Multi-sink Deployment Strategy for Wireless Sensor Networks Based on Improved Particle Swarm Clustering Optimization Algorithm

In wireless sensor networks(WSNs) with single sink,the nodes close to the sink consume their energy too fast due to transferring a large number of data packages,resulting in the "energy hole" problem.Deploying multiple sink nodes in WSNs is an effective strategy to solve this problem.A multi-sink deployment strategy based on improved particle swarm clustering optimization(IPSCO) algorithm for WSNs is proposed in this paper.The IPSCO algorithm is a combination of the improved particle swarm optimization(PSO) algorithm and K-means clustering algorithm.According to the sink nodes number K,the IPSCO algorithm divides the sensor nodes in the whole network area into K clusters based on the distance between them,making the total within-class scatter to minimum,and outputs the center of each cluster.Then,multiple sink nodes in the center of each cluster can be deployed,to achieve the effects of partition network reasonably and deploy multi-sink nodes optimally.The simulation results show that the deployment strategy can prolong the network lifetime.

Clustering algorithm based on density function and nichePSO

This paper introduces niching particle swarm optimiza- tion （nichePSO） into clustering analysis and puts forward a cluster- ing algorithm which uses nichePSO to optimize density functions. Firstly, this paper improves main swarm training models and in- creases their ability of space searching. Secondly, the radius of sub-swarms is defined adaptively according to the actual clus- tering problem, which can be useful for the niches＇ forming and searching. At last, a novel method that distributes samples to the corresponding cluster is proposed. Numerical results illustrate that this algorithm based on the density function and nichePSO could cluster unbalanced density datasets into the correct clusters auto- matically and accurately.

Collective motion of polar active particles on a sphere

Collective motion of active particles with polar alignment is investigated on a sphere.We discussed the factors that affect particle swarm motion and define an order parameter that can show the degree of particle swarm motion.In the model,we added a polar alignment strength,along with Gaussian curvature,affecting particles swarm motion.We find that when the force exceeds a certain limit,the order parameter will decrease with the increase of the force.Combined with our definition of order parameter and observation of the model,the reason is that particles begin to move side by side under the influence of polar forces.In addition,the effects of velocity,rotational diffusion coefficient,and packing fraction on particle swarm motion are discussed.It is found that the rotational diffusion coefficient and the packing fraction have a great influence on the clustering motion of particles,while the velocity has little influence on the clustering motion of particles.

Settling and spreading behaviour of particle clusters in quiescent liquids in confined vessels

Here we report experiments on particle cluster settling at high Reynolds number in quiescent liquid contained in a vessel.The particles were observed to spread at the vessel bottom surface in a near-circular annular shape after settling irrespective of the shape of the vessel cross-section and particle shape,size,and types.Effect of different parameters such as mass,type and aspect ratio of the particles,height,and viscosity of liquid was investigated on spreading behaviour.Formation of the hemispherical bottom cap of the cluster that bounces upon hitting the vessel bottom surface was found to be responsible for the final circular annular shape of the settled structure.Particle leakage from the cluster was seen in the form of a tail.In the liquid having viscosity beyond 100 cP,cluster breakage was observed that resulted in hindered settling and asymmetric shapes of finally settled particles.The observations are useful to understand the overall area over which settling and spreading of such clusters can be observed.

Particle clustering(mesoscale structure)of high-flux gas-solid circulating fluidized bed

Particle clustering is an important dynamic phenomenon in circulating-fluidized-bed(CFBs)systems,and has been suggested as a key contributing factor to the non-uniform hydrodynamics of CFBs.Studies show that particle clusters can be affected by solids flux,in terms of frequency,duration,and solids holdup.To understand the characteristics of particle clusters under high-solids-flux conditions,experimental and modeling studies in high-solids-flux gas-solids CFBs were reviewed and summarized.Optical and electrical measurements and imaging methods were used to monitor the particle-clustering phenomenon in CFBs.Particles were found to cluster in high-flux CFBs,and were characterized by a denser cluster-solids holdup and a shorter time fraction,which was different from the behavior in low-flux CFBs.Particle properties affected particle clustering in high-flux CFBs significantly.In modeling work,Eulerian-Eulerian and Eulerian-Lagrangian methods were used to study the particle-cluster characteristics.Good results can be obtained by using the Eulerian-Eulerian method to simulate the CFB system,especially the high-flux CFBs,and by considering the effects of particle clusters.The Eulerian-Lagrangian method is used to obtain detailed cluster characteristics.Because of limits in computing power,no obvious results exist to model particle clusters under high-solids-flux conditions.Because high-solids-flux conditions are used extensively in industrial applications,further experimental and numerical investigations on the clustering behavior in HF/DCFBs are required.

