An adaptive singular ES-FEM for mechanics problems with singular field of arbitrary order

This paper presents a singular edge-based smoothed finite element method (sES-FEM) for mechanics problems with singular stress fields of arbitrary order. The sES-FEM uses a basic mesh of three-noded linear triangular (T3) elements and a special layer of five-noded singular triangular elements (sT5) connected to the singular-point of the stress field. The sT5 element has an additional node on each of the two edges connected to the singular-point. It allows us to represent simple and efficient enrichment with desired terms for the displacement field near the singular-point with the satisfaction of partition-of-unity property. The stiffness matrix of the discretized system is then obtained using the assumed displacement values (not the derivatives) over smoothing domains associated with the edges of elements. An adaptive procedure for the sES-FEM is proposed to enhance the quality of the solution with minimized number of nodes. Several numerical examples are provided to validate the reliability of the present sES-FEM method. (C) 2012 Elsevier B.V. All rights reserved.

Statistical Methods for Accelerated Life Testing with Particular Reference to Resin Impregnated Paper Bushings

Electrical failure of insulation is known to be an extremal random process wherein nominally identical pro-rated specimens of equipment insulation, at constant stress fail at inordinately different times even under laboratory test conditions. In order to be able to estimate the life of power equipment, it is necessary to run long duration ageing experiments under accelerated stresses, to acquire and analyze insulation specific failure data. In the present work, Resin Impregnated Paper (RIP) a relatively new insulation system of choice used in transformer bushings, is taken as an example. The failure data has been processed using proven statistical methods, both graphical and analytical. The physical model governing insulation failure at constant accelerated stress has been assumed to be based on temperature dependent inverse power law model.

Device oriented statistical modeling method for process variability in 45nm analog CMOS technology

With the rapid scaling down of the semiconductor process technology, the process variation aware circuit design has become essential today. Several statistical models have been proposed to deal with the process variation. We propose an accurate BSIM model for handling variability in 45nm CMOS technology. The MOSFET is designed to meet the specification of low standby power technology of International Technology Roadmap for Semiconductors (ITRS).The process parameters variation of annealing temperature, oxide thickness, halo dose and title angle of halo implant are considered for the model development. One parameter variation at a time is considered for developing the model. The model validation is done by performance matching with device simulation results and reported error is less than 10%.© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

Fracture studies on 3D geometrically similar beams

In the present work, a discrete numerical approach is adopted to understand size effect and fracture behavior in concrete. First, a comparison is performed between 2D and 3D geometrically similar structures to analyze thickness effect. The study is supplemented with element failure pattern to analyze crack propagation. Further, changing influence of notch to depth ratio is analyzed by comparing 3D geometrically similar structures with different values of notch depth ratio. Finally, a statistical analysis is performed to understand the influence of structure size and heterogeneity on regression parameters namely Bf(t)' and D-0. (C) 2012 Elsevier Ltd. All rights reserved.

Thermal vibration analysis of monolayer graphene embedded in elastic medium based on nonlocal continuum mechanics

This paper presents the thermal vibration analysis of single-layer graphene sheet embedded in polymer elastic medium, using the plate theory and nonlocal continuum mechanics for small scale effects. The graphene is modeled based on continuum plate theory and axial stress caused by the thermal effects is also considered. Nonlocal governing equation of motion for this graphene sheet system is derived from the principle of virtual displacements. The closed form solution for thermal-vibration frequencies of a simply supported rectangular nanoplate has been obtained by using the Navier's method of solution. Numerical results obtained by the present theory are compared with available solutions in the literature and the molecular dynamics results. The influences of the small scale coefficient, the room or low temperature, the high temperature, the half wave number and the aspect ratio of nanoplate on the natural frequencies are considered and discussed in detail. The thermal vibration analysis of single- and double-layer graphene sheets are considered for the analysis. The mode shapes of the respective graphene system are also captured in this work. The present analysis results can be used for the design of the next generation of nanodevices that make use of the thermal vibration properties of the graphene.

Experimental Studies on the Mechanics of Cohesive Frictional Granular Media

The mechanical behaviour of cohesive-frictional granular materials is a combination of the strength pervading as intergranular friction (represented as an angle of internal friction - Phi), and the cohesion (C) between these particles. Most behavioral or constitutive models of this class of granular materials comprise of a cohesion and frictional component with no regard to the length scale i.e. from the micro structural models through the continuum models. An experimental study has been made on a model granular material, viz. angular sand with different weights of binding agents (varying degrees of cohesion) at multiple length scales to physically map this phenomenon. Cylindrical specimen of various diameters - 10, 20, 38, 100, 150 mm (and with an aspect ratio of 2) are reconstituted with 2, 4 and 8% by weight of a binding agent. The magnitude of this cohesion is analyzed using uniaxial compression tests and it is assumed to correspond to the peak in the normalized stress-strain plot. Increase in the cohesive strength of the material is seen with increasing size of the specimen. A possibility of ``entanglement'' occurring in larger specimens is proposed as a possible reason for deviation from a continuum framework.

