Studies on elastic coupling parameters of fracture modes in orthotropic materials

The characterisation of cracks is usually done using the well known three basic fracture modes, namely opening, shearing and tearing modes. In isotropic materials these modes are uncoupled and provide a convenient way to define the fracture parameters. It is well known that these fracture modes are coupled in anisotropic materials. In the case of orthotropic materials also, coupling exists between the fracture modes, unless the crack plane coincides with one of the axes of orthotropy. The strength of coupling depends upon the orientation of the axes of orthotropy with respect to the crack plane and so the energy release rate components associated with each of the modes vary with crack orientation. The variation, of these energy release rate components with the crack orientation with respect to orthotropic axes, is analyzed in this paper. Results indicate that in addition to the orthotropic planes there exists other planes with reference to which fracture modes are uncoupled.

Determination of diffusion parameters and activation energy of diffusion in V3Si phase with A15 crystal structure

Diffusion such is the integrated diffusion coefficient of the phase, the tracer diffusion coefficient of species at different temperatures and the activation energy for diffusion, are determined in V3Si phase with A15 crystal structure. The tracer diffusion coefficient of Si Was found to be negligible compared to the tracer diffusion coefficient of V. The calculated diffusion parameters will help to validate the theoretical analysis of defect structure of the phase, which plays an important role in the superconductivity.

Non-linear regression model for spatial variation in precipitation chemistry for South India

Chemical composition of rainwater changes from sea to inland under the influence of several major factors - topographic location of area, its distance from sea, annual rainfall. A model is developed here to quantify the variation in precipitation chemistry under the influence of inland distance and rainfall amount. Various sites in India categorized as 'urban', 'suburban' and 'rural' have been considered for model development. pH, HCO3, NO3 and Mg do not change much from coast to inland while, SO4 and Ca change is subjected to local emissions. Cl and Na originate solely from sea salinity and are the chemistry parameters in the model. Non-linear multiple regressions performed for the various categories revealed that both rainfall amount and precipitation chemistry obeyed a power law reduction with distance from sea. Cl and Na decrease rapidly for the first 100 km distance from sea, then decrease marginally for the next 100 km, and later stabilize. Regression parameters estimated for different cases were found to be consistent (R-2 similar to 0.8). Variation in one of the parameters accounted for urbanization. Model was validated using data points from the southern peninsular region of the country. Estimates are found to be within 99.9% confidence interval. Finally, this relationship between the three parameters - rainfall amount, coastline distance, and concentration (in terms of Cl and Na) was validated with experiments conducted in a small experimental watershed in the south-west India. Chemistry estimated using the model was in good correlation with observed values with a relative error of similar to 5%. Monthly variation in the chemistry is predicted from a downscaling model and then compared with the observed data. Hence, the model developed for rain chemistry is useful in estimating the concentrations at different spatio-temporal scales and is especially applicable for south-west region of India. (C) 2008 Elsevier Ltd. All rights reserved.

A probabilistic constrained nonlinear optimization framework to optimize RED parameters

The random early detection (RED) technique has seen a lot of research over the years. However, the functional relationship between RED performance and its parameters viz,, queue weight (omega(q)), marking probability (max(p)), minimum threshold (min(th)) and maximum threshold (max(th)) is not analytically availa ble. In this paper, we formulate a probabilistic constrained optimization problem by assuming a nonlinear relationship between the RED average queue length and its parameters. This problem involves all the RED parameters as the variables of the optimization problem. We use the barrier and the penalty function approaches for its Solution. However (as above), the exact functional relationship between the barrier and penalty objective functions and the optimization variable is not known, but noisy samples of these are available for different parameter values. Thus, for obtaining the gradient and Hessian of the objective, we use certain recently developed simultaneous perturbation stochastic approximation (SPSA) based estimates of these. We propose two four-timescale stochastic approximation algorithms based oil certain modified second-order SPSA updates for finding the optimum RED parameters. We present the results of detailed simulation experiments conducted over different network topologies and network/traffic conditions/settings, comparing the performance of Our algorithms with variants of RED and a few other well known adaptive queue management (AQM) techniques discussed in the literature.

