This paper presents an Eulerian-Lagrangian algorithm for direct numerical simulation(DNS)of particle-laden flows.The algorithm is applicable to perform simulations of dilute suspensions of small inertial particles in ...This paper presents an Eulerian-Lagrangian algorithm for direct numerical simulation(DNS)of particle-laden flows.The algorithm is applicable to perform simulations of dilute suspensions of small inertial particles in turbulent carrier flow.The Eulerian framework numerically resolves turbulent carrier flow using a parallelized,finite-volume DNS solver on a staggered Cartesian grid.Particles are tracked using a point-particle method utilizing a Lagrangian particle tracking(LPT)algorithm.The proposed Eulerian-Lagrangian algorithm is validated using an inertial particle-laden turbulent channel flow for different Stokes number cases.The particle concentration profiles and higher-order statistics of the carrier and dispersed phases agree well with the benchmark results.We investigated the effect of fluid velocity interpolation and numerical integration schemes of particle tracking algorithms on particle dispersion statistics.The suitability of fluid velocity interpolation schemes for predicting the particle dispersion statistics is discussed in the framework of the particle tracking algorithm coupled to the finite-volume solver.In addition,we present parallelization strategies implemented in the algorithm and evaluate their parallel performance.展开更多
We present a numerical framework for simulating viscous compressible flows in the presence of solid particles with large size ratios.The volume-filtered Navier-Stokes equations are discretized using a class of high-or...We present a numerical framework for simulating viscous compressible flows in the presence of solid particles with large size ratios.The volume-filtered Navier-Stokes equations are discretized using a class of high-order low-dissipative finite difference operators with energy-preserving properties.No-slip,adiabatic boundary conditions are enforced at the surface of large particles(with diameters significantly larger than the local grid spacing)using a ghost-point immersed boundary method.Two-way coupling between the gas phase and small particles(with diameters proportional to the grid spacing)is accounted for through volumetric source terms for interphase momentum and energy exchange.A simple and efficient approach for collision detection between small and large particles is proposed.The framework is applied to simulations of planar shocks interacting with bidisperse distributions of particles with size ratios of approximately thirty.Particle dispersion and size segregation are reported and a simple analytical model for size segregation is proposed.展开更多
Aiming to solve the steering instability and hysteresis of agricultural robots in the process of movement,a fusion PID control method of particle swarm optimization(PSO)and genetic algorithm(GA)was proposed.The fusion...Aiming to solve the steering instability and hysteresis of agricultural robots in the process of movement,a fusion PID control method of particle swarm optimization(PSO)and genetic algorithm(GA)was proposed.The fusion algorithm took advantage of the fast optimization ability of PSO to optimize the population screening link of GA.The Simulink simulation results showed that the convergence of the fitness function of the fusion algorithm was accelerated,the system response adjustment time was reduced,and the overshoot was almost zero.Then the algorithm was applied to the steering test of agricultural robot in various scenes.After modeling the steering system of agricultural robot,the steering test results in the unloaded suspended state showed that the PID control based on fusion algorithm reduced the rise time,response adjustment time and overshoot of the system,and improved the response speed and stability of the system,compared with the artificial trial and error PID control and the PID control based on GA.The actual road steering test results showed that the PID control response rise time based on the fusion algorithm was the shortest,about 4.43 s.When the target pulse number was set to 100,the actual mean value in the steady-state regulation stage was about 102.9,which was the closest to the target value among the three control methods,and the overshoot was reduced at the same time.The steering test results under various scene states showed that the PID control based on the proposed fusion algorithm had good anti-interference ability,it can adapt to the changes of environment and load and improve the performance of the control system.It was effective in the steering control of agricultural robot.This method can provide a reference for the precise steering control of other robots.展开更多
Bacterial cells are widely accepted as nucleation sites for calcium carbonate precipitation in biomineralization based on the Microbially Induced Carbonate Precipitation(MICP)process.For MICP-based insitu biotreatment...Bacterial cells are widely accepted as nucleation sites for calcium carbonate precipitation in biomineralization based on the Microbially Induced Carbonate Precipitation(MICP)process.For MICP-based insitu biotreatment,the firstproblem to be solved is how to introduce and retain the bacterial cells in the soil,which involves the migration and retention of bacterial cells during the biogrouting process.Soil particle size,a key factor in determining pore throat size,can have a significanteffect on the migration and retention of bacterial cells in the soil and therefore on biomineralization.To investigate the effect of particle size on the migration and retention of bacterial cells in sand and its biomineralization,two sets of tests were carried out in this study,including percolation tests and sand column treatment tests.Soil urease activity(definedas urease activity per unit mass of soil)and calcium carbonate content of the biomineralized sand were measured to comprehensively assess the migration and retention of bacterial cells in the sand.The results indicate that sands with a particle size smaller than 0.25 mmwould inhibit the migration of bacteria in the sand,resulting in a nonuniform distribution of precipitated calcium carbonate and a low strength enhancement of biomineralization.On the other hand,sands with a particle size larger than 1.18 mm are unfavorable for retaining bacterial cells in the sand,resulting in low calcium conversion efficiency.Meanwhile,particle size would also affect the formation of effective calcium carbonate through interparticle contact number and interparticle pore size,and thus biomineralization.展开更多
The stress-strain behavior of calcareous sand is significantly influencedby particle breakage(B)and initial relative density(Dri),but few constitutive models consider their combined effects.To bridge this gap,we condu...The stress-strain behavior of calcareous sand is significantly influencedby particle breakage(B)and initial relative density(Dri),but few constitutive models consider their combined effects.To bridge this gap,we conducted a series of triaxial tests on calcareous sand with varying Dri and stress paths,examining particle breakage and critical state behavior.Key findingsinclude:(1)At a constant stress ratio(η),B follows a hyperbolic relationship with mean effective stress(p'),and for a given p',B increases proportionally withη;(2)The critical state line(CSL)moves downward with increasing Dri,whereas the critical state friction angle(φcs)decreases with increasing B.Based on these findings,we propose a unifiedbreakage evolution model to quantify particle breakage in calcareous sand under various loading conditions.Integrating this model with the Normal Consolidation Line(NCL)and CSL equations,we successfully simulate the steepening of NCL and CSL slopes as B increases with the onset of particle breakage.Furthermore,we quantitatively evaluate the effect of B onφcs.Finally,within the framework of Critical State Soil Mechanics and Hypoplasticity theory,we develop a hypoplastic model incorporating B and Dri.The model is validated through strong agreement with experimental results across various initial relative densities,stress paths and drainage conditions.展开更多
