Enhanced Performance of Discharge Plasma in Raw Engine Exhaust Treatment-Operation under Different Temperatures and Loads

This paper reports improved performance of discharge plasma in raw engine exhaust treatment. For the purpose of investigation, both filtered and raw diesel engine exhaust were separately treated by the discharge plasma. In raw exhaust environment, the discharge plasma exhibits a superior performance with regard to NOx removal, energy consumption and formation of by-products. In this study, experiments were conducted at conditions of different temperatures and loads.

Nonthermal plasma approach in direct methanol synthesis from CH4

Conversion of hydrocarbon fuels to methanol promoted their efficient utilization as methanol can easily be converted to hydrogen gas, which has higher available energy. In this regard, nonthermal plasma approach using electrical discharges is gaining significance to improve the conversion process of methanol. The efficiency of this nonthermal plasma chemical reaction is affected by various chemical and electrical parameters. This paper presents some important results of the parametric study carried out in methanol synthesis with the aim of reducing energy losses associated with the conventional method. The parameters include the concentration of the reactants, corona electrode configurations, gas mixtures, etc. Further, an attempt was made to study the combined effect of catalysts and electrical discharges on methanol synthesis. Main emphasis was laid on the electrical aspects like electric field, power transfer efficiency, etc. The gas analysis was carried out under carefully maintained laboratory conditions

Pulsed plasma treatment for NOx reduction from filtered/unfiltered stationary diesel engine exhaust

A detailed study on the removal of oxides of nitrogen (NOx) from the filtered/unfiltered exhaust of a stationary diesel engine was carried out using non-thermal plasma (pulsed electrical discharge plasma) process and cascaded processes namely plasma- adsorbent and plasma-catalyst processes. The superior performance of discharge plasma with regard to NOx removal, energy consumption and formation of by-products in unfiltered exhaust environment is identified. In the cascaded plasma-adsorbent process, the plasma was cascaded with adsorbents (MS13X/Activated alumina/Activated charcoal). The cascaded process treating unfiltered exhaust exhibits a very high NOx removal compared to the individual processes and further, the cascaded process gives almost the same NOx removal efficiency irrespective of type of adsorbent used. In the cascaded plasma- catalyst process, the plasma was cascaded with activated alumina catalyst at high temperature. The synergy effect and improved performance of the cascaded process are explained. Further, experiments were conducted at room temperature as well as at higher temperatures.

Corona treatment for NOx reduction from stationary diesel engine exhaust: Impact of nature of energization and exhaust composition

A detailed study on the removal of oxides of nitrogen (NOx) from the exhaust of a stationary diesel engine was carried out using non-thermal plasma (dielectric barrier discharge) process. The objective of the study was to explore the effect of different voltage energizations and exhaust composition on the NOx removal process. Three types of voltage energizations, namely AC, DC and Pulse were examined. Due to the ease of generation of high voltage AC/DC electrical discharges from automobile/Vehicular battery supply for possible retrofitting in exhaust cleaning circuit, it was found relevant to investigate individual energisation cases in detail for NOx removal. AC and Pulse energisations exhibit a superior NOx removal efficiency compared to DC energisation. However,Pulse energisation is found to be more energy efficient. Experiments were further carried out with filtered/ unfiltered (raw) exhaust under pulse energisations. The results were discussed with regard to NOx removal, energy consumption and formation of by-products.

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.

Decentralised carbon footprint analysis for opting climate change mitigation strategies in India

