Rubble mound breakwaters, a prevalent type of sloping breakwater structure, are extensively employed in port and coastal infrastructure projects. Under soft soil foundation conditions, the process of squeezing silt by...Rubble mound breakwaters, a prevalent type of sloping breakwater structure, are extensively employed in port and coastal infrastructure projects. Under soft soil foundation conditions, the process of squeezing silt by riprap is implemented to enhance bearing capacity through soft soil replacement and compaction. However, predicting the depth law of squeezing silt by riprap and understanding its mechanism remain significant engineering design challenges.This study employs particle flow code(PFC) based on the discrete element method to simulate the squeezing silt process by riprap, examining variations in depth law under different geological conditions and its mechanical characteristics.Through calibration of the PFC model's meso-parameters via macro-experiments, the study analyzes the effects of riprap size, drop height, and soft soil properties on the depth law of squeezing silt. Findings demonstrate that riprap drop height and soft soil thickness substantially influence the depth, while appropriate calibration of meso-parameters enhances simulation accuracy. This research contributes theoretical and practical guidance for optimizing rubble mound breakwater design, understanding squeezing silt mechanisms, construction practices, and riprap quantity estimation.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
为了提高通信配电系统中不间断电源(Uninterruptible Power Supply,UPS)输入级的电能质量,引入三相功率因数校正(Power Factor Correction,PFC)技术,优化UPS输入级结构,设计适用于不平衡电网条件的三相PFC拓扑与控制策略,并完成硬件选...为了提高通信配电系统中不间断电源(Uninterruptible Power Supply,UPS)输入级的电能质量,引入三相功率因数校正(Power Factor Correction,PFC)技术,优化UPS输入级结构,设计适用于不平衡电网条件的三相PFC拓扑与控制策略,并完成硬件选型与实验验证。实验结果表明,所提方案可显著提高输入端功率因数,抑制电流谐波,降低总谐波畸变率,使三相信号更加均衡。研究结果对提高UPS系统输入效率、保障电力设备稳定运行具有重要意义。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
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
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
Imidazole(IM)particles in the atmosphere affect climate,atmospheric chemical reactions,and human health.However,research on IM particles in the Sichuan Basin(SCB),one of the areas of China affected most heavily by haz...Imidazole(IM)particles in the atmosphere affect climate,atmospheric chemical reactions,and human health.However,research on IM particles in the Sichuan Basin(SCB),one of the areas of China affected most heavily by haze,remains very scarce.This study used single-particle aerosol mass spectrometry to investigate IM-containing particles in Chengdu,one of the megacities in the SCB,during summer and winter before and after implemen-tation of the Three-year Action Plan to Win the Blue-Sky Defense War(BSDW).We found that IM-containing particles accounted for 1.2%–12.0%of all detected particles,and they highly mixed with carbonaceous com-ponents,secondary inorganic species,and organic nitrogen.From before to after the BSDW,the proportion of IM-containing particles decreased by 1.8%in summer,but increased by 9.6%in winter.Ammonium/amines and carbonyl compounds were closely related to IM-containing particles;the highest proportion of IM-containing particles occurred in particles mixed with amines and carbonyls.The number fraction of IM-containing particles in all seasons was higher at night than during daytime.The potential source areas of IM-containing particles showed notable narrowing after the BSDW,and the high-value areas were found distributed closer to Chengdu and its surrounding areas.In the winter before the BSDW,most IM-containing particles(>70%)were mixed with organic carbon(OC)particles,and the contributions of OC and mixed organic–elemental carbon(OC-EC)particles increased with aggravation of pollution,whereas OC-EC and Metal particles played a more crucial role in the winter after the BSDW.展开更多
