A PPCA based non-parametric modeling and retrieval of PD signal buried in excessive noise

The problem of on-line recognition and retrieval of relatively weak industrial signals such as partial discharges (PD), buried in excessive noise, has been addressed in this paper. The major bottleneck being the recognition and suppression of stochastic pulsive interference (PI) due to the overlapping broad band frequency spectrum of PI and PD pulses. Therefore, on-line, onsite, PD measurement is hardly possible in conventional frequency based DSP techniques. The observed PD signal is modeled as a linear combination of systematic and random components employing probabilistic principal component analysis (PPCA) and the pdf of the underlying stochastic process is obtained. The PD/PI pulses are assumed as the mean of the process and modeled instituting non-parametric methods, based on smooth FIR filters, and a maximum aposteriori probability (MAP) procedure employed therein, to estimate the filter coefficients. The classification of the pulses is undertaken using a simple PCA classifier. The methods proposed by the authors were found to be effective in automatic retrieval of PD pulses completely rejecting PI.

Performance modeling and architecture exploration of network processors

This paper proposes a Petri net model for a commercial network processor (Intel iXP architecture) which is a multithreaded multiprocessor architecture. We consider and model three different applications viz., IPv4 forwarding, network address translation, and IP security running on IXP 2400/2850. A salient feature of the Petri net model is its ability to model the application, architecture and their interaction in great detail. The model is validated using the Intel proprietary tool (SDK 3.51 for IXP architecture) over a range of configurations. We conduct a detailed performance evaluation, identify the bottleneck resource, and propose a few architectural extensions and evaluate them in detail.

A Long Memory Process Based Parametric Modeling and Recognition of PD Signal

We address the problem of recognition and retrieval of relatively weak industrial signal such as Partial Discharges (PD) buried in excessive noise. The major bottleneck being the recognition and suppression of stochastic pulsive interference (PI) which has similar time-frequency characteristics as PD pulse. Therefore conventional frequency based DSP techniques are not useful in retrieving PD pulses. We employ statistical signal modeling based on combination of long-memory process and probabilistic principal component analysis (PPCA). An parametric analysis of the signal is exercised for extracting the features of desired pules. We incorporate a wavelet based bootstrap method for obtaining the noise training vectors from observed data. The procedure adopted in this work is completely different from the research work reported in the literature, which is generally based on deserved signal frequency and noise frequency.

Modeling and optimization of a natural convection-based agricultural dryer

This study presents development of a computational fluid dynamic (CFD) model to predict unsteady, two-dimensional temperature, moisture and velocity distributions inside a novel, biomass-fired, natural convection-type agricultural dryer. Results show that in initial stages of drying, when material surface is wet and moisture is easily available, moisture removal rate from surface depends upon the condition of drying air. Subsequently, material surface becomes dry and moisture removal rate is driven by diffusion of moisture from inside to the material surface. An optimum 9-tray configuration is found to be more efficient than for the same mass of material and volume of dryer. A new configuration of dryer, mainly to explore its potential to increasing uniformity in drying across all trays, is also analyzed. This configuration involves diverting a portion of hot air before it enters over the first tray and is supplied directly at an intermediate location in the dryer. Uniformity in drying across trays has increased for the kind of material simulated.

Premixed flame response to equivalence ratio fluctuations: Comparison between reduced order modeling and detailed computations

Combustion instability events in lean premixed combustion systems can cause spatio-temporal variations in unburnt mixture fuel/air ratio. This provides a driving mechanism for heat-release oscillations when they interact with the flame. Several Reduced Order Modelling (ROM) approaches to predict the characteristics of these oscillations have been developed in the past. The present paper compares results for flame describing function characteristics determined from a ROM approach based on the level-set method, with corresponding results from detailed, fully compressible reacting flow computations for the same two dimensional slot flame configuration. The comparison between these results is seen to be sensitive to small geometric differences in the shape of the nominally steady flame used in the two computations. When the results are corrected to account for these differences, describing function magnitudes are well predicted for frequencies lesser than and greater than a lower and upper cutoff respectively due to amplification of flame surface wrinkling by the convective Darrieus-Landau (DL) instability. However, good agreement in describing function phase predictions is seen as the ROM captures the transit time of wrinkles through the flame correctly. Also, good agreement is seen for both magnitude and phase of the flame response, for large forcing amplitudes, at frequencies where the DL instability has a minimal influence. Thus, the present ROM can predict flame response as long as the DL instability, caused by gas expansion at the flame front, does not significantly alter flame front perturbation amplitudes as they traverse the flame. (C) 2012 The Combustion Institute. Published by Elsevier Inc. All rights reserved.

