Granular superconductors:from the nonlinear σ model to the Bose-Hubbard description

We modify a nonlinear σ model (NLσM) for the description of a granular disordered system in the presence of both the Coulomb repulsion and the Cooper pairing. We show that under certain controlled approximations the action of this model is reduced to the Ambegaokar-Eckern-Schön (AES) action, which is further reduced to the Bose-Hubbard (or “dirty-boson”) model with renormalized coupling constants. We obtain an effective action which is more general than the AES one but still simpler than the full NLσM action. This action can be applied in the region of parameters where the reduction to the AES or the Bose-Hubbard model is not justified. This action may lead to a different picture of the superconductor-insulator transition in two-dimensional systems.

Blue-detuned optical ring trap for Bose-Einstein condensates based on conical refraction

We present a novel approach for the optical manipulation of neutral atoms in annular light structures produced by the phenomenon of conical refraction occurring in biaxial optical crystals. For a beam focused to a plane behind the crystal, the focal plane exhibits two concentric bright rings enclosing a ring of null intensity called the Poggendorff ring. We demonstrate both theoretically and experimentally that the Poggendorff dark ring of conical refraction is confined in three dimensions by regions of higher intensity. We derive the positions of the confining intensity maxima and minima and discuss the application of the Poggendorff ring for trapping ultra-cold atoms using the repulsive dipole force of blue-detuned light. We give analytical expressions for the trapping frequencies and potential depths along both the radial and the axial directions. Finally, we present realistic numerical simulations of the dynamics of a 87Rb Bose-Einstein condensate trapped inside the Poggendorff ring which are in good agreement with corresponding experimental results.

On some Mixture Distributions

The aim of this paper is to establish some mixture distributions that arise in stochastic processes. Some basic functions associated with the probability mass function of the mixture distributions, such as k-th moments, characteristic function and factorial moments are computed. Further we obtain a three-term recurrence relation for each established mixture distribution.

A mixture density network approach to modelling and exploiting uncertainty in nonlinear control problems

In nonlinear and stochastic control problems, learning an efficient feed-forward controller is not amenable to conventional neurocontrol methods. For these approaches, estimating and then incorporating uncertainty in the controller and feed-forward models can produce more robust control results. Here, we introduce a novel inversion-based neurocontroller for solving control problems involving uncertain nonlinear systems which could also compensate for multi-valued systems. The approach uses recent developments in neural networks, especially in the context of modelling statistical distributions, which are applied to forward and inverse plant models. Provided that certain conditions are met, an estimate of the intrinsic uncertainty for the outputs of neural networks can be obtained using the statistical properties of networks. More generally, multicomponent distributions can be modelled by the mixture density network. Based on importance sampling from these distributions a novel robust inverse control approach is obtained. This importance sampling provides a structured and principled approach to constrain the complexity of the search space for the ideal control law. The developed methodology circumvents the dynamic programming problem by using the predicted neural network uncertainty to localise the possible control solutions to consider. A nonlinear multi-variable system with different delays between the input-output pairs is used to demonstrate the successful application of the developed control algorithm. The proposed method is suitable for redundant control systems and allows us to model strongly non-Gaussian distributions of control signal as well as processes with hysteresis. © 2004 Elsevier Ltd. All rights reserved.

A Bayesian Spatial Mixture Model for FMRI Analysis

We develop, implement and study a new Bayesian spatial mixture model (BSMM). The proposed BSMM allows for spatial structure in the binary activation indicators through a latent thresholded Gaussian Markov random field. We develop a Gibbs (MCMC) sampler to perform posterior inference on the model parameters, which then allows us to assess the posterior probabilities of activation for each voxel. One purpose of this article is to compare the HJ model and the BSMM in terms of receiver operating characteristics (ROC) curves. Also we consider the accuracy of the spatial mixture model and the BSMM for estimation of the size of the activation region in terms of bias, variance and mean squared error. We perform a simulation study to examine the aforementioned characteristics under a variety of configurations of spatial mixture model and BSMM both as the size of the region changes and as the magnitude of activation changes.

Novel Ni-Mg-Al-Ca catalyst for enhanced hydrogen production for the pyrolysis-gasification of a biomass/plastic mixture

A Ni-Mg-Al-Ca catalyst was prepared by a co-precipitation method for hydrogen production from polymeric materials. The prepared catalyst was designed for both the steam cracking of hydrocarbons and for the in situ absorption of CO2 via enhancement of the water-gas shift reaction. The influence of Ca content in the catalyst and catalyst calcination temperature in relation to the pyrolysis-gasification of a wood sawdust/polypropylene mixture was investigated. The highest hydrogen yield of 39.6molH2/g Ni with H2/CO ratio of 1.90 was obtained in the presence of the Ca containing catalyst of molar ratio Ni:Mg:Al:Ca=1:1:1:4, calcined at 500°C. In addition, thermogravimetric and morphology analyses of the reacted catalysts revealed that Ca introduction into the Ni-Mg-Al catalyst prevented the deposition of filamentous carbon on the catalyst surface. Furthermore, all metals were well dispersed in the catalyst after the pyrolysis-gasification process with 20-30nm of NiO sized particles observed after the gasification without significant aggregation.

