Effect of substrate surface roughness on electric current induced flow of liquid metals

Electric current can induce long-range flow of liquid metals over a conducting substrate. This work reports on the effect of the substrate surface roughness on the liquid metal-front velocity during such a flow. Experiments were conducted by passing electric current through liquid gallium placed over similar to 170 nm thick, 500 mu m wide gold and platinum films of varying roughness. The ensuing flow, thus, resembles micro-fluidics behavior in an open-channel. The liquid-front velocity decreased linearly with the substrate surface roughness; this is attributed to the reduction in the effective electric field along the liquid metal-substrate interface with the substrate surface roughness. (C) 2013 American Institute of Physics. http://dx.doi.org/10.1063/1.4790182]

Fast acoustic likelihood computation using low-rank matrix approximation

Acoustic modeling using mixtures of multivariate Gaussians is the prevalent approach for many speech processing problems. Computing likelihoods against a large set of Gaussians is required as a part of many speech processing systems and it is the computationally dominant phase for LVCSR systems. We express the likelihood computation as a multiplication of matrices representing augmented feature vectors and Gaussian parameters. The computational gain of this approach over traditional methods is by exploiting the structure of these matrices and efficient implementation of their multiplication.In particular, we explore direct low-rank approximation of the Gaussian parameter matrix and indirect derivation of low-rank factors of the Gaussian parameter matrix by optimum approximation of the likelihood matrix. We show that both the methods lead to similar speedups but the latter leads to far lesser impact on the recognition accuracy. Experiments on a 1138 word vocabulary RM1 task using Sphinx 3.7 system show that, for a typical case the matrix multiplication approach leads to overall speedup of 46%. Both the low-rank approximation methods increase the speedup to around 60%, with the former method increasing the word error rate (WER) from 3.2% to 6.6%, while the latter increases the WER from 3.2% to 3.5%.

The curvature of the liquid-vapor reduced pressure curve and its relation with the critical region

For most fluids, there exist a maximum and a minimum in the curvature of the reduced vapor pressure curve, p(r) = p(r)(T-r) (with p(r) = p/p(c) and T-r = T/T-c, p(c) and T-c being the pressure and temperature at the critical point). By analyzing National Institute of Standards and Technology (NIST) data on the liquid-vapor coexistence curve for 105 fluids, we find that the maximum occurs in the reduced temperature range 0.5 <= T-r <= 0.8 while the minimum occurs in the reduced temperature range 0.980 <= T-r <= 0.995. Vapor pressure equations for which d(2)p(r)/dT(r)(2) diverges at the critical point present a minimum in their curvature. Therefore, the point of minimum curvature can be used as a marker for the critical region. By using the well-known Ambrose-Walton (AW) vapor pressure equation we obtain the reduced temperatures of the maximum and minimum curvature in terms of the Pitzer acentric factor. The AW predictions are checked against those obtained from NIST data. (C) 2013 Elsevier Ltd. All rights reserved.

A method for measurement of planar liquid volume fraction in dense sprays

A methodology for measurement of planar liquid volume fraction in dense sprays using a combination of Planar Laser-Induced Fluorescence (PLIF) and Particle/Droplet Imaging Analysis (PDIA) is presented in this work. The PLIF images are corrected for loss of signal intensity due to laser sheet scattering, absorption and auto-absorption. The key aspect of this work pertains to simultaneously solving the equations involving the corrected PLIF signal and liquid volume fraction. From this, a quantitative estimate of the planar liquid volume fraction is obtained. The corrected PLIF signal and the corrected planar Mie scattering can be also used together to obtain the Sauter Mean Diameter (SMD) distribution by using data from the PDIA technique at a particular location for calibration. This methodology is applied to non-evaporating sprays of diesel and a more viscous pure plant oil at an injection pressure of 1000 bar and a gas pressure of 30 bar in a high pressure chamber. These two fuels are selected since their viscosity values are very different with a consequently very different spray structure. The spatial distribution of liquid volume fraction and SMD is obtained for two fuels. The proposed method is validated by comparing liquid volume fraction obtained by the current method with data from PDIA technique. (C) 2012 Elsevier Inc. All rights reserved.

A Finite Element Method Based Approach for Evaluating the Sensitivity of Faraday-Type Electromagnetic Flow Meter for Liquid Sodium Flow

Faraday-type electromagnetic flow meters are employed for measuring the flow rate of liquid sodium in fast breeder reactors. The calibration of such flow meters, owing to the required elaborative arrangements is rather difficult. On the other hand, theoretical approach requires solution of two coupled electromagnetic partial differential equation with profile of the flow and applied magnetic field as the inputs. This is also quite involved due to the 3D nature of the problem. Alternatively, Galerkin finite element method based numerical solution is suggested in the literature as an attractive option for the required calibration. Based on the same, a computer code in Matlab platform has been developed in this work with both 20 and 27 node brick elements. The boundary conditions are correctly defined and several intermediate validation exercises are carried out. Finally it is shown that the sensitivities predicted by the code for flow meters of four different dimensions agrees well with the results given by analytical expression, thereby providing strong validation. Sensitivity for higher flow rates, for which analytical approach does not exist, is shown to decrease with increase in flow velocity.

