Particle Wall Research Articles

Modeling Stochastical Particle Rebound based on High Velocity Experiments

Abstract Solid particle erosion is a major deterioration process which contributes to performance deterioration of modern axial compressors. The prediction of this deterioration process requires the correct computation of particle movement through the machine and their resulting impacts on the effected components. Especially for particles with high Stokes numbers the movement is determined mainly by the particle wall interaction, which is described by coefficients of restitution. Today, they are derived from experiments featuring high particle velocities and target materials, which are representative for turbomachinery applications. In this study, an already published rebound model is optimized for particle materials and velocities within high pressure compressors. The statistical spread of the rebound experiment is evaluated and the implementation into the rebound model is shown, which improves the prediction capability of the model. The model is implemented into a CFD software and numerical simulations are performed. The model is applied to a cylinder test specimen within a sand blast facility. The simulation shows the importance of the stochastics of the rebound, which is often neglected in particle wall models. Moreover, the numerical study shows requirements for the test specimen and its positioning in the experimental setup, which are prerequisites for the derivation of the coefficients of restitution using two dimensional particle evaluation equipment.

First SOLEDGE3X-EIRENE simulations of the ITER Neon seeded burning plasma boundary up to the first wall

Boundary plasma simulations are essential to estimate expected divertor and first wall (FW) heat and particle loads on ITER during burning plasma operation. A key missing feature of existing SOLPS simulations (Pitts et al., 2019) is the absence of a plasma solution out to the main chamber walls, essential to self-consistently estimate the gross sputtering of wall material. Here, SOLEDGE3X is applied for the first time to obtain up-to-the wall burning plasma solutions of the ITER boundary plasma at the nominal PSOL = 100 MW of the main SOLPS database simulations, including He ash, Ne seeding but without fluid drifts. Compared with the most recent SOLPS-ITER simulations, our simulations show differences in the exact impurity distribution, but the key results for divertor and wall heat flux remain consistent. In the context of the ITER re-baselining exercise (Pitts, 2024), in which the Be FW armour is proposed to be exchanged for tungsten (W), estimates of W wall sources are key to the assessment of likely core contamination and hence impact on fusion gain. We compare the W gross erosion rates due to the different species excluding W self-sputtering. For the cases simulated spanning 0.27%–0.47% separatrix-averaged Ne concentration and 7.5×1022s−1−1.95×1023s−1 D fuelling, Ne8+ remains the largest contributor to the sputtering flux with the largest source being the outer divertor and baffle. The species-wise contribution to W sputtering changes with fuelling with sputtering due to lower Ne charge states being significant at low D fuelling. In general, the gross W sputtering source is found to decrease with increase in D fuelling and increase with increased Ne seeding.

Dynamics of single cavitation bubble collapse jet under particle-wall synergy

The interaction between a particle and a cavitation bubble significantly influences the erosive effect on the wall surface of flow passage components in fluid machinery. This paper investigates the dynamics of a single bubble collapse jet under the synergetic effects of a particle and a wall, using Kelvin impulse theory and high-speed photographic experiments. A theoretical model to predict the intensity and direction of the collapse jet at arbitrary locations near the particle and the wall is constructed on the basis of the image method and Weiss's theorem. The accuracy of the model is verified by comparison with a large number of experimental results. The mechanisms underlying the relative contributions of the particle and wall to the behavior of jet intensity and direction are explored. The effects of key parameters on jet intensity and direction are also quantitatively analyzed, including the relative positions of the particle, wall, and the bubble and the dimensionless particle radius. The main conclusions are as follows: (1) the particle will cause a deflection in the direction of the collapse jet near the wall, leading to the formation of a jet attraction zone. The proposed theoretical model effectively predicts the spatial location of this zone. (2) There exists a region in which the jet is weak, and there is a jet equilibrium point with zero impulse between the particle and the wall. The position of this equilibrium point gradually approaches the wall in a nonlinear manner with increasing particle size and in a quasi-linear manner with decreasing particle–wall distance. (3) When the particle and the bubble are the same distance from the wall, the jet direction gradually changes from toward the particle to vertical to the wall in a nonlinear manner as the bubble–particle distance increases. Moreover, the effective range of the particle's influence on the jet direction decreases as the particle–wall distance decreases.

