Papers by Keyword: Cluster

Abstract: Following the fundamental work by Bazaron, Bulgadaev and Derjaguin [6] on the observation of shear elasticity of low viscous liquids, we build on this study by examining viscous liquids, polymers and suspensions of nanoparticles. In this paper, we review our past and current efforts in these areas. The mechanical properties of liquids, polymers and nanosuspensions have been studied at relatively low frequencies of 10⁵ Hz. The real and imaginary shear moduli of these samples were obtained on equipment using the acoustic resonance technique. It was shown that the shear modulus and viscosity decreases with increasing shear deformation. The behavior of viscoelastic fluids near surfaces is similar to that of colloidal and polymer suspensions, suggesting that the liquid component is determined by the mechanical response of suspensions.

Abstract: The effects of [001] uniaxial strain on the stable structures and structural evolution of vacancy clusters in fcc metals, Cu, Ni, Al and Fe, have been studied and compared. Under uniaxial strain, the clusters in all these metals tend to align parallel or perpendicular to the strain axis under tensile or compressive strain. Moreover, both the body cluster and the {001} planar cluster become the dominant types. In addition, the stacking fault tetrahedron cluster becomes another dominant type in Al under compressive strain. The cluster structures in Fe are disordered under strain possibly because the pure fcc Fe is thermodynamically unstable under the current simulation condition.

Abstract: The effects of Sn addition on clustering and age-hardening behavior in an Al-0.6Mg-1.0Si (mass %) alloy were investigated. Addition of Sn delayed the age-hardening in single aging at 170 ̊C. On the other hand, Sn promoted the age-hardening response in 3-step aging process which comprises a pre-aging (PA) at 90 ̊C for 18ks followed by natural aging (NA) for 604.8ks and artificial aging (AA) at 170 ̊C. The characteristics of clusters formed during PA and NA were evaluated by differential scanning calorimetry (DSC) analysis and atom probe tomography (APT). The DSC results show that the endothermic peak at around 160 ̊C to 200 ̊C was observed in the Sn-free alloy. On the other hand, in the Sn-added alloy, endothermic peak was not observed. It is suggested that Sn addition suppresses the formation of the clusters formed during NA. The APT results show that the Sn addition decreases the number density of clusters, especially smaller clusters. No Sn precipitates were found in Mg-Si precipitates formed during AA at 170 ̊C for 3.6ks. It is speculated that suppression of smaller cluster formation by addition of Sn promotes the age-hardening response

Abstract: The deposition of a single Cu cluster on the Si (001) and Si (111) surfaces was studied by molecular dynamics simulations. EAM, SW and Morse potentials were used to describe the interaction of Cu-Cu, Si-Si, and the Cu-Si atoms, respectively. The results show that the crystallographic surface of the substrate had a large effect on film growth. On the Si (111) surface, the cluster structure demonstrate good uniformity and epitaxial relation to the substrate. There is no appreciable intermixing or silicide formation at the film-substrate interface, nor silicon segregation on the surface with incident energy between 0.1 and 1.0eV/atom. However, as the incident energy increases to 3.0eV/atom, intermixing began to appear for Cu₁₃ and Cu₁₉ clusters. For the Cu₁₄₇ cluster intermixing starts to appear at a lower energy of 1.6eV/atom. In contrast, intermixing appears on the Si (001) surface for a range of incident energy from 0.1 to 3.0eV/atom for all the three clusters studied. Furthermore, the epitaxial relation with the Si substrate result in (001)- or (111)-oriented Cu clusters on Si (001) or Si (111), respectively. This behavior is consistent with experimental observations. We found that the effect of cluster deposition on film property depends not only on the substrate-film material combination and cluster size but also on the substrate crystallographic orientation and incident energy.

Abstract: The process of impact interaction of a powder material particle with sprayed-on surface is described. A mathematical simulation is developed for the process of plastic deformation of a solid-phase particle to a disk-shaped cluster. The paper considers the influence of thermal and kinetic factors on the degree of plastic transformation of a particle.

