability of algorithms which relate POC to bbp is typically limited due to the complexity of interactions between light and natural assemblages of marine particles, which depend on variations in particle concentration, composition, and size distribution. This study expands on our previous work by analysis of an extended field dataset created with judicious data inclusion criteria with the aim to provide POC algorithms for multiple light wavelengths of measured bbp, which can be useful for applications with in situ optical sensors as well as above-water active or passive measurement systems. We describe an improved empirical multivariable approach to estimate POC from simultaneous measurements of bbp and chlorophyll-a concentration (Chla) to better account for the effects of variable particle composition on the relationship between POC and bbp. The multivariable regression models are formulated using a relatively large dataset of coincident measurements of POC, bbp, and Chla, including surface and subsurface data from the Atlantic, Pacific, Arctic, and Southern Oceans. We show that the multivariable algorithm provides reduced uncertainty of estimated POC across diverse marine environments when compared with a traditional univariate algorithm based on only bbp. We also propose an improved formulation of univariate algorithm based on bbp alone. Finally, we examine performance of several algorithms to estimate POC using our dataset as well as a dataset consisting of optical measurements from BGC-Argo floats and traditional POC measurements collected during a coincident research cruise in the Atlantic Ocean.

Effects of preconditioning with TNFα and IFNγ in angiogenic potential of mesenchymal stromal cell-derived extracellular vesicles.

Introduction: Mesenchymal stromal cells (MSCs) have demonstrated therapeutic properties both in vitro and in vivo to treat various diseases, including anti-inflammatory, immunomodulatory and pro-angiogenic effects. These therapeutic effects are mediated by their secretome composed of soluble factors and extracellular vesicles (EVs). The composition of EVs reflects the molecular and functional characteristics of parental cells. MSC preconditioning can alter the composition of EVs, thereby influencing their therapeutic potential. Methods: MSCs were subjected to preconditioning with two cytokines, TNFα and IFNγ. Following 24h of preconditioning, MSC-EVs secreted into the culture supernatant were isolated through tangential filtration. Particle concentration and size distribution were measured by nanoparticle tracking analysis, and the surface antigen expression of the EV-specific CD63 was quantified via Enzyme Linked ImmunoSorbent Assay. The angiogenic potential of MSCEVs obtained after preconditioning MSCs was assessed by the analysis of their protein composition and their influence on human umbilical vein endothelial cell (HUVECs) proliferation, migration, and tube-forming ability. Results: Preconditioning with TNFα and IFNγ did not influence the MSC-EV profile but did induce changes in their protein content. Indeed, the expression of pro-angiogenic proteins increased in EVs from preconditioned MSCs compared to EVs from no-preconditioned MSCs. EVs from preconditioned MSCs tend to stimulate HUVEC migration, proliferation and tubeforming ability. These observations imply the presence of a pro-angiogenic potential in EVs obtained after preconditioning of MSCs with TNFα and IFNγ. Discussion: In conclusion, it appears that the pro-angiogenic potential of EVs is enhanced through preconditioning of MSCs with TNFα and IFNγ. The use of these MSCs-EVs in therapy would circumvent the limitations of current cell-based therapies. Indeed, the therapeutic potential of MSC-EVs presents an attractive strategy for exploiting the clinical benefits of MSC therapy. For example, in the field of regenerative medicine, the exploitation of cell-free therapy using highly pro-angiogenic MSC-EVs is of great interest.

Experimental study of transient particle suspension in bioreactors using a light attenuation technique

The culture of mesenchymal stromal cells relies on the use of suspended microcarriers as adhesion supports. During the particle suspension phases, the temporal evolution of the spatial distribution of particle concentrations is generally poorly characterized. In this study, the light attenuation technique was used to access this distribution and the duration of particle homogenization. Considering the minimal agitation rate Nref for which particle suspension was observed for all the microcarrier concentrations 〈C〉 studied, the results showed that using an agitation frequency close to Nref significantly increased the homogenization duration compared to N≃1.7×Nref. The transient microcarrier overconcentration was also determined locally. At N=Nref, the resuspension time was negatively impacted by 〈C〉, which also resulted in longer particle overconcentrations. A time-integral particle overconcentration term was considered to estimate the severity of inter-microcarrier collisions. The results suggested that increased agitation could limit time-cumulative overconcentrations beyond a particle concentration of 3 g/L.

