Electrical transport in magnesium aluminate

The conductivity of MgAl2O4 has been measured at 1273, 1473 and 1673 K as a function of the partial pressure of oxygen ranging from 105 to 10−14 Pa. The MgAl2O4 pellet, sandwiched between two platinum electrodes, was equilibrated with a flowing stream of either Ar + O2, CO + CO2 or Ar + H2 + H2O mixture of known composition. The gas mixture established a known oxygen partial pressure. All measurements were made at a frequency of 1 kHz. These measurements indicate pressure independent ionic conductivity in the range 1 to 10−14 Pa at 1273 K, 10−1 to 10−12 Pa at 1473 K and 10−1 to 10−4 Pa at 1673 K. The activation energy for ionic conduction is 1·48 eV, close to that for self-diffusion of Mg2+ ion in MgAl2O4 calculated from the theoretical relation of Glyde. Using the model, the energy for cation vacancy formation and activation energy for migration are estimated.

Dynamic response of latex modified concrete machine foundations

New materials in concrete constructions have been widely used to improve various properties such as impact resistance, strength and durability. Polymer modified concrete is one of the new materials which has been developed for potential application in the construction industry. This Paper describes the use of polymer latex for foundation blocks subjected to dynamic loads. Experiments were conducted using ordinary concrete and latex modified concrete footings of three different thicknesses, for three static loads at four excitation levels. Experimental results have revealed that the amplitude of resonance is reduced considerably in the latex modified concrete footings.

A structure-preserving energy function for stability analysis of AC/DC systems

Direct stability analysis ofAC/DC power systems using a structure-preserving energy function (SPEF) is proposed in this paper. The system model considered retains the load buses thereby enabling the representation of nonlinear voltage dependent loads. TheHVDC system is represented with the same degree of detail as is normally done in transient stability simulation. The converter controllers can be represented by simplified or detailed models. Two or multi-terminalDC systems can be considered. The stability analysis is illustrated with a 3-machine system example and encouraging results have been obtained.

Effect of High Pressure on the Electrical Conductivity of TlInX2 (X = Se, Te) Layered Semiconductors

The dc electrical conductivity of TlInX2 (X = Se, Te) single crystals, parallel and perpendicular to the (001) c-axis is studied under high quasi-hydrostatic pressure up to 7.0 GPa, at room temperature. Conductivity measurements parallel to the c-axis are carried out at high pressures and down to liquid nitrogen temperatures. These materials show continuous metallization under pressure. Both compounds have almost the same pressure coefficient of the electrical activation energy parallel to the c-axis, d(ΔE∥)/dP = −2.9 × 10−10 eV/Pa, which results from the narrowing of the band gap under pressure. The results are discussed in the light of the band structure of these compounds.

Electrical properties of cobalt‐zinc ferrites

The electrical properties of Co1−xZnxFe2O4 (x=0–1) spinel ferrites were investigated by impedance spectroscopy. The grain‐boundary resistance was found to increase as a function of composition up to x=0.6, and decreases beyond x=0.6. The variation in the bulk resistance and the activation energy as a function of composition is found to exhibit a similar trend whereas the grain resistance appears to be an independent parameter. The observed results suggest that the bulk properties of solid solution spinel ferrites are primarily controlled by the grain‐boundary phase.

Electrical-Resistivity Studies on GE-SE Glasses at High-Pressures and Low-Temperatures

High pressure electrical resistivity measurements were carried out on GexSe100-x (0 less-than-or-equal-to x less-than-or-equal-to 40) glasses at ambient and low temperatures using the Bridgman anvil system. All the melt quenched glasses show a discontinuous glassy semiconductor to crystalline metal transition at high pressures. The high pressure phases of Ge-Se samples do not correspond to any of the equilibrium phases of the system. Additionally, the variation of transition pressure (P(T)), ambient resistivity (rho0) and the activation energy (DELTAE(t)) with composition, exhibit a change in behaviour at x = 20 and 33. The unusual variations observed in these glasses are discussed in the light of chemical and percolation thresholds occurring in the glassy system.

Electrical switching and short-range order in As-Te glasses

The local structural order in chalcogenide network glasses is known to change markedly at two critical compositions, namely, the percolation and chemical thresholds. In the AsxTe100-x glassy system, both the thresholds coincide at the composition x = 40 (40 at. % of arsenic). It is demonstrated that the electrical switching fields of As-Te glasses exhibit a distinct change at this composition.

Electrical Contact Resistance in Thin (<= 0.5 mu m) Gold Plated Contacts: Effect of Gold Plating Thickness

This paper describes the electrical contact resistance (ECR) measurements made on thin gold plated (gold plating of <= 0.5 mu m with a Ni underlayer of similar to 2 mu m) oxygen free high conductivity (OFHC) Cu contacts in vacuum environment. ECR in gold plated OFHC Cu contacts is found to be slightly higher than that in bare OFHC Cu contacts. Even though gold is a softer material than copper, the relatively high ECR values observed in gold plated contacts are mainly due to the higher hardness and electrical resistivity of the underlying Ni layer. It is well known that ECR is directly related to plating factor, which increases with increasing coating thickness when the electrical resistivity of coating material is more than that of substrate. Surprisingly, in the present case it is found that the ECR decreases with increasing gold layer thickness on OFHC Cu substrate (gold has higher electrical resistivity than OFHC Cu). It is analytically demonstrated from the topography and microhardness measurements results that this peculiar behavior is associated with thin gold platings, where the changes in surface roughness and microhardness with increasing layer thickness overshadow the effect of plating factor on ECR.

