Pseudo-time particle filtering for diffuse optical tomography

We recast the reconstruction problem of diffuse optical tomography (DOT) in a pseudo-dynamical framework and develop a method to recover the optical parameters using particle filters, i.e., stochastic filters based on Monte Carlo simulations. In particular, we have implemented two such filters, viz., the bootstrap (BS) filter and the Gaussian-sum (GS) filter and employed them to recover optical absorption coefficient distribution from both numerically simulated and experimentally generated photon fluence data. Using either indicator functions or compactly supported continuous kernels to represent the unknown property distribution within the inhomogeneous inclusions, we have drastically reduced the number of parameters to be recovered and thus brought the overall computation time to within reasonable limits. Even though the GS filter outperformed the BS filter in terms of accuracy of reconstruction, both gave fairly accurate recovery of the height, radius, and location of the inclusions. Since the present filtering algorithms do not use derivatives, we could demonstrate accurate contrast recovery even in the middle of the object where the usual deterministic algorithms perform poorly owing to the poor sensitivity of measurement of the parameters. Consistent with the fact that the DOT recovery, being ill posed, admits multiple solutions, both the filters gave solutions that were verified to be admissible by the closeness of the data computed through them to the data used in the filtering step (either numerically simulated or experimentally generated). (C) 2011 Optical Society of America

Single Particle and Packed Bed Combustion in Modern Gasifier Stoves—Density Effects

This article is concerned with a study of an unusual effect due to density of biomass pellets in modern stoves based on close-coupled gasification-combustion process. The two processes, namely, flaming with volatiles and glowing of the char show different effects. The mass flux of the fuel bears a constant ratio with the air flow rate of gasification during the flaming process and is independent of particle density; char glowing process shows a distinct effect of density. The bed temperatures also have similar features: during flaming, they are identical, but distinct in the char burn (gasification) regime. For the cases, wood char and pellet char, the densities are 350, 990 kg/m(3), and the burn rates are 2.5 and 3.5 g/min with the bed temperatures being 1380 and 1502 K, respectively. A number of experiments on practical stoves showed wood char combustion rates of 2.5 +/- 0.5 g/min and pellet char burn rates of 3.5 +/- 0.5 g/min. In pursuit of the resolution of the differences, experimental data on single particle combustion for forced convection and ambient temperatures effects have been obtained. Single particle char combustion rate with air show a near-d(2) law and surface and core temperatures are identical for both wood and pellet char. A model based on diffusion controlled heat release-radiation-convection balance is set up. Explanation of the observed results needs to include the ash build-up over the char. This model is then used to explain observed behavior in the packed bed; the different packing densities of the biomass chars leading to different heat release rates per unit bed volume are deduced as the cause of the differences in burn rate and bed temperatures.

Long term stability studies of particle storage rings using polynomial Maps

Long-term stability studies of particle storage rings can not be carried out using conventional numerical integration algorithms. We require symplectic integration algorithms which are both fast and accurate. In this paper, we study a symplectic integration method wherein the sym-plectic map representing the Hamiltonian system is refactorized using polynomial symplectic maps. This method is used to perform long term integration on a particle storage ring.

Effect of particle size on the giant magnetoresistance of La0.7Ca0.3MnO3

Effect of particle size on the electron transport and magnetic properties of La0.7Ca0.3MnO3 has been investigated. While the ferromagnetic Tc, low field magnetic susceptibility, and insulator‐metal transition are markedly affected by the particle size, the maximum magnetoresistance exhibited by the samples near Tc is not sensitive to the particle size. However, the magnetoresistance at 4.2 K increases with decrease in particle size, suggesting a substantial contribution by the grain boundaries. Preliminary measurements on La0.7Sr0.3MnO3 samples of different particle sizes also corroborate the above conclusions.

