High-density Particles Research Articles

Spatiotemporal dynamics and tidal transport of microplastics in the tropical waters of the Gulf of Thailand

Microplastics (MPs) contamination was investigated along a freshwater-seawater continuum from Chumphon River to the Gulf of Thailand. The vertical distribution in the water column and contamination in green mussels were also studied. MPs were detected in all water samples and sediment samples. Furthermore, MPs were detected in 75% of the green mussels. A higher abundance of MPs was observed in the river system than in the coastal region, indicating that river runoff associated with inland human activities is the major sources of MPs in the coastal regions and cultured green mussels. In the water column, a polymer gradient varying with depth existed where low-density particles decreased from surface to subsurface and sediment while high-density particles exhibited the opposite pattern. Polymers in surface and subsurface water were predominantly composed of low-density polyethylene, polypropylene, and polystyrene particles. However, sediment samples were equally dominated by those mentioned low-density polymers and high-density polyethylene terephthalate, polyamide, rayon, and cotton particles. Furthermore, fibers were the most common shape found in water, sediment, and mussel samples representing 95% of all particles in river water samples and were evenly distributed throughout the water column regardless of density. However, only shorter fiber (mostly <1 mm) was detected in green mussel samples similar to their living environment. Blue, black and white particles dominated all samples. During the tidal cycle, half of the MPs entering the Gulf of Thailand returned to the river during high tide. This backflow predominantly comprised small fibers and low-density polymer MPs. The average daily load of MPs from Chumphon River to the Gulf of Thailand was 3.33 × 102 million items/day.

Kilogauss magnetic field and jet dynamics in the quasar NRAO 530

The advancement of the Event Horizon Telescope has enabled the study of relativistic jets in active galactic nuclei down to sub-parsec linear scales even at high redshift. Quasi-simultaneous multifrequency observations provide insights into the physical conditions in compact regions and allow accretion theories to be tested. Initially, we aimed to measure the magnetic field strength close to the central supermassive black hole in by studying the frequency-dependent opacity of the jet matter, Faraday rotation, and the spectral index in the millimeter-radio bands. was observed quasi-simultaneously at 15, 22, 43, 86, and 227\,GHz at four different very long baseline interferometer (VLBI) networks. By means of imaging and model-fitting, we aligned the images, taken at different frequencies. We explored opacity along the jet and the distribution of the linearly polarized emission in it. Our findings reveal that the jet of at 86 and 227\,GHz is transparent down to its origin, with 70\,mJy emission detected at 227\,GHz potentially originating from the accretion disk. The magnetic field strength near the black hole, estimated at $5r_ g $, is $3 (depending on the central black hole mass). These values represent some of the highest magnetic field strengths reported for active galaxies. We also report the first ever VLBI measurement of the Faraday rotation at 43--227\,GHz, which reveals rotation measure values as high as -48000 rad/m2, consistent with higher particle density and stronger magnetic fields at the jet's outset. The complex shape of the jet in is in line with the expected behavior of a precessing jet, with a period estimated to be around $6 years.

A calibration-informed deep learning model for three-dimensional particle reconstruction of volumetric particle image velocimetry

Accurately reconstructing three-dimensional particle fields is essential in fluid velocity measurement research. This study addresses the limitations of current three-dimensional (3D) particle reconstruction methods, such as computational efficiency, precision at high particle density, and particle morphology issues, by introducing a calibration-informed deep learning model named the calibrated pixel to voxel convolutional neural network (CPV-CNN) for 3D Particle Reconstruction. This innovative neural network framework employs a unique Gaussian attention mechanism that bridges pixels and voxels, enabling the mapping of pixel features from two-dimensional (2D) particle images to 3D voxel features. This approach eliminates the need for an initial particle field for particle reconstruction, while significantly enhancing reconstruction efficiency. Additionally, the neural network incorporates camera calibration parameters and the physical coordinates of the reconstructed domain, thereby improving the model's generalization capability and flexibility. Numerical experiments demonstrate that CPV-CNN delivers superior results in terms of accuracy, generalization, and robustness in 3D particle reconstruction. The reconstructed particles exhibit favorable morphology, without the elongation issues commonly observed with conventional methods. This achievement illustrates a practical particle reconstruction algorithm based on artificial intelligence (AI) techniques and represents an important step toward developing an end-to-end AI-based particle reconstruction method in the future.