One-dimensional model for vertical hydraulic transport of high-concentration mineral particles

A novel model is proposed for analyzing high-concentration granular flow systems comprising equally sized spherical particles within vertical, long straight pipelines. This model is specifically tailored for simulating the vertical hydraulic transport of ore particles in marine mining projects. The proposed model treats the granular system akin to a pseudo-fluid and operates through three mechanisms. First, fluid characteristics of the granular system are derived from particle–particle collisions. Second, the resistance exerted by the pipe wall on the granular system is calculated based on the momentum loss of particles during particle–wall collisions. Third, the interaction between individual particles and the surrounding fluid is transformed into an interaction between the carrier fluid and the pseudo-fluid. Additionally, the present work develops a dedicated numerical format and iterative method for solving the one-dimensional two-fluid governing equations. The one-dimensional (1D) model notably enhances computational efficiency and facilitates accurate tracking of high-concentration particles over extended distances within straight pipelines. Notably, the proposed 1D model demonstrates a high degree of predictive accuracy when compared against experimental data as well as results from computational fluid dynamics and discrete element method simulations.

Research on the Effect of Deflection Secondary Air on Slagging in Coal Fired Boilers

Abstract In response to the slagging phenomenon in coal-fired boilers, the combustion characteristics of pulverized coal and the effect of deflected secondary air on slagging in a 350MW Corner-tangentially-fired boiler are numerically investigated by the commercial software. The research results indicate that when the deflection secondary air (CFS air) volume increases, the tangential diameter will significantly increase, and the degree of influence is higher than the angle, which has a significant impact on wall temperature and smoke wall brushing. Only adjusting the CFS wind angle or wind volume has a relatively small impact on particle wall brushing; When CFS wind is superimposed with large Angle and high air volume, the temperature and the degree of smoke brushing near the water wall will be significantly increased, and the risk of slag formation on the water wall will be magnified.

Continuous Focusing of Particles by AC-Electroosmosis and Induced Dipole Interactions.

Continuous particle focusing by using microfluidics is an effective method for separating particles, cells, or droplets for analytical purposes. Previously, it was shown that an alternating current across rectangular microchannels with slightly deformed side walls results in vortex flow patterns caused by alternating current electroosmosis (AC-EOF) and could lead to particle focusing. In this work, we explore this mechanism by experimentally studying the particle focusing behavior for various fluid flow velocities through a microchannel. Since it is unlikely that the particles are kept in their focused position solely by convection, a theoretical force balance between the hydrodynamic and the induced dipole force was determined. In our experiments, it was found that there is no substantial effect of the pressure-driven fluid velocity on the particle focusing velocity within the studied range. From the theoretical force balance calculations, it was determined that while the addition of the induced dipole force can still not completely describe the experimentally observed particle focusing, the induced dipole can be strong enough to overcome the hydrodynamic force. Finally, it is hypothesized that under specific circumstances, including a repulsive electrostatic force between a particle and electrode wall can complete the theoretical particle focusing force balance. Alternative phenomena that could also play a role in particle focusing are proposed.

Optimization of non-spherical particle flow in vertical waste heat recovery devices: Analyzing structural configurations

Vertical waste heat recovery devices are emerging but are immature. The vertical waste heat recovery devices of circular, square, and optimized designs were analyzed for a full capacity of 8 tons of sintered ore. Using DEM theory, the effects of particle size distribution, velocity, and wall forces on void fraction distribution and particle flow were examined. The circular device demonstrated superior mixed particle flow compared to the square device, achieving integrated flow for 50 % of particles in the cone, in contrast to 26 % for the square device. An optimized circular device achieved integral flow for 90 % of particles, significantly enhancing overall flow and reducing wall adhesion, attributed to its improved internal design. Through insert and distributor design, the overall particle flow within the device improved, with almost no particles remaining on the walls. These findings underscore the potential for enhanced heat recovery efficiency through optimized internal structures in waste heat recovery devices.

Tumor lysate particle only vaccine (TLPO) vs. Tumor lysate particle-loaded, dendritic cell vaccine (TLPLDC) to prevent recurrence in resected stage III/IV melanoma patients: Results of a phase I/IIa trial

