Inelastic Postbuckling of Columns of Variable Flexural Rigidity

Effects of large deformation and inelasticity are considered in formulating the behavior of columns of variable cross section subjected to an axial compressive load. Simple, approximate methods are used to obtain numerical results. The combined effect of the nonlinearities is shown to be of a hardening type for small column deflections

Moiré Displacement Transducer for N/C Systems

Noncontact method of sensing accurately the magnitude and direction of displacements is essential in systems such as the numerically controlled machines. A displacement transducer, using Moiré transmission gratings is described. The notable feature of this instrument is that it requires only gratings of small lengths, even for measurement of large displacements.

Vibrations of Multifiber Composite Shells-Some Numerical Results

A study of vibrations of multifiber composite shells is presented. Special attention is paid to the effect of composition of different fibers on the frequency spectrum of a freely vibrating cylindrical shell. The numerical results indicate clustering of frequency spectrum of a freely vibrating cylindrical composite shell as compared with the isotropic shell, and the spectrum varies considerably with the composition of the constituent materials.

A strategy for scheduling tightly coupled parallel applications on clusters

Although various strategies have been developed for scheduling parallel applications with independent tasks, very little work exists for scheduling tightly coupled parallel applications on cluster environments. In this paper, we compare four different strategies based on performance models of tightly coupled parallel applications for scheduling the applications on clusters. In addition to algorithms based on existing popular optimization techniques, we also propose a new algorithm called Box Elimination that searches the space of performance model parameters to determine the best schedule of machines. By means of real and simulation experiments, we evaluated the algorithms on single cluster and multi-cluster setups. We show that our Box Elimination algorithm generates up to 80% more efficient schedule than other algorithms. We also show that the execution times of the schedules produced by our algorithm are more robust against the performance modeling errors.

Analysis of DNA sequence transformations on grids

Study of the evolution of species or organisms is essential for various biological applications. Evolution is typically studied at the molecular level by analyzing the mutations of DNA sequences of organisms. Techniques have been developed for building phylogenetic or evolutionary trees for a set of sequences. Though phylogenetic trees capture the overall evolutionary relationships among the sequences, they do not reveal fine-level details of the evolution. In this work, we attempt to resolve various fine-level sequence transformation details associated with a phylogenetic tree using cellular automata. In particular, our work tries to determine the cellular automata rules for neighbor-dependent mutations of segments of DNA sequences. We also determine the number of time steps needed for evolution of a progeny from an ancestor and the unknown segments of the intermediate sequences in the phylogenetic tree. Due to the existence of vast number of cellular automata rules, we have developed a grid system that performs parallel guided explorations of the rules on grid resources. We demonstrate our techniques by conducting experiments on a grid comprising machines in three countries and obtaining potentially useful statistics regarding evolutions in three HIV sequences. In particular, our work is able to verify the phenomenon of neighbor-dependent mutations and find that certain combinations of neighbor-dependent mutations, defined by a cellular automata rule, occur with greater than 90% probability. We also find the average number of time steps for mutations for some branches of phylogenetic tree over a large number of possible transformations with standard deviations less than 2.

A fast dual algorithm for kernel logistic regression

This paper gives a new iterative algorithm for kernel logistic regression. It is based on the solution of a dual problem using ideas similar to those of the Sequential Minimal Optimization algorithm for Support Vector Machines. Asymptotic convergence of the algorithm is proved. Computational experiments show that the algorithm is robust and fast. The algorithmic ideas can also be used to give a fast dual algorithm for solving the optimization problem arising in the inner loop of Gaussian Process classifiers.

Pressure and thermally induced stages of wear in dry sliding of a steel ball against an aluminium-silicon alloy flat

Wear of etched near-eutectic aluminium silicon alloy slid against a steel ball under ambient is explored. The sliding velocity is kept low (0.01 m/s) and the nominal contact pressure is varied in a 15-40 MPa range. Four stages of wear are identified; ultra mild wear, mild wear, severe wear and post severe oxidative wear. The first transition is controlled by the protrusions of silicon particles, projecting out of the aluminium alloy matrix. Once these protrusions disappear under pressure and sliding, oxidation and bulk energy dissipation mechanisms take over to institute transitions to other stages of wear. The phenomenological characteristics of wear stages are explored using a variety of techniques including nanoindentation, focused ion beam milling, electron microscopy, X-ray photoelectron spectroscopy (XPS), energy dispersive X-ray spectroscopy (EDS) and optical interferometry. (c) 2010 Elsevier B.V. All rights reserved.