Comparative studies of transient and steady state analysis for a typical 765kV/400kV EHV transmission system in Indian power system

This paper describes an approach for the analysis and design of 765kV/400kV EHV transmission system which is a typical expansion in Indian power grid system, based on the analysis of steady state and transient over voltages. The approach for transmission system design is iterative in nature. The first step involves exhaustive power flow analysis, based on constraints such as right of way, power to be transmitted, power transfer capabilities of lines, existing interconnecting transformer capabilities etc. Acceptable bus voltage profiles and satisfactory equipment loadings during all foreseeable operating conditions for normal and contingency operation are the guiding criteria. Critical operating strategies are also evolved in this initial design phase. With the steady state over voltages obtained, comprehensive dynamic and transient studies are to be carried out including switching over voltages studies. This paper presents steady state and switching transient studies for alternative two typical configurations of 765kV/400 kV systems and the results are compared. Transient studies are carried out to obtain the peak values of 765 kV transmission systems and are compared with the alternative configurations of existing 400 kV systems.

A neural network based CBIR system using STI features and relevance feedback

Multimedia mining primarily involves, information analysis and retrieval based on implicit knowledge. The ever increasing digital image databases on the Internet has created a need for using multimedia mining on these databases for effective and efficient retrieval of images. Contents of an image can be expressed in different features such as Shape, Texture and Intensity-distribution(STI). Content Based Image Retrieval(CBIR) is an efficient retrieval of relevant images from large databases based on features extracted from the image. Most of the existing systems either concentrate on a single representation of all features or linear combination of these features. The paper proposes a CBIR System named STIRF (Shape, Texture, Intensity-distribution with Relevance Feedback) that uses a neural network for nonlinear combination of the heterogenous STI features. Further the system is self-adaptable to different applications and users based upon relevance feedback. Prior to retrieval of relevant images, each feature is first clustered independent of the other in its own space and this helps in matching of similar images. Testing the system on a database of images with varied contents and intensive backgrounds showed good results with most relevant images being retrieved for a image query. The system showed better and more robust performance compared to existing CBIR systems

Soft condensed matter -A special issue of solid state communications -Foreword

It is a policy of Solid State Communications’ Executive Editorial Board to organize special issues from time to time on topics of current interests. The present issue focuses on soft condensed matter, a rapidly developing and diverse area of importance not only for the basic science, but also for its potential applications. The ten articles in this issue are intended to give the readers a snapshot of some latest developments in soft condensed matter, mainly from the point of view of basic science. As the special issues are intended for a broad audience, most articles are short reviews that introduce the readers to the relevant topics. Hence this special issue can be especially helpful to readers who might not be specialists in this area but would like to have a quick grasp on some of the interesting research directions.

Robust multivariable controllers for a tublar ammonia reactor

The specific objective of this paper is to develop multivariable controllers that would achieve asymptotic regulation in the presence of parameter variations and disturbance inputs for a tubular reactor used in ammonia synthesis. A ninth order state space model with three control inputs and two disturbance inputs is generated from the nonlinear distributed model using linearization and lumping approximations. Using this model, an approach for control system design is developed keeping in view the imperfections of the model and the measurability of the state variables. Specifically, the design of feedforward and robust integral controllers using state and output feedback is considered. Also, the design of robust multiloop proportional integral controllers is presented. Finally the performance of these controllers is evaluated through simulation.

Fate of the superconducting ground state on the Moyal plane

It is known that Berry curvature of the band structure of certain crystals can lead to effective noncommutativity between spatial coordinates. Using the techniques of twisted quantum field theory, we investigate the question of the formation of a paired state of twisted fermions in such a system. We find that to leading order in the noncommutativity parameter, the gap between the non-interacting ground state and the paired state is smaller compared to its commutative counterpart. This suggests that BCS type superconductivity, if present in such systems, is more fragile and easier to disrupt. (C) 2010 Elsevier B.V. All rights reserved.

