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
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
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
Recent advances in artificial intelligence(AI)have led to the development of sophisticated algorithms that significantly improve image analysis capabilities.This combination of AI and microscopic imaging is transformi...Recent advances in artificial intelligence(AI)have led to the development of sophisticated algorithms that significantly improve image analysis capabilities.This combination of AI and microscopic imaging is transforming the way we interpret and analyze imaging data,simplifying complex tasks and enabling innovative experimental methods previously thought impossible.In smart manufacturing,these improvements are especially impactful,increasing precision and efficiency in production processes.This review examines the convergence of AI with particle image analysis,an area we refer to as“particle vision analysis(PVA).”We offer a detailed overview of how this technology integrates into and impacts various fields within the physical sciences and materials sectors,where it plays a crucial role in both innovation and operational improvements.We explore four key areas of advancement-namely,particle classification,detection,segmentation,and object tracking-along with a look into the emerging field of augmented microscopy.This paper also underscores the vital role of the existing datasets and implementations that support these applications,which provide essential insights and resources that drive continuous research and development in this fast-evolving field.Our thorough analysis aims to outline the transformative potential of AI-driven PVA in improving precision in future manufacturing at the microscopic scale and thereby preparing the ground for significant technological progress and broad industrial applications in nanomanufacturing,biomanufacturing,and pharmaceutical manufacturing.This exploration not only highlights the advantages of integrating AI into conventional manufacturing processes but also anticipates the rise of next-generation smart manufacturing,which is set to revolutionize industry standards and operational practices.展开更多
The stability of oil-dominated emulsions,including oil-based drilling fluids and crude oils,is crucial for mitigating gas hydrate risks in the petroleum and natural gas industries.Nanoparticles can stabilize oilwater ...The stability of oil-dominated emulsions,including oil-based drilling fluids and crude oils,is crucial for mitigating gas hydrate risks in the petroleum and natural gas industries.Nanoparticles can stabilize oilwater systems(Pickering emulsions)by residing at the oil-water interface.However,their effects on the kinetics of hydrate formation in these systems remain unclear.To address this,we experimentally investigated how hydrophilic and hydrophobic nano-CaCO_(3) influence CH4 hydrate formation within dynamic oil-water systems.A series of hydrate formation experiments were conducted with varying water cuts and different concentrations of nano-CaCO_(3) at a particle size of 20 nm,under 3℃ and 6 MPa.The induction time,hydrate formation volume,and hydrate growth rate were measured and calculated.The results indicate that hydrophilic nano-CaCO_(3) generally inhibits hydrate formation,particularly at high water cuts,while hydrophobic nano-CaCO_(3) can significantly inhibit or even prevent hydrate formation at low water cuts.Water cut strongly influences the kinetics of hydrate formation,and nanoparticle concentration also impacts the results,likely due to changes in oil-water interface stability caused by nanoparticle distribution.This study will offer valuable insights for designing deepwater oilbased drilling fluids using nanoparticles and ensuring safe multiphase flow in deepwater oil and gas operations.展开更多
In this study,an artificial intelligence-based machine vision system was developed for in-line particle size analysis during the pellet layering process.Drug-layered pellets were produced by coating microcrystalline c...In this study,an artificial intelligence-based machine vision system was developed for in-line particle size analysis during the pellet layering process.Drug-layered pellets were produced by coating microcrystalline cellulose cores with an ibuprofen-containing layering liquid until the target drug content was achieved.Drug content increases with pellet size;therefore,particle size monitoring can ensure product safety and quality.The direct imaging system,consisting of a rigid endoscope,a light source,and a high-speed camera,provides real-time information about pellet size and layer uniformity,enabling timely intervention in the case of out-of-spec products.A convolutional neural network-based instance segmentation algorithm was employed to detect particles in focus,ensuring that pellet size could be accurately determined despite the dense flow of the particles.After training the model,the performance of the developed system was assessed by analysing the particle size distribution of pellet cores with variable sizes within the 250 e850 mm size range.The endoscopic system was tested in-line at a larger scale during the drug layering of inert pellet cores.The particle size data acquired in real time with the endoscopic imaging system corresponded with the reference methods,demonstrating the feasibility of the proposed machine vision-based method as a process analytical technology tool for in-line process monitoring.