74 resultados para Cloud discharge


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A transient 2D axi-symmetric and lumped parameter (LP) model with constant outflow conditions have been developed to study the discharge capacity of an activated carbon bed. The predicted discharge times and variations in bed pressure and temperature are in good agreement with experimental results obtained from a 1.82 l adsorbed natural gas (ANG) storage system. Under ambient air conditions, a maximum temperature drop of 29.5 K and 45.5 K are predicted at the bed center for discharge rates of 1.0 l min(-1) and 5.0 l min(-1) respectively. The corresponding discharge efficiencies are 77% and 71.5% respectively with discharge efficiencies improving with decreasing outflow rates. Increasing the LID ratio from 1.9 to 7.8 had only a marginal increase in the discharge efficiency. Forced convection (exhaust gas) heating had a significant effect on the discharge efficiency, leading to efficiencies as high as 92.8% at a discharge of 1.0 l min(-1) and 88.7% at 5 l min(-1). Our study shows that the LP model can be reliably used to obtain discharge times due to the uniform pressure distributions in the bed. Temperature predictions with the LP model were more accurate at ambient conditions and higher discharge rates, due to greater uniformity in bed temperatures. For the low thermal conductivity carbon porous beds, our study shows that exhaust gas heating can be used as an effective and convenient strategy to improve the discharge characteristics and performance of an ANG system. (C) 2013 Elsevier Ltd. All rights reserved.

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In this paper we present a combination of technologies to provide an Energy-on-Demand (EoD) service to enable low cost innovation suitable for microgrid networks. The system is designed around the low cost and simple Rural Energy Device (RED) Box which in combination with Short Message Service (SMS) communication methodology serves as an elementary proxy for Smart meters which are typically used in urban settings. Further, customer behavior and familiarity in using such devices based on mobile experience has been incorporated into the design philosophy. Customers are incentivized to interact with the system thus providing valuable behavioral and usage data to the Utility Service Provider (USP). Data that is collected over time can be used by the USP for analytics envisioned by using remote computing services known as cloud computing service. Cloud computing allows for a sharing of computational resources at the virtual level across several networks. The customer-system interaction is facilitated by a third party Telecom Service provider (TSP). The approximate cost of the RED Box is envisaged to be under USD 10 on production scale.

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In this study, the Tropical Rainfall Measurement Mission based Microwave Imager estimates (2A12) have been used to compare and contrast the characteristics of cloud liquid water and ice over the Indian land region and the ocean surrounding it, during the premonsoon (May) and monsoon (June-September) seasons. Based on the spatial homogeneity of rainfall, we have selected five regions for our study (three over ocean, two over land). Comparison across three ocean regions suggests that the cloud liquid water (CLW) over the orographically influenced Arabian Sea (close to the Indian west coast) behaves differently from the CLW over a trapped ocean (Bay of Bengal) or an open ocean (equatorial Indian Ocean). Specifically, the Arabian Sea region shows higher liquid water for a lower range of rainfall, whereas the Bay of Bengal and the equatorial Indian Ocean show higher liquid water for a higher range of rainfall. Apart from geographic differences, we also documented seasonal differences by comparing CLW profiles between monsoon and premonsoon periods, as well as between early and peak phases of the monsoon. We find that the CLW during the lean periods of rainfall (May or June) is higher than during the peak and late monsoon season (July-September) for raining clouds. As active and break phases are important signatures of the monsoon progression, we also analysed the differences in CLW during various phases of the monsoon, namely, active, break, active-to-break and break-to-active transition phases. We find that the cloud liquid water content during the break-to-active transition phase is significantly higher than during the active-to-break transition phase over central India. We speculate that this could be attributed to higher amount of aerosol loading over this region during the break phase. We lend credence to this aerosol-CLW/rain association by comparing the central Indian CLW with that over southeast Asia (where the aerosol loading is significantly smaller) and find that in the latter region, there are no significant differences in CLW during the different phases of the monsoon. While our hypothesis needs to be further investigated with numerical models, the results presented in this study can potentially serve as a good benchmark in evaluating the performance of cloud resolving models over the Indian region.

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Corona discharge is recognized as one of the mechanisms that can influence the surface hydrophobicity of Silicone Rubber (SR) because of the chemical changes that occur on its surface. In this study SR samples were exposed to positive and negative DC corona for 25 and 50 hours using a needle-plane electrode system. Hydrophobicity changes were monitored using a sessile drop contact angle measurement facility. The physical changes on the surface were studied using Scanning Electron Microscopy (SEM) and surface roughness measurements. The effect of positive dc corona was found to be different from that of negative dc corona. Significant surface degradation and loss of hydrophobicity was found in the case of negative dc corona exposed samples. Significant improvement in the above mentioned properties were obtained by adding small quantities of nSIL into the SR matrix.