Microcracking and fracture process in cement mortar and concrete: a comparative study using acoustic emission technique

This article reports the acoustic emission (AE) study of precursory micro-cracking activity and fracture behaviour of quasi-brittle materials such as concrete and cement mortar. In the present study, notched three-point bend specimens (TPB) were tested under crack mouth opening displacement (CMOD) control at a rate of 0.0004 mm/sec and the accompanying AE were recorded using a 8 channel AE monitoring system. The various AE statistical parameters including AE event rate , AE energy release rate , amplitude distribution for computing the AE based b-value, cumulative energy (I E) pound and ring down count (RDC) were used for the analysis. The results show that the micro-cracks initiated and grew at an early stage in mortar in the pre peak regime. While in the case of concrete, the micro-crack growth occurred during the peak load regime. However, both concrete and mortar showed three distinct stages of micro-cracking activity, namely initiation, stable growth and nucleation prior to the final failure. The AE statistical behavior of each individual stage is dependent on the number and size distribution of micro-cracks. The results obtained in the laboratory are useful to understand the various stages of micro-cracking activity during the fracture process in quasi-brittle materials such as concrete & mortar and extend them for field applications.

Photocurrent spectroscopic studies of diketopyrrolopyrrole-based statistical copolymers

Diketopyrrolopyrrole (DPP) containing copolymers have gained a lot of interest in organic optoelectronics with great potential in organic photovoltaics. In this work, DPP based statistical copolymers, with slightly different bandgap energies and a varying fraction of donor-acceptor ratio are investigated using monochromatic photocurrent spectroscopy and Fourier-transform photocurrent spectroscopy (FTPS). The statistical copolymer with a lower DPP fraction, when blended with a fullerene derivative, shows the signature of an inter charge transfer complex state in photocurrent spectroscopy. Furthermore, the absorption spectrum of the blended sample with a lower DPP fraction is seen to change as a function of an external bias, qualitatively similar to the quantum confined Stark effect, from where we estimate the exciton binding energy. The statistical copolymer with a higher DPP fraction shows no signal of the inter charge transfer states and yields a higher external quantum efficiency in a photovoltaic structure. In order to gain insight into the origin of the observed charge transfer transitions, we present theoretical studies using density-functional theory and time-dependent density-functional theory for the two pristine DPP based statistical monomers.

Photocurrent spectroscopic studies of diketopyrrolopyrrole-based statistical copolymers

Diketopyrrolopyrrole (DPP) containing copolymers have gained a lot of interest in organic optoelectronics with great potential in organic photovoltaics. In this work, DPP based statistical copolymers, with slightly different bandgap energies and a varying fraction of donor-acceptor ratio are investigated using monochromatic photocurrent spectroscopy and Fourier-transform photocurrent spectroscopy (FTPS). The statistical copolymer with a lower DPP fraction, when blended with a fullerene derivative, shows the signature of an inter charge transfer complex state in photocurrent spectroscopy. Furthermore, the absorption spectrum of the blended sample with a lower DPP fraction is seen to change as a function of an external bias, qualitatively similar to the quantum confined Stark effect, from where we estimate the exciton binding energy. The statistical copolymer with a higher DPP fraction shows no signal of the inter charge transfer states and yields a higher external quantum efficiency in a photovoltaic structure. In order to gain insight into the origin of the observed charge transfer transitions, we present theoretical studies using density-functional theory and time-dependent density-functional theory for the two pristine DPP based statistical monomers.

Role of Crosslinking and Entanglements in the Mechanics of Silicone Networks

The goal of this study is to investigate the applicability of different constitutive models for silicone networks using comprehensive multiaxial experimental tests, including non-equibiaxial mechanical tests which introduce differential constraints on the networks in the two orthogonal directions, on samples prepared using various crosslinking densities. Uniaxial stress-strain experiments show that a decrease in crosslinker amounts used in the preparation of silicone networks lead to more compliant material response as compared to that obtained using higher amounts of crosslinker. Biaxial data were used to obtain fits to the neo- Hookean, Mooney-Rivlin, Arruda-Boyce and the Edward-Vilgis slip-link constitutive models. Our results show that the slip-link model, based on separation of the individual contributions of chemical crosslinks and physical entanglements, is better at describing the stress-strain response of highly crosslinked networks at low stretches as compared to other constitutive models. Modulus obtained using the slip-link model for highly crosslinked networks agrees with experimentally determined values obtained using uniaxial tension experiments. In contrast, moduli obtained using coefficients to the other constitutive models underpredict experimentally determined moduli by over 40 %. However, the slip-link model did not predict the experimentally observed stiffening response at higher stretches which was better captured using the Arruda-Boyce model.