Particle dynamics in the channel flow of a turbulent particle-gas suspension at high Stokes number. Part 1. DNS and fluctuating force model

The fluctuating force model is developed and applied to the turbulent flow of a gas-particle suspension in a channel in the limit of high Stokes number, where the particle relaxation time is large compared to the fluid correlation time, and low particle Reynolds number where the Stokes drag law can be used to describe the interaction between the particles and fluid. In contrast to the Couette flow, the fluid velocity variances in the different directions in the channel are highly non-homogeneous, and they exhibit significant variation across the channel. First, we analyse the fluctuating particle velocity and acceleration distributions at different locations across the channel. The distributions are found to be non-Gaussian near the centre of the channel, and they exhibit significant skewness and flatness. However, acceleration distributions are closer to Gaussian at locations away from the channel centre, especially in regions where the variances of the fluid velocity fluctuations are at a maximum. The time correlations for the fluid velocity fluctuations and particle acceleration fluctuations are evaluated, and it is found that the time correlation of the particle acceleration fluctuations is close to the time correlations of the fluid velocity in a `moving Eulerian' reference, moving with the mean fluid velocity. The variances of the fluctuating force distributions in the Langevin simulations are determined from the time correlations of the fluid velocity fluctuations and the results are compared with direct numerical simulations. Quantitative agreement between the two simulations are obtained provided the particle viscous relaxation time is at least five times larger than the fluid integral time.

Particle dynamics in the channel flow of a turbulent particle-gas suspension at high Stokes number. Part 2. Comparison of fluctuating force simulations and experiments

The particle and fluid velocity fluctuations in a turbulent gas-particle suspension are studied experimentally using two-dimensional particle image velocimetry with the objective of comparing the experiments with the predictions of fluctuating force simulations. Since the fluctuating force simulations employ force distributions which do not incorporate the modification of fluid turbulence due to the particles, it is of importance to quantify the turbulence modification in the experiments. For experiments carried out at a low volume fraction of 9.15 x 10(-5) (mass loading is 0.19), where the viscous relaxation time is small compared with the time between collisions, it is found that the gas-phase turbulence is not significantly modified by the presence of particles. Owing to this, quantitative agreement is obtained between the results of experiments and fluctuating force simulations for the mean velocity and the root mean square of the fluctuating velocity, provided that the polydispersity in the particle size is incorporated in the simulations. This is because the polydispersity results in a variation in the terminal velocity of the particles which could induce collisions and generate fluctuations; this mechanism is absent if all of the particles are of equal size. It is found that there is some variation in the particle mean velocity very close to the wall depending on the wall-collision model used in the simulations, and agreement with experiments is obtained only when the tangential wall-particle coefficient of restitution is 0.7. The mean particle velocity is in quantitative agreement for locations more than 10 wall units from the wall of the channel. However, there are systematic differences between the simulations and theory for the particle concentrations, possibly due to inadequate control over the particle feeding at the entrance. The particle velocity distributions are compared both at the centre of the channel and near the wall, and the shape of the distribution function near the wall obtained in experiments is accurately predicted by the simulations. At the centre, there is some discrepancy between simulations and experiment for the distribution of the fluctuating velocity in the flow direction, where the simulations predict a bi-modal distribution whereas only a single maximum is observed in the experiments, although both distributions are skewed towards negative fluctuating velocities. At a much higher particle mass loading of 1.7, where the time between collisions is smaller than the viscous relaxation time, there is a significant increase in the turbulent velocity fluctuations by similar to 1-2 orders of magnitude. Therefore, it becomes necessary to incorporate the modified fluid-phase intensity in the fluctuating force simulation; with this modification, the mean and mean-square fluctuating velocities are within 20-30% of the experimental values.

