Pulsed plasma treatment of polluted gas using wet/low temperature corona reactors

Application of pulsed plasma for gas cleaning is gaining prominence in recent years mainly from the energy consideration point of view. Normally, gas treatment is carried out, at or above room temperature, by a conventional dry type corona reactor. However, this treatment is still inadequate in the removal of certain stable gases present in the exhaust/flue gas mixture. The authors report some interesting results of the treatment of such stable gases with pulsed plasma at very low ambient temperature. Also reported in the paper is an improvement in DeNO/DeNOx efficiency using unconventional wet-type reactors, designed and fabricated by the authors, operating at different ambient temperatures. Apart from laboratory tests on simulated gas mixtures, field tests were also carried out on the exhaust gas of a 8 kW diesel engine. Further, an attempt was made to test the feasibility of a helical wire as a corona electrode in place of the conventional straight wire electrode. A comparative analysis of the various tests is presented together with a note on the energy consideration

Performance evaluation of nonthermal plasma reactors for NO oxidation in diesel engine exhaust gas treatment

The discharge plasma-chemical hybrid process for NO/sub x/ removal from the due gas emissions is an extremely effective and economical approach in comparison with the conventional selective catalytic reduction system. In this paper we bring out a relative comparison of several discharge plasma reactors from the point of NO removal efficiency. The reactors were either energized by AC or by repetitive pulses. Ferroelectric pellets were used to study the effect of pellet assisted discharges on gas cleaning. Diesel engine exhaust, at different loads, is used to approximately simulate the due gas composition. Investigations were carried out at room temperature with respect to the variation of reaction products against the discharge power. Main emphasis is laid on the oxidation of NO to NO/sub 2/, without reducing NOx concentration (i.e., minimum reaction byproducts), with least power consumption. The produced NO/sub 2/ will be totally converted to N/sub 2/ and Na/sub 2/SO/sub 4/ using Na/sub 2/SO/sub 3/. The AC packed bed reactor and pelletless pulsed corona reactor showed better performance, with minimum reaction products for a given power, when the NO concentration was low (/spl sim/100 ppm). At high engine loads (NO>300 ppm) there was not much decrease in NO/sub x/ reduction and more or less all the reactors performed equally. The paper discusses these observations in detail.

Neural network based power system damping controller for SVC

The development of a neural network based power system damping controller (PSDC) for a static VAr compensator (SVC), designed to enhance the damping characteristics of a power system network representing a part of the Electricity Generating Authority of Thailand (EGAT) system is presented. The proposed stabilising controller scheme of the SVC consists of a neuro-identifier and a neuro-controller which have been developed based on a functional link network (FLN) model. A recursive online training algorithm has been utilised to train the two networks. The simulation results have been obtained under various operating conditions and disturbance cases to show that the proposed stabilising controller can provide a better damping to the low frequency oscillations, as compared to the conventional controllers. The effectiveness of the proposed stabilising controller has also been compared with a conventional power system stabiliser provided in the generator excitation system

Neural network based power system damping controller for SVC

The development of a neural network based power system damping controller (PSDC) for a static Var compensator (SVC), designed to enhance the damping characteristics of a power system network representing a part of the Electricity Generating Authority of Thailand (EGAT) system is presented. The proposed stabilising controller scheme of the SVC consists of a neuro-identifier and a neuro-controller which have been developed based on a functional link network (FLN) model. A recursive online training algorithm has been utilised to train the two networks. The simulation results have been obtained under various operating conditions and disturbance cases to show that the proposed stabilising controller can provide a better damping to the low frequency oscillations, as compared to the conventional controllers. The effectiveness of the proposed stabilising controller has also been compared with a conventional power system stabiliser provided in the generator excitation system.

A neural network based power system stabilizer suitable for on-line training-a practical case study for EGAT system

This paper presents the development of a neural network based power system stabilizer (PSS) designed to enhance the damping characteristics of a practical power system network representing a part of Electricity Generating Authority of Thailand (EGAT) system. The proposed PSS consists of a neuro-identifier and a neuro-controller which have been developed based on functional link network (FLN) model. A recursive on-line training algorithm has been utilized to train the two neural networks. Simulation results have been obtained under various operating conditions and severe disturbance cases which show that the proposed neuro-PSS can provide a better damping to the local as well as interarea modes of oscillations as compared to a conventional PSS