Nucleation dynamics and pool boiling characteristics of high pressure refrigerant using thermochromic liquid crystals

This paper reports an experimental investigation of oscillating temperature field beneath a single isolated nucleation site using a non-invasive TLC (thermochromic liquid crystal) based thermography technique. Empirical correlations are presented to demonstrate the influence of system pressure and wall heat flux on different ebullition characteristics in the nucleate pool boiling regime of refrigerant R-134a. TLC transient response and two-phase flow structure are captured using synchronized, high resolution imaging. It is observed that the area of influence of nucleation site exhibits a two-part distinct transient behavior during the bubble growth period and broadens to a maximum of 1.57 times the bubble diameter at the instant of bubble departure. This is accompanied by a sharp fall of 2.5 degrees C in the local excess temperature at the nucleation site, which results in momentary augmentation (similar to 40%) in the local heat transfer coefficient at the nucleation origin. The enhanced heat transfer rate observed during the bubble peel-off event is primarily due to transient micro-convection in the wake of the retreating bubble. Further, the results indicate that a slight increase in system pressure from 813.6 to 882.5 kPa has no considerable effect on either the wall superheat or the overall heat transfer coefficient and ebullition frequency. In addition, correlations have been obtained for bubble Reynolds number, Jackob number and the dimensionless bubble generation frequency in terms of modified boiling number.

Hybrid online non-negative matrix factorization for clustering of documents

When document corpus is very large, we often need to reduce the number of features. But it is not possible to apply conventional Non-negative Matrix Factorization(NMF) on billion by million matrix as the matrix may not fit in memory. Here we present novel Online NMF algorithm. Using Online NMF, we reduced original high-dimensional space to low-dimensional space. Then we cluster all the documents in reduced dimension using k-means algorithm. We experimentally show that by processing small subsets of documents we will be able to achieve good performance. The method proposed outperforms existing algorithms.

Ancilla-assisted quantum state tomography in multiqubit registers

The standard method of quantum state tomography (QST) relies on the measurement of a set of noncommuting observables, realized in a series of independent experiments. Ancilla-assisted QST (AAQST) proposed by Nieuwenhuizen and co-workers Phys. Rev. Lett. 92, 120402 (2004)] greatly reduces the number of independent measurements by exploiting an ancilla register in a known initial state. In suitable conditions AAQST allows mapping out density matrix of an input register in a single experiment. Here we describe methods for explicit construction of AAQST experiments in multiqubit registers. We also report nuclear magnetic resonance studies on AAQST of (i) a two-qubit input register using a one-qubit ancilla in an isotropic liquid-state system and (ii) a three-qubit input register using a two-qubit ancilla register in a partially oriented system. The experimental results confirm the effectiveness of AAQST in such multiqubit registers.

Effect of Ti concentration on the growth of Nb3Sn between solid Nb(Ti) and liquid Sn

The change in the growth rate of the Nb3Sn product phase because of Ti addition is studied for solid Nb(Ti)-liquid Sn interactions. The growth rate increased from no Ti to 1 at.% and 2 at.% of Ti in Nb, and the activation energy decreased from 221 kJ/mol to 146 kJ/mol. Based on the estimated values, the role of grain boundary and lattice diffusion is discussed in light of the possibility of increased grain boundary area and point defects such as antisites and vacancies.

Solid-liquid transition in polydisperse Lennard-Jones systems

We study melting of a face-centered crystalline solid consisting of polydisperse Lennard-Jones spheres with Gaussian polydispersity in size. The phase diagram reproduces the existence of a nearly temperature invariant terminal polydispersity (delta(t) similar or equal to 0.11), with no signature of reentrant melting. The absence of reentrant melting can be attributed to the influence of the attractive part of the potential upon melting. We find that at terminal polydispersity the fractional density change approaches zero, which seems to arise from vanishingly small compressibility of the disordered phase. At constant temperature and volume fraction the system undergoes a sharp transition from crystalline solid to the disordered amorphous or fluid state with increasing polydispersity. This has been quantified by second- and third-order rotational invariant bond orientational order, as well as by the average inherent structure energy. The translational order parameter also indicates a similar sharp structural change at delta similar or equal to 0.09 in case of T* = 1.0, phi = 0.58. The free energy calculation further supports the sharp nature of the transition. The third-order rotationally invariant bond order shows that with increasing polydispersity, the local cluster favors a more icosahedral arrangement and the system loses its local crystalline symmetry. Interestingly, the value of structure factor S(k) of the amorphous phase at delta similar or equal to 0.10 (just beyond the solid-liquid transition density at T* = 1) becomes 2.75, which is below the value of 2.85 required for freezing given by the empirical Hansen-Verlet rule of crystallization, well known in the theory of freezing.