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Terrestrial water storage (TWS) plays a key role in the global water cycle and is highly influenced by climate variability and human activities. In this study, monthly TWS, rainfall and Ganga-Brahmaputra river discharge (GBRD) are analysed over India for the period of 2003-12 using remote sensing satellite data. The spatial pattern of mean TWS shows a decrease over a large and populous region of Northern India comprising the foothills of the Himalayas, the Indo-Gangetic Plains and North East India. Over this region, the mean monthly TWS exhibits a pronounced seasonal cycle and a large interannual variability, highly correlated with rainfall and GBRD variations (r > 0.8) with a lag time of 2 months and 1 month respectively. The time series of monthly TWS shows a consistent and statistically significant decrease of about 1 cm year(-1) over Northern India, which is not associated with changes in rainfall and GBRD. This recent change in TWS suggests a possible impact of rapid industrialization, urbanization and increase in population on land water resources. Our analysis highlights the potential of the Earth-observation satellite data for hydrological applications.

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We present deep Washington photometry of 45 poorly populated star cluster candidates in the Large Magellanic Cloud (LMC). We have performed a systematic study to estimate the parameters of the cluster candidates by matching theoretical isochrones to the cleaned and dereddened cluster color-magnitude diagrams. We were able to estimate the basic parameters for 33 clusters, out of which 23 are identified as single clusters and 10 are found to be members of double clusters. The other 12 cluster candidates have been classified as possible clusters/asterisms. About 50% of the true clusters are in the 100-300 Myr age range, whereas some are older or younger. We have discussed the distribution of age, location, and reddening with respect to field, as well as the size of true clusters. The sizes and masses of the studied sample are found to be similar to that of open clusters in the Milky Way. Our study adds to the lower end of cluster mass distribution in the LMC, suggesting that the LMC, apart from hosting rich clusters, also has formed small, less massive open clusters in the 100-300 Myr age range.

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Virtualization is one of the key enabling technologies for Cloud computing. Although it facilitates improved utilization of resources, virtualization can lead to performance degradation due to the sharing of physical resources like CPU, memory, network interfaces, disk controllers, etc. Multi-tenancy can cause highly unpredictable performance for concurrent I/O applications running inside virtual machines that share local disk storage in Cloud. Disk I/O requests in a typical Cloud setup may have varied requirements in terms of latency and throughput as they arise from a range of heterogeneous applications having diverse performance goals. This necessitates providing differential performance services to different I/O applications. In this paper, we present PriDyn, a novel scheduling framework which is designed to consider I/O performance metrics of applications such as acceptable latency and convert them to an appropriate priority value for disk access based on the current system state. This framework aims to provide differentiated I/O service to various applications and ensures predictable performance for critical applications in multi-tenant Cloud environment. We demonstrate through experimental validations on real world I/O traces that this framework achieves appreciable enhancements in I/O performance, indicating that this approach is a promising step towards enabling QoS guarantees on Cloud storage.

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Experiments were conducted at laboratory level to treat the oxides of nitrogen (NOx) present in raw and dry biodiesel exhaust utilizing a combination of electric discharge plasma and bauxite residue, i. e., red mud, an industrial waste byproduct from the aluminum industry. In this paper, the adsorption and a possible catalytic property of bauxite residue are discussed. Nonthermal plasma was generated using dielectric barrier discharges initiated by ac/repetitive pulse energization. The effect of corona electrodes on the plasma generation was qualitatively studied through NOx cleaning. The plasma reactor and adsorbent reactors were connected in cascade while treating the exhaust. The diesel generator, running on biodiesel fuel, was electrically loaded to study the effectiveness of the cascade system in cleaning the exhaust. Interestingly, under the laboratory conditions studied, plasma-bauxite residue combination has shown good synergistic properties and enhanced the NOx removal up to about 90%. With proper scaling up, the suggested cascade system may become an economically feasible option to treat the exhaust in larger installations. The results were discussed emphasizing the role of bauxite residue as an adsorbent and as a room temperature catalyst.

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Recent studies, over regions influenced by biomass burning aerosol, have shown that it is possible to define a critical cloud fraction' (CCF) at which the aerosol direct radiative forcing switch from a cooling to a warming effect. Using 4 years of multi-satellite data analysis, we show that CCF varies with aerosol composition and changed from 0.28 to 0.13 from postmonsoon to winter as a result of shift from less absorbing to moderately absorbing aerosol. Our results indicate that we can estimate aerosol absorption from space using independently measured top of the atmosphere (TOA) fluxes Cloud Aerosol Lidar with Orthogonal Polarization-Moderate resolution Imaging Spectroradiometer-Clouds and the Earth's Radiant Energy System (CALIPSO-MODIS-CERES)] combined algorithms for example.

