Stationary crack tip fields in elastic-plastic solids: an overview of recent numerical simulations

In this paper, an overview of some recent numerical simulations of stationary crack tip fields in elastic-plastic solids is presented. First, asymptotic analyses carried out within the framework of 2D plane strain or plane stress conditions in both pressure insensitive and pressure sensitive plastic solids are reviewed. This is followed by discussion of salient results obtained from recent computational studies. These pertain to 3D characteristics of elastic-plastic near-front fields under mixed mode loading, mechanics of fracture and simulation of near-tip shear banding process of amorphous alloys and influence of crack tip constraint on the structure of near-tip fields in ductile single crystals. These results serve to illustrate several important features associated with stress and strain distributions near the crack tip and provide the foundation for understanding the operative failure mechanisms. The paper concludes by highlighting some of the future prospects for this field of study.

Prediction of Candidate Primary Immunodeficiency Disease Genes Using a Support Vector Machine Learning Approach

Screening and early identification of primary immunodeficiency disease (PID) genes is a major challenge for physicians. Many resources have catalogued molecular alterations in known PID genes along with their associated clinical and immunological phenotypes. However, these resources do not assist in identifying candidate PID genes. We have recently developed a platform designated Resource of Asian PDIs, which hosts information pertaining to molecular alterations, protein-protein interaction networks, mouse studies and microarray gene expression profiling of all known PID genes. Using this resource as a discovery tool, we describe the development of an algorithm for prediction of candidate PID genes. Using a support vector machine learning approach, we have predicted 1442 candidate PID genes using 69 binary features of 148 known PID genes and 3162 non-PID genes as a training data set. The power of this approach is illustrated by the fact that six of the predicted genes have recently been experimentally confirmed to be PID genes. The remaining genes in this predicted data set represent attractive candidates for testing in patients where the etiology cannot be ascribed to any of the known PID genes.

Influence of roughness parameters and surface texture on friction during sliding of pure lead over 080 M40 steel

In the present investigation, tests were conducted on a tribological couple made of cylindrical lead pin with spherical tip against 080 M40 steel plates of different textures with varying roughness under both dry and lubricated conditions using an inclined pin-on-plate sliding tester. Surface roughness parameters of the steel plates were measured using optical profilometer. The morphologies of the worn surfaces of the pins and the formation of transfer layer on the counter surfaces were observed using a scanning electron microscope. It was observed that the coefficient of friction and the formation of transfer layer depend primarily on the surface texture of hard surfaces. A newly formulated non-dimensional hybrid roughness parameter called 'xi' (a product of number of peaks and maximum profile peak height) of the tool surface plays an important role in determining the frictional behaviour of the surfaces studied. The effect of surfaces texture on coefficient of friction was attributed to the variation of plowing component of friction, which in turn depends on the roughness parameter 'xi'.

Crack Tip Fields in a Single Edge Notched Aluminum Single Crystal Specimen

We report a combined experimental and computational study of a low constraint aluminum single crystal fracture geometry and investigate the near-tip stress and strain fields. To this end, a single edge notched tensile (SENT) specimen is considered. A notch, with a radius of 50 µm, is taken to lie in the (010) plane and its front is aligned along the [101] direction. Experiments are conducted by subjecting the specimen to tensile loading using a special fixture inside a scanning electron microscope chamber. Both SEM micrographs and electron back-scattered diffraction (EBSD) maps are obtained from the near-tip region. The experiments are complemented by performing 3D and 2D plane strain finite element simulations within a continuum crystal plasticity framework assuming an isotropic hardening response characterized by the Pierce–Asaro–Needleman model. The simulations show a distinct slip band forming at about 55 deg with respect to the notch line corresponding to slip on (11-bar 1)[011] system, which corroborates well with experimental data. Furthermore, two kink bands occur at about 45 deg and 90 deg with respect to the notch line within which large rotations in the crystal orientation take place. These predictions are in good agreement with the EBSD observations. Finally, the near-tip angular variations of the 3D stress and plastic strain fields in the low constraint SENT fracture geometry are examined in detail.

Gaussian mixture model based switched split vector quantization of LSF parameters

We address the issue of rate-distortion (R/D) performance optimality of the recently proposed switched split vector quantization (SSVQ) method. The distribution of the source is modeled using Gaussian mixture density and thus, the non-parametric SSVQ is analyzed in a parametric model based framework for achieving optimum R/D performance. Using high rate quantization theory, we derive the optimum bit allocation formulae for the intra-cluster split vector quantizer (SVQ) and the inter-cluster switching. For the wide-band speech line spectrum frequency (LSF) parameter quantization, it is shown that the Gaussian mixture model (GMM) based parametric SSVQ method provides 1 bit/vector advantage over the non-parametric SSVQ method.