BackgroundThe autologous tumor lysate, particle-loaded, dendritic cell (TLPLDC) vaccine is produced from dendritic cells (DC) loaded ex vivo with autologous tumor lysate (TL). TLPLDC has been shown to decrease recurrence in resected Stage III/IV melanoma patients in a Phase IIb trial. The TL particle only (TLPO) vaccine is produced by loading of yeast cell wall particles with autologous TL and direct injection allowing for in vivo DC loading. We have compared the TLPO and TLPLDC vaccines in an embedded Phase I/IIa trial of a larger Phase IIb trial of the TLPLDC vaccine. MethodsPatients rendered clinically disease-free after surgery were randomized 2:1 to receive the TLPO or TLPLDC vaccine and followed for recurrence and death. Patients had scheduled intradermal inoculations at 0, 1, 2, 6, 12, and 18 months after enrollment. Kaplan-Meier and log-rank analysis were used to compare disease-free survival (DFS) and overall survival (OS) in an intention-to-treat (ITT) analysis. ResultsSixty-three patients were randomized, 43 TLPO and 20 TLPLDC. Patients randomized to the TLPO arm were more likely to be female (37.2% vs. 10.0 %, p = 0.026), but otherwise no significant clinicopathological differences were identified. No differences in related adverse events (AE) were found between treatment arms. At a median follow-up of 20.5 months, the DFS (60.8% vs. 58.7 %, p = 0.714) and OS (94.6% vs. 93.8 %, p = 0.966) were equivalent between the TLPO and TLPLDC groups, respectively. No statistical differences were found in subgroup analyses between vaccine types, which accounted for receipt of immunotherapy and the use of G-CSF pre-blood draw. ConclusionsIn a randomized, double-blind Phase I/IIa trial, there were no differences in DFS or OS in resected Stage III/IV melanoma patients receiving adjuvant TLPO versus TLPLDC vaccines. Given manufacturing advantages, further efficacy testing of TLPO is warranted in a Phase III trial.

DEM investigation on the dynamic characteristics of wall normal stress and particle flow during silo discharge

Violent fluctuations of wall normal stress and particle velocity during silo discharge have been frequently reported by researchers, yet a detailed particle-scale description of these phenomena is still lacking. In this work, the discharge of granular assembly from a flat-bottomed silo was investigated by performing three-dimensional (3D) Discrete Element Method (DEM) simulations. It is found that arc-shaped rupture surfaces, characterized by the lower solid volume fraction, stronger shear interaction between particles and higher particle rotating velocity, developed continuously in the bottom converging part of flowing zone. And the temporal evolution of particle velocity field in this converging part presented a swinging feature manifested by the alternate appearance of large particle velocity magnitude in the right- and left- side regions. Discrete Fourier transform results showed that the fluctuation of wall normal stress at the transition point contained two dominate frequencies. The lower frequency matched well with the dynamic evolution of the rupture surface joining the transition point, and the higher frequency was nearly the same as the fluctuating frequency of particle vertical velocity. Thus, our DEM simulation results suggested that for the silo discharge considered in this work, the periodic fluctuation of wall normal stress at the transition point was contributed by both the alternating flow pattern mechanism and the free-fall arch mechanism.

Investigating Pulmonary Neutrophil Responses to Inflammation in Mice via Flow Cytometry.

Neutrophils play a crucial role in maintaining lung health by defending against infections and participating in inflammation processes. Here we describe a detailed protocol for evaluating pulmonary neutrophil phenotype using a murine model of sterile inflammation induced by the fungal cell wall particle zymosan. We provide step-by-step instructions for the isolation of single cells from both lung tissues and airspaces, followed by comprehensive staining techniques for both cell surface markers and intracellular components. This protocol facilitates the sorting and detailed characterization of lung neutrophils via flow cytometry, making it suitable for downstream applications such as mRNA extraction, single-cell sequencing, and analysis of neutrophil heterogeneity. We also identify and discuss essential considerations for conducting successful neutrophil flow cytometry experiments. This work is aimed at researchers exploring the intricate functions of neutrophils in the lung under physiological and pathological conditions with the aid of flow cytometry.

Experimental study of the wall particle motion in a screw reactor

Screw reactors are gas/solid systems widely employed in industrial applications. Understanding the local powder mixing within these reactors is crucial, particularly at the reactor wall where wall/solid heat transfer occurs. This study proposes a non-invasive measurement method utilizing optical devices to assess wall particle motion. Two techniques for evaluating the particle motion are compared: a simple visual tracking method and particle image velocimetry. Both methods yield similar results, demonstrating consistent wall particle motion across the tube periphery during experimentation. The influence of operational and geometric parameters has been investigated, revealing that filling degree, powder flowability, and screw geometry significantly impact wall particle motion. Symbolic regression has been employed to derive dimensionless models that effectively predict experimental data. These models can be utilized to forecast wall particle motion, serving as a valuable tool for screw conveyor design.

Particle shells from relativistic bubble walls

Relativistic bubble walls from cosmological phase transitions (PT) necessarily accumulate expanding shells of particles. We systematically characterize shell properties, and identify and calculate the processes that prevent them from free streaming: phase-space saturation effects, out-of-equilibrium 2 → 2 and 3 → 2 shell-shell and shell-bath interactions, and shell interactions with bubble walls. We find that shells do not free stream in scenarios widely studied in the literature, where standard predictions will need to be reevaluated, including those of bubble wall velocities, gravitational waves (GW) and particle production. Our results support the use of bulk-flow GW predictions in all regions where shells free stream, irrespectively of whether or not the latent heat is mostly converted in the scalar field gradient.