Analysis of the beta-glucoside utilization (bgl) genes of Shigella sonnei: evolutionary implications for their maintenance in a cryptic state

The pattern of expression of the genes involved in the utilization of aryl beta-glucosides such as arbutin and salicin is different in the genus Shigella compared to Escherichia coli. The results presented here indicate that the homologue of the cryptic bgl operon of E. coli is conserved in Shigella sonnei and is the primary system involved in beta-glucoside utilization in the organism. The organization of the bgl genes in 5. sonnei is similar to that of E. coli; however there are three major differences in terms of their pattern of expression. (i) The bglB gene, encoding phospho-beta-glucosidase B, is insertionally inactivated in 5. sonnei. As a result, mutational activation of the silent bgl promoter confers an Arbutin-positive (Arb(+)) phenotype to the cells in a single step; however, acquiring a Salicin-positive (Sal(+)) phenotype requires the reversion or suppression of the bglB mutation in addition. (ii) Unlike in E. coli, a majority of the activating mutations (conferring the Arb(+) phenotype) map within the unlinked hns locus, whereas activation of the E. coli bgl operon under the same conditions is predominantly due to insertions within the bglR locus. (iii) Although the bgl promoter is silent in the wild-type strain of 5. sonnei (as in the case of E. coli), transcriptional and functional analyses indicated a higher basal level of transcription of the downstream genes. This was correlated with a 1 bp deletion within the putative Rho-independent terminator present in the leader sequence preceding the homologue of the bglG gene. The possible evolutionary implications of these differences for the maintenance of the genes in the cryptic state are discussed.

Studies on nonisothermal solid state galvanic cells — effect of gradients on EMF

An expression for the EMF of a nonisothermal galvanic cell, with gradients in both temperature and chemical potential across a solid electrolyte, is derived based on the phenomenological equations of irreversible thermodynamics. The EMF of the nonisothermal cell can be written as a sum of the contributions from the chemical potential gradient and the EMF of a thermocell operating in the same temperature gradient but at unit activity of the neutral form of the migrating species. The validity of the derived equation is confirmed experimentally by imposing nonlinear gradients of temperature and chemical potential across galvanic cells constructed using fully stabilized zirconia as the electrolyte. The nature of the gradient has no effect on the EMF.

Reliability models for existing structures based on dynamic state estimation and data based asymptotic extreme value analysis

The problem of time variant reliability analysis of existing structures subjected to stationary random dynamic excitations is considered. The study assumes that samples of dynamic response of the structure, under the action of external excitations, have been measured at a set of sparse points on the structure. The utilization of these measurements m in updating reliability models, postulated prior to making any measurements, is considered. This is achieved by using dynamic state estimation methods which combine results from Markov process theory and Bayes' theorem. The uncertainties present in measurements as well as in the postulated model for the structural behaviour are accounted for. The samples of external excitations are taken to emanate from known stochastic models and allowance is made for ability (or lack of it) to measure the applied excitations. The future reliability of the structure is modeled using expected structural response conditioned on all the measurements made. This expected response is shown to have a time varying mean and a random component that can be treated as being weakly stationary. For linear systems, an approximate analytical solution for the problem of reliability model updating is obtained by combining theories of discrete Kalman filter and level crossing statistics. For the case of nonlinear systems, the problem is tackled by combining particle filtering strategies with data based extreme value analysis. In all these studies, the governing stochastic differential equations are discretized using the strong forms of Ito-Taylor's discretization schemes. The possibility of using conditional simulation strategies, when applied external actions are measured, is also considered. The proposed procedures are exemplifiedmby considering the reliability analysis of a few low-dimensional dynamical systems based on synthetically generated measurement data. The performance of the procedures developed is also assessed based on a limited amount of pertinent Monte Carlo simulations. (C) 2010 Elsevier Ltd. All rights reserved.