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
Stereoscopic particle image velocimetry technology was employed to investigate the planar three-dimensional velocity field and the process of proppant entry into branch fractures in a fracture configuration of“vertic...Stereoscopic particle image velocimetry technology was employed to investigate the planar three-dimensional velocity field and the process of proppant entry into branch fractures in a fracture configuration of“vertical main fracture-vertical branch fracture”intersecting at a 90°angle.This study analyzed the effects of pumping rate,fracturing fluid viscosity,proppant particle size,and fracture width on the transport behavior of proppant into branch fractures.Based on the deflection behavior of proppant,the main fractures can be divided into five regions:pre-entry transition,pre-entry stabilization,deflection entry at the fracture mouth,rear absorption entry,and movement away from the fracture mouth.Proppant primarily deflects into the branch fracture at the fracture mouth,with a small portion drawn in from the rear of the intersection.Increasing the pumping rate,reducing the proppant particle size,and widening the branch fracture are conducive to promoting proppant deflection into the branch.With increasing fracturing fluid viscosity,the ability of proppant to enter the branch fracture first improves and then declines,indicating that excessively high viscosity is unfavorable for proppant entry into the branch.During field operations,a high pumping rate and micro-to small-sized proppant can be used in the early stage to ensure effective placement in the branch fractures,followed by medium-to large-sized proppant to ensure adequate placement in the main fracture and enhance the overall conductivity of the fracture network.展开更多
To enhance the accuracy of path planning of unmanned surface vehicles(USVs),the particle swarm optimization algorithm(PSO)is improved based on species migration strategies observed in ecology.By incorporating the conc...To enhance the accuracy of path planning of unmanned surface vehicles(USVs),the particle swarm optimization algorithm(PSO)is improved based on species migration strategies observed in ecology.By incorporating the concept of particle sight distance,an improved algorithm,called SD-IPSO,is proposed for the real-time autonomous navigation of USVs in marine environments.The algorithm refines the individual behavior pattern of particles in the population,effectively improving both local and global search capabilities while avoiding premature convergence.The effectiveness of the algorithm is validated using standard test functions from CEC-2017 function library,assessing it from multiple dimensions.Sensitivity analysis is conducted on key parameters in the algorithm,including particle sight distance and population size.Results indicate that compared with PSO,SD-IPSO demonstrates significant advantages in optimization accuracy and convergence speed.The application of SD-IPSO in path planning is further investigated through a 14-point traveling salesman problem(TSP)example and navigation autonomous tests of USVs in marine environments.Findings demonstrate that the proposed algorithm exhibits superior optimization capabilities and can effectively address the path planning challenges of USVs.展开更多
Rapid corrosion of magnesium alloys in the physiological environment limits their use as orthopedic implant materials.Therefore,the silane film modified with nano-hydroxyapatite(n HA)was prepared on the surface of AZ3...Rapid corrosion of magnesium alloys in the physiological environment limits their use as orthopedic implant materials.Therefore,the silane film modified with nano-hydroxyapatite(n HA)was prepared on the surface of AZ31 magnesium alloy to improve its corrosion resistance.The silane films are continuous,uniform,and adherent well to the Mg substrate,and the modification of the film by n HA increased the thickness from~1.92 to~3.25μm.Compared to the bare substrate,the corrosion current density of the sample with the silane film modified with n HA decreases by three orders of magnitude from 9.23×10^(-5)to 2.779×10^(-8)A/cm~2.According to the immersion tests,it is found that the synergistic effect of sub-film corrosion and blistering is the dominant mode of film failure.During the immersion of less than 72 h,the modification by n HA improves the corrosion resistance by delaying the sub-film corrosion and blistering of the film.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