Numerical study of sheath formation in multi‐ion species plasmas

AbstractA study of multi‐ion species plasmas in divertor region through kinetic simulation helps us understand particle transports and wall interactions. We analyzed plasma sheath behavior without collisions involving electrons, hydrogen isotopes, and helium ions using a one‐dimensional spatial space and three‐dimensional velocity space (1D3V) Particle‐In‐Cell (PIC) simulation. The PIC simulation model follows Maxwellian velocity distributions with the pre‐sheath acceleration for each particle species in the plasma source, and the plasmas move to the absorption wall with equal and constant flux. This revealed spatial potential variations due to differences in masses and charges of multi‐ion species plasmas, including independent sound velocities of each ion species. Increasing ion masses result in a more negative wall potential. The electrostatic force repels electrons and accelerates multi‐ions to reach the absorption wall. This information is found in the phase spaces of velocity in the sheath.

Lagrangian-based simulation method using constrained Stokesian dynamics for particulate flows in microchannel

A simulation method has been developed to efficiently evaluate the motion of colloidal particles in a low-Reynolds-number confined microchannel flow using a Lagrangian-based approach. In this method, the background velocity within the channel, in the absence of suspended particles, is obtained from a fluid dynamics solver and is used to update the velocity at the particle centres using the Stokesian dynamics (SD) method, which incorporates multi-body hydrodynamic interactions. As a result, instead of computing the momentum of both the fluid and particles throughout the entire computational domain, the microscopic balance equation is solved only at the particle centres, increasing the computational efficiency. To accommodate complex boundary conditions within the SD framework, imaginary particles are placed on the channel walls, allowing the mobility relation to be reformulated to apply velocity constraints to immobilized wall particles. By employing this constrained SD approach, global mobility interactions that need to be computed at each time step are limited to the interior particles, resulting in a significant reduction in computational cost. The efficiency of this study is demonstrated through case studies on particulate flows in contraction and cross-flow microchannels. By using colloidal particles that incorporate Brownian motion and inter-particle attraction, observations through the entire stages of fouling dynamics are possible, from particle inflow to channel blockage. The fouling patterns observed in the simulations are consistent with experiments conducted under the same flow conditions. This study provides an efficient approach for analysing the effect of hydrodynamic interactions on particle dynamics in microfluidics and materials processing fields while allowing for predictions about structural changes over long-time scales, including complex phenomena such as clogging.

Dynamic Wall Shear Stress Measurement Using Event-Based 3D Particle Tracking

We describe the implementation of a 3d Lagrangian particle tracking (LPT) system based on event-based vision (EBV) sensors and demonstrate its application for the near-wall characterization of a turbulent boundary layer (TBL) in air. The viscous sublayer of the TBL is illuminated by a thin light sheet that grazes the surface of a glass window inserted into the flat wall of the wind tunnel wall. The data simultaneously captured by three synchronized EBV-cameras is used to reconstruct the 3d particle tracks within 0.4 mm of the wall on a field of view of 12.0 mm by 7.5 mm. The velocity and position of particles within the viscous sub-layer permit the estimation of the local, unsteady wall shear stress vector under the assumption of linearity between particle velocity and wall shear stress. Thereby, 2d distributions and higher order statistics of the unsteady wall shear stress are obtained. The systematic underestimation of the spanwise shear stress fluctuation can be explained on the basis of DNS data; a methodology for its mitigation is proposed. The employed EBV hardware coupled with suited LPT algorithms provide data quality on par with currently used, considerably more expensive, high-speed framing cameras.

Quantifying the effects of inlet gas and collision models in direct metal deposition using a CFD-DEM approach

Simulations of the powder jet in direct metal deposition (DMD) are often made with significant simplifications such as being incompressible, steady-state, or single-component, and do not provide explanation for the choice of parameters in the collision model. This work presents a coupled Computational Fluid Dynamics–Discrete Element Method model for the powder jet in DMD that considers all of the following features: compressibility effects, particle–wall and particle–particle collisions, turbulence, gas mixing, and melt pool boundaries. The goal of the simulation is to optimize the operating conditions and to predict the outcomes of experiments. After effective validation against experimental results, the effects of inlet gas, collision models and different boundary conditions in DMD have been comprehensively studied. It is demonstrated that gases with higher diffusivities, such as helium, are less effective shielding gases than those with lower diffusivities, such as argon. The increased wall temperature arising from the melt pool and track has little influence on the particle distribution.