This study investigates the properties of high-purity starches extracted from Polygonum multiflorum(PMS)and Smilax glabra(SGS).The starches were characterized by scanning electron microscopy,Fouriertransform infrared ...This study investigates the properties of high-purity starches extracted from Polygonum multiflorum(PMS)and Smilax glabra(SGS).The starches were characterized by scanning electron microscopy,Fouriertransform infrared spectroscopy,X-ray diffraction,high-performance anion-exchange chromatography,and differential scanning calorimetry.Significant differences were observed in their morphological,physicochemical,and functional properties.PMS had a smaller particle size(13.68 μm),irregular polygonal shape,A-type,lower water absorption(62.67 %),and higher oil absorption(51.17 %).In contrast,SGS exhibited larger particles(31.75 μm),a nearly spherical shape,B-type,higher crystallinity(50.66 %),and greater amylose content(21.54 %),with superior thermal stability,shear resistance,and gelatinization enthalpy.SGS also contained higher resistant starch(83.28 %) and longer average chain length(20.58 %),but showed lower solubility,swelling power,light transmittance,and freeze-thaw stability.The physicochemical properties differences in crystal pattern and particle morphology between PMS and SGS lead to distinct behaviors during in vitro digestion and fermentation.These findings highlight the potential of medicinal plant starches in functional ingredients and industrial processes.展开更多
In this study,we perform particle-resolved simulations of settling spheroidal particles,considering oblate and prolate spheroids and spheres,and investigate the shape effect on the particle dynamics in suspensions wit...In this study,we perform particle-resolved simulations of settling spheroidal particles,considering oblate and prolate spheroids and spheres,and investigate the shape effect on the particle dynamics in suspensions with volume fraction 1%and 5%.We first examine the single-point statistics of the translational and rotational motion of the settling particles.The horizontal velocity has a symmetrical distribution with standard deviation dependent on the particle shape.The greater horizontal velocity fluctuations of the non-spherical particles,compared to that of spheres,are attributed to the horizontal drift of settling spheroids with oblique orientations induced by the fluid-particle and particle-particle interactions.The fluctuation of particle vertical velocity,instead,is skewed under the effect of wake-induced hydrodynamic interactions.Further,we explore the particle pair statistics,which demonstrate the formation of column-like particle micro-structures for the lowest volume fraction considered.This clustering is more pronounced for spheroidal particles than spheres,due to the stronger attractions among vertically-aligned settling spheroids.Moreover,the particle pair statistics are directly related to the collision rate among the dispersed particles.The local accumulation of oblate/prolate spheroids serves as the major mechanism to promote the particle-particle collisions in dilute suspensions.展开更多
Particle-and droplet-laden flows are central to many problems in mechanics and transport.They occur in sedimentladen boundary layers,gas-solid and gas-liquid dispersions,and surface-water films driven by external forc...Particle-and droplet-laden flows are central to many problems in mechanics and transport.They occur in sedimentladen boundary layers,gas-solid and gas-liquid dispersions,and surface-water films driven by external forcing.They also underpin practical applications ranging from environmental transport to high-speed and aerothermal systems.Despite decades of progress,prediction remains difficult.The physics spans a wide range of scales and often couples turbulence,interphase momentum exchange,collisions,and interfacial transport.Reliable computation therefore requires both robust numerical methodology and careful physical interpretation.展开更多
Multi-label feature selection(MFS)is a crucial dimensionality reduction technique aimed at identifying informative features associated with multiple labels.However,traditional centralized methods face significant chal...Multi-label feature selection(MFS)is a crucial dimensionality reduction technique aimed at identifying informative features associated with multiple labels.However,traditional centralized methods face significant challenges in privacy-sensitive and distributed settings,often neglecting label dependencies and suffering from low computational efficiency.To address these issues,we introduce a novel framework,Fed-MFSDHBCPSO—federated MFS via dual-layer hybrid breeding cooperative particle swarm optimization algorithm with manifold and sparsity regularization(DHBCPSO-MSR).Leveraging the federated learning paradigm,Fed-MFSDHBCPSO allows clients to perform local feature selection(FS)using DHBCPSO-MSR.Locally selected feature subsets are encrypted with differential privacy(DP)and transmitted to a central server,where they are securely aggregated and refined through secure multi-party computation(SMPC)until global convergence is achieved.Within each client,DHBCPSO-MSR employs a dual-layer FS strategy.The inner layer constructs sample and label similarity graphs,generates Laplacian matrices to capture the manifold structure between samples and labels,and applies L2,1-norm regularization to sparsify the feature subset,yielding an optimized feature weight matrix.The outer layer uses a hybrid breeding cooperative particle swarm optimization algorithm to further refine the feature weight matrix and identify the optimal feature subset.The updated weight matrix is then fed back to the inner layer for further optimization.Comprehensive experiments on multiple real-world multi-label datasets demonstrate that Fed-MFSDHBCPSO consistently outperforms both centralized and federated baseline methods across several key evaluation metrics.展开更多
During electrochemical machining(ECM),the passivation film formed on the surface of titanium alloy can lead to uneven dissolution and pitting.Solid particle erosion can effectively remove this passivation film.In this...During electrochemical machining(ECM),the passivation film formed on the surface of titanium alloy can lead to uneven dissolution and pitting.Solid particle erosion can effectively remove this passivation film.In this paper,the electrochemical dissolution behavior of Ti-6.5Al-2Zr-1Mo-1V(TA15)titanium alloy at without particle impact,low(15°)and high(90°)angle particle impact was investigated,and the influence of Al_(2)O_(3)particles on ECM was systematically expounded.It was found that under the condition of no particle erosion,the surface of electrochemically processed titanium alloy had serious pitting corrosion due to the influence of the passivation film,and the surface roughness(Sa)of the local area reached 10.088μm.Under the condition of a high-impact angle(90°),due to the existence of strain hardening and particle embedding,only the edge of the surface is dissolved,while the central area is almost insoluble,with the surface roughness(S_(a))reaching 16.086μm.On the contrary,under the condition of a low-impact angle(15°),the machining efficiency and surface quality of the material were significantly improved due to the ploughing effect and galvanic corrosion,and the surface roughness(S_(a))reached 2.823μm.Based on these findings,the electrochemical dissolution model of TA15 titanium alloy under different particle erosion conditions was established.展开更多