Spatial Wavelet Approach to Local Matrix Crack Detection in Composite Beams with Ply Level Material Uncertainty

Wavelet coefficients based on spatial wavelets are used as damage indicators to identify the damage location as well as the size of the damage in a laminated composite beam with localized matrix cracks. A finite element model of the composite beam is used in conjunction with a matrix crack based damage model to simulate the damaged composite beam structure. The modes of vibration of the beam are analyzed using the wavelet transform in order to identify the location and the extent of the damage by sensing the local perturbations at the damage locations. The location of the damage is identified by a sudden change in spatial distribution of wavelet coefficients. Monte Carlo Simulations (MCS) are used to investigate the effect of ply level uncertainty in composite material properties such as ply longitudinal stiffness, transverse stiffness, shear modulus and Poisson's ratio on damage detection parameter, wavelet coefficient. In this study, numerical simulations are done for single and multiple damage cases. It is observed that spatial wavelets can be used as a reliable damage detection tool for composite beams with localized matrix cracks which can result from low velocity impact damage.

Near infrared detectors based on HgSe and HgCdSe quantum dots generated at the liquid-liquid interface

HgSe and Hg0.5Cd0.5Se quantum dos (QDs) are synthesized at room temperature by a novel liquid-liquid interface method and their photodetection properties in the near-IR region are investigated. The photodetection properties of our Te-free systems are found to be comparable to those of the previously reported high performance QD vis-IR detectors including HgTe. The present synthesis indicates the cost-effectiveness of selenium based IR detectors owing to the abundance and lower toxicity of selenium compared to tellurium.

Tb3+ sensitization in a deoxycholate organogel matrix, and selective quenching of luminescence by an aromatic nitro derivative

In this article, we present the discovery of a metallo-organogel derived from a Tb3+ salt and sodium deoxycholate (NaDCh) in methanol. The gel was made luminescent through sensitization of Tb3+ by doping with 2,3-dihydroxynaphthalene (DHN) in micromolar concentrations. Rheological measurements of the mechanical properties of the organogel confirmed the characteristics of a true gel. Significant quenching of Tb3+ luminescence was observed in the deoxycholate gel matrix by 2,4,7-trinitrofluorenone (TNF), but not by several other polynitro aromatics. Microscopic studies (AFM, TEM and SEM) revealed a highly entangled fibrous network. The xerogels retained luminescent properties suggesting the possibility for application in coatings, etc.

Effect of TiN particulate reinforcement on corrosive behaviour of aluminium 6061 composites in chloride medium

In the present investigation, the corrosive behaviour of Al 6061-TiN particulate composites prepared by liquid metallurgy has been studied in chloride medium using electroanalytical techniques such as Tafel, cyclic polarization and electrochemical impedance spectroscopy (EIS). Surface morphology of the sample electrodes was examined using scanning electron micrography and energy dispersive X-ray methods. X-ray diffraction technique was used to confirm inclusion of TiN particulates in the matrix alloy and identify the alloying elements and intermetallic compounds in the Al 6061 composites. Polarization studies indicate an increase in the corrosion resistance in composites compared to the matrix alloy. EIS study reveals that the polarization resistance (R (p)) increases with increase in TiN content in composites, thus confirming improved corrosion resistance in composites. The observed decrease in corrosion rate in the case of composites is due to decoupling between TiN particles and Al 6061 alloy. It is understood that after the initiation of corrosion, interfacial corrosion products may have decoupled the conducting ceramic TiN from Al 6061 matrix alloy thus eliminating the galvanic effect between them.

Multivariate Granger causality: an estimation framework based on factorization of the spectral density matrix

Granger causality is increasingly being applied to multi-electrode neurophysiological and functional imaging data to characterize directional interactions between neurons and brain regions. For a multivariate dataset, one might be interested in different subsets of the recorded neurons or brain regions. According to the current estimation framework, for each subset, one conducts a separate autoregressive model fitting process, introducing the potential for unwanted variability and uncertainty. In this paper, we propose a multivariate framework for estimating Granger causality. It is based on spectral density matrix factorization and offers the advantage that the estimation of such a matrix needs to be done only once for the entire multivariate dataset. For any subset of recorded data, Granger causality can be calculated through factorizing the appropriate submatrix of the overall spectral density matrix.