Towards asphalt mixture morphology evaluation with the virtual specimen approach

The morphology of asphalt mixture can be defined as a set of parameters describing the geometrical characteristics of its constituent materials, their relative proportions as well as spatial arrangement in the mixture. The present study is carried out to investigate the effect of the morphology on its meso- and macro-mechanical response. An analysis approach is used for the meso-structural characterisation based on the X-ray computed tomography (CT) data. Image processing techniques are used to systematically vary the internal structure to obtain different morphology structures. A morphology framework is used to characterise the average mastic coating thickness around the main load carrying structure in the structures. The uniaxial tension simulation shows that the mixtures with the lowest coating thickness exhibit better inter-particle interaction with more continuous load distribution chains between adjacent aggregate particles, less stress concentrations and less strain localisation in the mastic phase.

Developmental exposure to a complex PAH mixture causes persistent behavioral effects in naive Fundulus heteroclitus (killifish) but not in a population of PAH-adapted killifish.

Acute exposures to some individual polycyclic aromatic hydrocarbons (PAHs) and complex PAH mixtures are known to cause cardiac malformations and edema in the developing fish embryo. However, the heart is not the only organ impacted by developmental PAH exposure. The developing brain is also affected, resulting in lasting behavioral dysfunction. While acute exposures to some PAHs are teratogenically lethal in fish, little is known about the later life consequences of early life, lower dose subteratogenic PAH exposures. We sought to determine and characterize the long-term behavioral consequences of subteratogenic developmental PAH mixture exposure in both naive killifish and PAH-adapted killifish using sediment pore water derived from the Atlantic Wood Industries Superfund Site. Killifish offspring were embryonically treated with two low-level PAH mixture dilutions of Elizabeth River sediment extract (ERSE) (TPAH 5.04 μg/L and 50.4 μg/L) at 24h post fertilization. Following exposure, killifish were raised to larval, juvenile, and adult life stages and subjected to a series of behavioral tests including: a locomotor activity test (4 days post-hatch), a sensorimotor response tap/habituation test (3 months post hatch), and a novel tank diving and exploration test (3months post hatch). Killifish were also monitored for survival at 1, 2, and 5 months over 5-month rearing period. Developmental PAH exposure caused short-term as well as persistent behavioral impairments in naive killifish. In contrast, the PAH-adapted killifish did not show behavioral alterations following PAH exposure. PAH mixture exposure caused increased mortality in reference killifish over time; yet, the PAH-adapted killifish, while demonstrating long-term rearing mortality, had no significant changes in mortality associated with ERSE exposure. This study demonstrated that early embryonic exposure to PAH-contaminated sediment pore water caused long-term locomotor and behavioral alterations in killifish, and that locomotor alterations could be observed in early larval stages. Additionally, our study highlights the resistance to behavioral alterations caused by low-level PAH mixture exposure in the adapted killifish population. Furthermore, this is the first longitudinal behavioral study to use killifish, an environmentally important estuarine teleost fish, and this testing framework can be used for future contaminant assessment.

Strontium isotope analysis of seawater and at a mixture of planktic foraminifera during the Paleocene and Early Eocene from different holes of ODP Leg 2008

We refined the strontium isotope seawater curve for the Paleocene and early Eocene by analysis of samples recovered from the Walvis Ridge during Ocean Drilling Project (ODP) Leg 208. The highest 87Sr/86Sr values occurred in the earliest Paleocene at 65 Ma and generally decreased throughout the Paleocene, reaching minimum values between 53 and 51 Ma in the early Eocene before beginning to increase again at 50 Ma. A plausible explanation for the 87Sr/86Sr decrease between 65 and 51 Ma is increased rates of hydrothermal activity and/or the eruption and weathering of large igneous provinces (e.g., Deccan Traps and North Atlantic). Strontium isotope variations closely parallel sea level and benthic d18O changes during the late Paleocene and early Eocene, supporting previous studies linking tectonic reorganization and increased volcanism to high sea level, high CO2, and warm global temperatures.