An in-depth understanding of the behaviours of solid propellants under low-velocity impact loads is crucial for enhancing their safety in applications such as aerospace propulsion.This study investigated the dynamic r...An in-depth understanding of the behaviours of solid propellants under low-velocity impact loads is crucial for enhancing their safety in applications such as aerospace propulsion.This study investigated the dynamic responses of single ammonium perchlorate(AP)/octogen(HMX)particles embedded in a hydroxyl-terminated polybutadiene(HTPB)binder under dynamic compression loading via real-time synchrotron-based X-ray phase contrast imaging and a modified split Hopkinson pressure bar(SHPB)system.The compression of the viscoelastic binder and subsequent dynamic fracturing of the AP/HMX particles were captured.During compression,transverse cracks developed within the AP particles,and their propagation led to particle fracturing,resulting in ductile fracturing.Unlike AP,HMX generated numerous short cracks within the internal and edge regions simultaneously,leading to fragmentation and brittle fracturing.Moreover,particle damage reduced the modulus of the sample,shifting its dynamic stress response from nonlinear elasticity to strain softening and further strain hardening as the binder exhibited plastic deformation.A compression simulation incorporating a real particle microscopic structure was established to study the mechanical response of the interface and particles.The simulation results agreed with the experimental observations.These results indicate that the shear stress at the HTPB-AP interface is greater than that at the HTPB-HMX interface,which is a factor influencing the differences in the mesoscale damage mechanisms of the particles.展开更多
Rubber-toughened thermoplastic materials have become ubiquitous in modern society owing to their lightweight nature and desirable combination of advantageous performances.Despite the ever-increasing demand,the develop...Rubber-toughened thermoplastic materials have become ubiquitous in modern society owing to their lightweight nature and desirable combination of advantageous performances.Despite the ever-increasing demand,the development of polymer alloys that are lightweight,high-strength,and high-toughness remains an ongoing challenge.Inspired by the unique“salami”microstructure from commercial acrylonitrile butadiene styrene copolymer(ABS)and high-impact polystyrene(HIPS),a facile approach was developed to overcome the trade-off between enhancing the toughness and rigidity of fully polymer-based alloys by virtue of elastomeric salami particles.This strategy entails pre-grafting rigid poly(lactic acid)(PLLA)chains with glycidyl methacrylate-grafted octene ethylene copolymer(POE-g-GMA)using complementary reactive groups.It can be envisaged that the PLLA grafts featuring strong incompatibility with polypropylene(PP)remain fixed in elastomer phase upon the subsequent melt compounding,facilitating the in situ formation of“hard core(PLLA)-soft shell(polyolefin elastomer,POE)”particles in polypropylene(PP)matrix.The all-polymer alloys containing elastomeric salami particles demonstrated unprecedented performance combinations,including upper notched impact strengths(56.8 kJ/m2),even higher tensile strength(36.8 MPa),and Young’s modulus(0.93 GPa)than that of the PP matrix.Furthermore,these materials are lightweight without the incorporation of reinforcing nano-fillers,which is competitive with industrial engineering plastics.It is highly anticipated that this universal and highly efficient protocol will be appropriate for arbitrary rubber toughened/reinforced systems,offering a paradigm in the design of advanced all-polymer alloys.展开更多