Neural network architecture search model for thermal radiation in dense particulate systems

In the CFD-DEM simulation of the many dense particulate systems, particle-scale thermal radiation is an important heat transfer mode under high temperatures. In this work, neural network architecture search model with different layer connection matrix is applied to the view factor regression of the thermal radiation in dense particulate systems. Deep neural networks with 3346 feasible architectures are evaluated by the HyperBand algorithm to find the local optimal solution. Neural architecture search model trained by the big data of the view factor gives a good prediction of the macroscopic radiative properties and it is in general agreement with the empirical correlations and experimental data. The particle–wall radiation decreases strongly with the distance and the maximum interaction depth is about 2.0 times the sphere diameter. The trained deep neural network model provides an efficient data-driven closure to discuss the thermal radiation of the particle–particle and particle–wall interactions in particle bed.

AI-assisted deep learning segmentation and quantitative analysis of X-ray microtomography data from biomass ashes

X-ray microtomography is a non-destructive method that allows for detailed three-dimensional visualisation of the internal microstructure of materials. In the context of using phosphorus-rich residual streams in combustion for further ash recycling, physical properties of ash particles can play a crucial role in ensuring effective nutrient return and sustainable practices. In previous work, parameters such as surface area, porosity, and pore size distribution, were determined for ash particles. However, the image analysis involved binary segmentation followed by time-consuming manual corrections. The current work presents a method to implement deep learning segmentation and an approach for quantitative analysis of morphology, porosity, and internal microstructure. Deep learning segmentation was applied to microtomography data. The model, with U-Net architecture, was trained using manual input and algorithm prediction.•The trained and validated deep learning model could accurately segment material (ash) and air (pores and background) for these heterogeneous particles.•Quantitative analysis was performed for the segmented data on porosity, open pore volume, pore size distribution, sphericity, particle wall thickness and specific surface area.•Material features with similar intensities but different patterns, intensity variations in the background and artefacts could not be separated by manual segmentation – this challenge was resolved using the deep learning approach.

Microstructure and performances of rigid polyurethane foam prepared using double‐effect baking powder as a foaming agent

AbstractThe preparation of rigid polyurethane foam with uniform pore size is extremely challenging. In this work, double‐effect baking powder was used as foaming agent, and rigid polyurethane foam with regular morphology was successfully prepared through semi‐prepolymerization. The rigid polyurethane foam apertures with regular morphology were controlled by the secondary release of CO2 when the content of baking powder is 0.30 part. Combined with theoretical calculation and experimental test, it is found that the particle size distribution, wall thickness, and hole shape are uniform, regular, thin, polygonal, and few broken holes. The compression strength, contact angle, and surface energy of the rigid polyurethane foam are 33.36 kPa, 109.6°, and 21.8 mJ/m2 after adding 0.20 part of double‐effect baking powder, respectively. By adjusting the amount of double‐acting baking powder, the porosity, mechanical properties and foam rate of the polyurethane foams could be significantly improved. Due to the molecular solvation effect, rigid polyurethane foams will deform in the water and oil due phase, but it can remain stable for a long time at room temperature without solvent. It provides a new method for the preparation of rigid polyurethane foam, which is expected to be widely used in transportation and other fields.Highlights Baking powder was firstly used as a foaming modifier for rigid polyurethane. Baking powder releases CO2 twice to ensure uniform structure of polyurethane cell. Rigid polyurethane foam has long‐term stability and regular, uniform cell holes. The porosity and mechanical properties of foams could be significantly improved. Foaming mechanism of rigid polyurethane using baking powder was firstly revealed.

An Investigation into Electrolytes and Cathodes for Room-Temperature Sodium–Sulfur Batteries

In the pursuit of high energy density batteries beyond lithium, room-temperature (RT) sodium–sulfur (Na-S) batteries are studied, combining sulfur, as a high energy density active cathode material and a sodium anode considered to offer high energy density and very good standard potential. Different liquid electrolyte systems, including three different salts and two different solvents, are investigated in RT Na-S battery cells, on the basis of the solubility of sulfur and sulfides, specific capacity, and cyclability of the cells at different C-rates. Two alternative cathode host materials are explored: A bimodal pore size distribution activated carbon host AC MSC30 and a highly conductive carbon host of hollow particles with porous particle walls. An Na-S cell with a cathode coating with 44 wt% sulfur in the AC MSC30 host and the electrolyte 1M NaFSI in DOL/DME exhibited a specific capacity of 435 mAh/gS but poor cyclability. An Na-S cell with a cathode coating with 44 wt% sulfur in the host of hollow porous particles and the electrolyte 1M NaTFSI in TEGDME exhibited a specific capacity of 688 mAh/gS.