An experimental investigation on manifold‐injected hydrogen as a dual fuel for diesel engine system with different injection duration

Stringent emission norms and rapid depletion of petroleum resources have resulted in a continuous effort to search for alternative fuels. Hydrogen is one of the best alternatives for conventional fuels. Hydrogen has both the benefits and limitation to be used as a fuel in an automotive engine system. In the present investigation, hydrogen was injected into the intake manifold by using a hydrogen gas injector and diesel was introduced in the conventional, mode which also acts as an ignition source for hydrogen combustion. The flow rate of hydrogen was set at 5.5 l min^?1 at all the load conditions. The injection timing was kept constant at top dead center (TDC) and injection duration was adjusted to find the optimized injection condition. Experiments were conducted on a single cylinder, four stroke, water‐cooled, direct injection diesel engine coupled to an electrical generator. At 75% load the maximum brake thermal efficiency for hydrogen operation at injection timing of TDC and with injection duration of 30°CA is 25.66% compared with 21.59% for diesel. The oxides of nitrogen (NO_X) emission are 21.7 g kWh^?1 for hydrogen compared with diesel of 17.9 g k Wh^?1. Smoke emissions reduced to 1 Bosch smoke number (BSN) in hydrogen compared with diesel of 2.2 BSN. Hydrogen operation in the dual fuel mode with diesel exhibits a better performance and reduction in emissions compared with diesel in the entire load spectra. Copyright © 2009 John Wiley & Sons, Ltd.     

An experimental investigation on a DI diesel engine using waste plastic oil with exhaust gas recirculation

Environmental degradation and depleting oil reserves are matters of great concern around the globe. Developing countries like India depend heavily on oil import of about 125 Mt per annum (7:1 diesel/gasoline). Diesel being the main transport fuel in India, finding a suitable alternative to diesel is an urgent need. In this context, waste plastic solid is currently receiving renewed interest. Waste plastic oil is suitable for compression ignition engines and more attention is focused in India because of its potential to generate large-scale employment and relatively low environmental degradation. The present investigation was to study the effect of cooled exhaust gas recirculation (EGR) on four stroke, single cylinder, direct injection (DI) diesel engine using 100% waste plastic oil. Experimental results showed higher oxides of nitrogen emissions when fueled with waste plastic oil without EGR. NO_x emissions were reduced when the engine was operated with cooled EGR. The EGR level was optimized as 20% based on significant reduction in NO_x emissions, minimum possible smoke, CO, HC emissions and comparable brake thermal efficiency. Smoke emissions of waste plastic oil were higher at all loads. Combustion parameters were found to be comparable with and without EGR. Compression ignition engines run on waste plastic oil are found to emit higher oxides of nitrogen.     

Kinetics of high strength phenol degradation using Bacillus brevis

A strain of Bacillus brevis has been isolated and identified based on biochemical results. Phenol biodegradation in a batch reactor was studied using the pure culture of B. brevis. The isolated strain was optimized for various environmental conditions and the biodegradation of phenol was maximum at pH 8.0, 5% (v/v) of inoculum size and without any co-substrate. The kinetics of biodegradation according to Haldane's equation micro = micromaxS/(Ks + S + (S2/Ki)) adequately describes cell growth with kinetic constants in the ranges micromax = 0.026-0.078 h(-1), Ks =2.2-29.31 mg/l, Ki = 868.0-2434.7 mg/l. These values are specific for this organism and we have compared with literature for pure or mixed cultures degrading phenol.     

Solving subclasses of multi-player stochastic games via linear complementarity problem formulations—a survey and some new results

We briefly survey some results on the orderfield property of 2-player and multi-player stochastic games and their mixtures. Some of these classes of stochastic games can be solved by formulating them as a Linear Complementarity Problem (LCP) or (Generalized) Vertical Linear Complementarity Problem (VLCP). We discuss some of these results and prove that certain new subclasses and mixtures of multi-player (or n-person) stochastic games can be solved via LCP formulations. Mohan, Neogy and Parthasarathy (in Proceedings of the International Conference on Complementarity Problems, 1997) proposed an LCP formulation of ??-discounted (multi-player) polystochastic games where the transitions are controlled by one player, and proved that this LCP is processible by Lemke??s algorithm. Using this formulation repeatedly, we prove that we can solve a subclass of ??-discounted switching control polystochastic games. As our proof is constructive, we have an algorithm for solving this subclass. This algorithm only involves iteratively solving different LCPs and hence, it follows that this subclass has the orderfield property, a?question left open in the paper on orderfield property of mixtures of stochastic games by Krishnamurthy et al., (Indian J. Stat. 72:246?C275, 2010). Furthermore, we use results from Krishnamurthy et al., Indian J. Stat. 72:246?C275, (2010) to solve some mixture classes using LCP (or VLCP) formulations. We also propose two different VLCP formulations for ??-discounted zero-sum perfect information stochastic games, the underlying matrices of both formulations being R ₀. As a result, we also have an alternative proof of the orderfield property of such games.     

A novel adaptive beamformer for MEG source reconstruction effective when large background brain activities exist

This paper proposes a novel prewhitening eigenspace beamformer suitable for magnetoencephalogram (MEG) source reconstruction when large background brain activities exist. The prerequisite for the method is that control-state measurements, which contain only the contributions from the background interference, be available, and that the covariance matrix of the background interference can be obtained from such control-state measurements. The proposed method then uses this interference covariance matrix to remove the influence of the interference in the reconstruction obtained from the target measurements. A numerical example, as well as applications to two types of MEG data, demonstrates the effectiveness of the proposed method.     

Multimodal social intelligence in a real-time dashboard system

Social Networks provide one of the most rapidly evolving data sets in existence today. Traditional Business Intelligence applications struggle to take advantage of such data sets in a timely manner. The BBC SoundIndex, developed by the authors and others, enabled real-time analytics of music popularity using data from a variety of Social Networks. We present this system as a grounding example of how to overcome the challenges of working with this data from social networks. We discuss a variety of technologies to implement near real-time data analytics to transform Social Intelligence into Business Intelligence and evaluate their effectiveness in the music domain. The SoundIndex project helped to highlight a number of key research areas, including named entity recognition and sentiment analysis in Informal English. It also drew attention to the importance of metadata aggregation in multimodal environments. We explored challenges such as drawing data from a wide set of sources spanning a myriad of modalities, developing adjudication techniques to harmonize inputs, and performing deep analytics on extremely challenging Informal English snippets. Ultimately, we seek to provide guidance on developing applications in a variety of domains that allow an analyst to rapidly grasp the evolution in the social landscape, and show how to validate such a system for a real-world application.     

The Top Management Team,Reflexivity, Knowledge Sharing and New Product Performance: A Study of the Irish Software Industry

In the present study, we develop a model to predict new product performance incorporating the literature on top management team (TMT) composition, trustworthiness, knowledge sharing and task reflexivity in organizations. We hypothesize that diversity and trustworthiness in the TMT should influence knowledge sharing and reflexivity and reflexivity and knowledge sharing would be positively associated with new product performance. We test the model using data collected from 39 indigenous software firms in Ireland. Results indicate that age diversity was positively related to knowledge sharing ability while educational level, tenure and functional diversity of the TMT did not have any direct effect on reflexivity or knowledge sharing ability or motivation. However, educational level of TMT, tenure and age diversity had indirect effects on reflexivity and knowledge sharing through the intervening variable of TMT trustworthiness. Further, knowledge sharing and task reflexivity had direct effects on market new product performance. Implications for research and practice are discussed.     

Further studies on the tuned photoinitiators

Conclusions  Based on the results obtained from the present studies, the following conclusions can be drawn.