Ice lens initiation is the core issue in understanding the dynamic process of frost heave.However,there are still limitations to find an adequate criterion for describing the formation of ice lens.A series of one-dime...Ice lens initiation is the core issue in understanding the dynamic process of frost heave.However,there are still limitations to find an adequate criterion for describing the formation of ice lens.A series of one-dimensional freezing tests is designed using the particle image velocimetry(PIV)method to monitor the frost heave and ice lens formation.The results show that the conventional parameters,such as displacement and velocity,cannot be used to track the ice lens formation,while the strain can be employed to detect the ice lens formation and investigate the freezing change patterns.This study proposes strain as a new criterion for assessing ice lens initiation,applicable across various soil types and freezing conditions(constant freezing and ramped freezing).The strain change in the region where the ice lens forms is the largest during the freezing process.Additionally,strain curves at the top of the soil samples can reveal different freezing patterns and distinguish the first and second frost heave stages.This newly developed technology enables continuous,non-destructive monitoring of ice lens initiation across diverse conditions and soil types,enhancing data visualization and three-dimensional modeling of freezing parameters while improving traditional methods by directly measuring velocity and strain in frost heave investigations.The study is expected to enhance the research of ice lens criterion and provide a new perspective for monitoring the freezing process.展开更多
In this study,a fifth-degree cubature particle filter(5CPF)is proposed to address the limited estimation accuracy in traditional particle filter algorithms for bearings-only tracking(BOT).This algorithm calculates the...In this study,a fifth-degree cubature particle filter(5CPF)is proposed to address the limited estimation accuracy in traditional particle filter algorithms for bearings-only tracking(BOT).This algorithm calculates the recommended density function by introducing a fifth-degree cubature Kalman filter algorithm to guide particle sampling,which effectively alleviates the problem of particle degradation and significantly improves the estimation accuracy of the filter.However,the 5CPF algorithm exhibits high computational complexity,particularly in scenarios with a large number of particles.Therefore,we propose the extended Kalman filter(EKF)-5CPF algorithm,which employs an EKF to replace the time update step for each particle in the 5CPF.This enhances the algorithm’s real-time capability while maintaining the high precision advantage of the 5CPF algorithm.In addition,we construct bearing-only dual-station and single-motion station target tracking systems,and the filtering performances of 5CPF and EKF-5CPF algorithms under different conditions are analyzed.The results show that both the 5CPF algorithm and EKF-5CPF have strong robustness and can adapt to different noise environments.Furthermore,both algorithms significantly outperform traditional nonlinear filtering algorithms in terms of convergence speed,tracking accuracy,and overall stability.展开更多
Biocompatible amphiphilic nanoparticles(NPs)with tunable particle morphology and surface property are important for their applications as functional materials.However,previously developed methods to prepare amphiphili...Biocompatible amphiphilic nanoparticles(NPs)with tunable particle morphology and surface property are important for their applications as functional materials.However,previously developed methods to prepare amphiphilic NPs generally involve several steps,especially an additional step for surface modification,greatly hindering their largescale production and widespread applications.Here,a versatile one-step strategy is developed to prepare biocompatible amphiphilic dimer NPs with tunable particle morphology and surface property.The amphiphilic dimer NPs,which consist of a hydrophobic shellac bulb and a hydrophilic poly(lactic acid)(PLA)bulb with PLA-poly(ethylene glycol)(PEG)on the bulb surface,are prepared in a single step by controlled co-precipitation and self-assembly.Amphiphilic PLA-PEG/shellac dimer NPs demonstrate excellent tunability in particle morphology,thus showing good performances in controlling the interfacial curvature and emulsion type.In addition,temperatureresponsive PLA-poly(N-isopropyl acrylamide)(PNIPAM)/shellac dimer NPs are prepared following the same method and emulsions stabilized by them show temperature-triggered response.The applications of PLA-PEG-folic acid(FA)/shellac dimer NPs for drug delivery have also been demonstrated,which show a very good performance.The strategy of preparing the dimer NPs is green,scalable,facile and versatile,which provides a good platform for the design of dimer NPs with tunable particle morphology and surface property for diverse applications.展开更多
Accurately acquiring catalyst size and morphology is essential for supporting catalytic reaction process design and optimal control. We report an intelligent catalyst sizing and morphological classification method bas...Accurately acquiring catalyst size and morphology is essential for supporting catalytic reaction process design and optimal control. We report an intelligent catalyst sizing and morphological classification method based on the Mask-RCNN framework. A dataset of 9880 high-resolution images was captured by using a self-made fiber-optic endoscopic system for 13 kinds of silicoaluminophosphate-34 (SAPO-34) catalyst samples with different coke. Then there were approximately 877881 individual particles extracted from this dataset by our AI-based particle recognition algorithm. To clearly describe the morphology of irregular particles, we proposed a hybrid classification criterion that combines five different parameters, which are deformity, circularity, roundness, aspect ratio, and compactness. Therefore, catalyst morphology can be classified into two categories with four types. The first category includes regular types, such as the spherical, ellipsoidal, and rod-shaped types. And all the irregular types fall into the second category. The experimental results showed that a catalyst particle tends to be larger when its coke deposition increased. Whereas particle morphology remained primarily spherical and ellipsoidal, the ratio of each type varied slightly according to its coke. Our findings illustrate that this is a promising approach to be developing intelligent instruments for catalyst particle sizing and classification.展开更多
Brake wear particle(BWP)emissions are considered one of the dominant sources of particulate matter pollution in urban environments.BWP emissions have increased significantly under high-temperature conditions,emerging ...Brake wear particle(BWP)emissions are considered one of the dominant sources of particulate matter pollution in urban environments.BWP emissions have increased significantly under high-temperature conditions,emerging as a focal point of research interest.This study investigates the effect of brake temperatures on BWP emissions.The brake pad materials undergo violent decomposition and oxidation reactions and generate large amounts of incompletely oxidized organic products at temperatures above 475℃.These organic products cause particles below 200 nm to proliferate,and nanoparticles below 40 nm account for the largest contribution of total BWPs.When the friction surface temperature exceeds 475℃,the high-concentration BWPs below 200 nm will agglomerate into larger particles.High temperatures also cause the brake pad surface to delaminate and fragment into particles above 2.5μm.In addition,when the initial brake speed is above 160 km/h,or the brake pressure is above 7 bar,there is a sharp increase in particles below 200 nm.The results suggest that a significant number of nanoparticles below 40 nm are inferred to be generated as the flash temperature of the friction surface reaches the violent reaction temperature.This study provides guidelines for designing low-emission brake pads,as improving the high-temperature resistance of brake pad material components possibly reduces BWP generation.展开更多