Carbon footprint (CF) refers to the total amount of carbon dioxide and its equivalents emitted due to various anthropogenic activities. Carbon emission and sequestration inventories have been reviewed sector-wise for all federal states in India to identify the sectors and regions responsible for carbon imbalances. This would help in implementing appropriate climate change mitigation and management strategies at disaggregated levels. Major sectors of carbon emissions in India are through electricity generation, transport, domestic energy consumption, industries and agriculture. A majority of carbon storage occurs in forest biomass and soil. This paper focuses on the statewise carbon emissions (CO2. CO and CH4), using region specific emission factors and statewise carbon sequestration capacity. The estimate shows that CO2, CO and CH4 emissions from India are 965.9, 22.5 and 16.9 Tg per year, respectively. Electricity generation contributes 35.5% of total CO2 emission, which is followed by the contribution from transport. Vehicular transport exclusively contributes 25.5% of total emission. The analysis shows that Maharashtra emits higher CO2, followed by Andhra Pradesh, Uttar Pradesh, Gujarat, Tamil Nadu and West Bengal. The carbon status, which is the ratio of annual carbon storage against carbon emission, for each federal state is computed. This shows that small states and union territories (UT) like Arunachal Pradesh, Mizoram and Andaman and Nicobar Islands, where carbon sequestration is higher due to good vegetation cover, have carbon status > 1. Annually, 7.35% of total carbon emissions get stored either in forest biomass or soil, out of which 34% is in Arunachal Pradesh, Madhya Pradesh, Chhattisgarh and Orissa. (C) 2012 Elsevier Ltd. All rights reserved.

Optimal forwarding in delay tolerant networks with multiple destinations

We study the trade-off between delivery delay and energy consumption in a delay tolerant network in which a message (or a file) has to be delivered to each of several destinations by epidemic relaying. In addition to the destinations, there are several other nodes in the network that can assist in relaying the message. We first assume that, at every instant, all the nodes know the number of relays carrying the packet and the number of destinations that have received the packet. We formulate the problem as a controlled continuous time Markov chain and derive the optimal closed loop control (i.e., forwarding policy). However, in practice, the intermittent connectivity in the network implies that the nodes may not have the required perfect knowledge of the system state. To address this issue, we obtain an ODE (i.e., fluid) approximation for the optimally controlled Markov chain. This fluid approximation also yields an asymptotically optimal open loop policy. Finally, we evaluate the performance of the deterministic policy over finite networks. Numerical results show that this policy performs close to the optimal closed loop policy.

Greening the IP Over Optical Backbone Network

In this paper we examine the energy consumption of IP Over Optical WDM Networks. As the number of Internet users increases the Internet expands in reach and capacity. This results in increased energy consumption of the network. Minimizing the power consumption, termed as ``Greening the Internet'', is desirable to help service providers (SP) operate their networks and provide services more efficiently in terms of power consumption. Minimizing the operational power typically depends on the strategy (e. g., lightpath bypass, lightpath non-bypass and traffic grooming) and operations (e. g., electronic domain versus optical domain). We consider a typical optical backbone network model, and develop a model which minimizes the power consumption. Performance calculation shows that our method consumes less power compared to traffic grooming approach.

Optimal Forwarding in Delay-Tolerant Networks With Multiple Destinations

We study the tradeoff between delivery delay and energy consumption in a delay-tolerant network in which a message (or a file) has to be delivered to each of several destinations by epidemic relaying. In addition to the destinations, there are several other nodes in the network that can assist in relaying the message. We first assume that, at every instant, all the nodes know the number of relays carrying the message and the number of destinations that have received the message. We formulate the problem as a controlled continuous-time Markov chain and derive the optimal closed-loop control (i.e., forwarding policy). However, in practice, the intermittent connectivity in the network implies that the nodes may not have the required perfect knowledge of the system state. To address this issue, we obtain an ordinary differential equation (ODE) (i.e., a deterministic fluid) approximation for the optimally controlled Markov chain. This fluid approximation also yields an asymptotically optimal open-loop policy. Finally, we evaluate the performance of the deterministic policy over finite networks. Numerical results show that this policy performs close to the optimal closed-loop policy.

Balanced Excitatory and Inhibitory Synaptic Currents Promote Efficient Coding and Metabolic Efficiency

A balance between excitatory and inhibitory synaptic currents is thought to be important for several aspects of information processing in cortical neurons in vivo, including gain control, bandwidth and receptive field structure. These factors will affect the firing rate of cortical neurons and their reliability, with consequences for their information coding and energy consumption. Yet how balanced synaptic currents contribute to the coding efficiency and energy efficiency of cortical neurons remains unclear. We used single compartment computational models with stochastic voltage-gated ion channels to determine whether synaptic regimes that produce balanced excitatory and inhibitory currents have specific advantages over other input regimes. Specifically, we compared models with only excitatory synaptic inputs to those with equal excitatory and inhibitory conductances, and stronger inhibitory than excitatory conductances (i.e. approximately balanced synaptic currents). Using these models, we show that balanced synaptic currents evoke fewer spikes per second than excitatory inputs alone or equal excitatory and inhibitory conductances. However, spikes evoked by balanced synaptic inputs are more informative (bits/spike), so that spike trains evoked by all three regimes have similar information rates (bits/s). Consequently, because spikes dominate the energy consumption of our computational models, approximately balanced synaptic currents are also more energy efficient than other synaptic regimes. Thus, by producing fewer, more informative spikes approximately balanced synaptic currents in cortical neurons can promote both coding efficiency and energy efficiency.