This paper proposes an equivalent modeling method for photovoltaic(PV)power stations via a particle swarm optimization(PSO)K-means clustering(KMC)algorithm with passive filter parameter clustering to address the compl...This paper proposes an equivalent modeling method for photovoltaic(PV)power stations via a particle swarm optimization(PSO)K-means clustering(KMC)algorithm with passive filter parameter clustering to address the complexities,simulation time cost and convergence problems of detailed PV power station models.First,the amplitude–frequency curves of different filter parameters are analyzed.Based on the results,a grouping parameter set for characterizing the external filter characteristics is established.These parameters are further defined as clustering parameters.A single PV inverter model is then established as a prerequisite foundation.The proposed equivalent method combines the global search capability of PSO with the rapid convergence of KMC,effectively overcoming the tendency of KMC to become trapped in local optima.This approach enhances both clustering accuracy and numerical stability when determining equivalence for PV inverter units.Using the proposed clustering method,both a detailed PV power station model and an equivalent model are developed and compared.Simulation and hardwarein-loop(HIL)results based on the equivalent model verify that the equivalent method accurately represents the dynamic characteristics of PVpower stations and adapts well to different operating conditions.The proposed equivalent modeling method provides an effective analysis tool for future renewable energy integration research.展开更多
The influence mechanism of MgO particle fineness on the properties of MOC was comprehensively explored through means of grinding,sieving,hydration and apparent density testing,in conjunction with characterization meth...The influence mechanism of MgO particle fineness on the properties of MOC was comprehensively explored through means of grinding,sieving,hydration and apparent density testing,in conjunction with characterization methods such as setting time,stability,compressive strength,and microscopic morphology.The findings reveal that MOC demonstrates excellent stability and mechanical properties when the particle fineness of MgO is less than 75μm.When the MgO particle fineness exceeds 75μm,MOC exhibits superior fluidity and maneuverability.When 0.75μm MgO is employed as the raw material to prepare MOC,a water-cement ratio of 0.6 proves more favorable.These results can furnish a theoretical foundation for the preparation and application of MOC.展开更多
Rock-ice avalanches in cold high-mountain regions pose severe hazards due to their high mobility,yet the quantitative controls of particle-size ratio and ice content remain insufficiently constrained.This study invest...Rock-ice avalanches in cold high-mountain regions pose severe hazards due to their high mobility,yet the quantitative controls of particle-size ratio and ice content remain insufficiently constrained.This study investigates their coupled effects using inclinedflume experiments and Discrete Element Method(DEM)simulations,covering three gravel sizes(2-5 mm,5-7 mm,7-10 mm)and four ice-content levels(0%,20%,40%,60%).Run-out distance,velocity,energy components,flow regime(Savage number),and segregation indexαwere quantified.Increasing ice content significantly enhances mobility,but with diminishing marginal effectiveness.From 0%to 40%ice content,run-out distance increases by 41%-86%,whereas the additional increase from 40%to 60%contributes only 12%-23%.Particle-size ratio strongly governs segregation intensity.Fine-gravel groups reach segregation indices ofα=0.92-0.98,indicating nearly complete upward migration of ice,whereas medium-gravel and coarse-gravel groups exhibit much weaker segregation,stabilizing atα=0.68-0.74 and 0.60-0.69.Savage number analyses reveal marked flow-regime transitions.At 0%ice content,Savage numbers reach 1.0-1.5,indicating a collisional regime.Increasing ice content suppresses collisionality,with Savage numbers decreasing to 0.03-0.07 at 60%ice content,consistent with dense-regime flow.DEM energy analyses confirm this regime shift:for finegravel mixtures,collision energy decreases by 14%,while sliding-friction energy increases by 33%as ice content increases from 0%to 60%,reflecting enhanced overburden effects imposed by upward-segregated ice layers.Medium and coarse mixtures exhibit weaker or opposite energy-shift patterns,demonstrating strong size dependence.Mechanistically,large particle-size contrasts promote strong segregation and form dense basal rock layers that increase basal friction and reduce mobility.When particle sizes are similar or ice content is high,segregation remains limited,allowing ice to mix into the basal layer,thereby reducing basal friction and enhancing mobility.This research quantitatively demonstrates how composition controls particle spatial distribution,flow regime,and energy dissipation,offering new mechanistic insights into the propagation and deposition behaviors of rock-ice avalanches and improving hazard assessment in vulnerable high-mountain regions.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
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
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.
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funding support from the US National Science Foundation(2229092)supported by the Eric and Wendy Schmidt AI in Science Postdoctoral Fellowship,a program of Schmidt Sciences,LLC.