In this study,the mechanism and characteristics of the responseαparticles and the damage caused by them in CMOS active pixel(APS)sensors were investigated.A detection and compensation algorithm for dead pixels caused...In this study,the mechanism and characteristics of the responseαparticles and the damage caused by them in CMOS active pixel(APS)sensors were investigated.A detection and compensation algorithm for dead pixels caused byαparticle ionizing radiation was proposed,and the effects of dead-pixel compensation algorithms were compared and analyzed under different parameter conditions.The experimental results show thatαparticle response signal has highest accuracy at 9 dB gain,with an obvious“target-ring”distribution.With increasing cumulative dose,the CMOS APS pedestal tends to saturation while dead pixels continue increasing.Though some pixel damage recovers through natural annealing,the dead-to-noise ratio increases with irradiation time,reaching 32.54%after 72 h.A hierarchical clustering dead-pixel detection method is proposed,categorizing pixels into two types:those within and outside the response event.A classification compensation strategy combining mean and majority filtering is proposed.This compensation algorithm can address dead-pixel interference without affectingαparticle radiation response data.When iterated multiple times and with integration time exceeding 6.31 ms,the number of dead pixels can be effectively reduced.展开更多
Feature selection serves as a critical preprocessing step inmachine learning,focusing on identifying and preserving the most relevant features to improve the efficiency and performance of classification algorithms.Par...Feature selection serves as a critical preprocessing step inmachine learning,focusing on identifying and preserving the most relevant features to improve the efficiency and performance of classification algorithms.Particle Swarm Optimization has demonstrated significant potential in addressing feature selection challenges.However,there are inherent limitations in Particle Swarm Optimization,such as the delicate balance between exploration and exploitation,susceptibility to local optima,and suboptimal convergence rates,hinder its performance.To tackle these issues,this study introduces a novel Leveraged Opposition-Based Learning method within Fitness Landscape Particle Swarm Optimization,tailored for wrapper-based feature selection.The proposed approach integrates:(1)a fitness-landscape adaptive strategy to dynamically balance exploration and exploitation,(2)the lever principle within Opposition-Based Learning to improve search efficiency,and(3)a Local Selection and Re-optimization mechanism combined with random perturbation to expedite convergence and enhance the quality of the optimal feature subset.The effectiveness of is rigorously evaluated on 24 benchmark datasets and compared against 13 advancedmetaheuristic algorithms.Experimental results demonstrate that the proposed method outperforms the compared algorithms in classification accuracy on over half of the datasets,whilst also significantly reducing the number of selected features.These findings demonstrate its effectiveness and robustness in feature selection tasks.展开更多
In the present work,the porous Ti particle reinforced Mg-based bulk metallic glass matrix composites(BMGCs)have been successfully fabricated via a novel in-situ dealloying method in metallic melt.A dual reinforcing st...In the present work,the porous Ti particle reinforced Mg-based bulk metallic glass matrix composites(BMGCs)have been successfully fabricated via a novel in-situ dealloying method in metallic melt.A dual reinforcing structure,including large-scale between porous particles and fine-scale inside one particle,was induced to further overcome the strength-plasticity tradeoff.The microstructure and mechanical properties of such dual-scale structure-reinforced BMGCs with various volume fractions and diameters of porous Ti particles were investigated in detail.It is found that with more and finer porous Ti particles,the BMGC showed both high fracture strength(1131.9±39.1 MPa)and good plastic deformability(1.48±0.38%).The characteristic of the reinforcing structure(0.48μm)inside the porous particles was close to the plastic processing zone size of the matrix(0.1~0.2μm),which generated a locally ideal reinforcing structure.Such dual-scale reinforcing structures with more interfaces can effectively promote the multiplication of shear bands at the interfaces.Due to the size effect,the refined submicron matrix between the Ti ligaments inside the porous particles should exhibit homogeneous shearing events.Such delocalization behavior from the dual-scale reinforcing structures should help to enhance the role of the interactions between shear bands,thus improving the yield strength of the composites.Based on the in-situ dealloying method,the dual-scale structure design provides a novel approach to fabricate various BMGCs with both high strength and good plasticity.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