In the field of discretization-based meshfree/meshless methods,the improvements in the higher-order consistency,stability,and computational efficiency are of great concerns in computational science and numerical solut...In the field of discretization-based meshfree/meshless methods,the improvements in the higher-order consistency,stability,and computational efficiency are of great concerns in computational science and numerical solutions to partial differential equations.Various alternative numerical methods of the finite particle method(FPM)frame have been extended from mathematical theories to numerical applications separately.As a comprehensive numerical scheme,this study suggests a unified resolved program for numerically investigating their accuracy,stability,consistency,computational efficiency,and practical applicability in industrial engineering contexts.The high-order finite particle method(HFPM)and corrected methods based on the multivariate Taylor series expansion are constructed and analyzed to investigate the whole applicability in different benchmarks of computational fluid dynamics.Specifically,four benchmarks are designed purposefully from statical exact solutions to multifaceted hydrodynamic tests,which possess different numerical performances on the particle consistency,numerical discretized forms,particle distributions,and transient time evolutional stabilities.This study offers a numerical reference for the current unified resolved program.展开更多
1. Introduction High-speed gas-particle flows are crucial in engineering applications and natural phenomena, such as volcanic eruptions,combustion, and hypersonic flight. These flows involve complex gas-particle inter...1. Introduction High-speed gas-particle flows are crucial in engineering applications and natural phenomena, such as volcanic eruptions,combustion, and hypersonic flight. These flows involve complex gas-particle interactions, posing significant challenges for simulations and experiments. This research highlight summarizes recent advancements in gas-particle dynamics under compressible conditions, covering key findings, numerical and experimental progress, and future directions. Details can be found in the work of Capecelatro and Wagner (Gas-particle dynamics in high-speed flows. Annual Review of Fluid Mechanics 2024;56:379–403).展开更多
Particle settling in narrow rough fractures is a common but poorly understood phenomenon during hydraulic fracturing.This study first constructs a large slot with two rough surfaces to simulate rock fractures and empl...Particle settling in narrow rough fractures is a common but poorly understood phenomenon during hydraulic fracturing.This study first constructs a large slot with two rough surfaces to simulate rock fractures and employs the particle image velocimetry to measure particle settling.Results show that particle settling in the rough slot is more complex than in the smooth slot.Rough pathways significantly change particle settling characteristics.The rough-walled slot alters the classic settling process by creating preferential pathways,localized trapping,and vortex-driven redistribution.Particles settle along preferential pathways,increasing settling velocity.The wall retardation effect becomes more prominent for large particles,reducing the settling velocity.Particle settling induces vortices throughout the rough surface,affecting particle behavior.Higher particle volume fractions increase settling nonuniformity,leading to unstable fluid flow within fractures,characterized by high vorticity and upward flow.The frequent interplay between particles and particle-walls,and fluid resistance complicates particle trajectories and settling behavior.Fluid viscosity significantly changes settling patterns and promotes particle clusters,forming chain-like and curtain-like clusters in rough fractures.An innovative model is proposed to predict settling velocity in rough fractures.展开更多
Accurately forecasting peak particle velocity(PPV)during blasting operations plays a crucial role in mitigating vibration-related hazards and preventing economic losses.This research introduces an approach to PPV pred...Accurately forecasting peak particle velocity(PPV)during blasting operations plays a crucial role in mitigating vibration-related hazards and preventing economic losses.This research introduces an approach to PPV prediction by combining conventional empirical equations with physics-informed neural networks(PINN)and optimizing the model parameters via the Particle Swarm Optimization(PSO)algorithm.The proposed PSO-PINN framework was rigorously benchmarked against seven established machine learning approaches:Multilayer Perceptron(MLP),Extreme Gradient Boosting(XGBoost),Random Forest(RF),Support Vector Regression(SVR),Gradient Boosting Decision Tree(GBDT),Adaptive Boosting(Adaboost),and Gene Expression Programming(GEP).Comparative analysis showed that PSO-PINN outperformed these models,achieving RMSE reductions of 17.82-37.63%,MSE reductions of 32.47-61.10%,AR improvements of 2.97-21.19%,and R^(2)enhancements of 7.43-29.21%,demonstrating superior accuracy and generalization.Furthermore,the study determines the impact of incorporating empirical formulas as physical constraints in neural networks and examines the effects of different empirical equations,particle swarm size,iteration count in PSO,regularization coefficient,and learning rate in PINN on model performance.Lastly,a predictive system for blast vibration PPV is designed and implemented.The research outcomes offer theoretical references and practical recommendations for blast vibration forecasting in similar engineering applications.展开更多
Particle morphology is critical in affecting the crushing behavior of rockfill materials.In contrast,most current single particle simulations lack satisfactory morphology accuracy,and the resulting crushing modes devi...Particle morphology is critical in affecting the crushing behavior of rockfill materials.In contrast,most current single particle simulations lack satisfactory morphology accuracy,and the resulting crushing modes deviate from observations to some extent.Therefore,we reconstruct the real particle morphology with the spherical harmonic(SH)method and employ the finite-discrete element method(FDEM)to simulate the one-dimensional(1D)compressive crushing process of basalt particles commonly used in rockfill.The influences of four main morphological parameters,i.e.sphericity,aspect ratio,roundness,and convexity,on the single particle strength and the crushing modes are discussed.The results show that with the SH degree set to 15 and a mesh number of 20,480,the FDEM models of reconstructed particles achieve sufficient morphology accuracy and high computational efficiency.Based on the model,the simulation results demonstrate that the aspect ratio has the most significant impact on single particle strength,followed by sphericity.In contrast,roundness and convexity have a weaker effect than the above two parameters.Also,it is revealed that single particle strength decreases with increasing aspect ratio and sphericity,while it increases with higher roundness and convexity.Furthermore,aspect ratio significantly changes the initial crushing position,sphericity dominates post-crushing fragment size and quantity,and roundness mainly affects post-crushing morphology.The model results have been employed in establishing a support vector regression(SVR)-based predicted model,exhibiting good predictive performance and advantages for the optimization of rockfill particles in engineering.展开更多
基金supported by the P.G.Senapathy Center for Computing Resources at IIT Madrasfunding provided by the Ministry of Education,Government of Indiasupported by the National Natural Science Foundation of China(Grant Nos.12388101,12472224 and 92252104).