文摘Recent advances in artificial intelligence(AI)have led to the development of sophisticated algorithms that significantly improve image analysis capabilities.This combination of AI and microscopic imaging is transforming the way we interpret and analyze imaging data,simplifying complex tasks and enabling innovative experimental methods previously thought impossible.In smart manufacturing,these improvements are especially impactful,increasing precision and efficiency in production processes.This review examines the convergence of AI with particle image analysis,an area we refer to as“particle vision analysis(PVA).”We offer a detailed overview of how this technology integrates into and impacts various fields within the physical sciences and materials sectors,where it plays a crucial role in both innovation and operational improvements.We explore four key areas of advancement-namely,particle classification,detection,segmentation,and object tracking-along with a look into the emerging field of augmented microscopy.This paper also underscores the vital role of the existing datasets and implementations that support these applications,which provide essential insights and resources that drive continuous research and development in this fast-evolving field.Our thorough analysis aims to outline the transformative potential of AI-driven PVA in improving precision in future manufacturing at the microscopic scale and thereby preparing the ground for significant technological progress and broad industrial applications in nanomanufacturing,biomanufacturing,and pharmaceutical manufacturing.This exploration not only highlights the advantages of integrating AI into conventional manufacturing processes but also anticipates the rise of next-generation smart manufacturing,which is set to revolutionize industry standards and operational practices.
基金supported by the National Natural Science Foundation of China(No.42402319,51704266)the Anhui Provincial Natural Science Foundation(No.2308085QE151)+3 种基金the Natural Science Research Project of Anhui Educational Committee(No.2023AH051222)Young Talent Nurturing Program of Anhui Association For Science and Technology(No.RCTJ202403)the Open Foundation of the Innovation Base of Fine Mine Prospecting and Intelligent Monitoring Technology(No.2023-MPIM-01)partly supported by the Open Fund of Engineering Research Center of Rock-Soil Drilling&Excavation and Protection(No.202407).
文摘The stability of oil-dominated emulsions,including oil-based drilling fluids and crude oils,is crucial for mitigating gas hydrate risks in the petroleum and natural gas industries.Nanoparticles can stabilize oilwater systems(Pickering emulsions)by residing at the oil-water interface.However,their effects on the kinetics of hydrate formation in these systems remain unclear.To address this,we experimentally investigated how hydrophilic and hydrophobic nano-CaCO_(3) influence CH4 hydrate formation within dynamic oil-water systems.A series of hydrate formation experiments were conducted with varying water cuts and different concentrations of nano-CaCO_(3) at a particle size of 20 nm,under 3℃ and 6 MPa.The induction time,hydrate formation volume,and hydrate growth rate were measured and calculated.The results indicate that hydrophilic nano-CaCO_(3) generally inhibits hydrate formation,particularly at high water cuts,while hydrophobic nano-CaCO_(3) can significantly inhibit or even prevent hydrate formation at low water cuts.Water cut strongly influences the kinetics of hydrate formation,and nanoparticle concentration also impacts the results,likely due to changes in oil-water interface stability caused by nanoparticle distribution.This study will offer valuable insights for designing deepwater oilbased drilling fluids using nanoparticles and ensuring safe multiphase flow in deepwater oil and gas operations.
基金Project no.RRF-2.3.1-21-2022-00015 has been implemented with the support provided by the European Unionsupported by the Agency for Credits and Study Grants coordinated by the Romanian Ministry of National Education from the source of the research grant established through the Government Decision no.118/2023+1 种基金supported by the EKÖP-24-3-BME-103 New National Excellence Program of the Ministry for Culture and Innovation from the source of the National,Research,Development and Innovation Fundsupported by the Doctoral Excellence Fellowship Programme(DCEP)is funded by the National Research Development and Innovation Fund of the Ministry of Culture and Innovation and the Budapest University of Technology and Economics,under a grant agreement with the National Research,Development and Innovation Office.
