Modeling of growth and motion of equiaxed dendrites in a convecting melt

A numerical micro-scale model is developed to study the behavior of dendrite growth in presence of melt convection. In this method, an explicit, coupled enthalpy model is used to simulate the growth of an equiaxed dendrite, while a Volume of Fluid (VOF) method is used to track the movement of the dendrite in the convecting melt in a two-dimensional Eulerian framework. Numerical results demonstrate the effectiveness of the enthalpy model in simulating the dendritic growth involving complex shape, and the accuracy of VOF method in conserving mass and preserving the complex dendritic shape during motion. Simulations are performed in presence of uniform melt flow for both fixed and moving dendrites, and the difference in dendrite morphology is shown.

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.

A vision modeling framework for DHM using geometrically estimated FoV

Digital human modeling (DHM) involves modeling of structure, form and functional capabilities of human users for ergonomics simulation. This paper presents application of geometric procedures for investigating the characteristics of human visual capabilities which are particularly important in the context mentioned above. Using the cone of unrestricted directions through the pupil on a tessellated head model as the geometric interpretation of the clinical field-of-view (FoV), the results obtained are experimentally validated. Estimating the pupil movement for a given gaze direction using Listing's Law, FoVs are re-computed. Significant variation of the FoV is observed with the variation in gaze direction. A novel cube-grid representation, which integrated the unit-cube representation of directions and the enhanced slice representation has been introduced for fast and exact point classification for point visibility analysis for a given FoV. Computation of containment frequency of every grid-cell for a given set of FoVs enabled determination of percentile-based FoV contours for estimating the visual performance of a given population. This is a new concept which makes visibility analysis more meaningful from ergonomics point-of-view. The algorithms are fast enough to support interactive analysis of reasonably complex scenes on a typical desktop computer. (C) 2011 Elsevier Ltd. All rights reserved.

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.

Modeling stochastic hybrid systems

Stochastic hybrid systems arise in numerous applications of systems with multiple models; e.g., air traffc management, flexible manufacturing systems, fault tolerant control systems etc. In a typical hybrid system, the state space is hybrid in the sense that some components take values in a Euclidean space, while some other components are discrete. In this paper we propose two stochastic hybrid models, both of which permit diffusion and hybrid jump. Such models are essential for studying air traffic management in a stochastic framework.

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 of seepage flow through layered solis

A two-dimensional finite difference model, which solves mixed type of Richards' equation, whose non-linearity is dealt with modified Picard's iteration and strongly implicit procedure to solve the resulting equations, is presented. Modeling of seepage flow through heterogeneous soils, which is common in the field is addressed in the present study. The present model can be applied to both unsaturated and saturated soils and can handle very dry initial condition and steep wetting fronts. The model is validated by comparing experimental results reported in the literature. Newness of this two dimensional model is its application on layered soils with transient seepage face development, which has not been reported in the literature. Application of the two dimensional model for studying unconfined drainage due to sudden drop of water table at seepage face in layered soils is demonstrated. In the present work different sizes of rectangular flow domain with different types of layering are chosen. Sensitivity of seepage height due to problem dimension of layered system is studied. The effect of aspect ratio on seepage face development in case of the flow through layered soil media is demonstrated. The model is also applied to random heterogeneous soils in which the randomness of the model parameters is generated using the turning band technique. The results are discussed in terms of phreatic surface and seepage height development and also flux across the seepage face. Such accurate modeling of seepage face development and quantification of flux moving across the seepage face becomes important while modeling transport problems in variably saturated media.

Modeling of room temperature current-voltage measurements on homo-junction HgCdTe diodes exhibiting nonequilibrium effects

HgCdTe mid wave infrared (MWIR) n(+)/nu/p(+) homo-junction photodiodes with planar architecture are designed, fabricated, and measured at room temperature. An improved analytical I-V model is reported by incorporating trap assisted tunneling and electric field enhanced Shockley-Read-Hall generation recombination process due to dislocations. Tunneling currents are fitted before and after the Auger suppression of carriers with energy level of trap (E-t), trap density (N-t), and the doping concentrations of n(+) and nu regions as fitting parameters. Values of E-t and N-t are determined as 0.79 E-g and similar to 9 x 10(14) cm(-3), respectively, in all cases. Doping concentration of nu region was found to exhibit nonequilibrium depletion from a value of 2 x 10(16) to 4 x 10(15) cm(-3) for n(+) doping of 2 x 10(17) cm(-3). Pronounced negative differential resistance is observed in the homo-junction HgCdTe diodes. (C) 2012 American Institute of Physics. [doi:10.1063/1.3682483]

