Synthesis, Thermal stability and Mechanical Behavior of Nano-Nickel

Nanocrystalline materials exhibit very high strengths compared to conventional materials, but their thermal stability may be poor. Electrodeposition is one of the promising methods for obtaining dense nanomaterials. It is shown that use of two different baths and appropriate conditions enables the production of nano-Ni with properties similar to commercially available materials. Microindentation experiments revealed a four fold increase in hardness value for nano-Ni compared to conventional coarse grained Ni. An improved thermal stability of nano-Ni was observed on co-deposition of nano-Al2O3particles.

Microstructure, shape, stability and melting inembeddednanoparticles

The present article reviews some of the current work on a new class of materials which are nanoscale granular materials. We shall discuss in this paper two phase granular materials where one of the phases having nanometric dimension is embedded in a matrix of larger dimension. Known as nanoembedded materials, nanocomposites or ultrafine granular materials, this class of materials has attracted attention because of the opportunity of basic studies on the effect of size and embedding matrix on transformation behaviors as well as some novel properties, which include structural, magnetic and transport properties. These are in addition to the tremendous interests in what is known as quantum structures(embedded particles size less than 5 nm) for the case of semiconductors, which will not be discussed here. We shall primarily review the work done on metallic systems where the dispersed phases have low melting points and borrow extensively from the work done in our group. The phase transformations of the embedded particles show distinctive behavior and yield new insights. We shall first highlight briefly the strategy of synthesis of these materials by non-equilibrium processing techniques, which will be followed by examples where the effect of length scales on phase transformation behaviors like melting and solidification are discussed.

Stability numbers for an unsupported vertical circular excavation in c-phi soil

By using an axisymmetric lower bound finite element limit analysis formulation, the stability numbers (gamma H/C) for an unsupported vertical circular excavation in a cohesive-frictional soil have been generated. The numerical results are obtained for values of normalized excavation height (H/b) and friction angle (phi) greater than those considered previously in the literature. The results compare well with those available in literature. The stability numbers presented in this note would be beneficial from a design point of view. (C) 2011 Elsevier Ltd. All rights reserved.

CNT loading into cationic cholesterol suspensions show improved DNA binding and serum stability and ability to internalize into cancer cells

Methods which disperse single-walled carbon nanotubes (SWNTs) in water as `debundled', while maintaining their unique physical properties are highly useful. We present here a family of cationic cholesterol compounds (Chol(+)) {Cholest-5en-3 beta-oxyethyl pyridinium bromide (Chol-PB+), Cholest-5en-3 beta-oxyethyl N-methyl pyrrolidinium bromide (Chol-MPB+), Cholest-5en-3 beta-oxyethyl N-methyl morpholinium bromide (Chol-MMB+) and Cholest-5en-3 beta-oxyethyl diazabicyclo octanium bromide (Chol-DOB+)}. Each of these could be easily dispersed in water. The resulting cationic cholesterol (Chol(+)) suspensions solubilized single-walled carbon nanotubes (SWCNTs) by the non-specific physical adsorption of Chol(+) to form stable, transparent, dark aqueous suspensions at room temperature. Electron microscopy reveals the existence of highly segregated CNTs in these samples. Zeta potential measurements showed an increase in potential of cationic cholesterol aggregates on addition of CNTs. The CNT-Chol(+) suspensions were capable of forming stable complexes with genes (DNA) efficiently. The release of double-helical DNA from such CNT-Chol(+) complexes could be induced upon the addition of anionic micellar solution of SDS. Furthermore, the CNT-based DNA complexes containing cationic cholesterol aggregates showed higher stability in fetal bovine serum media at physiological conditions. Confocal studies confirm that CNT-Chol(+) formulations adhere to HeLa cell surfaces and get internalized more efficiently than the cationic cholesterol suspensions alone (devoid of any CNTs). These cationic cholesterol-CNT suspensions therefore appear to be a promising system for further use in biological applications.

