Recursive Technique For Computing System Reliability

This paper presents a simple recursive formula for calculating source-to-sink congestion, and hence reliability, in a network. This congestion is derived from individual blocking probabilities of each link. The method has an advantage of not requiring cut-sets. Such a knowledge is a prerequisite in most other methods of reliability analysis. We have programmed the algorithm using Pascal as it allows recursive procedure calls. An example illustrates the method.     

Meta-cognitive RBF Network and its Projection Based Learning algorithm for classification problems

‘Meta-cognitive Radial Basis Function Network’ (McRBFN) and its ‘Projection Based Learning’ (PBL) algorithm for classification problems in sequential framework is proposed in this paper and is referred to as PBL-McRBFN. McRBFN is inspired by human meta-cognitive learning principles. McRBFN has two components, namely the cognitive component and the meta-cognitive component. The cognitive component is a single hidden layer radial basis function network with evolving architecture. In the cognitive component, the PBL algorithm computes the optimal output weights with least computational effort by finding analytical minima of the nonlinear energy function. The meta-cognitive component controls the learning process in the cognitive component by choosing the best learning strategy for the current sample and adapts the learning strategies by implementing self-regulation. In addition, sample overlapping conditions are considered for proper initialization of new hidden neurons, thus minimizes the misclassification. The interaction of cognitive component and meta-cognitive component address the what-to-learn, when-to-learn and how-to-learn human learning principles efficiently. The performance of the PBL-McRBFN is evaluated using a set of benchmark classification problems from UCI machine learning repository and two practical problems, viz., the acoustic emission signal classification and the mammogram for cancer classification. The statistical performance evaluation on these problems has proven the superior performance of PBL-McRBFN classifier over results reported in the literature.     

Spectroscopic and photoluminescence properties of Dy-doped lead tungsten tellurite glasses for laser materials

Lead tungsten tellurite (LTT) glasses doped with different Dy³⁺ ion concentrations have been prepared and characterized through optical absorption, photoluminescence and decay measurements. The glassy nature of the LTT host has been confirmed through the XRD measurements. The three phenomelogical intensity parameters Ω_λ (λ = 2, 4, 6) have been determined from the absorption spectral intensities using the Judd-Ofelt (J-O) theory. The hypersensitivity of ⁶H_15/2 → ⁶F_11/2 transition based on the magnitude of Ω₂ parameter has also been discussed. By using the J-O intensity parameters several radiative properties such as spontaneous transition probabilities (A_R), fluorescence branching ratios (β_R) and radiative lifetimes (τ_R) have been determined. The effect of Dy³⁺ ion concentration on the emission intensities of ⁴F_9/2 → ⁶H_J′ (J′ = 15/2, 13/2, 11/2 and 9/2) transitions has also been reported.     

Corrosion susceptibility of potential rock bolts in aerated multi-ionic simulated concentrated water

Rock bolts used for the reinforcement of underground mines, tunnels and nuclear waste repositories are made up of low and medium carbon steels, and high strength low alloy steels. Typical rock bolt systems used for rock reinforcement are mechanically anchored bolts, grout anchored, frictional rock stabilizers and strand anchors. For nuclear waste repository sites such as Yucca Mountain (YM) as well as for mines and tunnels, in addition to mechanical properties, corrosion properties are also important due to potential seepage of water through the fractures or pores in the rock. During temporary rock support period of 50-100 years, the temperature of the tunnel at YM should be maintained at ambient conditions. For any reason if the rock bolts are exposed to YM waters and high temperatures in the tunnel then there is a chance of corrosion of steel rock bolts. In this study an attempt was made to study the corrosion properties of various potential rock bolts for YM tunnel support via the aid of electrochemical corrosion testing. At ambient temperature (25 °C) all the rock bolts that were studied showed good corrosion resistance in these waters. At higher temperatures, 60 °C and 90 °C, corrosion resistance of rock bolts decreased, but due to special stress relief heat treatment of one of the frictional rock stabilizers (Swellex Mn 24) the corrosion rates were lower than all other tested rock bolts. Note: Swellex, Split set and Williams are the proprietary names of Atlas Copco, International Roll Forms, Inc. and Williams Form Engineering Corp, respectively.     