The effect of particle size on performance of cathode materials of Li-ion batteries

Beginning with the ‘frog-leg experiment’ by Galvani (1786), followed by the demonstrations of Volta pile by Volta (1792) and lead-acid accumulator by Plante´ (1859), several battery chemistries have been developed and realized commercially. The development of lithium-ion rechargeable battery in the early 1990s is a breakthrough in the science and technology of batteries. Owing to its high energy density and high operating voltage, the Li-ion battery has become the battery of choice for various portable applications such as note-book computers, cellular telephones, camcorders, etc. Huge efforts are underway in succeeding the development of large size batteries for electric vehicle applications. The origin of lithium-ion battery lies in the discovery that Li+-ions can reversibly be intercalated into/de-intercalated from the Van der Walls gap between graphene sheets of carbon materials at a potential close to the Li/Li+ electrode. By employing carbon as the negative electrode material in rechargeable lithium-ion batteries, the problems associated with metallic lithium in rechargeable lithium batteries have been mitigated. Complimentary investigations on intercalation compounds based on transition metals have resulted in establishing LiCoO2 as the promising cathode material. By employing carbon and LiCoO2, respectively, as the negative and positive electrodes in a non-aqueous lithium-salt electrolyte,a Li-ion cell with a voltage value of about 3.5 V has resulted.Subsequent to commercialization of Li-ion batteries, a number of research activities concerning various aspects of the battery components began in several laboratories across the globe. Regarding the positive electrode materials, research priorities have been to develop different kinds of active materials concerning various aspects such as safety, high capacity, low cost, high stability with long cycle-life, environmental compatibility,understanding relationships between crystallographic and electrochemical properties. The present review discusses the published literature on different positive electrode materials of Li-ion batteries, with a focus on the effect of particle size on electrochemical performance.

Branching Particle Systems and Superprocess

In this paper, we describe a system of particles that perform independent random motions in space and at the end of their lifetimes give birth to a random number of offspring. We show that the system in the large density, small mass, rapid branching or long time scale limit converges to a measure-valued diffusion called the superprocess.

Particle image velocimetry and infrared thermography in a levitated droplet with nanosilica suspensions

Preferential accumulation and agglomeration kinetics of nanoparticles suspended in an acoustically levitated water droplet under radiative heating has been studied. Particle image velocimetry performed to map the internal flow field shows a single cell recirculation with increasing strength for decreasing viscosities. Infrared thermography and high speed imaging show details of the heating process for various concentrations of nanosilica droplets. Initial stage of heating is marked by fast vaporization of liquid and sharp temperature rise. Following this stage, aggregation of nanoparticles is seen resulting in various structure formations. At low concentrations, a bowl structure of the droplet is dominant, maintained at a constant temperature. At high concentrations, viscosity of the solution increases, leading to rotation about the levitator axis due to the dominance of centrifugal motion. Such complex fluid motion inside the droplet due to acoustic streaming eventually results in the formation of a ring structure. This horizontal ring eventually reorients itself due to an imbalance of acoustic forces on the ring, exposing larger area for laser absorption and subsequent sharp temperature rise.

Robust solver based on modified particle swarm optimization for improved solution of diffusion transport through containment facilities

Accurate estimation of mass transport parameters is necessary for overall design and evaluation processes of the waste disposal facilities. The mass transport parameters, such as effective diffusion coefficient, retardation factor and diffusion accessible porosity, are estimated from observed diffusion data by inverse analysis. Recently, particle swarm optimization (PSO) algorithm has been used to develop inverse model for estimating these parameters that alleviated existing limitations in the inverse analysis. However, PSO solver yields different solutions in successive runs because of the stochastic nature of the algorithm and also because of the presence of multiple optimum solutions. Thus the estimated mean solution from independent runs is significantly different from the best solution. In this paper, two variants of the PSO algorithms are proposed to improve the performance of the inverse analysis. The proposed algorithms use perturbation equation for the gbest particle to gain information around gbest region on the search space and catfish particles in alternative iterations to improve exploration capabilities. Performance comparison of developed solvers on synthetic test data for two different diffusion problems reveals that one of the proposed solvers, CPPSO, significantly improves overall performance with improved best, worst and mean fitness values. The developed solver is further used to estimate transport parameters from 12 sets of experimentally observed diffusion data obtained from three diffusion problems and compared with published values from the literature. The proposed solver is quick, simple and robust on different diffusion problems. (C) 2012 Elsevier Ltd. All rights reserved.