Eulerian investigation of the mechanism of Ultra-low NOx emissions from CFB boilers with finer bed material

Industrial practice has confirmed that decreasing the bed material size substantially diminishes nitrogen oxide (NOx) emissions in coal-fired circulating fluidized bed (CFB) boilers. This reduction allows for compliance with the stringent ultra-low emissions standard (NOx < 50 mg/Nm3@6%O₂, dry) proposed by the Chinese government, all without the need for supplementary denitrification devices. Consequently, it becomes essential to delve into the mechanisms through which particle size, as a gas–solid flow characteristic, directly affects the chemical reaction dynamics within the coal combustion process. Due to the difficulty of field tests, this paper employs the Eulerian-Eulerian numerical method suitable for wide particle size distributions to investigate the impact of bed material particle size on gas–solid flow and NOx concentration. Furthermore, the generalized QC-EMMS drag model is utilized to predict the heterogeneous flow across varying particle size conditions. Industrial test data validated the simulation accuracy, with prediction errors of bed pressure drop, temperature, and NOx emission concentration ranging from 5 % to 8.1 %. The analysis revealed that the particle concentration distribution heterogeneity decreases as the particle size diminishes. The variation trends of NOx with particle size exhibit distinct differences between the lower dense phase region and the upper dilute phase region within the bed. For finer bed material particles, the high NOx concentration generated in the dense phase region experiences a more thorough reduction in the dilute phase region. Through the analysis of material concentration and reaction rate, it is believed that this phenomenon is related to the increased catalytic effect of fine ash particles in the dilute phase region, that is, the reduction in particle size leads to an increase in catalytic specific surface area, enhancing NOx reduction, thus achieving ultra-low emissions at the outlet. These research results provide theoretical support for further development of ultra-low emission coal-fired CFB boilers.

Experimentally trained hybrid machine learning algorithm for predicting turbulent particle-laden flows in pipes

A hybrid learning algorithm consisting of a preprocessor, a k-nearest neighbors regressor, a noise generator, and a particle–wall collision model is introduced for predicting features of turbulent single-phase and particle–liquid flows in a pipe. The hybrid learning algorithm has the ability to learn and predict the behavior of such complex fluid dynamic systems using experimental dynamic databases. Given a small amount of typical training data, the algorithm is able to reliably predict the local liquid and particle velocities as well as the spatial distribution of particle concentration within and without the limits of the range of training data. The algorithm requires an order of magnitude less training data than a typical full set of experimental measurements to give predictions on the same level of accuracy (typically, 20 cf. 100 trajectories for phase velocity distribution and 40 cf. 500 trajectories for phase concentration distribution), thus leading to huge reductions in experimentation and simulation. A feature importance analysis revealed the effects of the different experimental variables on the particle velocity field in a two-phase particulate flow, with particle–liquid density ratio and particle vertical radial position being the most influential and particle concentration the least. The algorithm is amenable to extension by using more complex databanks to address a much more comprehensive range of flow situations.