This study investigates the motion behavior of a slender flexible particle in a backward-facing step(BFS)flow using the direct-forcing fictitious domain method,with a particular focus on the trapping phenomena near th...This study investigates the motion behavior of a slender flexible particle in a backward-facing step(BFS)flow using the direct-forcing fictitious domain method,with a particular focus on the trapping phenomena near the separation vortex region.Three distinct motion modes are identified:periodic rotation or oscillation within the vortex(trapping),downstream transport(escape),and transition state exhibiting unstable trapping.A dynamic balance among inward migration,centrifugal effects,wall interactions,and elastic forces enables the particle to achieve stable orbital motion within two distinct limit cycles.The topology of these orbits is governed by parameters,including the aspect ratio,structural flexibility,deformation intensity,and fluid inertia,all of which are characterized by the Reynolds number(Re).Specifically,fluid inertia plays a dominant role in facilitating particle trapping.At a fixed Re,a particle with a smaller aspect ratio tends to migrate inward and become trapped,whereas one with a larger aspect ratio is more likely to escape.Structural flexibility,especially when enhanced by confinement near the wall,leads to elastic deformation that induces secondary vortices and a weak flipping motion.The deformation intensityαsignificantly influences the lateral migration of the slender particle after the initial release;a largerαcauses it to drift toward the channel centerline,increasing the probability of escape.These findings provide a theoretical foundation for optimizing the transport and capture of slender soft swimmers in complex flow environments.展开更多
Droplet-based microfluidics is a transformative technology with applications across diverse scientific and industrial domains.However,predicting the droplet size generated by individual microchannels before experiment...Droplet-based microfluidics is a transformative technology with applications across diverse scientific and industrial domains.However,predicting the droplet size generated by individual microchannels before experiments or simulations remains a significant challenge.In this study,we focus on a double T-junction microfluidic geometry and employ a hybrid modeling approach that combines machine learning with metaheuristic optimization to address this issue.Specifically,particle swarm optimization(PSO)is used to optimize the hyperparameters of a decision tree(DT)model,and its performance is compared with that of a DT optimized through grid search(GS).The hybrid models are developed to estimate the droplet diameter based on four parameters:the main width,side width,thickness,and flow rate ratio.The dataset of more than 300 cases,generated by a three-dimensional numerical model of the double T-junction,is used for training and testing.Multiple evaluation metrics confirm the predictive accuracy of the models.The results demonstrate that the proposed DT-PSO model achieves higher accuracy,with a coefficient of determination of 0.902 on the test data,while simultaneously reducing prediction time.This methodology holds the potential to minimize design iterations and accelerate the integration of microfluidic technology into the biological sciences.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
Colitis-associated colorectal cancer(CAC)is a major contributor to cancer-related mortality worldwide.Titanium dioxide(TiO_(2),E171),a widely used food additive,has been insufficiently studied regarding its effects on...Colitis-associated colorectal cancer(CAC)is a major contributor to cancer-related mortality worldwide.Titanium dioxide(TiO_(2),E171),a widely used food additive,has been insufficiently studied regarding its effects on macrophages within colon tumors during CAC development.In this study,CAC mouse models were used to investigate the biological impact of dietary E171 on macrophages in vivo,while lipopolysaccharide(LPS)-stimulated RAW264.7 macrophage cell lines were employed to elucidate the underlying mechanisms in vitro.We found that dietary E171 intake accelerated CAC development,exacerbated inflammatory responses and oxidative stress,and upregulated CAC-associated genes,including S100a8,S100a9,Lcn2,S100a11,Cxcl2,and interleukin-1α(Il-1α).E171 also increased the expression of S100A8,S100A9,NOD-like receptor family pyrin domain-containing 3(NLRP3),and gasdermin-D