Multicriterion differential games with applications to combat problems

In this paper a theory for two-person zero sum multicriterion differential games is presented. Various solution concepts based upon the notions of Pareto optimality (efficiency), security and equilibrium are defined. These are shown to have interesting applications in the formulation and analysis of two target or combat differential games. The methods for obtaining outcome regions in the state space, feedback strategies for the players and the mode of play has been discussed in the framework of bicriterion zero sum differential games. The treatment is conceptual rather than rigorous.

Spatial survival probability for one-dimensional fluctuating interfaces in the steady state

We report numerical and analytic results for the spatial survival probability for fluctuating one-dimensional interfaces with Edwards-Wilkinson or Kardar-Parisi-Zhang dynamics in the steady state. Our numerical results are obtained from analysis of steady-state profiles generated by integrating a spatially discretized form of the Edwards-Wilkinson equation to long times. We show that the survival probability exhibits scaling behavior in its dependence on the system size and the "sampling interval" used in the measurement for both "steady-state" and "finite" initial conditions. Analytic results for the scaling functions are obtained from a path-integral treatment of a formulation of the problem in terms of one-dimensional Brownian motion. A "deterministic approximation" is used to obtain closed-form expressions for survival probabilities from the formally exact analytic treatment. The resulting approximate analytic results provide a fairly good description of the numerical data.

Joint Source-Channel Coding over a Fading Multiple Access Channel with Partial Channel State Information

In this paper we address the problem of transmission of correlated sources over a fast fading multiple access channel (MAC) with partial channel state information available at both the encoders and the decoder. We provide sufficient conditions for transmission with given distortions. Next these conditions are specialized to a Gaussian MAC (GMAC). We provide the optimal power allocation strategy and compare the strategy with various levels of channel state information.

Trade Liberalization, Heterogeneous Firms and Industrial Dynamics

This master thesis studies how trade liberalization affects the firm-level productivity and industrial evolution. To do so, I built a dynamic model that considers firm-level productivity as endogenous to investigate the influence of trade on firm’s productivity and the market structure. In the framework, heterogeneous firms in the same industry operate differently in equilibrium. Specifically, firms are ex ante identical but heterogeneity arises as an equilibrium outcome. Under the setting of monopolistic competition, this type of model yields an industry that is represented not by a steady-state outcome, but by an evolution that rely on the decisions made by individual firms. I prove that trade liberalization has a general positive impact on technological adoption rates and hence increases the firm-level productivity. Besides, this endogenous technology adoption model also captures the stylized facts: exporting firms are larger and more productive than their non-exporting counterparts in the same sector. I assume that the number of firms is endogenous, since, according to the empirical literature, the industrial evolution shows considerably different patterns across countries; some industries experience large scale of firms’ exit in the period of contracting market shares, while some industries display relative stable number of firms or gradually increase quantities. The special word “shakeout” is used to describe the dramatic decrease in the number of firms. In order to explain the causes of shakeout, I construct a model where forward-looking firms decide to enter and exit the market on the basis of their state of technology. In equilibrium, firms choose different dates to adopt innovation which generate a gradual diffusion process. It is exactly this gradual diffusion process that generates the rapid, large-scale exit phenomenon. Specifically, it demonstrates that there is a positive feedback between firm’s exit and adoption, the reduction in the number of firms increases the incentives for remaining firms to adopt innovation. Therefore, in the setting of complete information, this model not only generates a shakeout but also captures the stability of an industry. However, the solely national view of industrial evolution neglects the importance of international trade in determining the shape of market structure. In particular, I show that the higher trade barriers lead to more fragile markets, encouraging the over-entry in the initial stage of industry life cycle and raising the probability of a shakeout. Therefore, more liberalized trade generates more stable market structure from both national and international viewpoints. The main references are Ederington and McCalman(2008,2009).

Determination of activation energy for thermal regeneration of EL2 from its metastable state by thermally stimulated photocurrent measurements

It is shown that thermally stimulated photocurrent measurements provide a simple and effective method of determining the activation energy of thermal regeneration rate of EL2 from the metastable state to the normal state in undoped semi‐insulating GaAs. The thermal regeneration rate r is found to be 2.5×108 exp(−0.26 eV/kT) s−1.