Particle size influence on effective permittivity of particle-gas mixture with particle clusters

The influence of particle size on the effective permittivity of a particle-gas mixture in the presence of particle clusters was studied using numerical analysis involving the three-dimensional finite element method. The effective permittivity of the mixture was obtained by calculating the electrostatic energy generated in the computation domain, Numerical results show that for fixed volume fraction of particles in the mixture, the effective permittivity of the mixture increases with decreasing particle size, Static experiments were carried out by using a differential capacitance sensor with parallel plates. The variation of the effective permittivity with particle size is shown by experimental data to agree with the numerical results. The methodology described and the results obtained in this paper may be used to help modify the measurement of particles volume fraction in the presence of particle clusters when a capacitance sensor is used.

Characteristics of atmospheric particles and heavy metals in winter in Chang-Zhu-Tan city clusters, China

To understand the pollution characteristics of atmospheric particles and heavy metals in winter in Chang-Zhu-Tan city clusters, China, total suspended particulate （TSP） and PMI0 samples were collected in cities of Changsha, Zhuzhou and Xiangtan from December 2011 to January 2012, and heavy metals of Cd, Pb, Cr, and As were analyzed. It shows that the average TSP concentration in Changsha, Zhuzhou and Xiangtan were （183 ± 73）, （201± 84） and （190 ±66） μg/m3 respectively, and the average PM10 were （171 ± 82）, （178 ± 65） and （179 ± 55） μg/m3 respectively. The lowest TSP and PM10 concentrations occurred at the background Shaping site of Changsha. The average ratio of p（PM10）/p（TSP） was 91.9%, ranging from 81.3% to 98.9%. Concerning heavy metals, in TSP samples, the concentration of Cr, As, Cd and Pb were 28.8-56.5, 18.1-76.3, 3.9-26.1 and 148.0-460.9 ng/m3, respectively, while in PMI0 samples, were 16.4--42.1, 15.5-67.9, 3.3-22.2 and 127.9-389.3 ng/m3, respectively. The enrichment factor of Cd was the highest, followed by Pb and As, while that of Cr was the lowest.

Isolated mixing regions and mixing enhancement in a high-viscosity laminar stirred tank

Laminar mixing in the stirred tank is widely encountered in chemical and biological industries.Isolated mixing regions(IMRs)usually exist when the fluid medium has high viscosity,which are not conducive to mixing.In this work,the researches on IMRs,enhancement of laminar mixing and the phenomenon of particle clustering within IMRs are reviewed.For most studies,the aim is to destroy IMRs and improve the chaotic mixing.To this end,the mechanism of chaotic mixing and the structure of IMRs were well investigated.The methods developed to destroy IMRs include off-centered agitation,dynamic mixing protocol,special designs of impellers,baffles,etc.In addition,the methods to characterize the shape and size of IMRs as well as mixing effect by experiments and simulations are summarized.However,IMRs are not always nuisance,and it may be necessary in some situations.Finally,the present engineering applications are summarized,and the prospect of the future application is predicted.For example,particle clustering will form in the co-existing system of chaotic mixing and IMRs,which can be used for solid–liquid separation and recovery of particles from high viscosity fluid.

Numerical and experimental study of the effects of wind turbine operation on sand-dust transport characteristics

Given factors such as reduced land availability for onshore wind farms,wind resource enrichment levels,and costs,there is a growing trend of establishing wind farms in deserts,the Gobi,and other arid regions.Therefore,the relationship between sanddust weather environments and wind turbine operations has garnered significant attention.To investigate the impact of wind turbine wakes on sand-dust transportation,this study employs large eddy simulation to model flow fields,coupled with an actuator line model for simulating rotating blades and a multiphase particle in cell model for simulating sand particles.The research focuses on a horizontal axis wind turbine model and examines the motion and spatiotemporal distribution characteristics of four typical sizes of sand particles in the turbine wake.The findings reveal that sand particles of varying sizes exhibit a spiral settling pattern after traversing the rotating plane of wind turbine blades,influenced by blade shedding vortex and gravity.Sand particles tend to cluster in the peripheries of the vortex cores of low vorticity in the wind turbine wake.The rotation of wind turbines generates a wake vortex structure that causes a significant clustering of sand particles at the tip vortex.As the wake distance increases,the particles that cluster at the turbine's tip gradually spread outward to approximately twice the rotor diameter and then begin to mix with the incoming flow environment.Wind turbines have a noticeable impact on sand-dust transportation,hindering their movement to a significant extent.The average sand-blocking rate exhibits a trend of initially increasing and then decreasing as the wake distance increases.At its peak,the sand-blocking rate reaches an impressive 67.55%.The presence of wind turbines induces the advanced settling of sand particles,resulting in a“triangular”distribution of the deposition within the ground projection area of the wake.