Computationally efficient optimum weighting function for vector quantization of LSF parameters

We propose a new weighting function which is computationally simple and an approximation to the theoretically derived optimum weighting function shown in the literature. The proposed weighting function is perceptually motivated and provides improved vector quantization performance compared to several weighting functions proposed so far, for line spectrum frequency (LSF) parameter quantization of both clean and noisy speech data.

Cluster based training for scaling non-linear support vector machines

Support Vector Machines(SVMs) are hyperplane classifiers defined in a kernel induced feature space. The data size dependent training time complexity of SVMs usually prohibits its use in applications involving more than a few thousands of data points. In this paper we propose a novel kernel based incremental data clustering approach and its use for scaling Non-linear Support Vector Machines to handle large data sets. The clustering method introduced can find cluster abstractions of the training data in a kernel induced feature space. These cluster abstractions are then used for selective sampling based training of Support Vector Machines to reduce the training time without compromising the generalization performance. Experiments done with real world datasets show that this approach gives good generalization performance at reasonable computational expense.

Hanle-Zeeman redistribution matrix. I. Classical theory expressions in the laboratory frame

Polarized scattering in spectral lines is governed by a 4; 4 matrix that describes how the Stokes vector is scattered and redistributed in frequency and direction. Here we develop the theory for this redistribution matrix in the presence of magnetic fields of arbitrary strength and direction. This general magnetic field case is called the Hanle- Zeeman regime, since it covers both of the partially overlapping weak- and strong- field regimes in which the Hanle and Zeeman effects dominate the scattering polarization. In this general regime, the angle-frequency correlations that describe the so-called partial frequency redistribution (PRD) are intimately coupled to the polarization properties. We develop the theory for the PRD redistribution matrix in this general case and explore its detailed mathematical properties and symmetries for the case of a J = 0 -> 1 -> 0 scattering transition, which can be treated in terms of time-dependent classical oscillator theory. It is shown how the redistribution matrix can be expressed as a linear superposition of coherent and noncoherent parts, each of which contain the magnetic redistribution functions that resemble the well- known Hummer- type functions. We also show how the classical theory can be extended to treat atomic and molecular scattering transitions for any combinations of quantum numbers.

Grain boundary sliding during diffusion and dislocation creep in a Mg-0.7 pct Al alloy

Early studies on grain boundary sliding (GBS) in Mg alloys have suggested frequently that the contribution of GBS to creep is high even under conditions corresponding to dislocation creep. The role of creep strain and grain size in influencing the experimental measurements has not been clearly identified. Grain boundary sliding measurements were conducted in detail over experimental conditions corresponding to diffusion creep as well as dislocation creep in a single-phase Mg-0.7 wt pet Al alloy. The results indicated clearly that the GBS contribution to creep was Very high during,, diffusion creep at low stresses (similar to 75 pct) and substantially reduced during dislocation creep at high stresses (similar to 15 pct). These measurements were consistent with the observation of significant intragranular slip band activity observed in most grains at high stresses and very little slip band activity at low stresses. The experimental measurements and analysis indicated also that the GBS contribution to creep was high during the initial stages of creep and decreased to a steady-state value at large strains.

Fluorescent Fields: electric lighting and the rationalization of the modern corporate workplace

This study investigates the implications of the introduction of electric lighting systems, building technologies, and theories of worker efficiency on the deep spatial and environmental transformations that occurred within the corporate workplace during the twentieth century. Examining the shift from daylighting strategies to largely artificially lit workplace environments, this paper argues that electric lighting significantly contributed to the architectural rationalization of both office work and the modern office environment. Contesting the historical and critical marginalization of lighting within the discourse of the modern built environment, this study calls for a reassessment of the role of artificial lighting in the development of the modern corporate workplace. Keywords: daylighting, fluorescent lighting, rationalization, workplace design

OCR Prediction Using Support Vector Machine Based on Piezocone Data

The determination of the overconsolidation ratio (OCR) of clay deposits is an important task in geotechnical engineering practice. This paper examines the potential of a support vector machine (SVM) for predicting the OCR of clays from piezocone penetration test data. SVM is a statistical learning theory based on a structural risk minimization principle that minimizes both error and weight terms. The five input variables used for the SVM model for prediction of OCR are the corrected cone resistance (qt), vertical total stress (sigmav), hydrostatic pore pressure (u0), pore pressure at the cone tip (u1), and the pore pressure just above the cone base (u2). Sensitivity analysis has been performed to investigate the relative importance of each of the input parameters. From the sensitivity analysis, it is clear that qt=primary in situ data influenced by OCR followed by sigmav, u0, u2, and u1. Comparison between SVM and some of the traditional interpretation methods is also presented. The results of this study have shown that the SVM approach has the potential to be a practical tool for determination of OCR.

