Treatment of NOx from Diesel Engine Exhaust by Dielectric Barrier Discharge Method

This paper reports improved performance of advantages when compared to its counterpart as it is cost discharge plasma in filtered engine exhaust treatment. Our effective, low capital and operation costs, salable by- paper deals about the removal of NOX emissions from the diesel products, and integration with the existing systems. In this exhaust by electric discharge plasma. For the treatment of diesel paper we describe an alternate reactor geometry referred to exhaust a new type of reactor referred to as cross-flow dielectric as cross-flow DBD reactor, where the exhaust gas flow barrier discharge reactor has been used, where the gas flow is perpendicular to the wire-cylinder reaction chamber. This perpendicular to the corona electrode. Experiments were reactor is used to treat the actual exhaust of a 3.75 kW diesel- conducted at different flow rates ranging from 2 l/min to 10 l/ generator set. The main emphasis is laid on the NOX treatment min. The discharge plasma assisted barrier discharge reactor of diesel engine exhaust. Experiments were carried out at has shown promising results in NOX removal at high flow rates.

Chitosan-polyvinyl alcohol-sulfonated polyethersulfone mixed-matrix membranes as methanol-barrier electrolytes for DMFCs

Chitosan (CS)-polyvinyl alcohol (PVA) cross-linked with sulfosuccinic acid (SSA) and modified with sulfonated polyethersulfone (SPES) mixed-matrix membranes are reported for their application in direct methanol fuel cells (DMFCs). Polyethersulfone (PES) is sulfonated by chlorosulfonic acid and factors affecting the sulfonation reaction, such as time and temperature, are studied. The ion-exchange capacity, degree of sulfonation, sorption, and proton conductivity for the mixed-matrix membranes are investigated. The mixed-matrix membranes are also characterised for their mechanical and thermal properties. The methanol-crossover flux across the mixed-matrix membranes is studied by measuring the mass balance of methanol using the density meter. The methanol cross-over for these membranes is found to be about 33% lower in relation to Nafion-117 membrane. The DMFC employing CS-PVA-SPES mixed-matrix membrane with an optimum content of 25 wt % SPES delivers a peak power-density of 5.5 mW cm-2 at a load current-density of 25 mA cm-2 while operating at 70 degrees C. (C) 2011 Wiley Periodicals, Inc. J Appl Polym Sci, 2012

Dielectric Barrier Discharge Cascaded with Red Mud Waste to Enhance NOX Removal from Diesel Engine Exhaust

Red mud is a waste by-product generated during the processing of bauxite, the most common ore of aluminium. With the presence of ferric oxide, high surface area, resistance to poisoning and low cost, red mud made itself a good alternative to the existing commercial automobile catalyst. The cascading of dielectric barrier discharge plasma with red mud improved the NOX removal from diesel engine exhaust significantly. The DeNO(X) efficiency with discharge plasma was 74% and that with red mud was 31%. The efficiency increased to 92% when plasma was cascaded with red mud catalyst operating at a temperature of 400 degrees C. The NOX removal was dominated by NO2 removal. The studies were conducted at different temperatures and the results were discussed.

Damage-tolerant design optimization of laminated composite structures using dispersion of ply angles by genetic algorithm

This article aims to obtain damage-tolerant designs with minimum weight for a laminated composite structure using genetic algorithm. Damage tolerance due to impacts in a laminated composite structure is enhanced by dispersing the plies such that too many adjacent plies do not have the same angle. Weight of the structure is minimized and the Tsai-Wu failure criterion is considered for the safe design. Design variables considered are the number of plies and ply orientation. The influence of dispersed ply angles on the weight of the structure for a given loading conditions is studied by varying the angles in the range of 0 degrees-45 degrees, 0 degrees-60 degrees and 0 degrees-90 degrees at intervals of 5 degrees and by using specific ply angles tailored to loading conditions. A comparison study is carried out between the conventional stacking sequence and the stacking sequence with dispersed ply angles for damage-tolerant weight minimization and some useful designs are obtained. Unconventional stacking sequence is more damage tolerant than the conventional stacking sequence is demonstrated by performing a finite element analysis under both tensile as well as compressive loading conditions. Moreover, a new mathematical function called the dispersion function is proposed to measure the dispersion of ply angles in a laminate. The approach for dispersing ply angles to achieve damage tolerance is especially suited for composite material design space which has multiple local minima.

Applying Genetic Algorithms to Optimize Power in Tiled SNUCA Chip Multicore Architectures

We propose a novel technique for reducing the power consumed by the on-chip cache in SNUCA chip multicore platform. This is achieved by what we call a "remap table", which maps accesses to the cache banks that are as close as possible to the cores, on which the processes are scheduled. With this technique, instead of using all the available cache, we use a portion of the cache and allocate lesser cache to the application. We formulate the problem as an energy-delay (ED) minimization problem and solve it offline using a scalable genetic algorithm approach. Our experiments show up to 40% of savings in the memory sub-system power consumption and 47% savings in energy-delay product (ED).

Applying Genetic Algorithms to Optimize Power in Tiled SNUCA Chip Multicore Architectures

We propose a novel technique for reducing the power consumed by the on-chip cache in SNUCA chip multicore platform. This is achieved by what we call a "remap table", which maps accesses to the cache banks that are as close as possible to the cores, on which the processes are scheduled. With this technique, instead of using all the available cache, we use a portion of the cache and allocate lesser cache to the application. We formulate the problem as an energy-delay (ED) minimization problem and solve it offline using a scalable genetic algorithm approach. Our experiments show up to 40% of savings in the memory sub-system power consumption and 47% savings in energy-delay product (ED).