MULTI-SCALE AGGREGATION OF PARTICLES IN GAS-SOLIDS FLUIDIZED BEDS

The multi-scale characteristics of clusters in a fast fluidized bed and of agglomerates in a fluidized bed of cohesive particles are discussed on the basis of large amounts of experiments. The cluster size and concentration are dominated by the local voidage of the bed. A cluster consists of many sub-clusters with different sizes and discrete par-ticles, and the sub-cluster size probability density distribution appears as a negative exponential function. The agglom-erates in a fluidized bed of cohesive particles also possess the multi-scale nature. The large agglomerates form a fixed bed at the bottom, the medium agglomerates are fluidized in the middle, and the small agglomerates and discrete parti-cles become the dilute-phase region in the upper part of the bed. The agglomerate size is mainly affected by cohesive forces and gas velocity. The present models for predicting the size of clusters and agglomerates can not tackle the in-trinsic mechanism of the multi-scale aggregation, and a challenging problem for establishing mechanistic model is put forward.

Extraction, detection, and profiling of serum biomarkers using designed Fe3O4@SiO2@HA core-shell particles

Serum biomarkers in the form of proteins （e.g. cluster of differentiation-44 （CD44）） have been demonstrated to have high clinical sensitivity and specificity for disease diagnosis and prognosis. Owing to the high sample complexity and low molecular abundance in serum, the detection and profiling of biomarkers rely on efficient extraction by materials and devices, mostly using immunoassays via antibody-antigen recognition. Antibody-free approaches are promising and need to be developed for real-case applications in serum to address the limitations of antibody-based techniques in terms of robustness, expense, and throughput. In this work, we demonstrated a novel approach using hyaluronic acid （HA）-modified materials/devices for the extraction, detection, and profiling of serum biomarkers via ligand-protein interactions. We constructed Fe304@SiOa@HA particles with different sizes through layer-by-layer assembly and for the first time applied HA-functionalized particles in the facile extraction and sequence identification of CD44 in serum by mass spectrometry. We also first validated HA-CD44 binding through electrochemical sensing using HA- modified electrodes in both standard solutions and diluted serum samples, achieving a detection limit of -0.6 ng/mL and a linear response range from I ng/mL to 10 ~tg/mL. Furthermore, we performed profiling of HA-binding serum proteome, providing a new preliminary benchmark for the construction of future databases, and we investigated selected surface chemistries of particles for the capture of proteins in serum. Our work not only resulted in the development of a platform technology for CD44 extraction/detection and HA-binding proteome identification, but also guided the design of ligand affinity-based approaches for antibody-free analysis of serum biomarkers towards diagnostic applications.

Characteristics of settling of dilute suspension of particles with different density at high Reynolds numbers

Dilute suspension of particles with same density and size develops clusters when settle at high Reynolds number(≥250).It is due to particles entrapment in the wakes produced by upstream particles.In this work,this phenomenon is studied for suspension having particles with different densities by numerical simulations.The particle-fluid interactions are modelled using immersed boundary method and inter-particle collisions are modelled using discrete element method.In simulations,settling Reynolds number is always kept above 250 and the suspension solid volume fraction is nearly 0.1 percent.Two particle density ratios(i.e.density of heavy particles to lighter particles)equal to 4:1 and 2:1 and particles with same density are studied.For each density ratio,the percentage volume fraction of each particle density is nearly varied from 0.8 to 0.2.Settling characteristics such as microstructures of settling particle,average settling velocity and velocity fluctuations of settling particles are studied.Simulations show that for different density particles settling characteristics of suspension is largely dominated by heavy particles.At the end of paper,the underlying physics is explained for the anomalies observed in simulation.