Nterminal(GSDMD-N)in macrophages within colon tumors.In inflammatory macrophages,E171 exposure enhanced cell viability,increased reactive oxygen species(ROS)levels,and elevated the expression and secretion of S100A8 and S100A9,consistent with in vivo histological observations.Furthermore,E171-induced secretion of S100A8 and S100A9 in macrophages was suppressed by specific inhibitors,including N-acetylcysteine(NAC,ROS inhibitor),MCC950(NLRP3 inhibitor),Z-YVAD-FMK(caspase 1 inhibitor),disulfiram(GSDMD inhibitor),and transfection of NLRP3 small interfering ribonucleic acid(siRNA).These results indicate that dietary E171 promotes CAC development by activating macrophages,with S100A8 and S100A9 serving as key mediators,and the NLRP3/caspase 1/GSDMD pathway acting as a critical mechanism.展开更多
基金financially supported by the Fundamental Research Funds for the Central Universities (Grant Nos.B200202087 and B200204032)the National Natural Science Foundation of China (Grant No.51609071)。
文摘Rubble mound breakwaters, a prevalent type of sloping breakwater structure, are extensively employed in port and coastal infrastructure projects. Under soft soil foundation conditions, the process of squeezing silt by riprap is implemented to enhance bearing capacity through soft soil replacement and compaction. However, predicting the depth law of squeezing silt by riprap and understanding its mechanism remain significant engineering design challenges.This study employs particle flow code(PFC) based on the discrete element method to simulate the squeezing silt process by riprap, examining variations in depth law under different geological conditions and its mechanical characteristics.Through calibration of the PFC model's meso-parameters via macro-experiments, the study analyzes the effects of riprap size, drop height, and soft soil properties on the depth law of squeezing silt. Findings demonstrate that riprap drop height and soft soil thickness substantially influence the depth, while appropriate calibration of meso-parameters enhances simulation accuracy. This research contributes theoretical and practical guidance for optimizing rubble mound breakwater design, understanding squeezing silt mechanisms, construction practices, and riprap quantity estimation.
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.
文摘为了提高通信配电系统中不间断电源(Uninterruptible Power Supply,UPS)输入级的电能质量,引入三相功率因数校正(Power Factor Correction,PFC)技术,优化UPS输入级结构,设计适用于不平衡电网条件的三相PFC拓扑与控制策略,并完成硬件选型与实验验证。实验结果表明,所提方案可显著提高输入端功率因数,抑制电流谐波,降低总谐波畸变率,使三相信号更加均衡。研究结果对提高UPS系统输入效率、保障电力设备稳定运行具有重要意义。
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 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supported by Sichuan Science and Technology Program(No.2024NSFSC0060)the National Natural Science Foundation of China(No.U23A2030)the Basic Research Cultivation Support Plan of Southwest Jiaotong University(No.2682023ZTPY016).
文摘Imidazole(IM)particles in the atmosphere affect climate,atmospheric chemical reactions,and human health.However,research on IM particles in the Sichuan Basin(SCB),one of the areas of China affected most heavily by haze,remains very scarce.This study used single-particle aerosol mass spectrometry to investigate IM-containing particles in Chengdu,one of the megacities in the SCB,during summer and winter before and after implemen-tation of the Three-year Action Plan to Win the Blue-Sky Defense War(BSDW).We found that IM-containing particles accounted for 1.2%–12.0%of all detected particles,and they highly mixed with carbonaceous com-ponents,secondary inorganic species,and organic nitrogen.From before to after the BSDW,the proportion of IM-containing particles decreased by 1.8%in summer,but increased by 9.6%in winter.Ammonium/amines and carbonyl compounds were closely related to IM-containing particles;the highest proportion of IM-containing particles occurred in particles mixed with amines and carbonyls.The number fraction of IM-containing particles in all seasons was higher at night than during daytime.The potential source areas of IM-containing particles showed notable narrowing after the BSDW,and the high-value areas were found distributed closer to Chengdu and its surrounding areas.In the winter before the BSDW,most IM-containing particles(>70%)were mixed with organic carbon(OC)particles,and the contributions of OC and mixed organic–elemental carbon(OC-EC)particles increased with aggravation of pollution,whereas OC-EC and Metal particles played a more crucial role in the winter after the BSDW.