文摘This paper presents an Eulerian-Lagrangian algorithm for direct numerical simulation(DNS)of particle-laden flows.The algorithm is applicable to perform simulations of dilute suspensions of small inertial particles in turbulent carrier flow.The Eulerian framework numerically resolves turbulent carrier flow using a parallelized,finite-volume DNS solver on a staggered Cartesian grid.Particles are tracked using a point-particle method utilizing a Lagrangian particle tracking(LPT)algorithm.The proposed Eulerian-Lagrangian algorithm is validated using an inertial particle-laden turbulent channel flow for different Stokes number cases.The particle concentration profiles and higher-order statistics of the carrier and dispersed phases agree well with the benchmark results.We investigated the effect of fluid velocity interpolation and numerical integration schemes of particle tracking algorithms on particle dispersion statistics.The suitability of fluid velocity interpolation schemes for predicting the particle dispersion statistics is discussed in the framework of the particle tracking algorithm coupled to the finite-volume solver.In addition,we present parallelization strategies implemented in the algorithm and evaluate their parallel performance.
基金This work used Expanse systems at UCSD through an allocation[PHY240089]from the Advanced Cyberinfrastructure Coordination Ecosystem:Services&Support(ACCESS)programsupported by U.S.National Science Foundation(Grant Nos.2138259,2138286,2138307,2137603 and 2138296).
文摘We present a numerical framework for simulating viscous compressible flows in the presence of solid particles with large size ratios.The volume-filtered Navier-Stokes equations are discretized using a class of high-order low-dissipative finite difference operators with energy-preserving properties.No-slip,adiabatic boundary conditions are enforced at the surface of large particles(with diameters significantly larger than the local grid spacing)using a ghost-point immersed boundary method.Two-way coupling between the gas phase and small particles(with diameters proportional to the grid spacing)is accounted for through volumetric source terms for interphase momentum and energy exchange.A simple and efficient approach for collision detection between small and large particles is proposed.The framework is applied to simulations of planar shocks interacting with bidisperse distributions of particles with size ratios of approximately thirty.Particle dispersion and size segregation are reported and a simple analytical model for size segregation is proposed.
文摘Aiming to solve the steering instability and hysteresis of agricultural robots in the process of movement,a fusion PID control method of particle swarm optimization(PSO)and genetic algorithm(GA)was proposed.The fusion algorithm took advantage of the fast optimization ability of PSO to optimize the population screening link of GA.The Simulink simulation results showed that the convergence of the fitness function of the fusion algorithm was accelerated,the system response adjustment time was reduced,and the overshoot was almost zero.Then the algorithm was applied to the steering test of agricultural robot in various scenes.After modeling the steering system of agricultural robot,the steering test results in the unloaded suspended state showed that the PID control based on fusion algorithm reduced the rise time,response adjustment time and overshoot of the system,and improved the response speed and stability of the system,compared with the artificial trial and error PID control and the PID control based on GA.The actual road steering test results showed that the PID control response rise time based on the fusion algorithm was the shortest,about 4.43 s.When the target pulse number was set to 100,the actual mean value in the steady-state regulation stage was about 102.9,which was the closest to the target value among the three control methods,and the overshoot was reduced at the same time.The steering test results under various scene states showed that the PID control based on the proposed fusion algorithm had good anti-interference ability,it can adapt to the changes of environment and load and improve the performance of the control system.It was effective in the steering control of agricultural robot.This method can provide a reference for the precise steering control of other robots.
基金support by the National Natural Science Foundation of China(NSFC)(Grant Nos.52178319,42477160,52338007).
文摘Bacterial cells are widely accepted as nucleation sites for calcium carbonate precipitation in biomineralization based on the Microbially Induced Carbonate Precipitation(MICP)process.For MICP-based insitu biotreatment,the firstproblem to be solved is how to introduce and retain the bacterial cells in the soil,which involves the migration and retention of bacterial cells during the biogrouting process.Soil particle size,a key factor in determining pore throat size,can have a significanteffect on the migration and retention of bacterial cells in the soil and therefore on biomineralization.To investigate the effect of particle size on the migration and retention of bacterial cells in sand and its biomineralization,two sets of tests were carried out in this study,including percolation tests and sand column treatment tests.Soil urease activity(definedas urease activity per unit mass of soil)and calcium carbonate content of the biomineralized sand were measured to comprehensively assess the migration and retention of bacterial cells in the sand.The results indicate that sands with a particle size smaller than 0.25 mmwould inhibit the migration of bacteria in the sand,resulting in a nonuniform distribution of precipitated calcium carbonate and a low strength enhancement of biomineralization.On the other hand,sands with a particle size larger than 1.18 mm are unfavorable for retaining bacterial cells in the sand,resulting in low calcium conversion efficiency.Meanwhile,particle size would also affect the formation of effective calcium carbonate through interparticle contact number and interparticle pore size,and thus biomineralization.
基金support to this study from the National Natural Science Foundation of China,NSFC(Grant No.52278367)The Belt and Road Special Foundation of the National Key Laboratory ofWater Disaster Prevention(Grant No.2024nkms08).
文摘The stress-strain behavior of calcareous sand is significantly influencedby particle breakage(B)and initial relative density(Dri),but few constitutive models consider their combined effects.To bridge this gap,we conducted a series of triaxial tests on calcareous sand with varying Dri and stress paths,examining particle breakage and critical state behavior.Key findingsinclude:(1)At a constant stress ratio(η),B follows a hyperbolic relationship with mean effective stress(p'),and for a given p',B increases proportionally withη;(2)The critical state line(CSL)moves downward with increasing Dri,whereas the critical state friction angle(φcs)decreases with increasing B.Based on these findings,we propose a unifiedbreakage evolution model to quantify particle breakage in calcareous sand under various loading conditions.Integrating this model with the Normal Consolidation Line(NCL)and CSL equations,we successfully simulate the steepening of NCL and CSL slopes as B increases with the onset of particle breakage.Furthermore,we quantitatively evaluate the effect of B onφcs.Finally,within the framework of Critical State Soil Mechanics and Hypoplasticity theory,we develop a hypoplastic model incorporating B and Dri.The model is validated through strong agreement with experimental results across various initial relative densities,stress paths and drainage conditions.