Soft-particle model analysis of effect of LPS on electrophoretic softness of Acidithiobacillus ferrooxidans grown in presence of different metal ions

The effect of Surface lipopolysaccharides (LPS) on the electrophoretic softness and fixed charge density in the ion-penetrable layer of Acidithiobacillus ferrooxidans cells grown in presence of copper or arsenic ions have been discussed, The electrophoretic mobility data were analyzed using the soft-particle electrophoresis theory. Cell surface potentials of all the strains based on soft-particle theory were lower than those estimated using the conventional Smoluchowski theory, Exposure to metal ions increased the Surface electrophoretic softness with decrease in the fixed charge density. Effect of cell surface lipopolysaccharides on the model parameters are investigated and discussed.

The Influence of Processing Parameters on Characteristics of an Aluminum Alloy Spray Deposition

In the present investigation, two nozzle configurations are used for spray deposition, convergent nozzle (nozzle-A), and convergent nozzle with 2 mm parallel portion attached at its end (nozzle-C) without changing the exit area. First, the conditions for subambient aspiration pressure, i.e., pressure at the tip of the melt delivery tube, are established by varying the protrusion length of the melt delivery tube at different applied gas pressures for both of the nozzles. Using these conditions, spray deposits in a reproducible manner are successfully obtained for 7075 Al alloy. The effect of applied gas pressure, flight distance, and nozzle configuration on various characteristics of spray deposition, viz., yield, melt flow rate, and gas-to-metal ratio, is examined. The over-spray powder is also characterized with respect to powder size distribution, shape, and microstructure. Some of the results are explained with the help of numerical analysis presented in an earlier article.

A Proposal for Concurrent Estimation of Static and Dynamic Nonlinearity of ADC

Despite great advances in very large scale integrated-circuit design and manufacturing, performance of even the best available high-speed, high-resolution analog-to-digital converter (ADC) is known to deteriorate while acquiring fast-rising, high-frequency, and nonrepetitive waveforms. Waveform digitizers (ADCs) used in high-voltage impulse recordings and measurements are invariably subjected to such waveforms. Errors resulting from a lowered ADC performance can be unacceptably high, especially when higher accuracies have to be achieved (e.g., when part of a reference measuring system). Static and dynamic nonlinearities (estimated independently) are vital indices for evaluating performance and suitability of ADCs to be used in such environments. Typically, the estimation of static nonlinearity involves 10-12 h of time or more (for a 12-b ADC) and the acquisition of millions of samples at high input frequencies for dynamic characterization. ADCs with even higher resolution and faster sampling speeds will soon become available. So, there is a need to reduce testing time for evaluating these parameters. This paper proposes a novel and time-efficient method for the simultaneous estimation of static and dynamic nonlinearity from a single test. This is achieved by conceiving a test signal, comprised of a high-frequency sinusoid (which addresses dynamic assessment) modulated by a low-frequency ramp (relevant to the static part). Details of implementation and results on two digitizers are presented and compared with nonlinearities determined by the existing standardized approaches. Good agreement in results and time savings achievable indicates its suitability.

An E-Convergence Method For The Evaluation Of Critical Parameters

A simple cconversence technique is applied to obtain accurate estimates of critical temperatures and critical it\ponmts of a few two- and threpdiniensional king models. When applied to the virial series for hard spheres and hard discs, this method predicts a divergence of the equation-of-state at the density of closest packing.

A Proposal for Concurrent Estimation of Static and Dynamic Nonlinearity of ADC

Despite great advances in very large scale integrated-circuit design and manufacturing, performance of even the best available high-speed, high-resolution analog-to-digital converter (ADC) is known to deteriorate while acquiring fast-rising, high-frequency, and nonrepetitive waveforms. Waveform digitizers (ADCs) used in high-voltage impulse recordings and measurements are invariably subjected to such waveforms. Errors resulting from a lowered ADC performance can be unacceptably high, especially when higher accuracies have to be achieved (e.g., when part of a reference measuring system). Static and dynamic nonlinearities (estimated independently) are vital indices for evaluating performance and suitability of ADCs to be used in such environments. Typically, the estimation of static nonlinearity involves 10-12 h of time or more (for a 12-b ADC) and the acquisition of millions of samples at high input frequencies for dynamic characterization. ADCs with even higher resolution and faster sampling speeds will soon become available. So, there is a need to reduce testing time for evaluating these parameters. This paper proposes a novel and time-efficient method for the simultaneous estimation of static and dynamic nonlinearity from a single test. This is achieved by conceiving a test signal, comprised of a high-frequency sinusoid (which addresses dynamic assessment) modulated by a low-frequency ramp (relevant to the static part). Details of implementation and results on two digitizers are presented and compared with nonlinearities determined by the existing standardized approaches. Good agreement in results and time savings achievable indicates its suitability.