LES of flame acceleration and DDT in hydrogen-air mixture using artificially thickened flame approach and detailed chemical kinetics

A large eddy simulation is performed to study the deflagration to detonation transition phenomenon in an obstructed channel containing premixed stoichiometric hydrogen–air mixture. Two-dimensional filtered reactive Navier–Stokes equations are solved utilizing the artificially thickened flame approach (ATF) for modeling sub-grid scale combustion. To include the effect of induction time, a 27-step detailed mechanism is utilized along with an in situ adaptive tabulation (ISAT) method to reduce the computational cost due to the detailed chemistry. The results show that in the slow flame propagation regime, the flame–vortex interaction and the resulting flame folding and wrinkling are the main mechanisms for the increase of the flame surface and consequently acceleration of the flame. Furthermore, at high speed, the major mechanisms responsible for flame propagation are repeated reflected shock–flame interactions and the resulting baroclinic vorticity. These interactions intensify the rate of heat release and maintain the turbulence and flame speed at high level. During the flame acceleration, it is seen that the turbulent flame enters the ‘thickened reaction zones’ regime. Therefore, it is necessary to utilize the chemistry based combustion model with detailed chemical kinetics to properly capture the salient features of the fast deflagration propagation.

Rheology and Microfluidic flows of a cationic surfactant and hydrotropic salt mixture

Thesis (Ph.D.)--University of Washington, 2016-08

Understanding near Fermi-level electronic structure through x-ray emission spectroscopy

Thesis (Ph.D.)--University of Washington, 2016-08

Effect of explosive mixture on quality of explosive welds of copper to aluminium

The aim of this research is to investigate the influence of explosive ratio and type of sensitizer on the quality of explosive welds between copper and aluminium alloy plates. The welds were performed on a partially overlapping joint configuration using an emulsion explosive (EE) with two different sensitizers, hollow glass microspheres (HGMS) and expanded polystyrene spheres (EPS). Welds with an improved surface were achieved by using the HGMS sensitizer. A higher wave amplitude was registered in welds produced with the EPS sensitizer. In turn, the dimension of the molten pockets was influenced by the explosive ratio, increasing in size with increases in the values of this parameter. The intermetallic content of these zones varied according to the sensitizer type. Unlike the CuAl2 phase, the Cu-richer phases CuAl and Cu9Al4 were only identified in welds performed using the EPS sensitizer. An increase in hardness was observed at the interface of all welds, which resulted from both the presence of intermetallic phases and the plastic deformation of the materials promoted by the impact. This effect was most evident on the aluminium alloy side. All the welds had a greater strength than copper, i.e. the weakest material of the joint. (C) 2016 Elsevier Ltd. All rights reserved.

Estimating Bat and Bird Mortality Occurring at Wind Energy Turbines from Covariates and Carcass Searches Using Mixture Models

Environmental impacts of wind energy facilities increasingly cause concern, a central issue being bats and birds killed by rotor blades. Two approaches have been employed to assess collision rates: carcass searches and surveys of animals prone to collisions. Carcass searches can provide an estimate for the actual number of animals being killed but they offer little information on the relation between collision rates and, for example, weather parameters due to the time of death not being precisely known. In contrast, a density index of animals exposed to collision is sufficient to analyse the parameters influencing the collision rate. However, quantification of the collision rate from animal density indices (e.g. acoustic bat activity or bird migration traffic rates) remains difficult. We combine carcass search data with animal density indices in a mixture model to investigate collision rates. In a simulation study we show that the collision rates estimated by our model were at least as precise as conventional estimates based solely on carcass search data. Furthermore, if certain conditions are met, the model can be used to predict the collision rate from density indices alone, without data from carcass searches. This can reduce the time and effort required to estimate collision rates. We applied the model to bat carcass search data obtained at 30 wind turbines in 15 wind facilities in Germany. We used acoustic bat activity and wind speed as predictors for the collision rate. The model estimates correlated well with conventional estimators. Our model can be used to predict the average collision rate. It enables an analysis of the effect of parameters such as rotor diameter or turbine type on the collision rate. The model can also be used in turbine-specific curtailment algorithms that predict the collision rate and reduce this rate with a minimal loss of energy production.

Spectroscopic Studies of Fermi LAT Blazars

Blazar research offers a view to one of the most energetic physical processes known to man. The high-energy end of blazar emission has been probed by the Fermi satellite mission since 2008, and it has catalogued more than a thousand gamma- ray bright blazars. However, a large fraction of these sources have no spectroscopic classification at lower energies. In this thesis, optical spectra for sixteen Fermi blazar candidates are published. The optical spectroscopic data have been observed with the Nordic Optical Telescope on the island of La Palma, Spain, during the summer of 2015. The ALFOSC instrument was used, with exposure times from 800 to 3000 seconds per target, yielding signal- to-noise ratios from 10 to 38. All of the sixteen targets show a flat, featureless optical spectrum, characteristic to BL Lacertae objects. The spectra of two targets contain faint emission features, and faint absorption features are seen in three targets. However, none of the features could be reliably identified. Therefore all of the targets are classified as BL Lacertae objects. This classification is supported by the statistical distribution of Fermi -selected active galactic nuclei; more than half of the identified Fermi AGN are BL Lacs. However, the classification of this sample could be improved further with a new observing campaign. This is especially true for the objects with uncertain spectral features.