基金supported by the National Natural Science Foundation of China (No.82174074)。
文摘This study investigates the properties of high-purity starches extracted from Polygonum multiflorum(PMS)and Smilax glabra(SGS).The starches were characterized by scanning electron microscopy,Fouriertransform infrared spectroscopy,X-ray diffraction,high-performance anion-exchange chromatography,and differential scanning calorimetry.Significant differences were observed in their morphological,physicochemical,and functional properties.PMS had a smaller particle size(13.68 μm),irregular polygonal shape,A-type,lower water absorption(62.67 %),and higher oil absorption(51.17 %).In contrast,SGS exhibited larger particles(31.75 μm),a nearly spherical shape,B-type,higher crystallinity(50.66 %),and greater amylose content(21.54 %),with superior thermal stability,shear resistance,and gelatinization enthalpy.SGS also contained higher resistant starch(83.28 %) and longer average chain length(20.58 %),but showed lower solubility,swelling power,light transmittance,and freeze-thaw stability.The physicochemical properties differences in crystal pattern and particle morphology between PMS and SGS lead to distinct behaviors during in vitro digestion and fermentation.These findings highlight the potential of medicinal plant starches in functional ingredients and industrial processes.
基金supported by the National Natural Science Foundation of China(Grant Nos.92252104,12388101,and 12472224).
文摘In this study,we perform particle-resolved simulations of settling spheroidal particles,considering oblate and prolate spheroids and spheres,and investigate the shape effect on the particle dynamics in suspensions with volume fraction 1%and 5%.We first examine the single-point statistics of the translational and rotational motion of the settling particles.The horizontal velocity has a symmetrical distribution with standard deviation dependent on the particle shape.The greater horizontal velocity fluctuations of the non-spherical particles,compared to that of spheres,are attributed to the horizontal drift of settling spheroids with oblique orientations induced by the fluid-particle and particle-particle interactions.The fluctuation of particle vertical velocity,instead,is skewed under the effect of wake-induced hydrodynamic interactions.Further,we explore the particle pair statistics,which demonstrate the formation of column-like particle micro-structures for the lowest volume fraction considered.This clustering is more pronounced for spheroidal particles than spheres,due to the stronger attractions among vertically-aligned settling spheroids.Moreover,the particle pair statistics are directly related to the collision rate among the dispersed particles.The local accumulation of oblate/prolate spheroids serves as the major mechanism to promote the particle-particle collisions in dilute suspensions.
文摘Particle-and droplet-laden flows are central to many problems in mechanics and transport.They occur in sedimentladen boundary layers,gas-solid and gas-liquid dispersions,and surface-water films driven by external forcing.They also underpin practical applications ranging from environmental transport to high-speed and aerothermal systems.Despite decades of progress,prediction remains difficult.The physics spans a wide range of scales and often couples turbulence,interphase momentum exchange,collisions,and interfacial transport.Reliable computation therefore requires both robust numerical methodology and careful physical interpretation.
文摘Multi-label feature selection(MFS)is a crucial dimensionality reduction technique aimed at identifying informative features associated with multiple labels.However,traditional centralized methods face significant challenges in privacy-sensitive and distributed settings,often neglecting label dependencies and suffering from low computational efficiency.To address these issues,we introduce a novel framework,Fed-MFSDHBCPSO—federated MFS via dual-layer hybrid breeding cooperative particle swarm optimization algorithm with manifold and sparsity regularization(DHBCPSO-MSR).Leveraging the federated learning paradigm,Fed-MFSDHBCPSO allows clients to perform local feature selection(FS)using DHBCPSO-MSR.Locally selected feature subsets are encrypted with differential privacy(DP)and transmitted to a central server,where they are securely aggregated and refined through secure multi-party computation(SMPC)until global convergence is achieved.Within each client,DHBCPSO-MSR employs a dual-layer FS strategy.The inner layer constructs sample and label similarity graphs,generates Laplacian matrices to capture the manifold structure between samples and labels,and applies L2,1-norm regularization to sparsify the feature subset,yielding an optimized feature weight matrix.The outer layer uses a hybrid breeding cooperative particle swarm optimization algorithm to further refine the feature weight matrix and identify the optimal feature subset.The updated weight matrix is then fed back to the inner layer for further optimization.Comprehensive experiments on multiple real-world multi-label datasets demonstrate that Fed-MFSDHBCPSO consistently outperforms both centralized and federated baseline methods across several key evaluation metrics.
基金supported by the National Natural Science Foundation of China(No.52175414)the Natural Science Foundation of Jiangsu Province of China(No.BK20220134)+1 种基金the Fundamental Research Funds for the Central Universities,China(No.NE2023002)the Postgraduate Research&Practice Innovation Program of Jiangsu Province,China(No.KYCX24_0559)。
文摘During electrochemical machining(ECM),the passivation film formed on the surface of titanium alloy can lead to uneven dissolution and pitting.Solid particle erosion can effectively remove this passivation film.In this paper,the electrochemical dissolution behavior of Ti-6.5Al-2Zr-1Mo-1V(TA15)titanium alloy at without particle impact,low(15°)and high(90°)angle particle impact was investigated,and the influence of Al_(2)O_(3)particles on ECM was systematically expounded.It was found that under the condition of no particle erosion,the surface of electrochemically processed titanium alloy had serious pitting corrosion due to the influence of the passivation film,and the surface roughness(Sa)of the local area reached 10.088μm.Under the condition of a high-impact angle(90°),due to the existence of strain hardening and particle embedding,only the edge of the surface is dissolved,while the central area is almost insoluble,with the surface roughness(S_(a))reaching 16.086μm.On the contrary,under the condition of a low-impact angle(15°),the machining efficiency and surface quality of the material were significantly improved due to the ploughing effect and galvanic corrosion,and the surface roughness(S_(a))reached 2.823μm.Based on these findings,the electrochemical dissolution model of TA15 titanium alloy under different particle erosion conditions was established.
基金supported by the National Natural Science Foundation of China(Grant No.52178376)National Key R&D Program of China(Grant No.2022YFB2603301)Science and Technology Research and Development Program of China Railway Group Limited(Grant No.2022-ZD-13).
