Catastrophic Failure of a Steel Chimney in a Lime Plant

Failure analysis of a steel chimney used in a lime plant was carried out. The chimney broke from two different locations during a storm. During the site visit, it was observed that the chimney was dislodged from weld joints. The chimney was made up of hot rolled mild steel plates. Investigations were carried out on the failed chimney plate and welding between plates. The investigation consists of visual observation, chemical analysis, characterization of macro- and microstructures, measurement of hardness, tensile property tests and energy-dispersive spectroscopy (EDS). Calculation of wind load at the location of breakage was also carried out. EDS analysis revealed entrapment of slag inside weld. Overall analysis suggested that the failure took place due to selection of improper reconditioning technique as well as poor workmanship in welding.     

Charge transport and structural morphology of HCl-doped polyaniline

The d.c. and a.c. (100 Hz–1 MHz) conductivities of HCl-doped polyaniline have been measured in the temperature range 77–300 K. At 77 K, the a.c. conductivity data, (), can be described by the relation ()=As, where the parameter s lies close to unity and decreases with increase in the doping level. The ratio of measured a.c. to d.c. conductivity shows dispersion at 77 K, which decreases with increase in the doping level. This decrease is found to be sharp around pH3.0. In the temperature range 77–150 K, the observed d.c. conductivity data can be described by Mott's three dimensional variable range hopping (VRH) model. Scanning electron microscopy studies reveal a sharp change in structural morphology of HCl-doped polyaniline at a pH3.0. A strikingly remarkable structural morphology has been observed in the formc of a channel at this pH value. This change is accompanied by a rapid increase in d.c. conductivity, dielectric constant, along with sharp changes in structural morphology, which indicates the existence of a doping-induced structural conductivity correlation in this system. © 1998 Chapman & Hall     

EPR study of Cu2+ in Na2O-NaF-B2O3-Bi2O3 glasses

Electron paramagnetic resonance (EPR) studies have been performed on the glass system (30–x) NaF-xNa₂O-50B₂O₃-20Bi₂O₃ doped with CuO as a paramagnetic probe. The calculated g values indicate that Cu²⁺ is in a tetragonally elongated octahedral co-ordination, and the Jahn-Teller character gives rise to anisotropic hyperfine structure. The spin-Hamiltonian parameters and -bonding parameter, ², are calculated. Varying the fluoride ion concentration and its effect on these parameters is also discussed.     

High order parameter-robust numerical method for time dependent singularly perturbed reaction–diffusion problems

We introduce a high order parameter-robust numerical method to solve a Dirichlet problem for one-dimensional time dependent singularly perturbed reaction-diffusion equation. A small parameter ε is multiplied with the second order spatial derivative in the equation. The parabolic boundary layers appear in the solution of the problem as the perturbation parameter ε tends to zero. To obtain the approximate solution of the problem we construct a numerical method by combining the Crank–Nicolson method on an uniform mesh in time direction, together with a hybrid scheme which is a suitable combination of a fourth order compact difference scheme and the standard central difference scheme on a generalized Shishkin mesh in spatial direction. We prove that the resulting method is parameter-robust or ε-uniform in the sense that its numerical solution converges to the exact solution uniformly well with respect to the singular perturbation parameter ε. More specifically, we prove that the numerical method is uniformly convergent of second order in time and almost fourth order in spatial variable, if the discretization parameters satisfy a non-restrictive relation. Numerical experiments are presented to validate the theoretical results and also indicate that the relation between the discretization parameters is not necessary in practice.     

Simulated annealing based automatic fuzzy clustering combined with ANN classification for analyzing microarray data

Microarray technology has made it possible to monitor the expression levels of many genes simultaneously across a number of experimental conditions. Fuzzy clustering is an important tool for analyzing microarray gene expression data. In this article, a real-coded Simulated Annealing (VSA) based fuzzy clustering method with variable length configuration is developed and combined with popular Artificial Neural Network (ANN) based classifier. The idea is to refine the clustering produced by VSA using ANN classifier to obtain improved clustering performance. The proposed technique is used to cluster three publicly available real life microarray data sets. The superior performance of the proposed technique has been demonstrated by comparing with some widely used existing clustering algorithms. Also statistical significance test has been conducted to establish the statistical significance of the superior performance of the proposed clustering algorithm. Finally biological relevance of the clustering solutions are established.     

Fairness of Transitions in Diagnosability of Discrete Event Systems

Failure diagnosability has been widely studied for discrete event system (DES) models because of modeling simplicity and computational efficiency due to abstraction. In the literature it is often held that for diagnosability, such models can be used not only for systems that fall naturally in the class of DES but also for the ones traditionally treated as continuous variable dynamic systems. A class of algorithms for failure diagnosability of DES models has been successfully developed for systems where fairness is not a part of the model. These algorithms are based on detecting cycles in the normal and the failure model that look identical. However, there exist systems with all transitions fair where the diagnosability condition that hinges upon this feature renders many failures non-diagnosable although they may actually be diagnosable by transitions out of a cycle. Hence, the diagnosability conditions based on cycle detection need to be modified to hold for many real-world systems where all transitions are fair. In this work, however, it is shown by means of an example that a system may have some transitions fair and some unfair. A new failure diagnosability mechanism is proposed for DES models with both fair and unfair transitions. Time complexity for deciding diagnosability of DES models with fair and unfair transitions is analyzed and compared with the time complexities of other DES diagnosability analysis methods reported in the literature.     

A new approach for generating efficient sample from market basket data

Classical data mining algorithms require expensive passes over the entire database to generate frequent items and hence to generate association rules. With the increase in the size of database, it is becoming very difficult to handle large amount of data for computation. One of the solutions to this problem is to generate sample from the database that acts as representative of the entire database for finding association rules in such a way that the distance of the sample from the complete database is minimal. Choosing correct sample that could represent data is not an easy task. Many algorithms have been proposed in the past. Some of them are computationally fast while others give better accuracy. In this paper, we present an algorithm for generating a sample from the database that can replace the entire database for generating association rules and is aimed at keeping a balance between accuracy and speed. The algorithm that is proposed takes into account the average number of small, medium and large 1-itemset in the database and average weight of the transactions to define threshold condition for the transactions. Set of transactions that satisfy the threshold condition is chosen as the representative for the entire database. The effectiveness of the proposed algorithm has been tested over several runs of database generated by IBM synthetic data generator. A vivid comparative performance evaluation of the proposed technique with the existing sampling techniques for comparing the accuracy and speed has also been carried out.