文摘In this study,an artificial intelligence-based machine vision system was developed for in-line particle size analysis during the pellet layering process.Drug-layered pellets were produced by coating microcrystalline cellulose cores with an ibuprofen-containing layering liquid until the target drug content was achieved.Drug content increases with pellet size;therefore,particle size monitoring can ensure product safety and quality.The direct imaging system,consisting of a rigid endoscope,a light source,and a high-speed camera,provides real-time information about pellet size and layer uniformity,enabling timely intervention in the case of out-of-spec products.A convolutional neural network-based instance segmentation algorithm was employed to detect particles in focus,ensuring that pellet size could be accurately determined despite the dense flow of the particles.After training the model,the performance of the developed system was assessed by analysing the particle size distribution of pellet cores with variable sizes within the 250 e850 mm size range.The endoscopic system was tested in-line at a larger scale during the drug layering of inert pellet cores.The particle size data acquired in real time with the endoscopic imaging system corresponded with the reference methods,demonstrating the feasibility of the proposed machine vision-based method as a process analytical technology tool for in-line process monitoring.
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Supported by Joint Funds of the National Natural Science Foundation of China(U23B6004).
文摘Stereoscopic particle image velocimetry technology was employed to investigate the planar three-dimensional velocity field and the process of proppant entry into branch fractures in a fracture configuration of“vertical main fracture-vertical branch fracture”intersecting at a 90°angle.This study analyzed the effects of pumping rate,fracturing fluid viscosity,proppant particle size,and fracture width on the transport behavior of proppant into branch fractures.Based on the deflection behavior of proppant,the main fractures can be divided into five regions:pre-entry transition,pre-entry stabilization,deflection entry at the fracture mouth,rear absorption entry,and movement away from the fracture mouth.Proppant primarily deflects into the branch fracture at the fracture mouth,with a small portion drawn in from the rear of the intersection.Increasing the pumping rate,reducing the proppant particle size,and widening the branch fracture are conducive to promoting proppant deflection into the branch.With increasing fracturing fluid viscosity,the ability of proppant to enter the branch fracture first improves and then declines,indicating that excessively high viscosity is unfavorable for proppant entry into the branch.During field operations,a high pumping rate and micro-to small-sized proppant can be used in the early stage to ensure effective placement in the branch fractures,followed by medium-to large-sized proppant to ensure adequate placement in the main fracture and enhance the overall conductivity of the fracture network.
文摘To enhance the accuracy of path planning of unmanned surface vehicles(USVs),the particle swarm optimization algorithm(PSO)is improved based on species migration strategies observed in ecology.By incorporating the concept of particle sight distance,an improved algorithm,called SD-IPSO,is proposed for the real-time autonomous navigation of USVs in marine environments.The algorithm refines the individual behavior pattern of particles in the population,effectively improving both local and global search capabilities while avoiding premature convergence.The effectiveness of the algorithm is validated using standard test functions from CEC-2017 function library,assessing it from multiple dimensions.Sensitivity analysis is conducted on key parameters in the algorithm,including particle sight distance and population size.Results indicate that compared with PSO,SD-IPSO demonstrates significant advantages in optimization accuracy and convergence speed.The application of SD-IPSO in path planning is further investigated through a 14-point traveling salesman problem(TSP)example and navigation autonomous tests of USVs in marine environments.Findings demonstrate that the proposed algorithm exhibits superior optimization capabilities and can effectively address the path planning challenges of USVs.
基金supported by the Key Research and Development Program of Shandong Province(No.2021ZLGX01)Shanghai Kindly Medical Instrument Co.,Ltd。
文摘Rapid corrosion of magnesium alloys in the physiological environment limits their use as orthopedic implant materials.Therefore,the silane film modified with nano-hydroxyapatite(n HA)was prepared on the surface of AZ31 magnesium alloy to improve its corrosion resistance.The silane films are continuous,uniform,and adherent well to the Mg substrate,and the modification of the film by n HA increased the thickness from~1.92 to~3.25μm.Compared to the bare substrate,the corrosion current density of the sample with the silane film modified with n HA decreases by three orders of magnitude from 9.23×10^(-5)to 2.779×10^(-8)A/cm~2.According to the immersion tests,it is found that the synergistic effect of sub-film corrosion and blistering is the dominant mode of film failure.During the immersion of less than 72 h,the modification by n HA improves the corrosion resistance by delaying the sub-film corrosion and blistering of the film.