Influence of surface texture and roughness parameters on friction and transfer layer formation during sliding of aluminium pin on steel plate

Surface texture of harder mating surfaces plays an important role during sliding against softer materials and hence the importance of characterizing the surfaces in terms of roughness parameters. In the present investigation, basic studies were conducted using inclined pin-on-plate sliding tester to understand the surface texture effect of hard surfaces on coefficient of friction and transfer layer formation. A tribological couple made of a super purity aluminium pin against steel plate was used in the tests. Two surface parameters of steel plates, namely roughness and texture, were varied in the tests. It was observed that the transfer layer formation and the coefficient of friction along with its two components, namely, the adhesion and plowing, are controlled by the surface texture and are independent of surface roughness (R-a). Among the various surface roughness parameters, the average or the mean slope of the profile was found to explain the variations best. Under lubricated conditions, stick-slip phenomena was observed, the amplitude of which depends on the plowing component of friction. The presence of stick-slip motion under lubricated conditions could be attributed to the molecular deformation of the lubricant component confined between asperities. (C) 2009 Elsevier B. V. All rights reserved.

Investigations on the influence of graphite filler on dry sliding wear and abrasive wear behaviour of carbon fabric reinforced epoxy composites

In this experimental study, the dry sliding wear and two-body abrasive wear behaviour of graphite filled carbon fabric reinforced epoxy composites were investigated. Carbon fabric reinforced epoxy composite was used as a reference material. Sliding wear experiments were conducted using a pin-on-disc wear tester under dry contact condition. Mass loss was determined as a function of sliding velocity for loads of 25, 50, 75, and 100 N at a constant sliding distance of 6000 m. Two-body abrasive wear experiments were performed under multi-pass condition using silicon carbide (SiC) of 150 and 320 grit abrasive papers. The effects of abrading distance and different loads have been studied. Abrasive wear volume and specific wear rate as a function of applied normal load and abrading distance were also determined. The results show that in dry sliding wear situations, for increased load and sliding velocity, higher wear loss was recorded. The excellent wear characteristics were obtained with carbon-epoxy containing graphite as filler. Especially, 10 wt.% of graphite in carbon-epoxy gave a low wear rate. A graphite surface film formed on the counterface was confirmed to be effective in improving the wear characteristics of graphite filled carbon-epoxy composites. In case of two-body abrasive wear, the wear volume increases with increasing load/abrading distance. Experimental results showed the type of counterface (hardened steel disc and SiC paper) material greatly influences the wear behaviour of the composites. Wear mechanisms of the composites were investigated using scanning electron microscopy. Wear of carbon-epoxy composite was found to be mainly due to a microcracking and fiber fracture mechanisms. It was found that the microcracking mechanism had been caused by progressive surface damage. Further, it was also noticed that carbon-epoxy composite wear is reduced to a greater extent by addition of the graphite filler, in which wear was dominated by microplowing/microcutting mechanisms instead of microcracking.

Multilevel Dodecagonal Space Vector Generation for Open-end Winding Induction Motor Drive Using Conventional Three Level Inverters

A novel dodecagonal space vector structure for induction motor drive is presented in this paper. It consists of two dodecagons, with the radius of the outer one twice the inner one. Compared to existing dodecagonal space vector structures, to achieve the same PWM output voltage quality, the proposed topology lowers the switching frequency of the inverters and reduces the device ratings to half. At the same time, other benefits obtained from existing dodecagonal space vector structure are retained here. This includes the extension of the linear modulation range and elimination of all 6+/-1 harmonics (n=odd) from the phase voltage. The proposed structure is realized by feeding an open-end winding induction motor with two conventional three level inverters. A detailed calculation of the PWM timings for switching the space vector points is also presented. Simulation and experimental results indicate the possible application of the proposed idea for high power drives.

Support vector machine applied to settlement of shallow foundations on cohesionless soils

The determination of settlement of shallow foundations on cohesionless soil is an important task in geotechnical engineering. Available methods for the determination of settlement are not reliable. In this study, the support vector machine (SVM), a novel type of learning algorithm based on statistical theory, has been used to predict the settlement of shallow foundations on cohesionless soil. SVM uses a regression technique by introducing an ε – insensitive loss function. A thorough sensitive analysis has been made to ascertain which parameters are having maximum influence on settlement. The study shows that SVM has the potential to be a useful and practical tool for prediction of settlement of shallow foundation on cohesionless soil.