基金supported by the National Natural Science Foundation of China(No.11905102)Hunan Provincial Postgraduate Research and Innovation Project(No.QL20230234)。
文摘In this study,the mechanism and characteristics of the responseαparticles and the damage caused by them in CMOS active pixel(APS)sensors were investigated.A detection and compensation algorithm for dead pixels caused byαparticle ionizing radiation was proposed,and the effects of dead-pixel compensation algorithms were compared and analyzed under different parameter conditions.The experimental results show thatαparticle response signal has highest accuracy at 9 dB gain,with an obvious“target-ring”distribution.With increasing cumulative dose,the CMOS APS pedestal tends to saturation while dead pixels continue increasing.Though some pixel damage recovers through natural annealing,the dead-to-noise ratio increases with irradiation time,reaching 32.54%after 72 h.A hierarchical clustering dead-pixel detection method is proposed,categorizing pixels into two types:those within and outside the response event.A classification compensation strategy combining mean and majority filtering is proposed.This compensation algorithm can address dead-pixel interference without affectingαparticle radiation response data.When iterated multiple times and with integration time exceeding 6.31 ms,the number of dead pixels can be effectively reduced.
基金supported by National Natural Science Foundation of China(62106092)Natural Science Foundation of Fujian Province(2024J01822,2024J01820,2022J01916)Natural Science Foundation of Zhangzhou City(ZZ2024J28).
文摘Feature selection serves as a critical preprocessing step inmachine learning,focusing on identifying and preserving the most relevant features to improve the efficiency and performance of classification algorithms.Particle Swarm Optimization has demonstrated significant potential in addressing feature selection challenges.However,there are inherent limitations in Particle Swarm Optimization,such as the delicate balance between exploration and exploitation,susceptibility to local optima,and suboptimal convergence rates,hinder its performance.To tackle these issues,this study introduces a novel Leveraged Opposition-Based Learning method within Fitness Landscape Particle Swarm Optimization,tailored for wrapper-based feature selection.The proposed approach integrates:(1)a fitness-landscape adaptive strategy to dynamically balance exploration and exploitation,(2)the lever principle within Opposition-Based Learning to improve search efficiency,and(3)a Local Selection and Re-optimization mechanism combined with random perturbation to expedite convergence and enhance the quality of the optimal feature subset.The effectiveness of is rigorously evaluated on 24 benchmark datasets and compared against 13 advancedmetaheuristic algorithms.Experimental results demonstrate that the proposed method outperforms the compared algorithms in classification accuracy on over half of the datasets,whilst also significantly reducing the number of selected features.These findings demonstrate its effectiveness and robustness in feature selection tasks.
基金supported by National Natural Science Foundation of China(No.52101138)Natural Science Foundation of Hubei Province(No.2023AFB798)+1 种基金Shenzhen Science and Technology Program(No.JCYJ20220530160813032)State Key Laboratory of Solidification Processing in NWPU(No.SKLSP202309).
文摘In the present work,the porous Ti particle reinforced Mg-based bulk metallic glass matrix composites(BMGCs)have been successfully fabricated via a novel in-situ dealloying method in metallic melt.A dual reinforcing structure,including large-scale between porous particles and fine-scale inside one particle,was induced to further overcome the strength-plasticity tradeoff.The microstructure and mechanical properties of such dual-scale structure-reinforced BMGCs with various volume fractions and diameters of porous Ti particles were investigated in detail.It is found that with more and finer porous Ti particles,the BMGC showed both high fracture strength(1131.9±39.1 MPa)and good plastic deformability(1.48±0.38%).The characteristic of the reinforcing structure(0.48μm)inside the porous particles was close to the plastic processing zone size of the matrix(0.1~0.2μm),which generated a locally ideal reinforcing structure.Such dual-scale reinforcing structures with more interfaces can effectively promote the multiplication of shear bands at the interfaces.Due to the size effect,the refined submicron matrix between the Ti ligaments inside the porous particles should exhibit homogeneous shearing events.Such delocalization behavior from the dual-scale reinforcing structures should help to enhance the role of the interactions between shear bands,thus improving the yield strength of the composites.Based on the in-situ dealloying method,the dual-scale structure design provides a novel approach to fabricate various BMGCs with both high strength and good plasticity.