Modeling of ternary solubilities of solids in supercritical carbon dioxide in the presence of cosolvents or cosolutes

The investigation of ternary solubilities of solids is essential for the efficient design of extraction processes. The ternary solubilities of solids for cosolvent and cosolute systems are complex functions of temperature, pressure and cosolvent/cosolute composition. The intermolecular interactions between the molecules have a significant role in the solubilities of mixed solids in SCCO2 and cosolvent ternary systems. Two model equations were developed for ternary SCCO2 + cosolvent/cosolute systems by using association and activity coefficient models. Both the model equations consist of five adjustable parameters and correlate the ternary solubilities of solids in terms of temperature, pressure, density and cosolvent/cosolute composition. The model equation for cosolvent systems correlated 43 solid pollutants-cosolvent-SCCO2, while the model equation for cosolute systems correlated 19 solute-cosolute-SCCO2 systems available in literature. The average AARD of the model equations are 4.73% and 4.87% for cosolvent ternary systems and mixed solids in SCCO2, respectively. (C) 2011 Elsevier B.V. All rights reserved.

Characterization and finite element modeling of montmorillonite/polypropylene nanocomposites

Finite element modeling can be a useful tool for predicting the behavior of composite materials and arriving at desirable filler contents for maximizing mechanical performance. In the present study, to corroborate finite element analysis results, quantitative information on the effect of reinforcing polypropylene (PP) with various proportions of nanoclay (in the range of 3-9% by weight) is obtained through experiments; in particular, attention is paid to the Young's modulus, tensile strength and failure strain. Micromechanical finite element analysis combined with Monte Carlo simulation have been carried out to establish the validity of the modeling procedure and accuracy of prediction by comparing against experimentally determined stiffness moduli of nanocomposites. In the same context, predictions of Young's modulus yielded by theoretical micromechanics-based models are compared with experimental results. Macromechanical modeling was done to capture the non-linear stress-strain behavior including failure observed in experiments as this is deemed to be a more viable tool for analyzing products made of nanocomposites including applications of dynamics. (C) 2011 Elsevier Ltd. All rights reserved.

A coupled VOF-IBM-enthalpy approach for modeling motion and growth of equiaxed dendrites in a solidifying melt

A coupled methodology for simulating the simultaneous growth and motion of equiaxed dendrites in solidifying melts is presented. The model uses the volume-averaging principles and combines the features of the enthalpy method for modeling growth, immersed boundary method for handling the rigid solid-liquid interfaces, and the volume of fluid method for tracking the advection of the dendrite. The algorithm also performs explicit-implicit coupling between the techniques used. A two-dimensional framework with incompressible and Newtonian fluid is considered. Validation with available literature is performed and dendrite growth in the presence of rotational and buoyancy driven flow fields is studied. It is seen that the flow fields significantly alter the position and morphology of the dendrites. (C) 2012 Elsevier Inc. All rights reserved.

Spectroscopic Characterization and Modeling of Quadrupolar Charge-Transfer Dyes with Bulky Substituents

Joint experimental and theoretical work is presented on two quadrupolar D-pi-A-pi-D chromophores characterized by the same bulky donor (D) group and two different central cores. The first chromophore, a newly synthesized species with a malononitrile-based acceptor (A) group, has a V-shaped structure that makes its absorption spectrum very broad, covering most of the visible region. The second chromophore has a squaraine-based core and therefore a linear structure, as also evinced from its absorption spectra. Both chromophores show an anomalous red shift of the absorption band upon increasing solvent polarity, a feature that is ascribed to the large, bulky structure of the moleCules. For these molecules, the basic description of polar solvation in terms of a uniform reaction field fails. Indeed, a simple extension of the model to account for two independent reaction fields associated with the two molecular arms quantitatively reproduces the observed linear absorption and fluorescence as well as fluorescence anisotropy spectra, fully rationalizing their nontrivial dependence on solvent polarity. The model derived from the analysis of linear spectra is adopted to predict nonlinear spectra and specifically hyper-Rayleigh scattering and two-photon absorption spectra. In polar solvents, the V-shaped chromophore is predicted to have a large HRS response in a wide spectral region (approximately 600-1300 nm). Anomalously large and largely solvent-dependent HRS responses for the linear chromophores are ascribed to symmetry lowering induced by polar solvation and amplified in this bulky system by the presence of two reaction fields.