Development and Evaluation of Statistical Downscaling Models for Monthly Precipitation

Several statistical downscaling models have been developed in the past couple of decades to assess the hydrologic impacts of climate change by projecting the station-scale hydrological variables from large-scale atmospheric variables simulated by general circulation models (GCMs). This paper presents and compares different statistical downscaling models that use multiple linear regression (MLR), positive coefficient regression (PCR), stepwise regression (SR), and support vector machine (SVM) techniques for estimating monthly rainfall amounts in the state of Florida. Mean sea level pressure, air temperature, geopotential height, specific humidity, U wind, and V wind are used as the explanatory variables/predictors in the downscaling models. Data for these variables are obtained from the National Centers for Environmental Prediction-National Center for Atmospheric Research (NCEP-NCAR) reanalysis dataset and the Canadian Centre for Climate Modelling and Analysis (CCCma) Coupled Global Climate Model, version 3 (CGCM3) GCM simulations. The principal component analysis (PCA) and fuzzy c-means clustering method (FCM) are used as part of downscaling model to reduce the dimensionality of the dataset and identify the clusters in the data, respectively. Evaluation of the performances of the models using different error and statistical measures indicates that the SVM-based model performed better than all the other models in reproducing most monthly rainfall statistics at 18 sites. Output from the third-generation CGCM3 GCM for the A1B scenario was used for future projections. For the projection period 2001-10, MLR was used to relate variables at the GCM and NCEP grid scales. Use of MLR in linking the predictor variables at the GCM and NCEP grid scales yielded better reproduction of monthly rainfall statistics at most of the stations (12 out of 18) compared to those by spatial interpolation technique used in earlier studies.

Statistical significance of episodes with general partial orders

Frequent episode discovery is one of the methods used for temporal pattern discovery in sequential data. An episode is a partially ordered set of nodes with each node associated with an event type. For more than a decade, algorithms existed for episode discovery only when the associated partial order is total (serial episode) or trivial (parallel episode). Recently, the literature has seen algorithms for discovering episodes with general partial orders. In frequent pattern mining, the threshold beyond which a pattern is inferred to be interesting is typically user-defined and arbitrary. One way of addressing this issue in the pattern mining literature has been based on the framework of statistical hypothesis testing. This paper presents a method of assessing statistical significance of episode patterns with general partial orders. A method is proposed to calculate thresholds, on the non-overlapped frequency, beyond which an episode pattern would be inferred to be statistically significant. The method is first explained for the case of injective episodes with general partial orders. An injective episode is one where event-types are not allowed to repeat. Later it is pointed out how the method can be extended to the class of all episodes. The significance threshold calculations for general partial order episodes proposed here also generalize the existing significance results for serial episodes. Through simulations studies, the usefulness of these statistical thresholds in pruning uninteresting patterns is illustrated. (C) 2014 Elsevier Inc. All rights reserved.

Fracture in metallic glasses: mechanics and mechanisms

Significant progress in understanding the mechanical behavior of metallic glasses (MGs) was made over the past decade, particularly on mechanisms of plastic deformation. However, recent research thrust has been on exploring the mechanics and physics of fracture. MGs can be very brittle with K-Ic values similar to silicate glasses and ceramics or very tough with K-Ic akin to high toughness crystalline metals. Even the tough MGs can become brittle with structural relaxation following annealing at temperatures close to glass transition temperature (T-g). Detailed experimental studies coupled with complementary numerical simulations of the recent past have provided insights on the micromechanisms of failure as well as nature of crack tip fields, and established the governing fracture criteria for ductile and brittle glasses. In this paper, the above advances are reviewed and outstanding issues in the context of fracture of amorphous alloys that need to be resolved are identified.

A Statistical Model of Current Loops and Magnetic Monopoles

We formulate a natural model of loops and isolated vertices for arbitrary planar graphs, which we call the monopole-dimer model. We show that the partition function of this model can be expressed as a determinant. We then extend the method of Kasteleyn and Temperley-Fisher to calculate the partition function exactly in the case of rectangular grids. This partition function turns out to be a square of a polynomial with positive integer coefficients when the grid lengths are even. Finally, we analyse this formula in the infinite volume limit and show that the local monopole density, free energy and entropy can be expressed in terms of well-known elliptic functions. Our technique is a novel determinantal formula for the partition function of a model of isolated vertices and loops for arbitrary graphs.