Functional characterization, homology modeling and docking studies of beta-glucosidase responsible for bioactivation of cyanogenic hydroxynitrile glucosides from Leucaena leucocephala (subabul)

Glycosyl hydrolase family 1 beta-glucosidases are important enzymes that serve many diverse functions in plants including defense, whereby hydrolyzing the defensive compounds such as hydroxynitrile glucosides. A hydroxynitrile glucoside cleaving beta-glucosidase gene (Llbglu1) was isolated from Leucaena leucocephala, cloned into pET-28a (+) and expressed in E. coli BL21 (DE3) cells. The recombinant enzyme was purified by Ni-NTA affinity chromatography. The optimal temperature and pH for this beta-glucosidase were found to be 45 A degrees C and 4.8, respectively. The purified Llbglu1 enzyme hydrolyzed the synthetic glycosides, pNPGlucoside (pNPGlc) and pNPGalactoside (pNPGal). Also, the enzyme hydrolyzed amygdalin, a hydroxynitrile glycoside and a few of the tested flavonoid and isoflavonoid glucosides. The kinetic parameters K (m) and V (max) were found to be 38.59 mu M and 0.8237 mu M/mg/min for pNPGlc, whereas for pNPGal the values were observed as 1845 mu M and 0.1037 mu M/mg/min. In the present study, a three dimensional (3D) model of the Llbglu1 was built by MODELLER software to find out the substrate binding sites and the quality of the model was examined using the program PROCHEK. Docking studies indicated that conserved active site residues are Glu 199, Glu 413, His 153, Asn 198, Val 270, Asn 340, and Trp 462. Docking of rhodiocyanoside A with the modeled Llbglu1 resulted in a binding with free energy change (Delta G) of -5.52 kcal/mol on which basis rhodiocyanoside A could be considered as a potential substrate.

Effect of resonator length and working fluid on the performance of twin thermoacoustic heat engine - experimental and simulation studies

Success in the advancement of thermoacoustic field led the researchers to develop the thermoacoustic engines which found its applications in various fields such as refrigeration, gas mixture separation, natural gas liquefaction, and cryogenics. The objective of this study is to design and fabricate the twin thermoacoustic heat engine (TAHE) producing the acoustic waves with high resonance frequencies which is used to drive a thermoacoustic refrigerator efficiently by the influence of geometrical parameters and working fluids. Twin TAHE has gained significant attention due to the production of high intensity acoustic waves than single TAHE. In order to drive an efficient thermoacoustic refrigerator, a twin thermoacoustic heat engine is built up and its performance are analysed by varying the resonator length and working fluid. The performance is measured in terms of onset temperature difference, resonance frequency and pressure amplitude of the oscillations generated from twin TAHE. The simulation is performed using free software DeltaEC, from LANL, USA. The simulated DeltaEC results are compared with experimental results and the deviations are found within +10%.

Experimental and simulation studies on the performance of standing wave thermoacoustic prime mover for pulse tube refrigerator

The thermoacoustic prime mover (TAPM) has gained considerable attention as a pressure wave generator to drive pulse tube refrigerator (PTR) due to no moving parts, reasonable efficiency, use of environmental friendly working fluids etc. To drive PTCs, lower frequencies (f) with larger pressure amplitudes (Delta P) are essential, which are affected by geometric and operating parameters of TAPM as well as working fluids. For driving PTRs, a twin standing wave TAPM is built and studied by using different working fluids such as helium, argon, nitrogen and their binary mixtures. Simulation results of DeltaEc are compared with experimental data wherever possible. DeltaEc predicts slightly increased resonance frequencies, but gives larger Delta P and lower temperature difference Delta T across stack. High mass number working fluid leads to lower frequency with larger Delta P, but higher Delta T. Studies indicate that the binary gas mixture of right composition with lower Delta T can be arrived at to drive TAPM of given geometry. (C) 2013 Elsevier Ltd and IIR. All rights reserved.