Cytocompatibility property evaluation of gas pressure sintered SiAlON-SiC composites with L929 fibroblast cells and Saos-2 osteoblast-like cells

Although the oxide ceramics have widely been investigated for their biocompatibility, non-oxide ceramics, such as SiAlON and SiC are yet to be explored in detail. Lack of understanding of the biocompatibility restricts the use of these ceramics in clinical trials. It is hence, essential to carry out proper and thorough study to assess cell adhesion, cytocompatibility and cell viability on the non-oxide ceramics for the potential applications. In this perspective, the present research work reports the cytocompatibility of gas pressure sintered SiAlON monolith and SiAlON-SiC composites with varying amount of SIC, using connective tissue cells (L929) and bone cells (Saos-2). The quantification of cell viability using MTT assay reveals the non-cytotoxic response. The cell viability has been found to be cell type dependent. An attempt has been made to discuss the cytocompatibility of the developed composites in the light of SiC content and type of sinter additives. (C) 2011 Elsevier B.V. All rights reserved.

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

Cause and Effect of Feedback: Multiphase Gas in Cluster Cores Heated by AGN Jets

Multiwavelength data indicate that the X-ray-emitting plasma in the cores of galaxy clusters is not cooling catastrophically. To a large extent, cooling is offset by heating due to active galactic nuclei (AGNs) via jets. The cool-core clusters, with cooler/denser plasmas, show multiphase gas and signs of some cooling in their cores. These observations suggest that the cool core is locally thermally unstable while maintaining global thermal equilibrium. Using high-resolution, three-dimensional simulations we study the formation of multiphase gas in cluster cores heated by collimated bipolar AGN jets. Our key conclusion is that spatially extended multiphase filaments form only when the instantaneous ratio of the thermal instability and free-fall timescales (t(TI)/t(ff)) falls below a critical threshold of approximate to 10. When this happens, dense cold gas decouples from the hot intracluster medium (ICM) phase and generates inhomogeneous and spatially extended Ha filaments. These cold gas clumps and filaments ``rain'' down onto the central regions of the core, forming a cold rotating torus and in part feeding the supermassive black hole. Consequently, the self-regulated feedback enhances AGN heating and the core returns to a higher entropy level with t(TI)/t(ff) > 10. Eventually, the core reaches quasi-stable global thermal equilibrium, and cold filaments condense out of the hot ICM whenever t(TI)/t(ff) less than or similar to 10. This occurs despite the fact that the energy from AGN jets is supplied to the core in a highly anisotropic fashion. The effective spatial redistribution of heat is enabled in part by the turbulent motions in the wake of freely falling cold filaments. Increased AGN activity can locally reverse the cold gas flow, launching cold filamentary gas away from the cluster center. Our criterion for the condensation of spatially extended cold gas is in agreement with observations and previous idealized simulations.

Isomeric identification of methylated naphthalenes using gas phase infrared spectroscopy

We report gas phase mid-infrared spectra of 1- and 2- methyl naphthalenes at 0.2 cm(-1) resolution. Assignment of observed bands have been made using scaled quantum mechanical (SQM) calculations where the force fields rather the frequencies are scaled to find a close fit between observed and calculated bands. The structure of the molecules has been optimized using B3LYP level of theory in conjunction with standard 6-311G** basis set to obtain the harmonic frequencies. Using the force constants in Cartesian coordinates from the Gaussian output, scaled force field calculations are carried out using a modified version of the UMAT program in the QCPE package. Potential energy distributions of the normal modes obtained from such calculations helped us assign the observed bands and identify the unique features of the spectra of 1- and 2-MNs which are important for their isomeric identification.

Experiments on and thermodynamic analysis of a turbocharged engine with producer gas as fuel

This article presents the studies conducted on turbocharged producer gas engines designed originally for natural gas (NG) as the fuel. Producer gas, whose properties like stoichiometric ratio, calorific value, laminar flame speed, adiabatic flame temperature, and related parameters that differ from those of NG, is used as the fuel. Two engines having similar turbochargers are evaluated for performance. Detailed measurements on the mass flowrates of fuel and air, pressures and temperatures at various locations on the turbocharger were carried out. On both the engines, the pressure ratio across the compressor was measured to be 1.40 +/- 0.05 and the density ratio to be 1.35 +/- 0.05 across the turbocharger with after-cooler. Thermodynamic analysis of the data on both the engines suggests a compressor efficiency of 70 per cent. The specific energy consumption at the peak load is found to be 13.1 MJ/kWh with producer gas as the fuel. Compared with the naturally aspirated mode, the mass flow and the peak load in the turbocharged after-cooled condition increased by 35 per cent and 30 per cent, respectively. The pressure ratios obtained with the use of NG and producer gas are compared with corrected mass flow on the compressor map.