Performance Analysis of a Cooperative MAC Protocol of Wireless Ad Hoc Networks

Different medium access control (MAC) layer protocols, for example, IEEE 802.11 series and others are used in wireless local area networks. They have limitation in handling bulk data transfer applications, like video-on-demand, videoconference, etc. To avoid this problem a cooperative MAC protocol environment has been introduced, which enables the MAC protocol of a node to use its nearby nodes MAC protocol as and when required. We have found on various occasions that specified cooperative MAC establishes cooperative transmissions to send the specified data to the destination. In this paper we propose cooperative MAC priority (CoopMACPri) protocol which exploits the advantages of priority value given by the upper layers for selection of different paths to nodes running heterogeneous applications in a wireless ad hoc network environment. The CoopMACPri protocol improves the system throughput and minimizes energy consumption. Using a Markov chain model, we developed a model to analyse the performance of CoopMACPri protocol; and also derived closed-form expression of saturated system throughput and energy consumption. Performance evaluations validate the accuracy of the theoretical analysis, and also show that the performance of CoopMACPri protocol varies with the number of nodes. We observed that the simulation results and analysis reflects the effectiveness of the proposed protocol as per the specifications.

Holistic Measures for Evaluating Prediction Models in Smart Grids

The performance of prediction models is often based on ``abstract metrics'' that estimate the model's ability to limit residual errors between the observed and predicted values. However, meaningful evaluation and selection of prediction models for end-user domains requires holistic and application-sensitive performance measures. Inspired by energy consumption prediction models used in the emerging ``big data'' domain of Smart Power Grids, we propose a suite of performance measures to rationally compare models along the dimensions of scale independence, reliability, volatility and cost. We include both application independent and dependent measures, the latter parameterized to allow customization by domain experts to fit their scenario. While our measures are generalizable to other domains, we offer an empirical analysis using real energy use data for three Smart Grid applications: planning, customer education and demand response, which are relevant for energy sustainability. Our results underscore the value of the proposed measures to offer a deeper insight into models' behavior and their impact on real applications, which benefit both data mining researchers and practitioners.

Adaptive Sleep-Wake Control using Reinforcement Learning in Sensor Networks

The aim in this paper is to allocate the `sleep time' of the individual sensors in an intrusion detection application so that the energy consumption from the sensors is reduced, while keeping the tracking error to a minimum. We propose two novel reinforcement learning (RL) based algorithms that attempt to minimize a certain long-run average cost objective. Both our algorithms incorporate feature-based representations to handle the curse of dimensionality associated with the underlying partially-observable Markov decision process (POMDP). Further, the feature selection scheme used in our algorithms intelligently manages the energy cost and tracking cost factors, which in turn assists the search for the optimal sleeping policy. We also extend these algorithms to a setting where the intruder's mobility model is not known by incorporating a stochastic iterative scheme for estimating the mobility model. The simulation results on a synthetic 2-d network setting are encouraging.

双套管密相气力输运过程的数值模拟和能耗分析

基于计算流体力学理论,提出一种可用于预测双套管密相气力输送系统能耗的新方法.与以往依靠经验的计算方法不同,本工作将输送管道分为起始段与充分发展段两部分,分别进行详细的计算流体力学模拟后汇总得出整个系统的总能耗.压力梯度为750 Pa/m的情况下,计算所得物料输送速率为10 t/h,耗气量为290 m~3/h,实验所得物料输送速率为8.0 t/h,耗气量240 m~3/h,证明本数模方法是可靠的.

Alternative trajectories for decarbonizing urban transportation

4 p.