The role of globalization on the recent evolution of energy demand in India: Implications for sustainable development

Using annual data for the period 1971–2012, this study explores the relationship between globalization and energy consumption for India by endogenizing economic growth, financial development and urbanization. The cointegration test proposed by Bayer–Hanck (2013) is applied to estimate the long-run and short-run relationships among the variables. After confirming the existence of cointegration, the overall results from the estimation of an ARDL energy demand function reveal that in the long run, the acceleration of globalization (measured in three dimensions — economic, social and overall globalization) leads to a decline in energy demand in India. Furthermore, while financial development is negatively related to energy consumption, economic growth and urbanization are the key factors leading to increased energy demand in the long run. These results have policy implications for the sustainable development of India. In particular, globalization and financial development provide a win–win situation for India to increase its economic growth in the long run and become more environmentally sustainable.     

Transducer invariant multi-class fault classification in a rotor-bearing system using support vector machines

Faults in a rotor-bearing system due to bearings and unbalance have been classified using support vector machines (SVMs). Vibration signals on a rotor-bearing system were measured simultaneously at five different rotating speeds using seven transducers. The most sensitive feature of the vibration signals has been determined using compensation distance evaluation technique. Multi-class SVMs classification algorithm was then implemented for classification of the faults by considering SVMs created by the possible combinations of the most two sensitive features for each type of fault. By using optimal SVM parameters, the effective location of transducer among seven transducers for best classification of the faults has been investigated and found that any transducer provides a classification of 75% or better and this classification rate increases when more transducers are considered. This paper provides a robust SVM based technique using only time domain data without any additional preprocessing for classifying bearing and unbalance faults.     

Synthesis of zirconia porous phosphate heterostructures (Zr-PPH) for Prins condensation

Porous phosphate heterostructure materials with zirconia galleries have been prepared. Their acid properties were studied via 2,6-di-tert-butyl-pyridine adsorption, infrared spectra of pyridine adsorption and potentiometric titration. The samples prepared in alcohol media are more thermal stable than those prepared in aqueous media. They are very active and selective for the Prins condensation of β-pinene with paraformaldehyde because of large amount of Lewis acid sites as well as proper L/B ratio. The selectivity towards Nopol can be further improved by ion-exchanging with sodium cations, due to the elimination of Brønsted acid sites which suppresses the by-reactions such as isomerization of β-pinene.     

Explicit solutions for the response probability density function of nonlinear transformations of static random inputs

This work is the second paper of two companion ones. Both of them show the use of a new version of the Probabilistic Transformation Method (PTM) for finding the probability density function (pdf) of a limited number of response quantities in the transformations of static random inputs. This is made without performing multi-dimensional integrals of the response total joint pdf for saturating the non-interested variables. While in the first paper the linear transformations have been considered, in the present one some nonlinear systems are taken into account. In particular, first the case when the loads on a linear structural system are a nonlinear combination of static random inputs is studied. Then the attention is placed on the case of nonlinear structural systems, for which the new version of the PTM allows to determine approximated, but accurate, results.     

Carbon emissions,energy consumption and economic growth: An aggregate and disaggregate analysis of the Indian economy

This study investigates the long and short run relationships among carbon emissions, energy consumption and economic growth in India at the aggregated and disaggregated levels during 1971–2014. The autoregressive distributed lag model is employed for the cointegration analyses and the vector error correction model is applied to determine the direction of causality between variables. Results show that a long run cointegration relationship exists and that the environmental Kuznets curve is validated at the aggregated and disaggregated levels. Furthermore, energy (total energy, gas, oil, electricity and coal) consumption has a positive relationship with carbon emissions and a feedback effect exists between economic growth and carbon emissions. Thus, energy-efficient technologies should be used in domestic production to mitigate carbon emissions at the aggregated and disaggregated levels. The present study provides policy makers with new directions in drafting comprehensive policies with lasting impacts on the economy, energy consumption and environment towards sustainable development.     

A direct two-dimensional pressure formulation in molecular dynamics

Two-dimensional (2D) pressure field estimation in molecular dynamics (MD) simulations has been done using three-dimensional (3D) pressure field calculations followed by averaging, which is computationally expensive due to 3D convolutions. In this work, we develop a direct 2D pressure field estimation method which is much faster than 3D methods without losing accuracy. The method is validated with MD simulations on two systems: a liquid film and a cylindrical drop of argon suspended in surrounding vapor.     