Adaptation of small capacity natural gas engine for producer gas operation

This article addresses the adaptation of a low-power natural gas engine for using producer gas as a fuel. The 5.9 L natural gas engine with a compression ratio of 10.5:1, rated at 55 kW shaft power, delivered 30 kW using producer gas as fuel in the naturally aspirated mode. Optimal ignition timing for peak power was found to be 20 degrees before top dead centre. Air-to-fuel ratio (A/F) was found to be 1.2 +/- 0.1 over a range of loads. Critical evaluation of the energy flows in the engine resulted in identifying losses and optimizing the engine cooling. The specific fuel consumption was found to be 1.2 +/- 0.1 kg of biomass per kilowatt hour. A reduction of 40 per cent in brake mean effective pressure was observed compared with natural gas operation. Governor response to load variations has been studied with respect to frequency recovery time. The study also attempts to adopt a turbocharger for higher power output. Preliminary results suggest a possibility of about 30 per cent increase in the output.

Infrared Spectra of Dimethylphenanthrenes in the Gas phase

Infrared spectra of atmospherically and astronomically important dimethylphenanthrenes (DMPs), namely 1,9-DMP, 2,4-DMP, and 3,9-DMP, were recorded in the gas phase from 400 to 4000 cm(-1) with a resolution of 0.5 cm(-1) at 110 degrees C using a 7.2 m gas cell. DFT calculations at the B3LYP/6-311G** level were carried out to get the harmonic and anharmonic frequencies and their corresponding intensities for the assignment of the observed bands. However, spectral assignments could not be made unambiguously using anharmonic or selectively scaled harmonic frequencies. Therefore, the scaled quantum mechanical (SQM) force field analysis method was adopted to achieve more accurate assignments. In this method force fields instead of frequencies were scaled. The Cartesian force field matrix obtained from the Gaussian calculations was converted to a nonredundant local coordinate force field matrix and then the force fields were scaled to match experimental frequencies in a consistent manner using a modified version of the UMAT program of the QCPE package. Potential energy distributions (PEDs) of the normal modes in terms of nonredundant local coordinates obtained from these calculations helped us derive the nature of the vibration at each frequency. The intensity of observed bands in the experimental spectra was calculated using estimated vapor pressures of the DMPs. An error analysis of the mean deviation between experimental and calculated intensities reveal that the observed methyl C-H stretching intensity deviates more compared to the aromatic C-H and non C-H stretching bands.

Strongly magnetized cold degenerate electron gas: Mass-radius relation of the magnetized white dwarf

We consider a relativistic, degenerate electron gas at zero temperature under the influence of a strong, uniform, static magnetic field, neglecting any form of interactions. Since the density of states for the electrons changes due to the presence of the magnetic field (which gives rise to Landau quantization), the corresponding equation of state also gets modified. In order to investigate the effect of very strong magnetic field, we focus only on systems in which a maximum of either one, two, or three Landau level(s) is/are occupied. This is important since, if a very large number of Landau levels are filled, it implies a very low magnetic field strength which yields back Chandrasekhar's celebrated nonmagnetic results. The maximum number of occupied Landau levels is fixed by the correct choice of two parameters, namely, the magnetic field strength and the maximum Fermi energy of the system. We study the equations of state of these one-level, two-level, and three-level systems and compare them by taking three different maximum Fermi energies. We also find the effect of the strong magnetic field on the mass-radius relation of the underlying star composed of the gas stated above. We obtain an exciting result that it is possible to have an electron-degenerate static star, namely, magnetized white dwarfs, with a mass significantly greater than the Chandrasekhar limit in the range 2.3-2.6M(circle dot), provided it has an appropriate magnetic field strength and central density. In fact, recent observations of peculiar type Ia supernovae-SN 2006gz, SN 2007if, SN 2009dc, SN 2003fg-seem to suggest super-Chandrasekhar-mass white dwarfs with masses up to 2.4-2.8M(circle dot) as their most likely progenitors. Interestingly, our results seem to lie within these observational limits.