Identification of parameters in unconfined aquifers

A method is presented for identification of parameters in unconfined aquifers from pumping tests, based on the optimisation of the objective function using the least squares approach. Four parameters are to be evaluated, namely: The hydraulic conductivity in the radial and the vertical directions, the storage coefficient and the specific yield. The sensitivity analysis technique is used for solving the optimisation problem. Besides eliminating the subjectivity involved in the graphical procedure, the method takes into account the field data at all time intervals without classifying them into small and large time intervals and does not use the approximation that the ratio of the storage coefficient to the specific yield tends to zero. Two illustrative examples are presented and it is found that the parameter estimates from the computational and graphical procedures differ fairly significantly.

A Fuzzy Approximation Scheme for Sequential Learning in Pattern Recognition

An adaptive learning scheme, based on a fuzzy approximation to the gradient descent method for training a pattern classifier using unlabeled samples, is described. The objective function defined for the fuzzy ISODATA clustering procedure is used as the loss function for computing the gradient. Learning is based on simultaneous fuzzy decisionmaking and estimation. It uses conditional fuzzy measures on unlabeled samples. An exponential membership function is assumed for each class, and the parameters constituting these membership functions are estimated, using the gradient, in a recursive fashion. The induced possibility of occurrence of each class is useful for estimation and is computed using 1) the membership of the new sample in that class and 2) the previously computed average possibility of occurrence of the same class. An inductive entropy measure is defined in terms of induced possibility distribution to measure the extent of learning. The method is illustrated with relevant examples.

Low-temperature and high-pressure Raman and x-ray studies of pyrochlore Tb2Ti2O7: Phonon anomalies and possible phase transition

We have carried out temperature- and pressure-dependent Raman and x-ray measurements on single crystals of Tb2Ti2O7. We attribute the observed anomalous temperature dependence of phonons to phonon-phonon anharmonic interactions. The quasiharmonic and anharmonic contributions to the temperature-dependent changes in phonon frequencies are estimated quantitatively using mode Grüneisen parameters derived from pressure-dependent Raman experiments and bulk modulus from high-pressure x-ray measurements. Further, our Raman and x-ray data suggest a subtle structural deformation of the pyrochlore lattice at ~9 GPa. We discuss possible implications of our results on the spin-liquid behavior of Tb2Ti2O7.

Estimation of cosmological parameters from neutral hydrogen observations of the post-reionization epoch

The emission from neutral hydrogen (HI) clouds in the post-reionization era (z <= 6), too faint to be individually detected, is present as a diffuse background in all low frequency radio observations below 1420MHz. The angular and frequency fluctuations of this radiation (similar to 1 mK) are an important future probe of the large-scale structures in the Universe. We show that such observations are a very effective probe of the background cosmological model and the perturbed Universe. In our study we focus on the possibility of determining the redshift-space distortion parameter beta, coordinate distance r(nu), and its derivative with redshift r(nu)('). Using reasonable estimates for the observational uncertainties and configurations representative of the ongoing and upcoming radio interferometers, we predict parameter estimation at a precision comparable with supernova Ia observations and galaxy redshift surveys, across a wide range in redshift that is only partially accessed by other probes. Future HI observations of the post-reionization era present a new technique, complementing several existing ones, to probe the expansion history and to elucidate the nature of the dark energy.

Effect of wave parameters on flood wave subsidence

A detailed analy~is on the propagation of a sinusoidal flood wave in a wide prismatic open channel b.as hen made by numc? ii.~ll~integrating We govemins nondimenional equations of unsteady flow in an open chamei. EmpE:dsis has been laid on the effect of wave parmefen on th propagation of 6.8 sinusoidal wave. Results show that the amount of subsidence is more in the case of small wave anplltude and wave duration cases. Further, wave duration has been noticed to have a relatively Vier influence on subsidence than wave amplitude. The speed at which the peak of the wave moves is observed to be a function of only the wave amplitude.