文摘Ice lens initiation is the core issue in understanding the dynamic process of frost heave.However,there are still limitations to find an adequate criterion for describing the formation of ice lens.A series of one-dimensional freezing tests is designed using the particle image velocimetry(PIV)method to monitor the frost heave and ice lens formation.The results show that the conventional parameters,such as displacement and velocity,cannot be used to track the ice lens formation,while the strain can be employed to detect the ice lens formation and investigate the freezing change patterns.This study proposes strain as a new criterion for assessing ice lens initiation,applicable across various soil types and freezing conditions(constant freezing and ramped freezing).The strain change in the region where the ice lens forms is the largest during the freezing process.Additionally,strain curves at the top of the soil samples can reveal different freezing patterns and distinguish the first and second frost heave stages.This newly developed technology enables continuous,non-destructive monitoring of ice lens initiation across diverse conditions and soil types,enhancing data visualization and three-dimensional modeling of freezing parameters while improving traditional methods by directly measuring velocity and strain in frost heave investigations.The study is expected to enhance the research of ice lens criterion and provide a new perspective for monitoring the freezing process.
基金Supported by the Guangxi Special Program for Technological Innovation Guidance(No.GuiKeAC25069006).
文摘In this study,a fifth-degree cubature particle filter(5CPF)is proposed to address the limited estimation accuracy in traditional particle filter algorithms for bearings-only tracking(BOT).This algorithm calculates the recommended density function by introducing a fifth-degree cubature Kalman filter algorithm to guide particle sampling,which effectively alleviates the problem of particle degradation and significantly improves the estimation accuracy of the filter.However,the 5CPF algorithm exhibits high computational complexity,particularly in scenarios with a large number of particles.Therefore,we propose the extended Kalman filter(EKF)-5CPF algorithm,which employs an EKF to replace the time update step for each particle in the 5CPF.This enhances the algorithm’s real-time capability while maintaining the high precision advantage of the 5CPF algorithm.In addition,we construct bearing-only dual-station and single-motion station target tracking systems,and the filtering performances of 5CPF and EKF-5CPF algorithms under different conditions are analyzed.The results show that both the 5CPF algorithm and EKF-5CPF have strong robustness and can adapt to different noise environments.Furthermore,both algorithms significantly outperform traditional nonlinear filtering algorithms in terms of convergence speed,tracking accuracy,and overall stability.
基金supported by National Natural Science Foundation of China(No.22278352)National Key Research and Development Program of China(No.2021YFC3001100)+3 种基金Longyan City Science and Technology Plan Project(No.2020LYF17043)Longyan City Science and Technology Plan Project(No.2020LYF17042)ARC Discovery Project(No.DP200101238)and NHMRC Investigator Grant(No.APP2008698)supported by the Harvard Materials Research Science and Engineering Center(No.DMR2011754)。
文摘Biocompatible amphiphilic nanoparticles(NPs)with tunable particle morphology and surface property are important for their applications as functional materials.However,previously developed methods to prepare amphiphilic NPs generally involve several steps,especially an additional step for surface modification,greatly hindering their largescale production and widespread applications.Here,a versatile one-step strategy is developed to prepare biocompatible amphiphilic dimer NPs with tunable particle morphology and surface property.The amphiphilic dimer NPs,which consist of a hydrophobic shellac bulb and a hydrophilic poly(lactic acid)(PLA)bulb with PLA-poly(ethylene glycol)(PEG)on the bulb surface,are prepared in a single step by controlled co-precipitation and self-assembly.Amphiphilic PLA-PEG/shellac dimer NPs demonstrate excellent tunability in particle morphology,thus showing good performances in controlling the interfacial curvature and emulsion type.In addition,temperatureresponsive PLA-poly(N-isopropyl acrylamide)(PNIPAM)/shellac dimer NPs are prepared following the same method and emulsions stabilized by them show temperature-triggered response.The applications of PLA-PEG-folic acid(FA)/shellac dimer NPs for drug delivery have also been demonstrated,which show a very good performance.The strategy of preparing the dimer NPs is green,scalable,facile and versatile,which provides a good platform for the design of dimer NPs with tunable particle morphology and surface property for diverse applications.
基金supported by the National Natural Science Foundation of China(22308348)the Natural Science Foundation of Liaoning Province of China(2024-MSBA-65)+1 种基金the Qin Chuangyuan Project for Introducing High-Level Innovative and Entrepreneurial Talents(QCYRCXM-2023-024)the Energy Revolution S&T Program of Yulin Innovation Institute of Clean Energy(E201041206).
文摘Accurately acquiring catalyst size and morphology is essential for supporting catalytic reaction process design and optimal control. We report an intelligent catalyst sizing and morphological classification method based on the Mask-RCNN framework. A dataset of 9880 high-resolution images was captured by using a self-made fiber-optic endoscopic system for 13 kinds of silicoaluminophosphate-34 (SAPO-34) catalyst samples with different coke. Then there were approximately 877881 individual particles extracted from this dataset by our AI-based particle recognition algorithm. To clearly describe the morphology of irregular particles, we proposed a hybrid classification criterion that combines five different parameters, which are deformity, circularity, roundness, aspect ratio, and compactness. Therefore, catalyst morphology can be classified into two categories with four types. The first category includes regular types, such as the spherical, ellipsoidal, and rod-shaped types. And all the irregular types fall into the second category. The experimental results showed that a catalyst particle tends to be larger when its coke deposition increased. Whereas particle morphology remained primarily spherical and ellipsoidal, the ratio of each type varied slightly according to its coke. Our findings illustrate that this is a promising approach to be developing intelligent instruments for catalyst particle sizing and classification.
基金supported by the National Natural Science Foundation of China(Nos.52172337 and 52272342)the Postdoctoral Fellowship Program(Grade B)of China Postdoctoral Science Foundation(No.GZB20240352)the Shuimu Tsinghua Scholar Program of Tsinghua University(No.2023SM230)。
文摘Brake wear particle(BWP)emissions are considered one of the dominant sources of particulate matter pollution in urban environments.BWP emissions have increased significantly under high-temperature conditions,emerging as a focal point of research interest.This study investigates the effect of brake temperatures on BWP emissions.The brake pad materials undergo violent decomposition and oxidation reactions and generate large amounts of incompletely oxidized organic products at temperatures above 475℃.These organic products cause particles below 200 nm to proliferate,and nanoparticles below 40 nm account for the largest contribution of total BWPs.When the friction surface temperature exceeds 475℃,the high-concentration BWPs below 200 nm will agglomerate into larger particles.High temperatures also cause the brake pad surface to delaminate and fragment into particles above 2.5μm.In addition,when the initial brake speed is above 160 km/h,or the brake pressure is above 7 bar,there is a sharp increase in particles below 200 nm.The results suggest that a significant number of nanoparticles below 40 nm are inferred to be generated as the flash temperature of the friction surface reaches the violent reaction temperature.This study provides guidelines for designing low-emission brake pads,as improving the high-temperature resistance of brake pad material components possibly reduces BWP generation.