Abstract: Natural aging during storage of Al-Mg-Si alloys at room temperature can significantly reduce the maximum strengthening potential (T6) during artificial aging and, therefore, is a key topic in aluminium research and industry. Many different strategies to understand and reduce the negative effect of natural aging have been investigated during the last decades, including analysis of different thermal pre-treatments and considering the effect of different microalloying elements. From these investigations, the vacancy evolution and the formation of clusters containing Mg and Si were found to be the governing aging mechanisms behind natural aging. In this work, we present a model to simulate and predict the behavior of these alloys when subjected to room temperature aging after solutionizing and demonstrate the effects of different thermal routes and chemical composition variations. In the implemented model, the evolution of excess quenched-in vacancies and the effect of solute vacancy traps are considered. Special emphasis is placed on co-cluster formation and its contribution to strengthening. The thermokinetic software MatCalc is used for the simulations and the results of the simulations are validated by experimental investigation.

Abstract: This paper presents the results of a defect structure investigation in commercially pure titanium alloy after hydrogen charging in a gaseous atmosphere at the temperature of 873 K up to the concentration of 5.1 at. %. Structure of samples was studied by positron lifetime, Doppler broadening and X-ray diffraction spectrometry. Several processes, corresponding to the different ranges of hydrogen concentrations were revealed. It was shown that hydrogen, penetrating in the material, expands its crystal lattice, initiates formation of vacancy-like defects of different dimensions and reacts with the last ones, forming the defect-hydrogen complexes.

Abstract: This paper presents a comparative study of clustering using Artificial Intelligence (AI) techniques. There are 3 methods to be compared, two methods are pure method, called Self Organising Map (SOM) which is branch of Artificial Neural Network (ANN) and Genetic Algorithm (GA), while one method is hybrid between GA and SOM, called GA-based SOM. SOM is one of the most popular method for cluster analysis. SOM will group objects based on the nearest distance between object and updateable cluster centres. However, there are disadvantages of SOM. Solution quality is depend on initial cluster centres that are generated randomly and cluster centres update algorithm is just based on a delta value without considering the searching direction. Basically, clustering case could be modelled as optimisation case. The objective function is to minimise total distance of all data to their cluster centre. Hence, GA has potentiality to be applied for clustering. Advantage of GA is it has multi searching points in finding the solution and stochastic movement from a phase to the next phase. Therefore, possibility of GA to find global optimum solution will be higher. However, there is still some possibility of GA just find near-optimum solution. The advantage of SOM is the smooth iterative procedure to improve existing cluster centres. Hybridisation of GA and SOM believed could provide better solution. In this study, there are 2 data sets used to test the performance of the three techniques. The study shows that when the solution domain is very wide then SOM and GA-based SOM perform better compared to GA while when the solution domain is not very wide then GA performs better.

Abstract: Wireless sensor network routing protocol is to prolong the survival time of wireless sensor networks by using the sensor nodes energy efficiently. Traditional LEACH protocol is random in the election of the cluster head, if a less energy node is first elected as a cluster head node, then the node might die soon, it will greatly reducing the lifetime of the network. In order to collect data more efficiently and prolong the network life cycle,we need better clustering protocol. Aim at the traditional LEACH protocol have some weakness,this paper improve the protocol based on traditional LEACH protocol, two influence factors which the residual energy and the number of elected cluster head of the nodes had been introduced to make the clustering more ideal. Simulation results show that compared to the traditional Leach algorithm ,the improved LEACH protocol can prolong the network life cycle more effective and reduce the energy consumption of the whole network.

Abstract: The terminal area is always a hot research topic by aviation experts all over the world. As the rapid growth of the demand of air transportation, the terminal area becomes busier than ever. The results are flight delays and cancellations. One of the solutions is to design a 4D trajectory for each flight. Under the four dimensional operation, the flights can fly more precisely and be arranged more closely so that the terminal area can hold more aircrafts. With the development of the technology of communication, navigation and surveillance, the flight of four-dimensional operation is possible. This paper presents a data-based method of 4D approach trajectory design in terminal area.