Seismic reliability assessment of internal stability of reinforced soil walls using the pseudo-dynamic method

The study focuses on probabilistic assessment of the internal seismic stability of reinforced soil structures (RSS) subjected to earthquake loading in the framework of the pseudo-dynamic method. In the literature, the pseudo-static approach has been used to compute reliability indices against the tension and pullout failure modes, and the real dynamic nature of earthquake accelerations cannot be considered. The work presented in this paper makes use of the horizontal and vertical sinusoidal accelerations, amplification of vibrations, shear wave and primary wave velocities and time period. This approach is applied to quantify the influence of the backfill properties, geosynthetic reinforcement and characteristics of earthquake ground motions on reliability indices in relation to the tension and pullout failure modes. Seismic reliability indices at different levels of geosynthetic layers are determined for different magnitudes of seismic acceleration, soil amplification, shear wave and primary wave velocities. The results are compared with the pseudo-static method, and the significance of the present methodology for designing reinforced soil structures is discussed.

Appraisal of Bishop's method of slope stability analysis

The stability of slopes is a major problem in geotechnical engineering. Of the methods available for the analysis of soil slopes such as limit equilibrium methods, limit analysis and numerical methods such as FEM and FDM, limit equilibrium methods are popular and generally used, owing to their simplicity in formulation and in evaluating the overall factor of safety of slope. However limit equilibrium methods possess certain disadvantages. They do not consider whether the slope is an embankment or natural slope or an excavation and ignore the effect of incremental construction, initial stress, stress strain behavior etc. In the work reported in this paper, a comparative study of actual state of stress and actual factor of safety and Bishop's factor of safety is performed. The actual factor of safety is obtained by consideration of contours of mobilised shear strains. Using Bishop's method of slices, the critical slip surfaces of a number of soil slopes with different geometries are determined and both the factors of safety are obtained. The actual normal stresses and shear stresses are determined from finite difference formulation using FLAG (Fast Lagrangian Analysis of Continuaa) with Mohr-Coulomb model. The comparative study is performed in terms of parameter lambda(c phi) (= gamma H tan phi/c). I is shown that actual factor of safety is higher than Bishop's factor of safety depending on slope angle and lambda(c phi).

Effect of strength - Matric suction variations on stability of a natural slope

Stability analysis of residual soil slopes are now increasingly being performed with the incorporation of the matric suction component of strength. The matric suction (u(a)-u(w)) component of shear strength is known as apparent cohesion. The relation between matric suction and apparent cohesion (c(app)) may be linear or non-linear. The impact of type of apparent strength versus matric suction relationship on the stability of an unsaturated residual soil slope is examined in this study. Results of the study showed that the factor of safety values were unaffected by the nature of the strength versus matric suction relationship for the residual soil slope examined. This was so as contribution from the effective stress- strength component to the factor of safety predominated over the contribution made by the apparent strength component.

Optimal static voltage stability improvement using a numerically stable SLP algorithm, for real time applications

A numerically stable sequential Primal–Dual LP algorithm for the reactive power optimisation (RPO) is presented in this article. The algorithm minimises the voltage stability index C 2 [1] of all the load buses to improve the system static voltage stability. Real time requirements such as numerical stability, identification of the most effective subset of controllers for curtailing the number of controllers and their movement can be handled effectively by the proposed algorithm. The algorithm has a natural characteristic of selecting the most effective subset of controllers (and hence curtailing insignificant controllers) for improving the objective. Comparison with transmission loss minimisation objective indicates that the most effective subset of controllers and their solution identified by the static voltage stability improvement objective is not the same as that of the transmission loss minimisation objective. The proposed algorithm is suitable for real time application for the improvement of the system static voltage stability.

Selection of Static VAR Compensator Location and Size for System Voltage Stability Improvement

This paper presents a methodology for selection of static VAR compensator location based on static voltage stability analysis of power systems. The analysis presented here uses the L-index of load buses, which includes voltage stability information of a normal load flow and is in the range of 0 (no load of system) to 1 (voltage collapse). An approach has been presented to select a suitable size and location of static VAR compensator in an EHV network for system voltage stability improvement. The proposed approach has been tested under simulated conditions on a few power systems and the results for a sample radial network and a 24-node equivalent EHV power network of a practical system are presented for illustration purposes. © 2000 Published by Elsevier Science S.A. All rights reserved.

