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.

Variation of the gas and radiation content in the sub-Keplerian accretion disk around black holes and its impact to the solutions

We investigate the variation of the gas and the radiation pressure in accretion disks during the infall of matter to the black hole and its effect to the flow. While the flow far away from the black hole might be non-relativistic, in the vicinity of the black hole it is expected to be relativistic behaving more like radiation. Therefore, the ratio of gas pressure to total pressure (beta) and the underlying polytropic index (gamma) should not be constant throughout the flow. We obtain that accretion flows exhibit significant variation of beta and then gamma, which affects solutions described in the standard literature based on constant beta. Certain solutions for a particular set of initial parameters with a constant beta do not exist when the variation of beta is incorporated appropriately. We model the viscous sub-Keplerian accretion disk with a nonzero component of advection and pressure gradient around black holes by preserving the conservations of mass, momentum, energy, supplemented by the evolution of beta. By solving the set of five coupled differential equations, we obtain the thermo-hydrodynamical properties of the flow. We show that during infall, beta of the flow could vary up to similar to 300%, while gamma up to similar to 20%. This might have a significant impact to the disk solutions in explaining observed data, e.g. super-luminal jets from disks, luminosity, and then extracting fundamental properties from them. Hence any conclusion based on constant gamma and beta should be taken with caution and corrected. (C) 2011 Elsevier B.V. All rights reserved.

Biofuel Prospects of Microalgal Community in Urban Wetlands

Microalgae are emerging as one of the most promising sources of biofuel because of their high photosynthetic efficiency and faster replication as compared to any other energy crops. Although, the concept of using microalgal lipid as a source of fuel is very mature, its approach in benefiting both environmental and energy-related is a frontier research area today. Algal community for the production of lipid depends on the physical, chemical as well as biological variables of aquatic ecosystems. This communication focuses on achieving the lipid haracterization of the microalgal community collected from four wetlands and one agricultural field of Bangalore, Karnataka with a wide range of environmental characteristics. Results reveal significant change in lipid component with change in algal community and chlorophyll content which was explained by community structure analysis and chlorophyll estimation. The presence of Triacyl glycerol (TAG) was examined through thin layer chromatography (TLC). The profile of TAG was further confirmed through Gas chromatography – mass spectroscopy (GC-MS). This study confirms the potential of algal community towards meeting growing demand for alternate sustainable fuel.

Gas-phase synthesis of size-classified polyhedral In(2)O(3) nanoparticles

Monodisperse polyhedral In(2)O(3) nanoparticles were synthesized by differential mobility classification of a polydisperse aerosol formed by evaporation of indium at atmospheric pressure. When free molten indium particles oxidize, oxygen is absorbed preferentially on certain planes leading to the formation of polyhedral In(2)O(3) nanoparticles. It is shown that the position of oxygen addition, its concentration, the annealing temperature and the type of carrier gas are crucial for the resulting particle shape and crystalline quality. Semiconducting nanopolyhedrals, especially nanocubes used for sensors, are expected to offer enhanced sensitivity and improved response time due to the higher surface area as compared to spherical particles.

Thermodynamics of ideal gas in doubly special relativity

We study thermodynamics of an ideal gas in doubly special relativity. A new type of special functions (which we call ``incomplete modified Bessel functions'') emerge. We obtain a series solution for the partition function and derive thermodynamic quantities. We observe that doubly special relativity thermodynamics is nonperturbative in the special relativity and massless limits. A stiffer equation of state is found.

Effect of gas injection on drag and surface heat transfer rates for a 30 degrees semi-apex angle blunt body flying at Mach 5.75

Effect of coolant gas injection in the stagnation region on the surface heat transfer rates and aerodynamic drag for a large angle blunt body flying at hypersonic Mach number is reported for two stagnation enthalpies. A 60° apex-angle blunt cone model is employed for this purpose with air injection at the nose through a hole of 2mm diameter. The convective surface heating rates and aerodynamic drag are measured simultaneously using surface mounted platinum thin film sensors and internally mounted accelerometer balance system, respectively. About 35–40% reduction in surface heating rates is observed in the vicinity of stagnation region whereas 15–25% reduction in surface heating rates is felt beyond the stagnation region at stagnation enthalpy of 1.6MJ/kg. The aerodynamic drag expressed in terms of drag coefficient is found to increase by 20% due to the air injection.