Suppression of the coffee-ring effect by controlling the solid particle density

Previous studies show that the coffee-ring effect can be suppressed by altering the droplet's evaporation rate, surface tension, surface properties, and shape of particles. This experiment used five types of particles with different densities to analyze their behavior during the droplet evaporation process. The results showed that when the particle density is close to the fluid density, the particles move within the droplet and accumulate at the edges, forming a pronounced coffee-ring effect. Conversely, with the higher difference between the particle density and the fluid density increases, they tended to deposit uniformly at the bottom of the droplet and were less likely to be pushed to the edges by capillary effects, effectively suppressing the coffee-ring effect. We also observed that the movement speed of high-density particles relatively slowed down through particle image velocimetry tracking technology. By analyzing the Peclet number and the timescale between particle sinking speed and particle movement speed due to capillary flow, we explained how particle density influences the critical factors of particle sinking and suspension, thereby inhibiting the formation of the coffee-ring effect.

Hydrodynamics and operation of a multistage fluidized bed with particles of super-high density

High-density particles are commonly used in fluidized bed reactors in uranium recycling processes of nuclear industry, where high fluidization quality (i.e. low gas-solids contacting efficiency) is difficult to achieve, resulting in various problems such as reduced conversion, low product selectivity, stronger equipment vibration and bad operating stability, etc. The objective of this study was to validate the feasibility and advantages of a multistage fluidized bed in processing a super-high-density powder. Wolfram carbide powder of true density of 15630 kg/m3 was used in a cold-model counter-current three-stage fluidized bed with downcomers. Stability of operation, operating range and hydrodynamics were systematically studied. The fluidization quality and operating stability were also compared with a single-stage conical fluidized bed of similar diameter and same solids inventories. The experimental results demonstrated that this high-density wolfram carbide powder could be fluidized and circulated continuously at this multistage fluidized bed, but lower fluidization quality was observed and the stable operating range is narrow. Narrower stable operating range was observed at higher solids circulation rates. At corresponding operating conditions, the fluidization quality of multistage fluidized bed is significantly better than that of the conical fluidized bed with a similar solids inventory.

Evaluation of particle tracking codes for dispersing particles in porous media

Particle tracking (PT) is a popular technique in microscopy, microfluidics and colloidal transport studies, where image analysis is used to reconstruct trajectories from bright spots in a video. The performance of many PT algorithms has been rigorously tested for directed and Brownian motion in open media. However, PT is frequently used to track particles in porous media where complex geometries and viscous flows generate particles with high velocity variability over time. Here, we present an evaluation of four PT algorithms for a simulated dispersion of particles in porous media across a range of particle speeds and densities. Of special note, we introduce a new velocity-based PT linking algorithm (V-TrackMat) that achieves high accuracy relative to the other PT algorithms. Our findings underscore that traditional statistics, which revolve around detection and linking proficiency, fall short in providing a holistic comparison of PT codes because they tend to underpenalize aggressive linking techniques. We further elucidate that all codes analyzed show a decrease in performance due to high speeds, particle densities, and trajectory noise. However, linking algorithms designed to harness velocity data show superior performance, especially in the case of high-speed advective motion. Lastly, we emphasize how PT error can influence transport analysis.

