Experimental and computational investigation of flow of pebbles in a pebble bed nuclear reactor

The Pebble Bed Reactor (PBR) is a 4th generation nuclear reactor which is conceptually similar to moving bed reactors used in the chemical and petrochemical industries. In a PBR core, nuclear fuel in the form of pebbles moves slowly under the influence of gravity. Due to the dynamic nature of the core, a thorough understanding about slow and dense granular flow of pebbles is required from both a reactor safety and performance evaluation point of view. In this dissertation, a new integrated experimental and computational study of granular flow in a PBR has been performed. Continuous pebble re-circulation experimental set-up, mimicking flow of pebbles in a PBR, is designed and developed. Experimental investigation of the flow of pebbles in a mimicked test reactor was carried out for the first time using non-invasive radioactive particle tracking (RPT) and residence time distribution (RTD) techniques to measure the pebble trajectory, velocity, overall/zonal residence times, flow patterns etc. The tracer trajectory length and overall/zonal residence time is found to increase with change in pebble\u27s initial seeding position from the center towards the wall of the test reactor. Overall and zonal average velocities of pebbles are found to decrease from the center towards the wall. Discrete element method (DEM) based simulations of test reactor geometry were also carried out using commercial code EDEM and simulation results were validated using the obtained benchmark experimental data. In addition, EDEM based parametric sensitivity study of interaction properties was carried out which suggests that static friction characteristics play an important role from a packed/pebble beds structural characterization point of view. To make the RPT technique viable for practical applications and to enhance its accuracy, a novel and dynamic technique for RPT calibration was designed and developed. Preliminary feasibility results suggest that it can be implemented as a non-invasive and dynamic calibration methodology for RPT technique which will enable its industrial applications. --Abstract, page iii

Reductive Biotransformation of Ethyl Acetoacetate: A Comparative Studies using Free and Immobilized Whole Yeast Cells

Bioreduction of ethyl acetoacetate with free and immobilized yeast whole cell was achieved by using water and sucrose combination. After detachment from immobilized beads under basic condition, the corresponding ethyl(S)-(+)-3-hydroxybutanoate was isolated with 98 to 100% yield. Immobilized beads of yeast whole cell were prepared at different temperature which affects the morphology and physiology of the beads for the diffusion of the enzyme, which shown the maximum conversion of the substrate to products as compared to the free yeast whole cell

HIV Nuclear Entry: Clearing the Fog

HIV-1 and other lentiviruses have the unusual capability of infecting nondividing cells, but the mechanism by which they cross an intact nuclear membrane is mysterious. Recent work, including a new study (Lee, K.; Ambrose, Z.; Martin, T.D.; Oztop, I.; Mulky, A.; Julias, J.G.; Vandergraaff, N.; Baumann, J.G.; Wang, R.; Yuen, W. et al. Flexible use of nuclear import pathways by HIV-1. Cell Host Microbe 2010, 7, 221–233) confirms that the viral capsid plays a key role in HIV-1 nuclear entry in both dividing and nondividing cells. The identification of mutations in the viral capsid that alter the virus’s dependence on host cell nucleoporins represents an important advance in this poorly understood stage of the virus life cycle

Interpreting quantum discord through quantum state merging

We present an operational interpretation of quantum discord based on the quantum state merging protocol. Quantum discord is the markup in the cost of quantum communication in the process of quantum state merging, if one discards relevant prior information. Our interpretation has an intuitive explanation based on the strong subadditivity of von Neumann entropy. We use our result to provide operational interpretations of other quantities like the local purity and quantum deficit. Finally, we discuss in brief some instances where our interpretation is valid in the single copy scenario.Comment: 5 pages, no figures. See http://arxiv.org/abs/1008.3205 for similar results. Typos fixed, references and acknowledgements updated. End note adde

Channel routing optimization using a genetic algorithm

A modified approach for the application of Genetic Algorithm (GA) to the Channel Routing Problem has been proposed. The code based on the algorithm proposed in [1] has been implemented for the GA procedures of Initial Population Generation, Crossover, Mutation and Selection. A few improvements over the existing work have been made and the results so far obtained have been encouraging. Further experimentation is being done on the algorithm and other ideas generated during the development of the code are being implemented for faster convergence of the algorithm and for generation of more efficient results. Also application of variations of the GA technique like Vector GA and even other computationally intelligent techniques like Particle Swarm Optimization to the channel routing problem is being thought of

DANTE: Deep AlterNations for Training nEural networks

We present DANTE, a novel method for training neural networks using the alternating minimization principle. DANTE provides an alternate perspective to traditional gradient-based backpropagation techniques commonly used to train deep networks. It utilizes an adaptation of quasi-convexity to cast training a neural network as a bi-quasi-convex optimization problem. We show that for neural network configurations with both differentiable (e.g. sigmoid) and non-differentiable (e.g. ReLU) activation functions, we can perform the alternations effectively in this formulation. DANTE can also be extended to networks with multiple hidden layers. In experiments on standard datasets, neural networks trained using the proposed method were found to be promising and competitive to traditional backpropagation techniques, both in terms of quality of the solution, as well as training speed.Comment: 19 page