Performance evaluation of neural network algorithms for multisensor data fusion in an airborne track while scan radar

This paper deals with the solution to the problem of multisensor data fusion for a single target scenario as detected by an airborne track-while-scan radar. The details of a neural network implementation, various training algorithms based on standard backpropagation, and the results of training and testing the neural network are presented. The promising capabilities of RPROP algorithm for multisensor data fusion for various parameters are shown in comparison to other adaptive techniques

A k-epsilon model for turbulent weld pool convection in gas metal arc welding process

In this paper, we present a modified k - epsilon model capable of addressing turbulent weld-pool convection in a GMAW process, taking into account the morphology of the phase change interface during a Gas Metal Arc Welding (GMAW) process. A three-dimensional turbulence mathematical model has been developed to study the heat transfer and fluid flow within the weld pool by considering the combined effect of three driving forces, viz., buoyancy, Lorentz force and surface tension (Marangoni convection). Mass and energy transports by the droplets are considered through the thermal analysis of the electrode. The falling droplet's heat addition to the molten pool is considered to be a volumetric heat source distributed in an imaginary cylindrical cavity ("cavity model") within the weld pool. This nature of heat source distribution takes into account the momentum and the thermal, energy of the falling droplets. The numerically predicted weld pool dimensions both from turbulence and laminar models are then compared with the experimental post-weld results sectioned across the weld axis. The above comparison enables us to analyze the overall effects of turbulent convection on the nature of heat and fluid flow and hence on the weld pool shape/size during the arc welding processes.

Tractable theories for the synthesis of neural networks

The Radius of Direct attraction of a discrete neural network is a measure of stability of the network. it is known that Hopfield networks designed using Hebb's Rule have a radius of direct attraction of Omega(n/p) where n is the size of the input patterns and p is the number of them. This lower bound is tight if p is no larger than 4. We construct a family of such networks with radius of direct attraction Omega(n/root plog p), for any p greater than or equal to 5. The techniques used to prove the result led us to the first polynomial-time algorithm for designing a neural network with maximum radius of direct attraction around arbitrary input patterns. The optimal synaptic matrix is computed using the ellipsoid method of linear programming in conjunction with an efficient separation oracle. Restrictions of symmetry and non-negative diagonal entries in the synaptic matrix can be accommodated within this scheme.

A neural network based automatic generation control design through reinforcement learning

This paper presents the design and implementation of a learning controller for the Automatic Generation Control (AGC) in power systems based on a reinforcement learning (RL) framework. In contrast to the recent RL scheme for AGC proposed by us, the present method permits handling of power system variables such as Area Control Error (ACE) and deviations from scheduled frequency and tie-line flows as continuous variables. (In the earlier scheme, these variables have to be quantized into finitely many levels). The optimal control law is arrived at in the RL framework by making use of Q-learning strategy. Since the state variables are continuous, we propose the use of Radial Basis Function (RBF) neural networks to compute the Q-values for a given input state. Since, in this application we cannot provide training data appropriate for the standard supervised learning framework, a reinforcement learning algorithm is employed to train the RBF network. We also employ a novel exploration strategy, based on a Learning Automata algorithm,for generating training samples during Q-learning. The proposed scheme, in addition to being simple to implement, inherits all the attractive features of an RL scheme such as model independent design, flexibility in control objective specification, robustness etc. Two implementations of the proposed approach are presented. Through simulation studies the attractiveness of this approach is demonstrated.

Transport through an electrostatically defined quantum dot lattice in a two-dimensional electron gas

Quantum dot lattices (QDLs) have the potential to allow for the tailoring of optical, magnetic, and electronic properties of a user-defined artificial solid. We use a dual gated device structure to controllably tune the potential landscape in a GaAs/AlGaAs two-dimensional electron gas, thereby enabling the formation of a periodic QDL. The current-voltage characteristics, I (V), follow a power law, as expected for a QDL. In addition, a systematic study of the scaling behavior of I (V) allows us to probe the effects of background disorder on transport through the QDL. Our results are particularly important for semiconductor-based QDL architectures which aim to probe collective phenomena.

Pulsed plasma treatment of polluted gas using wet/low temperature corona reactors

pplication of pulsed plasma for gas cleaning is gaining prominence in recent years mainly from the energy consideration point of view. Normally, gas treatment is carried out, at or above room temperature, by a conventional dry type corona reactor. However, this treatment is still inadequate in the removal of certain stable gases present in the exhaust/flue gas mixture. The authors report some interesting results of the treatment of such stable gases with pulsed plasma at very low ambient temperature. Also reported in the paper is an improvement in DeNO/DeNOx efficiency using unconventional wet-type reactors, designed and fabricated by the authors, operating at different ambient temperatures. Apart from laboratory tests on simulated gas mixtures, field tests were also carried out on the exhaust gas of a 8 kW diesel engine. Further, an attempt was made to test the feasibility of a helical wire as a corona electrode in place of the conventional straight wire electrode. A comparative analysis of the various tests is presented together with a note on the energy consideration