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.
基金supported by the National Natural Science Foundation of China(U2341288 and 12302492)。
文摘An in-depth understanding of the behaviours of solid propellants under low-velocity impact loads is crucial for enhancing their safety in applications such as aerospace propulsion.This study investigated the dynamic responses of single ammonium perchlorate(AP)/octogen(HMX)particles embedded in a hydroxyl-terminated polybutadiene(HTPB)binder under dynamic compression loading via real-time synchrotron-based X-ray phase contrast imaging and a modified split Hopkinson pressure bar(SHPB)system.The compression of the viscoelastic binder and subsequent dynamic fracturing of the AP/HMX particles were captured.During compression,transverse cracks developed within the AP particles,and their propagation led to particle fracturing,resulting in ductile fracturing.Unlike AP,HMX generated numerous short cracks within the internal and edge regions simultaneously,leading to fragmentation and brittle fracturing.Moreover,particle damage reduced the modulus of the sample,shifting its dynamic stress response from nonlinear elasticity to strain softening and further strain hardening as the binder exhibited plastic deformation.A compression simulation incorporating a real particle microscopic structure was established to study the mechanical response of the interface and particles.The simulation results agreed with the experimental observations.These results indicate that the shear stress at the HTPB-AP interface is greater than that at the HTPB-HMX interface,which is a factor influencing the differences in the mesoscale damage mechanisms of the particles.
基金financially supported by the National Natural Science Foundation of China(Nos.52373070,52273071 and U25A20255)the Special Support Plan for High-Level Talents in Zhejiang Province(No.2022R51008)the HZNU scientific research and innovation team project(No.TD2025004).
文摘Rubber-toughened thermoplastic materials have become ubiquitous in modern society owing to their lightweight nature and desirable combination of advantageous performances.Despite the ever-increasing demand,the development of polymer alloys that are lightweight,high-strength,and high-toughness remains an ongoing challenge.Inspired by the unique“salami”microstructure from commercial acrylonitrile butadiene styrene copolymer(ABS)and high-impact polystyrene(HIPS),a facile approach was developed to overcome the trade-off between enhancing the toughness and rigidity of fully polymer-based alloys by virtue of elastomeric salami particles.This strategy entails pre-grafting rigid poly(lactic acid)(PLLA)chains with glycidyl methacrylate-grafted octene ethylene copolymer(POE-g-GMA)using complementary reactive groups.It can be envisaged that the PLLA grafts featuring strong incompatibility with polypropylene(PP)remain fixed in elastomer phase upon the subsequent melt compounding,facilitating the in situ formation of“hard core(PLLA)-soft shell(polyolefin elastomer,POE)”particles in polypropylene(PP)matrix.The all-polymer alloys containing elastomeric salami particles demonstrated unprecedented performance combinations,including upper notched impact strengths(56.8 kJ/m2),even higher tensile strength(36.8 MPa),and Young’s modulus(0.93 GPa)than that of the PP matrix.Furthermore,these materials are lightweight without the incorporation of reinforcing nano-fillers,which is competitive with industrial engineering plastics.It is highly anticipated that this universal and highly efficient protocol will be appropriate for arbitrary rubber toughened/reinforced systems,offering a paradigm in the design of advanced all-polymer alloys.
基金supported by the Research Project of China Southern Power Grid(No.056200KK52222031).