Minimizing total completion time on a batch processing machine with job families

We consider the problem of minimizing the total completion time on a single batch processing machine. The set of jobs to be scheduled can be partitioned into a number of families, where all jobs in the same family have the same processing time. The machine can process at most B jobs simultaneously as a batch, and the processing time of a batch is equal to the processing time of the longest job in the batch. We analyze that properties of an optimal schedule and develop a dynamic programming algorithm of polynomial time complexity when the number of job families is fixed. The research is motivated by the problem of scheduling burn-in ovens in the semiconductor industry

Modelling and analysis of the variance in parallelism in parallel computations

In this paper, we introduce an analytical technique based on queueing networks and Petri nets for making a performance analysis of dataflow computations when executed on the Manchester machine. This technique is also applicable for the analysis of parallel computations on multiprocessors. We characterize the parallelism in dataflow computations through a four-parameter characterization, namely, the minimum parallelism, the maximum parallelism, the average parallelism and the variance in parallelism. We observe through detailed investigation of our analytical models that the average parallelism is a good characterization of the dataflow computations only as long as the variance in parallelism is small. However, significant difference in performance measures will result when the variance in parallelism is comparable to or higher than the average parallelism.

A Feature-Based Solution to Forward Problem in Electrical Capacitance Tomography of Conductive Materials

A new feature-based technique is introduced to solve the nonlinear forward problem (FP) of the electrical capacitance tomography with the target application of monitoring the metal fill profile in the lost foam casting process. The new technique is based on combining a linear solution to the FP and a correction factor (CF). The CF is estimated using an artificial neural network (ANN) trained using key features extracted from the metal distribution. The CF adjusts the linear solution of the FP to account for the nonlinear effects caused by the shielding effects of the metal. This approach shows promising results and avoids the curse of dimensionality through the use of features and not the actual metal distribution to train the ANN. The ANN is trained using nine features extracted from the metal distributions as input. The expected sensors readings are generated using ANSYS software. The performance of the ANN for the training and testing data was satisfactory, with an average root-mean-square error equal to 2.2%.

Resistivity imaging of a reconfigurable phantom with circular inhomogeneities in 2D-electrical impedance tomography

Resistivity imaging of a reconfigurable phantom with circular inhomogeneities is studied with a simple instrumentation and data acquisition system for Electrical Impedance Tomography. The reconfigurable phantom is developed with stainless steel electrodes and a sinusoidal current of constant amplitude is injected to the phantom boundary using opposite current injection protocol. Nylon and polypropylene cylinders with different cross sectional areas are kept inside the phantom and the boundary potential data are collected. The instrumentation and the data acquisition system with a DIP switch-based multiplexer board are used to inject a constant current of desired amplitude and frequency. Voltage data for the first eight current patterns (128 voltage data) are found to be sufficient to reconstruct the inhomogeneities and hence the acquisition time is reduced. Resistivity images are reconstructed from the boundary data for different inhomogeneity positions using EIDORS-2D. The results show that the shape and resistivity of the inhomogeneity as well as the background resistivity are successfully reconstructed from the potential data for single or double inhomogeneity phantoms. The resistivity images obtained from the single and double inhomogeneity phantom clearly indicate the inhomogeneity as the high resistive material. Contrast to noise ratio (CNR) and contrast recovery (CR) of the reconstructed images are found high for the inhomogeneities near all the electrodes arbitrarily chosen for the entire study. (C) 2010 Elsevier Ltd. All rights reserved.

Support vector machine for evaluating seismic-liquefaction potential using shear wave velocity

The use of the shear wave velocity data as a field index for evaluating the liquefaction potential of sands is receiving increased attention because both shear wave velocity and liquefaction resistance are similarly influenced by many of the same factors such as void ratio, state of stress, stress history and geologic age. In this paper, the potential of support vector machine (SVM) based classification approach has been used to assess the liquefaction potential from actual shear wave velocity data. In this approach, an approximate implementation of a structural risk minimization (SRM) induction principle is done, which aims at minimizing a bound on the generalization error of a model rather than minimizing only the mean square error over the data set. Here SVM has been used as a classification tool to predict liquefaction potential of a soil based on shear wave velocity. The dataset consists the information of soil characteristics such as effective vertical stress (sigma'(v0)), soil type, shear wave velocity (V-s) and earthquake parameters such as peak horizontal acceleration (a(max)) and earthquake magnitude (M). Out of the available 186 datasets, 130 are considered for training and remaining 56 are used for testing the model. The study indicated that SVM can successfully model the complex relationship between seismic parameters, soil parameters and the liquefaction potential. In the model based on soil characteristics, the input parameters used are sigma'(v0), soil type. V-s, a(max) and M. In the other model based on shear wave velocity alone uses V-s, a(max) and M as input parameters. In this paper, it has been demonstrated that Vs alone can be used to predict the liquefaction potential of a soil using a support vector machine model. (C) 2010 Elsevier B.V. All rights reserved.