Exceptional elevated-temperature properties of a Laves phase-strengthened CoNiCrFe high-entropy alloy

This work reported a Laves phase-strengthened high-entropy alloy, featured by high-density Laves phase particles uniformly distributed within a face-centered cubic matrix. The pinning effect from these fine Laves phase particles on matrix grain growth and dislocation gliding results in extraordinary microstructure stability and mechanical properties. Additionally, the alloy demonstrates superior oxidation resistance, attributed to the formation of a Cr/Si-rich oxide film and beneficial effects from the Laves phase.

Improvement in the Number of Velocity Vector Acquisitions Using an In-Picture Tracking Method for 3D3C Rainbow Particle Tracking Velocimetry

Particle image velocimetry and particle tracking velocimetry (PTV) have developed from two-dimensional two-component (2D2C) velocity vector measurements to 3D3C measurements. Rainbow particle tracking velocimetry is a low-cost 3D3C measurement technique adopting a single color camera. However, the vector acquisition rate is not so high. To increase the number of acquired vectors, this paper proposes a high probability and long-term tracking method. First, particles are tracked in a raw picture instead of in three-dimensional space. The tracking is aided by the color information. Second, a particle that temporarily cannot be tracked due to particle overlap is compensated for using the positional information at times before and after. The proposed method is demonstrated for flow under a rotating disk with different particle densities and velocities. The use of the proposed method improves the tracking rate, number of continuous tracking steps, and number of acquired velocity vectors. The method can be applied under the difficult conditions of high particle density (0.004 particles per pixel) and large particle movement (maximum of 60 pix).

Selection Results of Solid Material for Horizontal and Highly-Deviated Well Completion Gravel-Packing: Experiments, Numerical Simulation and Proposal

Lightweight and ultra-lightweight solid materials are being used in gravel packing for horizontal wells instead of traditional quartz and ceramsite to decrease the risk of premature plugging and improve packing efficiency. Physical and numerical simulation experiments of gravel packing were conducted to assess the effectiveness of reducing solid material density and investigate its impact on packing and sand control. Packed gravel destabilization experiments highlighted the importance of high-compaction degree packing for effective sand control. Further gravel packing experiments examined the packing performance of different solid materials, revealing that lightweight solids have minimal gravitational deposition effect because their density is similar to the gravel slurry, relying primarily on fluid flow for compaction. The numerical simulation indicated that lightweight ceramsite is unsuitable for horizontal and highly-deviated wells because of its poor compaction degree and sand control, especially with high-viscosity slurry. High-density particles enhance gravitational deposition, improving packing compaction and sand control. Lightweight materials are recommended only when advanced plugging of α wave packing cannot be avoided. In highly-deviated wells, high-density materials significantly improve packing stability and sand control. This study provides clear technical guidelines for selecting solid materials for gravel packing in horizontal and highly-deviated wells.

A Novel Structured Si-Based Composite with 2D Structured Graphite for High-Performance Lithium-Ion Batteries.

Silicon is a promising alternative to graphite anodes for achieving high-energy-density in lithium-ion batteries (LIBs) because of its high theoretical capacity (3579 mAh g-1). However, silicon anode must be developed to address its disadvantages, such as volume expansion and low electronic conductivity. Therefore, the use of silicon as composed with graphite and carbon anode materials is investigated, which requires properties such as a spherical morphology for high density and encapsulation of silicon particles in the composite. Herein, a graphite@silicon@carbon (Gr@Si@C) micro-sized spherical anode composite is synthesized by mechanofusion process. This composite comprises an outer surface, middle layer, and core pore, which are formed by the capillary force arising from 2D structured graphite and pitch properties. This structure effectively addresses the intrinsic issues associated with Si. Gr@Si@C exhibits a high capacity of 1622 mAh g-1 and capacity retention of 72.2% after 100 cycles, with a high areal capacity 4.2 mAh cm-2. When Gr@Si@C is blended with commercial graphite, the composite exhibits high capacity retention and average Coulombic efficiency after cycling. The Gr@Si@C blended electrode exhibits a high energy density of 820Wh L-1 with ≈16% metallic Si in the electrode (40wt.% composite), enabling the realization of practical commercial LIBs.

