132 resultados para estimated average requirement


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A study of environmental chloride and groundwater balance has been carried out in order to estimate their relative value for measuring average groundwater recharge under a humid climatic environment with a relatively shallow water table. The hybrid water fluctuation method allowed the split of the hydrologic year into two seasons of recharge (wet season) and no recharge (dry season) to appraise specific yield during the dry season and, second, to estimate recharge from the water table rise during the wet season. This well elaborated and suitable method has then been used as a standard to assess the effectiveness of the chloride method under forest humid climatic environment. Effective specific yield of 0.08 was obtained for the study area. It reflects an effective basin-wide process and is insensitive to local heterogeneities in the aquifer system. The hybrid water fluctuation method gives an average recharge value of 87.14 mm/year at the basin scale, which represents 5.7% of the annual rainfall. Recharge value estimated based on the chloride method varies between 16.24 and 236.95 mm/year with an average value of 108.45 mm/year. It represents 7% of the mean annual precipitation. The discrepancy observed between recharge value estimated by the hybrid water fluctuation and the chloride mass balance methods appears to be very important, which could imply the ineffectiveness of the chloride mass balance method for this present humid environment.

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In our work we have used the atomic hydrogen [HΙ] gas distribution in the HΙ 21-cm line emission to study the dark matter halo perturbations. For tHΙs analysis, the 2-D HΙ surface density and velocity maps (arcHΙval) of the galaxies in the Eridanus group (obtained using the GMRT) and in the Ursa Major group (obtained from WSRT) were used. In addition a few HΙckson Compact Groups of galaxies were also studied using the GMRT. The HΙ maps of these galaxies were Fourier analysed to estimate the asymmetry in the distribution and motion of gas. The average asymmetry parameter in the 1.5 to 2.5 K′-band scale lengths was found to be ~ 0.27 for the Eridanus group of galaxies wHΙle it was ~ 0.14 for the Ursa Major group of galaxies. The asymmetries in the distribution of HΙ as a function of Hubble type of galaxies were also studied and was found to be directly correlated with the compactness of the groups. In addition, the trend in the asymmetry as a function of the Hubble type of galaxies was opposite to that seen in the field galaxies, i.e., in the group galaxies, the early type galaxies showed more asymmetry than late type. These two aspects indicated that tidal interactions between the galaxies in a group environment to be the major cause of asymmetries. The observed asymmetry parameters were consistent with recent numerical simulations of asymmetries of gas disk caused by fly-by interactions. We have also estimated the perturbation of dark matter halo using the asymmetry parameter obtained from the Fourier series analysis of the surface density maps.

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A number of geophysical methods have been proposed for near-surface site characterization and measurement of shear wave velocity by using a great variety of testing configurations, processing techniques,and inversion algorithms. In particular, two widely-used techniques are SASW (Spectral Analysis of SurfaceWaves) and MASW (Multichannel Analysis of SurfaceWaves). MASW is increasingly being applied to earthquake geotechnical engineering for the local site characterization, microzonation and site response studies.A MASW is a geophysical method, which generates a shear-wave velocity (Vs) profile (i.e., Vs versus depth)by analyzing Raleigh-type surface waves on a multichannel record. MASW system consisting of 24 channels Geode seismograph with 24 geophones of 4.5 Hz frequency have been used in this investigation. For the site characterization program, the MASW field experiments consisting of 58 one-dimensional shear wave velocity tests and 20 two-dimensional shear wave tests have been carried out. The survey points have been selected in such a way that the results supposedly represent the whole metropolitan Bangalore having an area of 220 km2.The average shear wave velocity of Bangalore soils have been evaluated for depths of 5m, 10m, 15m, 20m, 25m and 30 m. The subsoil site classification has been made for seismic local site effect evaluation based on average shear wave velocity of 30m depth (Vs30) of sites using National Earthquake Hazards Reduction Program (NEHRP) and International Building Code (IBC) classification. Soil average shearwave velocity estimated based on overburden thickness from the borehole information is also presented. Mapping clearly indicates that the depth of soil obtained from MASW is closely matching with the soil layers in bore logs. Among total 55 locations of MASW survey carried out, 34 locations were very close to the SPT borehole locations and these are used to generate correlation between Vs and corrected “N” values. The SPT field “N” values are corrected by applying the NEHRP recommended corrections.