EESM-Based Link Adaptation in Point-to-Point and Multi-Cell OFDM Systems: Modeling and Analysis

In contemporary wideband orthogonal frequency division multiplexing (OFDM) systems, such as Long Term Evolution (LTE) and WiMAX, different subcarriers over which a codeword is transmitted may experience different signal-to-noise-ratios (SNRs). Thus, adaptive modulation and coding (AMC) in these systems is driven by a vector of subcarrier SNRs experienced by the codeword, and is more involved. Exponential effective SNR mapping (EESM) simplifies the problem by mapping this vector into a single equivalent fiat-fading SNR. Analysis of AMC using EESM is challenging owing to its non-linear nature and its dependence on the modulation and coding scheme. We first propose a novel statistical model for the EESM, which is based on the Beta distribution. It is motivated by the central limit approximation for random variables with a finite support. It is simpler and as accurate as the more involved ad hoc models proposed earlier. Using it, we develop novel expressions for the throughput of a point-to-point OFDM link with multi-antenna diversity that uses EESM for AMC. We then analyze a general, multi-cell OFDM deployment with co-channel interference for various frequency-domain schedulers. Extensive results based on LTE and WiMAX are presented to verify the model and analysis, and gain new insights.

Crack stability in edge-notched clamped beam specimens: modeling and experiments

Stability of a fracture toughness testing geometry is important to determine the crack trajectory and R-curve behavior of the specimen. Few configurations provide for inherent geometric stability, especially when the specimen being tested is brittle. We propose a new geometrical construction called the single edge notched clamped bend specimen (SENCB), a modified form of three point bending, yielding stable cracking under load control. It is shown to be particularly suitable for small-scale structures which cannot be made free-standing, (e.g., thin films, coatings). The SENCB is elastically clamped at the two ends to its parent material. A notch is inserted at the bottom center and loaded in bending, to fracture. Numerical simulations are carried out through extended finite element method to derive the geometrical factor f(a/W) and for different beam dimensions. Experimental corroborations of the FEM results are carried out on both micro-scale and macro-scale brittle specimens. A plot of vs a/W, is shown to rise initially and fall off, beyond a critical a/W ratio. The difference between conventional SENB and SENCB is highlighted in terms of and FEM simulated stress contours across the beam cross-section. The `s of bulk NiAl and Si determined experimentally are shown to match closely with literature values. Crack stability and R-curve effect is demonstrated in a PtNiAl bond coat sample and compared with predicted crack trajectories from the simulations. The stability of SENCB is shown for a critical range of a/W ratios, proving that it can be used to get controlled crack growth even in brittle samples under load control.

Investigation of selective sensing of a diamine for aldehyde by experimental and simulation studies

An organic molecule-o-phenylene diamine (OPD)-is selected as an aldehyde sensing material. It is studied for selectivity to aldehyde vapours both by experiment and simulation. A chemiresistor based sensor for detection of aldehyde vapours is fabricated. An o-phenylene diamine-carbon black composite is used as the sensing element. The amine groups in the OPD would interact with the carbonyl groups of the aldehydes. The selectivity and cross-sensitivity of the OPD-CB sensor to VOCs aldehyde, ketone and alcohol-are studied. The sensor shows good response to aldehydes compared to other VOCs. The higher response for aldehydes is attributed to the interaction of the carbonyl oxygen of aldehydes with-NH2 groups of OPD. The surface morphology of the sensing element is studied by scanning electron microscopy. The OPD-CB sensor is responsive to 10 ppm of formaldehyde. The interaction of the VOCs with the OPD-CB nanocomposite is investigated by molecular dynamics studies. The interaction energies of the analyte with the OPD-CB nanocomposite were calculated. It is observed that the interaction energies for aldehydes are higher than those for other analytes. Thus the OPD-CB sensor shows selectivity to aldehydes. The simulated radial distribution function is calculated for the O-H pair of analyte and OPD which further supports the finding that the amine groups are involved in the interaction. These results suggest that it is important and easy to identify appropriate sensing materials based on the understanding of analyte interaction properties.

Girsanov Transformation-Based Reliability Modeling and Testing of Actively Controlled Structures

The problem of estimation of the time-variant reliability of actively controlled structural dynamical systems under stochastic excitations is considered. Monte Carlo simulations, reinforced with Girsanov transformation-based sampling variance reduction, are used to tackle the problem. In this approach, the external excitations are biased by an additional artificial control force. The conflicting objectives of the two control forces-one designed to reduce structural responses and the other to promote limit-state violations (but to reduce sampling variance)-are noted. The control for variance reduction is fashioned after design-point oscillations based on a first-order reliability method. It is shown that for structures that are amenable to laboratory testing, the reliability can be estimated experimentally with reduced testing times by devising a procedure based on the ideas of the Girsanov transformation. Illustrative examples include studies on a building frame with a magnetorheologic damper-based isolation system subject to nonstationary random earthquake excitations. (C) 2014 American Society of Civil Engineers.