Preparation of tenofovir amibufenamide fumarate spherical particles to improve tableting performance and sticking propensity by designing a spherical crystallization process

Tenofovir amibufenamide fumarate (TMF) is the first oral drug developed in Asia for the treatment of adult patients with chronic viral hepatitis B, however, further applications are limited by poor tableting performance and high sticking propensity. In this work, the spherulitic growth process of TMF has been designed and explored with the help of molecular dynamics simulation and process analysis technologies (ATR-FTIR, FBRM and EasyViewer). The spherical particles with high bulk density, good flowability and uniform particle size distribution are prepared by a simple quenching process. More importantly, experimental results show that spherical particles have higher average tensile strength (100.8% increase), higher plastic deformability and lower amount of punch sticking (87.4% decrease in 30 tablets) compared to the commercial powder products. These contributions not only shed light on the design principle of drug spherulitic growth processes, but also provide guidance for the manufacture of high-quality tablet products.

Technique of Reactor Experiments of Tin-Lithium Alloy Interaction with Hydrogen Isotopes Under Neutron Irradiation Conditions

The implementation of the ITER and DEMO projects currently includes the investigation of the structural and functional material properties of fusion reactors (FRs). Research to support the use of liquid metals and alloys as plasma-facing materials (PFMs) is a crucial area of work during the development of new FRs. Recent studies indicate the prospects of the tin-lithium (Sn-Li) alloy as a new liquid metal for protecting the in-vessel elements of a FR from the energy flows and high-density particles. Sn-Li alloy has been widely explored for utilization as PFM; however, there is a shortage of investigations being performed at nuclear reactors. The utilization of Sn-Li alloy as PFM in a FR must be fully justified by validated experimental results on tests under extremely high heat, plasma, and radiation loads. The paper presents the methodology of in-pile experiments performed at the IVG.1M research reactor (Kurchatov, Kazakhstan) to study the interaction of hydrogen isotopes with Sn-Li alloy under neutron irradiation conditions. A Sn-Li sample with 73 at. % tin and 27 at. % lithium was manufactured. A unique experimental ampoule device (AD) with a Sn-Li sample had been developed and manufactured for in-pile tests. The results of neutron-physical and thermophysical calculations of designs of the experimental device with Sn-Li alloy under irradiation conditions of the IVG.1M reactor were performed to justify the AD design. Methodical experiments were performed to determine the temperature dependence of the change in the composition of the gas phase in the chamber with Sn-Li alloy. The time dependence of the partial pressure of hydrogen, tritium, and tritium-containing molecules in the AD volume with the Sn-Li alloy on its temperature under reactor irradiation conditions at a power of 3 MW has been studied. Key findings include the successful measurement of tritium release, the determination of temperature conditions for tritium generation and release, and the validation of our experimental AD for conducting such studies.

Experimental and Simulation Investigations of Proppant Transport and Distribution Between Perforation Clusters in a Horizontal Well

Summary Multistage hydraulic fracturing is widely used to stimulate tight reservoirs by means of plug and perforation technology. The proppant distribution between perforation clusters significantly impacts fracture conductivity and well productivity. Uneven slurry distribution is often the norm rather than the exception. Proppant transport behaviors and distribution characteristics are still poorly understood in a horizontal wellbore with clusters, especially at field scales. The objective is to propose an innovative and feasible method to quantitatively evaluate the distribution uniformity of proppant between clusters. In this work, we systematically investigate proppant migration and placement by means of laboratory tests and numerical simulation. Computational fluid dynamics (CFD) and the discrete element method (DEM) are coupled to analyze proppant-fluid flow. The experimental observation and results validate the numerical model and calibrate critical parameters. The transport efficiency (E) and normalized standard deviation (NSD) are used to evaluate proppant distribution. The effects of nine parameters on the E and NSD are investigated at field ranges. The calibrated CFD-DEM model is accurate in studying proppant distribution between multiple clusters. The toe bias is the primary distribution between clusters because of the large inertia originating from high injection rates. Fluid distribution and perforation configuration are critical factors that significantly change the toe bias at the cluster level. Fluid redistribution changes proppant distribution toward the heel. The inline up pattern has the best uniformity, followed by the 180° up-down pattern. The secondary characteristic is bottom-biased within a cluster. Increasing fluid viscosity, using small and light proppants, and pumping high-concentration slurry can improve proppant distribution. The slurry diversion into perforations is hardly changed unless external conditions change. The combination of high-concentration slurry and a large bed quickly induces premature screenout at the toe-side cluster, especially when injecting large and high-density particles. Slurry redistributes toward the heel if the toe-side cluster is blocked. The investigation provides a rational and feasible method for operators to understand proppant transport between clusters and optimize pumping parameters under field situations.