In situ synthesis of gold–polyaniline composite in nanopores of polycarbonate membrane

In situ one-step chemical synthesis route for the preparation of a gold–polyaniline composite in nanopores of polycarbonate (PC) membrane is reported. PC membrane, which was placed in a specially designed two-compartment cell, separated the aqueous solution of aniline from HAuCl₄ solution. Concentration gradient across the membrane caused movement of AuCl₄ ⁻ and anilinium ions in the pores of polycarbonate membrane. Nanopores in PC membrane acted as reaction vessels where aniline and HAuCl₄ were allowed to mix together, and the redox reaction between aniline and HAuCl₄ led to the formation of gold–polyaniline composite. The gold–polyaniline composite in PC membrane was characterised by EDXRF, XRD, UV–Vis spectroscopy, FTIR and TEM. Peak broadening in XRD suggests that Au particles formed in the membrane are nanocrystallites and average crystallite size is (24 ± 4) nm. TEM studies show that gold nanoparticles are randomly dispersed in polyaniline clusters formed in the nanopores of PC membrane. Characterisation results show that the surfaces of the PC membrane exposed to HAuCl₄ and aniline have significantly higher concentrations of Au nanoparticles and polyaniline, respectively.     

Investigation on natural radiation level and its hazardous nature of river sediments using γ-ray spectroscopy

The content of natural radionuclides (²³⁸U, ²³²Th, ⁴⁰K) in sediment samples of Ponnaiyar River, taken from different depths, were determined using a γ-ray spectroscopic system with a NaI(TI) detector with an aim of evaluating the radiation hazard. The results are compared with Indian and world average values. To know the complete radiological characteristics, the radiological indices such as absorbed dose rate, annual effective dose equivalent (indoor and outdoor), radium equivalent activity, hazard index (H _ex and H _in), γ-index, activity utilization index, and excess lifetime cancer risk were calculated. The results obtained were discussed and compared with the recommended values. The outdoor γ-dose rates were measured at each sampling site using an environmental radiation dosimeter. The measured results were compared with literature values and correlated with the calculated absorbed dose rate. Averages of all the radiation hazard indices and concentrations of all the measured radionuclides in all the layers are lower than the recommended level. The origin of the detected radionuclides is assessed by comparing the present results with the corresponding values for the earth crust and other rock formations.     

Grain Floatation During Equiaxed Solidification of an Al-Cu Alloy in a Side-Cooled Cavity: Part I—Experimental Studies

Experimental studies were performed to investigate the role and influence of grain movement on macrosegregation and microstructure evolution during equiaxed solidification. Casting experiments were performed with a grain-refined Al-Cu alloy in a rectangular sand mold. For the aluminum alloy studied, the equiaxed grains are lighter than the bulk melt and thus float up. Experiments were designed to investigate floatation phenomena of equiaxed grains in the presence of thermosolutal convection. Cooling curves were recorded at key locations in both the casting and the chill. Quantitative image analysis and spatial chemical analysis were performed on the solidified casting to observe the chemical and microstructural inhomogeneity created by the melt convection and solid floatation. Several notable features that can be attributed to grain movement were observed in temperature histories, macrosegregation patterns, and microstructures. In our experiments, the floatation of grains influences the thermal conditions and the overall flow direction in the casting cavity. In some cases, the induced flow resulting from the grain movement caused a flow reversal. This in turn influences the solidification direction, microstructure evolution, and the overall macrosegregation behavior.     

Computation of approximate optimal policies in a partially observed inventory model with rain checks

This paper proposes a new methodology to solve partially observed inventory problems. Generally, these problems have infinite-dimensional states that are conditional distributions of the inventory level. Our methodology involves linearizing the state transitions via unnormalized probabilities. It then uses an appropriate functional basis to represent the state. Considering the speed and stability of computations, we choose truncated Chebyshev polynomials as the basis. We use Fast Fourier Transforms along with an appropriate discretization of inventory levels to speed up the computations. These main ideas are blended to obtain an iterative algorithm to solve a partially observed inventory model with rain checks. In this model, the inventory manager (IM) does not know the inventory level when it is positive. Otherwise, the IM fully observes it. This model provides a context to illustrate our methodology, which applies to other such models. Although this model has been studied mathematically in the literature, the use of our algorithm provides a numerical approximation of the optimal order quantities. These are compared to the orders released under a base mean-stock policy, where the IM replaces the unobserved inventory level with its mean and applies the well-known base stock policy. We show numerically that the optimal order quantity is very close to the base mean-stock order quantity, when the variance of the inventory distribution is small. When the mean of the inventory distribution is large, the optimal order quantity is more than the base mean-stock quantity, and it is the other way around when the mean is small or negative. These insights are explained via uncertainty and information effects and their interplay. We expect this interplay to show up in other partially observed inventory models.