A LOCAL DYNAMIC CLUSTER SELF-ORGANIZATION ALGORITHM IN WIRELESS SENSOR NETWORKS FOR RAINFALL MONITORING

Wireless Sensor Networks for Rainfall Monitoring (RM-WSNs) is a sensor network for the large-scale regional and moving rainfall monitoring,which could be controlled deployment. Delivery delay and cross-cluster calculation leads to information inaccuracy by the existing dynamic collabo-rative self-organization algorithm in WSNs. In this letter,a Local Dynamic Cluster Self-organization algorithm (LDCS) is proposed for the large-scale regional and moving target monitoring in RM-WSNs. The algorithm utilizes the resource-rich node in WSNs as the cluster head,which processes target information obtained by sensor nodes in cluster. The cluster head shifts with the target moving in chance and re-groups a new cluster. The target information acquisition is limited in the dynamic cluster,which can reduce information across-clusters transfer delay and improve the real-time of information acquisition. The simulation results show that,LDCS can not only relieve the problem of "too frequent leader switches" in IDSQ,also make full use of the history monitoring information of target and con-tinuous monitoring of sensor nodes that failed in DCS.

Cluster dynamics modeling of niobium and titanium carbide precipitates inα-Fe andγ-Fe

Kinetic behaviors of niobium and titanium carbide precipitates in iron are simulated with cluster dynamics.The simulations,carried out in austenite and ferrite for niobium carbides,and in austenite for titanium carbide,are analyzed for dependences on temperature,solute concentration,and initial cluster distribution.The results are presented for different temperatures and solute concentrations,compared to experimental data available.They show little impact of initial cluster distribution beyond a certain relaxation time and that highly dilute alloys with monomers only present a significantly different behavior from denser alloys or ones with different initial cluster distributions.

Evolution of ion-irradiated point defect concentration by cluster dynamics simulation

The relationship between ions irradiation and the induced microstructures(point defects,dislocations,clusters,etc.)could be better analyzed and explained by simulation.The mean field rate theory and cluster dynamics are used to simulate the effect of implanted Fe on the point defects concentration quantitatively.It is found that the depth distribution of point defect concentration is relatively gentle than that of damage calculated by SRIM software.Specifically,the damage rate and point defect concentration increase by 1.5 times and 0.6 times from depth of 120 nm to 825 nm,respectively.With the consideration of implanted Fe ions,which effectively act as interstitial atoms at the depth of high ion implantation rate,the vacancy concentration Cv decreases significantly after reaching the peak value,while the interstitial atom concentration Ci increases significantly after decline of the previous stage.At the peak depth of ion implantation,Cv dropped by 86%,and Ci increased by 6.2 times.Therefore,the implanted ions should be considered into the point defects concentration under high dose of heavy ion irradiation,which may help predict the concentration distribution of defect clusters,further analyzing the evolution behavior of solute precipitation.

MOLECULAR DYNAMICS SIMULATIONS OF FILLED AND EMPTY CAGE-LIKE WATER CLUSTERS IN LIQUID WATER AND THEIR SIGNIFICANCE TO GAS HYDRATE FORMATION MECHANISMS

Molecular dynamics simulations are performed to observe the evolutions of 512 and 51262 cage-like water clusters filled with or without a methane molecule immersed in bulk liquid water at 250 K and 230 K. The lifetimes of these clusters are calculated according to their Lindemann index δ (t) using the criteria of δ≥0.07. For both the filled and empty clusters, we find the dynamics of bulk water determines the lifetimes of cage-like water clusters, and that the lifetime of 512 62 cage-like cluster is the same as that of 512 cage-like cluster. Although the methane molecule indeed makes the filled cage-like cluster more stable than the empty one, the empty cage-like cluster still has chance to be long-lived compared with the filled clusters. These observations support the labile cluster hypothesis on the formation mechanisms of gas hydrates.

Theoretical estimation of sonochemical yield in bubble cluster in acoustic field

In order to learn more about the physical phenomena occurring in cloud cavitation,the nonlinear dynamics of a spherical cluster of cavitation bubbles and cavitation bubbles in cluster in an acoustic field excited by a square pressure wave are numerically investigated by considering viscosity,surface tension,and the weak compressibility of the liquid.The theoretical prediction of the yield of oxidants produced inside bubbles during the strong collapse stage of cavitation bubbles is also investigated.The effects of acoustic frequency,acoustic pressure amplitude,and the number of bubbles in cluster on bubble temperature and the quantity of oxidants produced inside bubbles are analyzed.The results show that the change of acoustic frequency,acoustic pressure amplitude,and the number of bubbles in cluster have an effect not only on temperature and the quantity of oxidants inside the bubble,but also on the degradation types of pollutants,which provides a guidance in improving the sonochemical degradation of organic pollutants.

The relaxation of galaxy clusters at redshift z=0 in IllustrisTNG simulation

We study the dynamical states of the 30 most massive galaxy clusters in the TNG100 simulation at redshift z = 0 using three types of tracers: stars, dark matter particles and satellite galaxies. If the massive galaxy cluster is spherically symmetric and relaxed, we can obtain the underlying total mass distribution accurately from its dynamical tracers using the spherical Jeans equations. Although the three tracers of clusters have very different number densities, velocity dispersions and anisotropies, they still trace the same total mass profile. We obtain the total mass profiles of clusters using these tracers separately and compare them with the true mass distributions. We find that:(1) the kinematics of dark matter trace the total mass of all clusters well and the mass inferred from dark matter are generally consistent with the true mass profiles with relative deviations smaller than ~ 25% at all radii;(2) stars in ~ 60% massive clusters are approaching equilibrium and the total mass of these clusters inferred from stars have relative deviations smaller than ~50% at all radii. Stellar substructures are rich and the mass inferred from stars tend to be over-estimated in the inner region;and(3) satellite galaxies are unrelaxed in the inner region and become more relaxed as the radius increases. The total mass inferred from satellites are under-estimated in all regions.

A Cluster Dynamics Model for Accumulation of Helium in Tungsten under Helium Ions and Neutron Irradiation

A cluster dynamics model based on rate theory has been developed to describe the accumulation and diffusion processes of helium in tungsten under helium implantation alone or synergistic irradiationwith neutron,by involving different types of objects,adopting up-to-date parameters and complex reaction processes as well as considering the diffusion process along with depth.The calculated results under different conditions are in good agreement with experiments much well.The model describes the behavior of helium in tungsten within 2D space of defect type/size and depth on different ions incident conditions(energies and fluences)and material conditions(system temperature and existent sinks),by including the synergistic effect of helium-neutron irradiations and the influence of inherent sinks(dislocation lines and grain boundaries).The model,coded as IRadMat,would be universally applicable to the evolution of defects for ions/neutron irradiated on plasma-facing materials.

Generalized labeled multi-Bernoulli filter with signal features of unknown emitters

A novel algorithm that combines the generalized labeled multi-Bernoulli(GLMB) filter with signal features of the unknown emitter is proposed in this paper. In complex electromagnetic environments, emitter features(EFs) are often unknown and time-varying. Aiming at the unknown feature problem, we propose a method for identifying EFs based on dynamic clustering of data fields. Because EFs are time-varying and the probability distribution is unknown, an improved fuzzy C-means algorithm is proposed to calculate the correlation coefficients between the target and measurements, to approximate the EF likelihood function. On this basis, the EF likelihood function is integrated into the recursive GLMB filter process to obtain the new prediction and update equations.Simulation results show that the proposed method can improve the tracking performance of multiple targets,especially in heavy clutter environments.