基金supported by the National Natural Science Foundation of China(No.12002290)。
文摘In the field of discretization-based meshfree/meshless methods,the improvements in the higher-order consistency,stability,and computational efficiency are of great concerns in computational science and numerical solutions to partial differential equations.Various alternative numerical methods of the finite particle method(FPM)frame have been extended from mathematical theories to numerical applications separately.As a comprehensive numerical scheme,this study suggests a unified resolved program for numerically investigating their accuracy,stability,consistency,computational efficiency,and practical applicability in industrial engineering contexts.The high-order finite particle method(HFPM)and corrected methods based on the multivariate Taylor series expansion are constructed and analyzed to investigate the whole applicability in different benchmarks of computational fluid dynamics.Specifically,four benchmarks are designed purposefully from statical exact solutions to multifaceted hydrodynamic tests,which possess different numerical performances on the particle consistency,numerical discretized forms,particle distributions,and transient time evolutional stabilities.This study offers a numerical reference for the current unified resolved program.
文摘1. Introduction High-speed gas-particle flows are crucial in engineering applications and natural phenomena, such as volcanic eruptions,combustion, and hypersonic flight. These flows involve complex gas-particle interactions, posing significant challenges for simulations and experiments. This research highlight summarizes recent advancements in gas-particle dynamics under compressible conditions, covering key findings, numerical and experimental progress, and future directions. Details can be found in the work of Capecelatro and Wagner (Gas-particle dynamics in high-speed flows. Annual Review of Fluid Mechanics 2024;56:379–403).
基金supported by the National Natural Science Foundation of China(Grant No.52274035)。
文摘Particle settling in narrow rough fractures is a common but poorly understood phenomenon during hydraulic fracturing.This study first constructs a large slot with two rough surfaces to simulate rock fractures and employs the particle image velocimetry to measure particle settling.Results show that particle settling in the rough slot is more complex than in the smooth slot.Rough pathways significantly change particle settling characteristics.The rough-walled slot alters the classic settling process by creating preferential pathways,localized trapping,and vortex-driven redistribution.Particles settle along preferential pathways,increasing settling velocity.The wall retardation effect becomes more prominent for large particles,reducing the settling velocity.Particle settling induces vortices throughout the rough surface,affecting particle behavior.Higher particle volume fractions increase settling nonuniformity,leading to unstable fluid flow within fractures,characterized by high vorticity and upward flow.The frequent interplay between particles and particle-walls,and fluid resistance complicates particle trajectories and settling behavior.Fluid viscosity significantly changes settling patterns and promotes particle clusters,forming chain-like and curtain-like clusters in rough fractures.An innovative model is proposed to predict settling velocity in rough fractures.
基金supported by the National Natural Science Foundation of China(Grant No.52409143)the Basic Scientific Research Fund of Changjiang River Scientific Research Institute for Central-level Public Welfare Research Institutes(Grant No.CKSF2025184/YT)the Hubei Provincial Natural Science Foundation of China(Grant No.2022CFB673).
文摘Accurately forecasting peak particle velocity(PPV)during blasting operations plays a crucial role in mitigating vibration-related hazards and preventing economic losses.This research introduces an approach to PPV prediction by combining conventional empirical equations with physics-informed neural networks(PINN)and optimizing the model parameters via the Particle Swarm Optimization(PSO)algorithm.The proposed PSO-PINN framework was rigorously benchmarked against seven established machine learning approaches:Multilayer Perceptron(MLP),Extreme Gradient Boosting(XGBoost),Random Forest(RF),Support Vector Regression(SVR),Gradient Boosting Decision Tree(GBDT),Adaptive Boosting(Adaboost),and Gene Expression Programming(GEP).Comparative analysis showed that PSO-PINN outperformed these models,achieving RMSE reductions of 17.82-37.63%,MSE reductions of 32.47-61.10%,AR improvements of 2.97-21.19%,and R^(2)enhancements of 7.43-29.21%,demonstrating superior accuracy and generalization.Furthermore,the study determines the impact of incorporating empirical formulas as physical constraints in neural networks and examines the effects of different empirical equations,particle swarm size,iteration count in PSO,regularization coefficient,and learning rate in PINN on model performance.Lastly,a predictive system for blast vibration PPV is designed and implemented.The research outcomes offer theoretical references and practical recommendations for blast vibration forecasting in similar engineering applications.
基金financial support to this study from the National Natural Science Foundation of China,NSFC(Grant No.52278367).
文摘Particle morphology is critical in affecting the crushing behavior of rockfill materials.In contrast,most current single particle simulations lack satisfactory morphology accuracy,and the resulting crushing modes deviate from observations to some extent.Therefore,we reconstruct the real particle morphology with the spherical harmonic(SH)method and employ the finite-discrete element method(FDEM)to simulate the one-dimensional(1D)compressive crushing process of basalt particles commonly used in rockfill.The influences of four main morphological parameters,i.e.sphericity,aspect ratio,roundness,and convexity,on the single particle strength and the crushing modes are discussed.The results show that with the SH degree set to 15 and a mesh number of 20,480,the FDEM models of reconstructed particles achieve sufficient morphology accuracy and high computational efficiency.Based on the model,the simulation results demonstrate that the aspect ratio has the most significant impact on single particle strength,followed by sphericity.In contrast,roundness and convexity have a weaker effect than the above two parameters.Also,it is revealed that single particle strength decreases with increasing aspect ratio and sphericity,while it increases with higher roundness and convexity.Furthermore,aspect ratio significantly changes the initial crushing position,sphericity dominates post-crushing fragment size and quantity,and roundness mainly affects post-crushing morphology.The model results have been employed in establishing a support vector regression(SVR)-based predicted model,exhibiting good predictive performance and advantages for the optimization of rockfill particles in engineering.