An ANN based approach for voltage stability assessment

Artificial Neural Networks (ANNs) have recently been proposed as an alterative method for salving certain traditional problems in power systems where conventional techniques have not achieved the desired speed, accuracy or efficiency. This paper presents application of ANN where the aim is to achieve fast voltage stability margin assessment of power network in an energy control centre (ECC), with reduced number of appropriate inputs. L-index has been used for assessing voltage stability margin. Investigations are carried out on the influence of information encompassed in input vector and target out put vector, on the learning time and test performance of multi layer perceptron (MLP) based ANN model. LP based algorithm for voltage stability improvement, is used for generating meaningful training patterns in the normal operating range of the system. From the generated set of training patterns, appropriate training patterns are selected based on statistical correlation process, sensitivity matrix approach, contingency ranking approach and concentric relaxation method. Simulation results on a 24 bus EHV system, 30 bus modified IEEE system, and a 82 bus Indian power network are presented for illustration purposes.

Molybdenum trioxide catalyzed oxidative cross-dehydrogenative coupling of benzylic sp(3) C-H bonds: synthesis of alpha-aminophosphonates under aerobic conditions

Molybdenum trioxide (MoO3) catalyzed efficient oxidative cross-dehydrogenative-coupling (CDC) method for C-H functionalization of N-aryl tetrahydroisoquinolines has been explored. This user-friendly method of synthesizing alpha-aminophosphonates employs 1.1 equiv of dialkyl-H-phosphonate under aerobic condition. Formation of new C-P bonds from unfunctionalized starting materials under environmentally benign conditions provides an excellent avenue for the synthesis of biologically active alpha-aminophosphonates. (C) 2012 Elsevier Ltd. All rights reserved.

Voltage stability : some reflections on Q-V characteristics of loads

Considering voltage stability as a static viability problem, this paper takes a particular concern of Q-V characteristics and reflects on certain notions that do not seem to have been explicitly mentioned or derived in the existing documented literature. The equations of Q-V characteristics are rederived in exactness, some salient points on the curve are discovered and analysed. The results of the analysis are illustrated through a case study

Artificial neural network application to power system voltage stability improvement

As power systems grow in their size and interconnections, their complexity increases. Rising costs due to inflation and increased environmental concerns has made transmission, as well as generation systems be operated closer to design limits. Hence power system voltage stability and voltage control are emerging as major problems in the day-to-day operation of stressed power systems. For secure operation and control of power systems under normal and contingency conditions it is essential to provide solutions in real time to the operator in energy control center (ECC). Artificial neural networks (ANN) are emerging as an artificial intelligence tool, which give fast, though approximate, but acceptable solutions in real time as they mostly use the parallel processing technique for computation. The solutions thus obtained can be used as a guide by the operator in ECC for power system control. This paper deals with development of an ANN architecture, which provide solutions for monitoring, and control of voltage stability in the day-to-day operation of power systems.

Novel algorithm for online voltage stability assessment based on feed forward neural network

This paper presents an artificial feed forward neural network (FFNN) approach for the assessment of power system voltage stability. A novel approach based on the input-output relation between real and reactive power, as well as voltage vectors for generators and load buses is used to train the neural net (NN). The input properties of the feed forward network are generated from offline training data with various simulated loading conditions using a conventional voltage stability algorithm based on the L-index. The neural network is trained for the L-index output as the target vector for each of the system loads. Two separate trained NN, corresponding to normal loading and contingency, are investigated on the 367 node practical power system network. The performance of the trained artificial neural network (ANN) is also investigated on the system under various voltage stability assessment conditions. As compared to the computationally intensive benchmark conventional software, near accurate results in the value of L-index and thus the voltage profile were obtained. Proposed algorithm is fast, robust and accurate and can be used online for predicting the L-indices of all the power system buses. The proposed ANN approach is also shown to be effective and computationally feasible in voltage stability assessment as well as potential enhancements within an overall energy management system in order to determining local and global stability indices