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This study concerns the relationship between the power law recession coefficient k (in - dQ/dt = kQ(alpha), Q being discharge at the basin outlet) and past average discharge Q(N) (where N is the temporal distance from the center of the selected time span in the past to the recession peak), which serves as a proxy for past storage state of the basin. The strength of the k-Q(N) relationship is characterized by the coefficient of determination R-N(2), which is expected to indicate the basin's ability to hold water for N days. The main objective of this study is to examine how R-N(2) value of a basin is related with its physical characteristics. For this purpose, we use streamflow data from 358 basins in the United States and selected 18 physical parameters for each basin. First, we transform the physical parameters into mutually independent principal components. Then we employ multiple linear regression method to construct a model of R-N(2) in terms of the principal components. Furthermore, we employ step-wise multiple linear regression method to identify the dominant catchment characteristics that influence R-N(2) and their directions of influence. Our results indicate that R-N(2) is appreciably related to catchment characteristics. Particularly, it is noteworthy that the coefficient of determination of the relationship between R-N(2) and the catchment characteristics is 0.643 for N = 45. We found that topographical characteristics of a basin are the most dominant factors in controlling the value of R-N(2). Our results may be suggesting that it is possible to tell about the water holding capacity of a basin by just knowing about a few of its physical characteristics. (C) 2015 Elsevier B.V. All rights reserved.

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Classical models are not successful in describing discharge characteristics of a lead-acid battery when the current density is varied over a wide range. A model is developed in this work to overcome this lacuna by introducing into the standard models two mechanisms that have not been used earlier. Lead sulfate particles nucleate and grow on active materials of electrodes during discharge, resulting in coverage of active area. Increasing rate of discharge builds supersaturation of lead sulfate rapidly, and causes increased extents of nucleation and coverage. Electrodes behave almost like an insulator due to deposition of lead sulfate when active materials are converted to a critical extent, and this can stop discharge process. Influence of this mechanism is also rate dependent. The new model developed is tested against data on polarization behavior, and capacity drawn as a function of current. The model successfully predicts both polarization curves and Peukert behavior. The model is used to predict charge that can be drawn at a current after partial discharge at a different current. Model suggests that altering nucleation behavior can be useful in enhancing capacity available for discharge. (C) 2015 The Electrochemical Society.

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Studies were carried out to estimate the power input to Dielectric Barrier Discharge (DBD) reactors powered by AC high voltage in the context of their application in non-thermal plasma cleaning of exhaust gases. Power input to the reactors was determined both theoretically and experimentally. Four different reactor geometries energized with 50 Hz and 1.5 kHz AC excitation were considered for the study. The theoretically estimated power using Manley's equation was found to agree with the experimental results. Results show that the analytically computed capacitance, without including the electrode edge effects, gives sufficiently good results that are matching with the measured values. For complex geometries where analytical calculation of capacitance is often difficult, a novel method of estimating the reactor capacitance, and hence the power input to the reactor, was introduced in this paper. The predicted results were validated with experiments.

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We have estimated a metallicity map of the Large Magellanic Cloud (LMC) using the Magellanic Cloud Photometric Survey (MCPS) and Optical Gravitational Lensing Experiment (OGLE III) photometric data. This is a first of its kind map of metallicity up to a radius of 4 degrees-5 degrees, derived using photometric data and calibrated using spectroscopic data of Red Giant Branch (RGB) stars. We identify the RGB in the V, (V - I) colour-magnitude diagrams of small subregions of varying sizes in both data sets. We use the slope of the RGB as an indicator of the average metallicity of a subregion, and calibrate the RGB slope to metallicity using spectroscopic data for field and cluster red giants in selected subregions. The average metallicity of the LMC is found to be Fe/H] = -0.37 dex (sigmaFe/H] = 0.12) from MCPS data, and Fe/H] = -0.39 dex (sigmaFe/H] = 0.10) from OGLE III data. The bar is found to be the most metal-rich region of the LMC. Both the data sets suggest a shallow radial metallicity gradient up to a radius of 4 kpc (-0.049 +/- 0.002 dex kpc(-1) to -0.066 +/- 0.006 dex kpc(-1)). Subregions in which the mean metallicity differs from the surrounding areas do not appear to correlate with previously known features; spectroscopic studies are required in order to assess their physical significance.