Bose–Einstein condensation of photons in a vertical-cavity surface-emitting laser

Many bosons can occupy a single quantum state without a limit. It is described by the quantum-mechanical Bose–Einstein statistic, which allows Bose–Einstein condensation at low temperatures and high particle densities. Photons, historically the first considered bosonic gas, were late to show this phenomenon, observed in rhodamine-filled microcavities and doped fibre cavities. These findings have raised the question of whether condensation is also common in other laser systems with potential technological applications. Here we show the Bose–Einstein condensation of photons in a broad-area vertical-cavity surface-emitting laser with a slight cavity-gain spectral detuning. We observed a Bose–Einstein condensate in the fundamental transversal optical mode at a critical phase-space density. The experimental results follow the equation of state for a two-dimensional gas of bosons in thermal equilibrium, although the extracted spectral temperatures were lower than the device’s. This is interpreted as originating from the driven-dissipative nature of the photon gas. In contrast, non-equilibrium lasing action is observed in the higher-order modes in more negatively detuned device. Our work opens the way for the potential exploration of superfluid physics of interacting photons mediated by semiconductor optical nonlinearities. It also shows great promise for enabling single-mode high-power emission from a large-aperture device.

Effects of local bed layer characteristics on separation of low rank oil shale in a dry cascade beneficiation bed

Oil shale is considered a highly significant substitute energy source for the 21st century due to its abundant resources and feasibility for development and utilization. This paper utilizes a dry cascade beneficiation bed to upgrade 25–0 mm oil shale, focusing on the spatial distribution characteristics of local bed layer density and differential density particle spatial distribution rules. The study identifies the formation area of autogenous medium fluidization and systematically analyzes the force characteristics and spatial migration laws of particles in local bed layers. Factors influencing the mixing and separation of oil shale particles are investigated, and stages of the separation process are determined. Experimental results indicate that in area I, the density distribution range of autogenous medium bed layers is 2.21–2.25 g/cm3, representing the formation area of autogenous medium fluidization, predominantly with low-density oil shale particles at ρ = 1.95 g/cm3, ranging from 2.28 % to 4.37 % across particle size grades. Area II predominantly contains intermediate density particles at ρ = 2.20 g/cm3, with upper and lower layer contents of 10.9–11.6 % and 4.7–5.7 %, respectively; the upper bed layer is dominated by 13–25 mm particles, while the lower bed layer by 0–6 mm and 6–13 mm particles. Area III features high-density particles at ρ = 2.40 g/cm3, with upper and lower layer contents of 6.13–6.40 % and 1.86–2.11 %, respectively, showing particle size distribution consistent with area II. When Γ = 13.60–16.28, area I serves as a domain for low-density material separation, with peak forces of 6.95–7.0 mN; area II as a domain for separation of medium to high-density particles, with peak forces of 4.83–4.87 mN; and area III as a domain for high-density material transport, with peak forces of 2.01–2.03 mN. Particle acceleration along the Z-axis relative to the X-axis increases by 0.688 m/s2, 3.791 m/s2, and 4.670 m/s2 in areas I, II, and III, respectively, and relative to the Y-axis by 0.554 m/s2, 3.11 m/s2, and 3.396 m/s2. When U=2.36 m/s and Γ = 17.73–22.04, significant differences in distribution of same-density particles between upper and lower bed layers are observed, with differences in content for low-density materials (ρ = −1.8 g/cm3) of 13.23 %, 0.01 %, and 0.01 % in areas I, II, and III, respectively, and for high-density materials (ρ = +2.5 g/cm3) of 1.21 %, 0.91 %, and 2.17 %. By examining particle mixing and separation processes, three operational stages are defined: Area diffusion, stratified transition, and cascade distribution, and separation tests under optimal conditions achieve a concentrate yield of 39.23 % with an oil content of 10.18 %, and a tailings yield of 60.77 % with an oil content of 0.71 %. The probable error (Ep) is 0.08 g/cm3 achieves high-precision upgrading of oil shale.