Plasma-assisted synthesis of nano-sulfur adsorbent for efficient removal of mercury from flue gas

Adsorbents injection technology is one of the most promising strategies to control mercury emission from flue gas. However, existing literature has shown leaching risk of mercury and halogen from commercial halogen impregnated adsorbents. Therefore, we proposed a novel and convenient fabrication method for nano-sulfur adsorbent assisted with nonthermal plasma technology in order to address these issues. The morphology, number concentration and size distribution of as-obtained nano-sulfur particles was determined by High Resolution Transmission Electron Microscopy (HRTEM) and Scanning Mobility Particle Sizer (SMPS). The mercury adsorption experiments showed nano-sulfur adsorbent (removal efficiency: 88.2 %) was more effective than micron-sized elemental sulfur (less than 10 %). Furthermore, the chemical composition of elemental sulfur allotropes (S6, S7 and S8) was determined using High-performance Liquid Chromatography-Mass Spectrometry (HPLC-MS). It was found that nano-sulfur particles contained higher proportions of S6 (1.53 %) and S7 (1.29 %) allotropes, which are the active materials in elemental sulfur. To investigate the effects of adsorption temperature and simulated flue gas on the performance of nano-sulfur adsorbent, the optimal adsorption temperature of 110 °C was determined, indicating its suitability for coal-fired power plants equipped with a low-temperature electrostatic precipitator system. Additionally, it was observed that simulated flue gas had slight inhibitory effects on the adsorbent performance, with a reduction of approximately 5 % in Hg0 removal efficiency. In summary, this research proposed a novel method for synthesizing nano-sulfur adsorbent and revealed the differences in sulfur allotropes' reactions with mercury, thereby deepening our understanding of the mercury-sulfur reaction mechanism.

Fly ash and sorbent particles agglomeration and removal in system of electrostatic agglomerator and electrostatic precipitator

The paper presents experimental studies on the effect of sodium bicarbonate and calcium hydroxide dry, low temperature sorbent injection on the concentration and size distributions of precipitated particles (fly ash and sorbent particles mixture), fractional collection efficiency, and particles morphology. The measurements were carried out on a lab-scale system comprising unipolar electrostatic agglomerator and electrostatic precipitator. In the experiments presented in this paper, the sorbent was injected upstream of electrostatic agglomerator. Results of SEM studies revealed the process of sorbent and fly ash particles agglomeration. The measurement of resistivity of fly ash and sorbent mixtures have shown that injected sorbent has a large effect on the particles resistivity, when the temperature of dust cake is increasing. In practical situations, too high resistivity can lead to back corona discharge generation, while too low causes the particles re-entrainment; both of these phenomena can reduce the dust collection efficiency of an electrostatic system.

Investigation on axial evolution of particle group and conversion of a single coal particle in an impinging entrained-flow gasifier

Based on a bench-scale impinging entrained-flow gasifier and visualization system, the conversion of particle group and a single coal particle in the impinging-flow zone below the burner plane is investigated in-situ. The axial evolution of particle group including particle size, particle concentration, velocity field and spatial distribution is characterized with image processing algorithm and statistical method. The particle fragmentation, single particle conversion process and volatile oxidation behavior are discussed. The results indicate that the Sauter mean diameter (SMD) is distributed in 560–720 µm in all statistical regions, and the particle concentration is distributed in 20,000–360,000. With the axial downward movement of the particle group, the SMD, particle concentration and spatial distribution frequency show an overall decreasing trend. The proportion of particles ranging in the velocity interval of 0–4 m/s increases in the three impinging-flow zones, which are 85.76 %, 92.33 % and 97.88 %, respectively. The fragmentation mode of a single coal particle can be classified into central fragmentation and peripheral fragmentation. The occurrence probabilities of the two modes in the upper impinging-flow zone are more than one-third, indicating that the particles tend to be fragmented near the burner plane. The conversion of a single coal particle can be divided into heat up and pyrolysis, volatile oxidation, volatile/char oxidation and char oxidation. In the upper impinging-flow zone, less than 30 % of the particles are in volatile oxidation stage, while about 50 % of the particles are in char oxidation stage. With the axial downward movement of the particle group, the proportion of particles in char oxidation stage decreases, while the proportion of particles in volatile oxidation stage shows an opposite trend. A macroscopic description of ignition and propagation of particle volatile flame is proposed. The propagation of volatile flame between singles particles can be extended to the propagation of volatile flame within particle groups.