Genetic analysis of an Indian family with members affected with Waardenburg syndrome and Duchenne muscular dystrophy

Purpose: Waardenburg syndrome (WS) is characterized by sensorineural hearing loss and pigmentation defects of the eye, skin, and hair. It is caused by mutations in one of the following genes: PAX3 (paired box 3), MITF (microphthalmia-associated transcription factor), EDNRB (endothelin receptor type B), EDN3 (endothelin 3), SNAI2 (snail homolog 2, Drosophila) and SOX10 (SRY-box containing gene 10). Duchenne muscular dystrophy (DMD) is an X-linked recessive disorder caused by mutations in the DMD gene. The purpose of this study was to identify the genetic causes of WS and DMD in an Indian family with two patients: one affected with WS and DMD, and another one affected with only WS. Methods: Blood samples were collected from individuals for genomic DNA isolation. To determine the linkage of this family to the eight known WS loci, microsatellite markers were selected from the candidate regions and used to genotype the family. Exon-specific intronic primers for EDN3 were used to amplify and sequence DNA samples from affected individuals to detect mutations. A mutation in DMD was identified by multiplex PCR and multiplex ligation-dependent probe amplification method using exon-specific probes. Results: Pedigree analysis suggested segregation of WS as an autosomal recessive trait in the family. Haplotype analysis suggested linkage of the family to the WS4B (EDN3) locus. DNA sequencing identified a novel missense mutation p.T98M in EDN3. A deletion mutation was identified in DMD. Conclusions: This study reports a novel missense mutation in EDN3 and a deletion mutation in DMD in the same Indian family. The present study will be helpful in genetic diagnosis of this family and increases the mutation spectrum of EDN3.

Singlet-state creation and universal quantum computation in NMR using a genetic algorithm

The experimental implementation of a quantum algorithm requires the decomposition of unitary operators. Here we treat unitary-operator decomposition as an optimization problem, and use a genetic algorithm-a global-optimization method inspired by nature's evolutionary process-for operator decomposition. We apply this method to NMR quantum information processing, and find a probabilistic way of performing universal quantum computation using global hard pulses. We also demonstrate the efficient creation of the singlet state (a special type of Bell state) directly from thermal equilibrium, using an optimum sequence of pulses. © 2012 American Physical Society.

Singlet-state creation and universal quantum computation in NMR using a genetic algorithm

The experimental implementation of a quantum algorithm requires the decomposition of unitary operators. Here we treat unitary-operator decomposition as an optimization problem, and use a genetic algorithm-a global-optimization method inspired by nature's evolutionary process-for operator decomposition. We apply this method to NMR quantum information processing, and find a probabilistic way of performing universal quantum computation using global hard pulses. We also demonstrate the efficient creation of the singlet state (a special type of Bell state) directly from thermal equilibrium, using an optimum sequence of pulses.

Analysis of the temperature-dependent current-voltage characteristics and the barrier-height inhomogeneities of Au/GaN Schottky diodes

In this report, the currentvoltage (IV) characteristics of Au/GaN Schottky diodes have been carried out in the temperature range of 300510?K. The estimated values of the Schottky-barrier height (SBH) and the ideality factor of the diodes based on the thermionic emission (TE) mechanism were found to be temperature dependent. The barrier height was found to increase and the ideality factor to decrease with increasing temperature. The conventional Richardson plot of ln(Is/T2) versus 1/kT gives the SBH of 0.51?eV and Richardson constant value of 3.23?X?10-5?A?cm-2?K-2 which is much lower than the known value of 26.4?A?cm-2?K-2 for GaN. Such discrepancies of the SBH and Richardson constant value were attributed to the existence of barrier-height inhomogeneities at the Au/GaN interface. The modified Richardson plot of ln(Is/T2)q2 sigma 2/2k2T2 versus q/kT, by assuming a Gaussian distribution of barrier heights at the Au/GaN interface, provided the SBH of 1.47?eV and Richardson constant value of 38.8?A?cm-2?K-2. The temperature dependence of the barrier height is interpreted on the basis of existence of the Gaussian distribution of the barrier heights due to the barrier-height inhomogeneities at the Au/GaN interface.

Relation between the work function and Young's modulus of RhSi and estimate of Schottky-barrier height at RhSi/Si interface: An ab-initio study

Density-functional calculations are performed to explore the relationship between the work function and Young's modulus of RhSi, and to estimate the p-Schottky-barrier height (SBH) at the Si/RhSi(010) interface. It is shown that the Young's modulus and the workfunction of RhSi satisfy the generic sextic relation, proposed recently for elemental metals. The calculated p-SBH at the Si/RhSi interface is found to differ only by 0.04 eV in opposite limits, viz., no-pinning and strong pinning. We find that the p-SBH is reduced as much as by 0.28 eV due to vacancies at the interface. (C) 2012 American Institute of Physics. http://dx.doi.org/10.1063/1.4761994]

Combination of similarity measures for time series classification using genetic algorithms

Time series classification deals with the problem of classification of data that is multivariate in nature. This means that one or more of the attributes is in the form of a sequence. The notion of similarity or distance, used in time series data, is significant and affects the accuracy, time, and space complexity of the classification algorithm. There exist numerous similarity measures for time series data, but each of them has its own disadvantages. Instead of relying upon a single similarity measure, our aim is to find the near optimal solution to the classification problem by combining different similarity measures. In this work, we use genetic algorithms to combine the similarity measures so as to get the best performance. The weightage given to different similarity measures evolves over a number of generations so as to get the best combination. We test our approach on a number of benchmark time series datasets and present promising results.