文摘This paper proposes an equivalent modeling method for photovoltaic(PV)power stations via a particle swarm optimization(PSO)K-means clustering(KMC)algorithm with passive filter parameter clustering to address the complexities,simulation time cost and convergence problems of detailed PV power station models.First,the amplitude–frequency curves of different filter parameters are analyzed.Based on the results,a grouping parameter set for characterizing the external filter characteristics is established.These parameters are further defined as clustering parameters.A single PV inverter model is then established as a prerequisite foundation.The proposed equivalent method combines the global search capability of PSO with the rapid convergence of KMC,effectively overcoming the tendency of KMC to become trapped in local optima.This approach enhances both clustering accuracy and numerical stability when determining equivalence for PV inverter units.Using the proposed clustering method,both a detailed PV power station model and an equivalent model are developed and compared.Simulation and hardwarein-loop(HIL)results based on the equivalent model verify that the equivalent method accurately represents the dynamic characteristics of PVpower stations and adapts well to different operating conditions.The proposed equivalent modeling method provides an effective analysis tool for future renewable energy integration research.
基金Funded by the Ten National-level Science and Technology Innovation Platform Cultivation and Construction Projects in Qinghai Province(No.2025-ZJ-J01)the Leader of Natural Science and Engineering Technology in Qinghai Province(2023)the Western Young Scholars Program of Chinese Academy of Sciences(2024)。
文摘The influence mechanism of MgO particle fineness on the properties of MOC was comprehensively explored through means of grinding,sieving,hydration and apparent density testing,in conjunction with characterization methods such as setting time,stability,compressive strength,and microscopic morphology.The findings reveal that MOC demonstrates excellent stability and mechanical properties when the particle fineness of MgO is less than 75μm.When the MgO particle fineness exceeds 75μm,MOC exhibits superior fluidity and maneuverability.When 0.75μm MgO is employed as the raw material to prepare MOC,a water-cement ratio of 0.6 proves more favorable.These results can furnish a theoretical foundation for the preparation and application of MOC.
基金funded by the Natural Science Foundation of China(Grants No 42277127)。
文摘Rock-ice avalanches in cold high-mountain regions pose severe hazards due to their high mobility,yet the quantitative controls of particle-size ratio and ice content remain insufficiently constrained.This study investigates their coupled effects using inclinedflume experiments and Discrete Element Method(DEM)simulations,covering three gravel sizes(2-5 mm,5-7 mm,7-10 mm)and four ice-content levels(0%,20%,40%,60%).Run-out distance,velocity,energy components,flow regime(Savage number),and segregation indexαwere quantified.Increasing ice content significantly enhances mobility,but with diminishing marginal effectiveness.From 0%to 40%ice content,run-out distance increases by 41%-86%,whereas the additional increase from 40%to 60%contributes only 12%-23%.Particle-size ratio strongly governs segregation intensity.Fine-gravel groups reach segregation indices ofα=0.92-0.98,indicating nearly complete upward migration of ice,whereas medium-gravel and coarse-gravel groups exhibit much weaker segregation,stabilizing atα=0.68-0.74 and 0.60-0.69.Savage number analyses reveal marked flow-regime transitions.At 0%ice content,Savage numbers reach 1.0-1.5,indicating a collisional regime.Increasing ice content suppresses collisionality,with Savage numbers decreasing to 0.03-0.07 at 60%ice content,consistent with dense-regime flow.DEM energy analyses confirm this regime shift:for finegravel mixtures,collision energy decreases by 14%,while sliding-friction energy increases by 33%as ice content increases from 0%to 60%,reflecting enhanced overburden effects imposed by upward-segregated ice layers.Medium and coarse mixtures exhibit weaker or opposite energy-shift patterns,demonstrating strong size dependence.Mechanistically,large particle-size contrasts promote strong segregation and form dense basal rock layers that increase basal friction and reduce mobility.When particle sizes are similar or ice content is high,segregation remains limited,allowing ice to mix into the basal layer,thereby reducing basal friction and enhancing mobility.This research quantitatively demonstrates how composition controls particle spatial distribution,flow regime,and energy dissipation,offering new mechanistic insights into the propagation and deposition behaviors of rock-ice avalanches and improving hazard assessment in vulnerable high-mountain regions.
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.