Vertical distribution of Pacific oyster Crassostrea gigas larvae and modeling larval transport in Hiroshima Bay, Japan

Understanding vertical distribution of planktonic larvae is essential for elucidating larval dispersal and recruitment processes. We investigated the vertical distribution and horizontal transport of Pacific oyster Crassostrea gigas larvae by field observations and numerical simulations during their main spawning season in Hiroshima Bay, Japan. In field observations, despite horizontal differences and slight diurnal/semi-diurnal changes depending on larval sizes, most larvae were distributed in the upper 3 m layer. The relationship between C. gigas larvae and environmental conditions revealed that larval density increased with increasing temperature and chlorophyll a concentration, and the density peaked at salinity of approximately 20 for all larval sizes. The observed results suggest that the distribution characteristics of C. gigas larvae are suitable for survival in an estuarine area, where environmental conditions are potentially favorable but hydrodynamic conditions can drastically change over the short term due to variations in river discharge. To examine the effect of high river discharge on larval transport, numerical simulations were conducted using a particle-tracking model incorporating the vertical motion of C. gigas larvae. The simulation results reproduced the spatio-temporal dynamics of planktonic and settled larvae after the high river discharge. Although most particles simulating larvae outflowed from the main spawning area, an area of high particle density at the end of simulation corresponded with the offshore area for seedling collection. The present study suggests the role of vertical distribution of C. gigas larvae for recruitment, and the prospect of sustainability in oyster aquaculture with respect to seedling collection despite the frequent heavy rainfall associated with climate change.

Reconstruction of particle distribution for tomographic particle image velocimetry based on unsupervised learning method

The development of deep learning has inspired some new methods to solve the 3D reconstruction problem for Tomographic Particle Image Velocimetry (Tomo-PIV). However, the supervised learning method requires a large number of data with ground truth as training information, which is very difficult to gather from experiments. Although synthetic datasets can be used as alternatives, they are still not exactly the same with the real-world experimental data. In this paper, an Unsupervised Reconstruction Technique based on U-net (UnRTU) is proposed to reconstruct volume particle distribution explicitly. Instead of using ground truth data, a projection function is used as an unsupervised loss function for network training to reconstruct particle distribution. The UnRTU was compared with some traditional algebraic reconstruction algorithms and supervised learning method using synthetic data under different particle density and noise level. The results indicate that UnRTU outperforms these traditional approaches in both reconstruction quality and noise robustness, and is comparable to the supervised learning methods AI-PR. For experimental tests, particles dispersed in cured epoxy resin are moved by an electric rail with a certain speed to obtain the ground truth data of particle velocity. Compared with other algorithms, the reconstructed particle distribution by UnRTU has the best reconstruction fidelity. And the accuracy of the 3D velocity field estimated by UnRTU is 12.9% higher than that from the traditional MLOS-MART algorithm. It demonstrates significant potential and advantages for UnRTU in 3D reconstruction of particle distribution. Finally, UnRTU was successfully applied to the high-speed planar cascade airflow field, demonstrating its applicability for measuring complex fluid flow fields at higher particle density.