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Project supported by the National Natural Science Foundation of China(Nos.12132015,12332015,and 12302333)。
文摘This study investigates the motion behavior of a slender flexible particle in a backward-facing step(BFS)flow using the direct-forcing fictitious domain method,with a particular focus on the trapping phenomena near the separation vortex region.Three distinct motion modes are identified:periodic rotation or oscillation within the vortex(trapping),downstream transport(escape),and transition state exhibiting unstable trapping.A dynamic balance among inward migration,centrifugal effects,wall interactions,and elastic forces enables the particle to achieve stable orbital motion within two distinct limit cycles.The topology of these orbits is governed by parameters,including the aspect ratio,structural flexibility,deformation intensity,and fluid inertia,all of which are characterized by the Reynolds number(Re).Specifically,fluid inertia plays a dominant role in facilitating particle trapping.At a fixed Re,a particle with a smaller aspect ratio tends to migrate inward and become trapped,whereas one with a larger aspect ratio is more likely to escape.Structural flexibility,especially when enhanced by confinement near the wall,leads to elastic deformation that induces secondary vortices and a weak flipping motion.The deformation intensityαsignificantly influences the lateral migration of the slender particle after the initial release;a largerαcauses it to drift toward the channel centerline,increasing the probability of escape.These findings provide a theoretical foundation for optimizing the transport and capture of slender soft swimmers in complex flow environments.
文摘Droplet-based microfluidics is a transformative technology with applications across diverse scientific and industrial domains.However,predicting the droplet size generated by individual microchannels before experiments or simulations remains a significant challenge.In this study,we focus on a double T-junction microfluidic geometry and employ a hybrid modeling approach that combines machine learning with metaheuristic optimization to address this issue.Specifically,particle swarm optimization(PSO)is used to optimize the hyperparameters of a decision tree(DT)model,and its performance is compared with that of a DT optimized through grid search(GS).The hybrid models are developed to estimate the droplet diameter based on four parameters:the main width,side width,thickness,and flow rate ratio.The dataset of more than 300 cases,generated by a three-dimensional numerical model of the double T-junction,is used for training and testing.Multiple evaluation metrics confirm the predictive accuracy of the models.The results demonstrate that the proposed DT-PSO model achieves higher accuracy,with a coefficient of determination of 0.902 on the test data,while simultaneously reducing prediction time.This methodology holds the potential to minimize design iterations and accelerate the integration of microfluidic technology into the biological sciences.
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(Nos.81974441 and 82203619)the Science and Technology Planning Project of Shenzhen Municipality(Nos.JCYJ20190814105619048 and JCYJ20220530154202005)。
文摘Colitis-associated colorectal cancer(CAC)is a major contributor to cancer-related mortality worldwide.Titanium dioxide(TiO_(2),E171),a widely used food additive,has been insufficiently studied regarding its effects on macrophages within colon tumors during CAC development.In this study,CAC mouse models were used to investigate the biological impact of dietary E171 on macrophages in vivo,while lipopolysaccharide(LPS)-stimulated RAW264.7 macrophage cell lines were employed to elucidate the underlying mechanisms in vitro.We found that dietary E171 intake accelerated CAC development,exacerbated inflammatory responses and oxidative stress,and upregulated CAC-associated genes,including S100a8,S100a9,Lcn2,S100a11,Cxcl2,and interleukin-1α(Il-1α).E171 also increased the expression of S100A8,S100A9,NOD-like receptor family pyrin domain-containing 3(NLRP3),and gasdermin-D Nterminal(GSDMD-N)in macrophages within colon tumors.In inflammatory macrophages,E171 exposure enhanced cell viability,increased reactive oxygen species(ROS)levels,and elevated the expression and secretion of S100A8 and S100A9,consistent with in vivo histological observations.Furthermore,E171-induced secretion of S100A8 and S100A9 in macrophages was suppressed by specific inhibitors,including N-acetylcysteine(NAC,ROS inhibitor),MCC950(NLRP3 inhibitor),Z-YVAD-FMK(caspase 1 inhibitor),disulfiram(GSDMD inhibitor),and transfection of NLRP3 small interfering ribonucleic acid(siRNA).These results indicate that dietary E171 promotes CAC development by activating macrophages,with S100A8 and S100A9 serving as key mediators,and the NLRP3/caspase 1/GSDMD pathway acting as a critical mechanism.