Smart SCADA system for urban air pollution monitoring

There are a number of different types of monitoring stations for checking air quality levels in urban environments. These monitoring stations usually just perform data acquisition of the measured values from the sensors and store them in the database. The processing of the measured results as well as the statistical analysis is mainly done in other places where the data come from various communication systems. Acquisition of the measured data is commonly done on-line while the processing and statistical analysis is performed off-line. As opposed to these measurement systems, this implemented device enables the acquisition and statistical processing of the measured data in real time and the results are instantly available to all users. The system indicates the air pollutants using the ARMA model. The transmission of information in the realized smart SCADA system is done by the Modbus protocol using shared variables which gives the whole system a stronger hierarchical structure.     

Influence of iron deficiency on electric and magnetic behavior of Ho doped BiFeO3 electroceramic

The effect of iron deficiency for the improvement of multiferroic properties of Ho doped BiFeO₃ ceramics (BiHo_XFe_1?XO₃ for x = 0, 0.05, 0.1 and 0.15) prepared by conventional solid state reaction route were investigated carefully. As pure BiFeO₃ exhibited antiferromagnetism, lossy ferroelectric (P–E) hysteresis loop and low dielectric constant value so, device integration is significantly hindered due to the presence of impurity phases associated with it. However, suitable variation of metal ion concentration in Ho doped BiFeO₃ significantly enhanced both ferroelectric and ferromagnetic properties of the samples. Therefore, increase of Ho concentration certainly favors for suppression of impurity phases in rhombohedral (R3c) structure of BiFeO₃ along with no structural transformation. On the other hand, increase of iron deficiency may suppress transformation of Fe from Fe³⁺ to Fe²⁺ as a result, the dielectric constant value of the sample increases along with large reduction of leakage current behavior.     

Design and analysis of multi-source multi-area deregulated power system for automatic generation control using quasi-oppositional harmony search algorithm

The present article focuses on the study of automatic generation control (AGC) of a realistic power system having a distinct combination of multi-area multi-source generating units in each control area under deregulated framework. An attempt is made in this paper to integrate reheat thermal, hydro and gas generating unit in a single control area and, then, extended this combination to five control areas. In this work, six reheat thermal, six hydro and three gas generating units are taken into account for the modeling of five-area power system. Some important physical constraints like time delay, governor dead band and generation rate constraint are imposed in the power system dynamics to get an accurate perception of the deregulated AGC subject. The highlighting features of the present work are to model, simulate, optimize and co-relate their inter-related dynamic performances for the purpose of AGC study. For such a complex AGC model, the vital role of the proposed quasi-oppositional harmony search (QOHS) algorithm, as an optimizing tool, is signified while solving the AGC problem in deregulated regime. The simplicity of the structure and acceptability of the responses of the well-known proportional–integral–derivative controller, inherently, enforces to employ in this work. The three classes of extensive deregulated cases (in the presence of load following and physical constraints) are demonstrated by examining the closed loop performance of the studied model. The simulation results show that the designed power system model may be a feasible one and the proposed QOHS algorithm may be a promising optimization technique under these circumstances.     

Automatic generation control of a multi-area system using ant lion optimizer algorithm based PID plus second order derivative controller

This article presents the automatic generation control of an unequal three area thermal system. Single stage reheat turbines and generation rate constraints of 3%/min are considered in each control area. Controllers such as Integral (I), Proportional – Integral (PI), Proportional – Integral – Derivative (PID), and Proportional – Integral – Derivative Plus Second Order Derivative (PID + DD) are treated as secondary controllers separately. A nature inspired optimization technique called Ant Lion Optimizer (ALO) algorithm is used for simultaneous optimization of the controller gains. Comparison of dynamic responses of frequencies and tie line powers corresponding to ALO optimized I, PI, PID and PID + DD controller reveal the better performance of PID + DD controller in terms of lesser settling time, peak overshoots as well as reduced oscillations. Robustness of the optimum gains of best controller obtained at nominal conditions is evaluated using sensitivity analysis. Analysis exposed that the optimum PID + DD controller gains obtained at nominal are robust and not necessary to reset again for changes in loading, parameter like inertia constant (H), size and position of disturbance. Furthermore, the performance of PID + DD controller is found better as compared to PID controller against random loading pattern condition.