Mice and larvae tracking using a particle filter with an auto-adjustable observation model

This paper proposes a novel way to combine different observation models in a particle filter framework. This, so called, auto-adjustable observation model, enhance the particle filter accuracy when the tracked objects overlap without infringing a great runtime penalty to the whole tracking system. The approach has been tested under two important real world situations related to animal behavior: mice and larvae tracking. The proposal was compared to some state-of-art approaches and the results show, under the datasets tested, that a good trade-off between accuracy and runtime can be achieved using an auto-adjustable observation model. (C) 2009 Elsevier B.V. All rights reserved.

On exact time averages of a massive Poisson particle

In this work we study, under the Stratonovich definition, the problem of the damped oscillatory massive particle subject to a heterogeneous Poisson noise characterized by a rate of events, lambda(t), and a magnitude, Phi, following an exponential distribution. We tackle the problem by performing exact time averages over the noise in a similar way to previous works analysing the problem of the Brownian particle. From this procedure we obtain the long-term equilibrium distributions of position and velocity as well as analytical asymptotic expressions for the injection and dissipation of energy terms. Considerations on the emergence of stochastic resonance in this type of system are also set forth.

Effect of sonication on the particle size of montmorillonite clays

This paper reports on the effect of sonication on SAz-1 and SWy-1 montmorillonite suspensions. Changes in the size of the particles of these materials and modifications of their properties have been investigated. The variation of the particle size has been analyzed by DLS (dynamic light scattering). In all cases the clay particles show a bimodal distribution. Sonication resulted in a decrease of the larger modal diameter, as well as a reduction of its volume percentage. Simultaneously, the proportion of the smallest particles increases. After 60 min of sonication, SAz-1 presented a very broad particle size distribution with a modal diameter of 283 nm. On the other hand, the SWy-1 sonicated for 60 min presents a bimodal distribution of particles at 140 and 454 nm. Changes in the properties of the clay suspensions due to sonication were evaluated spectroscopically from dye-clay interactions, using Methylene Blue. The acidic sites present in the interlamellar region, which are responsible for dye protonation, disappeared after sonication of the clay. The changes in the size of the scattering particles and the lack of acidic sites after sonication suggest that sonication induces delamination of the clay particles. (c) 2008 Elsevier Inc. All rights reserved.

Modeling and forecasting long-term natural gas (NG) consumption in Iran, using particle swarm optimization (PSO)

The gradual changes in the world development have brought energy issues back into high profile. An ongoing challenge for countries around the world is to balance the development gains against its effects on the environment. The energy management is the key factor of any sustainable development program. All the aspects of development in agriculture, power generation, social welfare and industry in Iran are crucially related to the energy and its revenue. Forecasting end-use natural gas consumption is an important Factor for efficient system operation and a basis for planning decisions. In this thesis, particle swarm optimization (PSO) used to forecast long run natural gas consumption in Iran. Gas consumption data in Iran for the previous 34 years is used to predict the consumption for the coming years. Four linear and nonlinear models proposed and six factors such as Gross Domestic Product (GDP), Population, National Income (NI), Temperature, Consumer Price Index (CPI) and yearly Natural Gas (NG) demand investigated.

Picturing evaporation : learning science literacy through a particle representation

Evaporation is mostly taught in primary schools through a water cycle representation. This has its limitations in explaining mechanisms and local effects such as drops drying in a closed room, condensation on cold surfaces, or how we smell liquids. In this paper the authors describe a classroom sequence of activities for Grade 5 students that explored the use of a particle model in conjunction with a range of representational modes, to explain evaporation phenomena. In interviews the authors explored with students their visual and verbal accounts of particles, modelling a process of teacher-mediated negotiation of multiple representations. From the evidence, the authors argue that difficulties in understanding evaporation are inherently representational, and that by engaging with the multiple literacies of science teachers can support significant advances in conceptual learning.

Equal channel angular pressing of metal matrix composites: effect on particle distribution and fracture toughness

An Al6061-20%Al₂O₃ powder metallurgy (PM) metal matrix composite (MMC) with a strongly clustered particle distribution is subjected to equal channel angular pressing (ECAP) at a temperature of 370 °C. The evolution of the homogeneity of the particle distribution in the material during ECAP is investigated by the quadrat method. The model proposed by Tan and Zhang [Mater Sci Eng 1998;244:80] for estimating the critical particle size which is required for a homogeneous particle distribution in PM MMCs is extended to the case of a combination of extrusion and ECAP. The applicability of the model to predict a homogeneity of the particle distribution after extrusion and ECAP is discussed. It is shown that ECAP leads to an increase of the  uniformity of the particle distribution and the fracture toughness.

Application of radial return mapping algorithm for finite strain elastoplasticity in a hybrid finite element and particle-in-cell model

The radial return mapping algorithm within the computational context of a hybrid Finite Element and Particle-In-Cell (FE/PIC) method is constructed to allow a fluid flow FE/PIC code to be applied solid mechanic problems with large displacements and large deformations. The FE/PIC method retains the robustness of an Eulerian mesh and enables tracking of material deformation by a set of Lagrangian particles or material points. In the FE/PIC approach the particle velocities are interpolated from nodal velocities and then the particle position is updated using a suitable integration scheme, such as the 4th order Runge-Kutta scheme[1]. The strain increments are obtained from gradients of the nodal velocities at the material point positions, which are then used to evaluate the stress increment and update history variables. To obtain the stress increment from the strain increment, the nonlinear constitutive equations are solved in an incremental iterative integration scheme based on a radial return mapping algorithm[2]. A plane stress extension of a rectangular shape J2 elastoplastic material with isotropic, kinematic and combined hardening is performed as an example and for validation of the enhanced FE/PIC method. It is shown that the method is suitable for analysis of problems in crystal plasticity and metal forming. The method is specifically suitable for simulation of neighbouring microstructural phases with different constitutive equations in a multiscale material modelling framework.

Multiscale particle-in-cell modelling for advanced high strength steels

Advanced High Strength Steels (AHSS) offer outstanding characteristics for efficient and economic use of steel. The unique features of AHSS are direct result of careful heat treatment that creates martensite in the steel microstructure. Martensite and carbon content in the microstructure greatly affects the mechanical properties of AHSS, underlining more importance on microstructural discontinuities and their multiphase characteristics. In this paper, we present the Multiscale Particle-In-Cell (MPIC) method for microstructural modelling of AHSS. A specific particle method [1] usually used in fluid mechanics is adapted and implemented in a parallel multiscale framework. This multiscale method is based on homogenisation theories; with Particle-In-Cell (PIC) method in both micro and macroscale, and offers several advantages in comparison to finite element (FE) based formulation. Application of this method to a benchmark uniaxial tension test is presented and compared with conventional FE solutions.