Unbalanced Optimal Transport For Stochastic Particle Tracking

Non-invasive flow measurement techniques, such as particle tracking velocimetry, resolve 3D velocity fields by pairing tracer particle positions in successive time steps. These trajectories are crucial for evaluating physical quantities like vorticity, shear stress, pressure, and coherent structures. Traditional approaches deterministically reconstruct particle positions and extract particle tracks using tracking algorithms. However, reliable track estimation is challenging due to measurement noise caused by high particle density, particle image overlap, and falsely reconstructed 3D particle positions. To overcome this challenge, probabilistic approaches quantify the epistemic uncertainty in particle positions, typically using a Gaussian probability distribution. However, the standard deterministic tracking algorithms relying on nearest-neighbor search do not directly extend to the probabilistic setting. Moreover, such algorithms do not necessarily find globally consistent solutions robust to reconstruction errors. This paper aims to develop a globally consistent nearest-neighborhood algorithm that robustly extracts stochastic particle tracks from the reconstructed Gaussian particle distributions in all frames. Our tracking algorithm relies on the unbalanced optimal transport theory in the metric space of Gaussian measures. Specifically, we optimize a binary transport plan for efficiently moving the Gaussian distributions of reconstructed particle positions between time frames. We achieve this by computing the partial Wasserstein distance in the metric space of Gaussian measures. Our tracking algorithm is robust to position reconstruction errors since it automatically detects the number of particles that should be matched through hyperparameter optimization. Notably, our tracking algorithm also readily applies to the standard deterministic PTV case. Finally, we validate our method using an in vitro flow experiment using a 3D-printed cerebral aneurysm.

Study on the distribution of high ash slime in liquid-solid fluidized bed with different heights

ABSTRACT Liquid-solid fluidized bed (LSFB) sorting has been widely used in coarse coal slurry sorting in coal preparation plants in China. In this paper, the vertical distribution of high-ash fine sludge in the LSFB column was studied in depth, and the results showed that in the vertical direction of the column, the gradient of ash change of the + 0.25 mm particles was obviously larger than that of the −0.25 mm particles. For + 0.25 mm particles, the low-density fine coal particles accumulate in the middle and upper parts, while the high-density particles accumulate in the middle and lower parts, and the overflow −0.25 mm particles are basically uniformly distributed in each density class. In the overflow port and the upper part of the column, the ash content of −0.25 mm particle size is obviously higher than that of + 0.25 mm particle size, and the −0.125 mm high ash and fine sludge basically accumulate in the upper part of the LSFB, and eventually enter the overflow to seriously pollute the fine coal. This study is of great significance for the development and application of LSFB sorting machine and the optimization of coarse coal slurry sorting and recovery process.

Efficient point-based simulation of four-way coupled particles in turbulence at high number density.

In many natural and industrial applications, turbulent flows encompass some form of dispersed particles. Although this type of multiphase turbulent flow is omnipresent, its numerical modeling has proven to be a remarkably challenging problem. Models that fully resolve the particle phase are computationally very expensive, strongly limiting the number of particles that can be considered in practice. This warrants the need for efficient reduced order modeling of the complex system of particles in turbulence that can handle high number densities of particles. Here we present an efficient method for point-based simulation of particles in turbulence that are four-way coupled. In contrast with traditional one-way coupled simulations, where only the effect of the fluid phase on the particle phase is modeled, this method additionally captures the back-reaction of the particle phase on the fluid phase, as well as the interactions between particles themselves. We focus on the most challenging case of very light particles or bubbles, which show strong clustering in the high-vorticity regions of the fluid. This strong clustering poses numerical difficulties which are systematically treated in our work. Our method is valid in the limit of small particles with respect to the Kolmogorov scales of the flow and is able to handle very large number densities of particles. This methods paves the way for comprehensive studies of the collective effect of small particles in fluid turbulence for a multitude of applications.