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The work reported in this thesis is an attempt to enhance heat transfer in electronic devices with the use of impinging air jets on pin-finned heat sinks. The cooling per-formance of electronic devices has attracted increased attention owing to the demand of compact size, higher power densities and demands on system performance and re-liability. Although the technology of cooling has greatly advanced, the main cause of malfunction of the electronic devices remains overheating. The problem arises due to restriction of space and also due to high heat dissipation rates, which have increased from a fraction of a W/cm2to 100s of W /cm2. Although several researchers have at-tempted to address this at the design stage, unfortunately the speed of invention of cooling mechanism has not kept pace with the ever-increasing requirement of heat re- moval from electronic chips. As a result, efficient cooling of electronic chip remains a challenge in thermal engineering. Heat transfer can be enhanced by several ways like air cooling, liquid cooling, phase change cooling etc. However, in certain applications due to limitations on cost and weight, eg. air borne application, air cooling is imperative. The heat transfer can be increased by two ways. First, increasing the heat transfer coefficient (forced convec- tion), and second, increasing the surface area of heat transfer (finned heat sinks). From previous literature it was established that for a given volumetric air flow rate, jet im-pingement is the best option for enhancing heat transfer coefficient and for a given volume of heat sink material pin-finned heat sinks are the best option because of their high surface area to volume ratio. There are certain applications where very high jet velocities cannot be used because of limitations of noise and presence of delicate components. This process can further be improved by pulsating the jet. A steady jet often stabilizes the boundary layer on the surface to be cooled. Enhancement in the convective heat transfer can be achieved if the boundary layer is broken. Disruptions in the boundary layer can be caused by pulsating the impinging jet, i.e., making the jet unsteady. Besides, the pulsations lead to chaotic mixing, i.e., the fluid particles no more follow well defined streamlines but move unpredictably through the stagnation region. Thus the flow mimics turbulence at low Reynolds number. The pulsation should be done in such a way that the boundary layer can be disturbed periodically and yet adequate coolant is made available. So, that there is not much variation in temperature during one pulse cycle. From previous literature it was found that square waveform is most effective in enhancing heat transfer. In the present study the combined effect of pin-finned heat sink and impinging slot jet, both steady and unsteady, has been investigated for both laminar and turbulent flows. The effect of fin height and height of impingement has been studied. The jets have been pulsated in square waveform to study the effect of frequency and duty cycle. This thesis attempts to increase our understanding of the slot jet impingement on pin-finned heat sinks through numerical investigations. A systematic study is carried out using the finite-volume code FLUENT (Version 6.2) to solve the thermal and flow fields. The standard k-ε model for turbulence equations and two layer zonal model in wall function are used in the problem Pressure-velocity coupling is handled using the SIMPLE algorithm with a staggered grid. The parameters that affect the heat transfer coefficient are: height of the fins, total height of impingement, jet exit Reynolds number, frequency of the jet and duty cycle (percentage time the jet is flowing during one complete cycle of the pulse). From the studies carried out it was found that: a) beyond a certain height of the fin the rate of enhancement of heat transfer becomes very low with further increase in height, b) the heat transfer enhancement is much more sensitive to any changes at low Reynolds number than compared to high Reynolds number, c) for a given total height of impingement the use of fins and pulsated jet, increases the effective heat transfer coefficient by almost 200% for the same average Reynolds number, d) for all the cases it was observed that the optimum frequency of impingement is around 50 − 100 Hz and optimum duty cycle around 25-33.33%, e) in the case of turbulent jets the enhancement in heat transfer due to pulsations is very less compared to the enhancement in case of laminar jets.

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Spatial Decision Support System (SDSS) assist in strategic decision-making activities considering spatial and temporal variables, which help in Regional planning. WEPA is a SDSS designed for assessment of wind potential spatially. A wind energy system transforms the kinetic energy of the wind into mechanical or electrical energy that can be harnessed for practical use. Wind energy can diversify the economies of rural communities, adding to the tax base and providing new types of income. Wind turbines can add a new source of property value in rural areas that have a hard time attracting new industry. Wind speed is extremely important parameter for assessing the amount of energy a wind turbine can convert to electricity: The energy content of the wind varies with the cube (the third power) of the average wind speed. Estimation of the wind power potential for a site is the most important requirement for selecting a site for the installation of a wind electric generator and evaluating projects in economic terms. It is based on data of the wind frequency distribution at the site, which are collected from a meteorological mast consisting of wind anemometer and a wind vane and spatial parameters (like area available for setting up wind farm, landscape, etc.). The wind resource is governed by the climatology of the region concerned and has large variability with reference to space (spatial expanse) and time (season) at any fixed location. Hence the need to conduct wind resource surveys and spatial analysis constitute vital components in programs for exploiting wind energy. SDSS for assessing wind potential of a region / location is designed with user friendly GUI’s (Graphic User Interface) using VB as front end with MS Access database (backend). Validation and pilot testing of WEPA SDSS has been done with the data collected for 45 locations in Karnataka based on primary data at selected locations and data collected from the meteorological observatories of the India Meteorological Department (IMD). Wind energy and its characteristics have been analysed for these locations to generate user-friendly reports and spatial maps. Energy Pattern Factor (EPF) and Power Densities are computed for sites with hourly wind data. With the knowledge of EPF and mean wind speed, mean power density is computed for the locations with only monthly data. Wind energy conversion systems would be most effective in these locations during May to August. The analyses show that coastal and dry arid zones in Karnataka have good wind potential, which if exploited would help local industries, coconut and areca plantations, and agriculture. Pre-monsoon availability of wind energy would help in irrigating these orchards, making wind energy a desirable alternative.

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Most of the developing countries including India depend heavily on bioenergy and it accounts for about 15% of the global energy usage. Its role in meeting a region’s requirement has increased the interest of assessing the status of biomass availability in a region. The present work deals with the bioenergy status in the Linganamakki reservoir catchment of the Sharavathi river basin, Western Ghats,India, by assessing the energy supply and sector wise energy consumption. The study reveals that majority of the households (92.17%) depend on fuelwood for their domestic energy needs with the per capita fuelwood consumption of 1.2 tonnes/year, which is higher than the national average (0.7 tonnes/year). This higher dependence on fuelwood has contributed to the degradation of forests,resulting in scarcity of bioresources necessitating exploration of viable energy alternatives to meet the growing energy demand.

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Fault-tolerance is due to the semiconductor technology development important, not only for safety-critical systems but also for general-purpose (non-safety critical) systems. However, instead of guaranteeing that deadlines always are met, it is for general-purpose systems important to minimize the average execution time (AET) while ensuring fault-tolerance. For a given job and a soft (transient) error probability, we define mathematical formulas for AET that includes bus communication overhead for both voting (active replication) and rollback-recovery with checkpointing (RRC). And, for a given multi-processor system-on-chip (MPSoC), we define integer linear programming (ILP) models that minimize AET including bus communication overhead when: (1) selecting the number of checkpoints when using RRC, (2) finding the number of processors and job-to-processor assignment when using voting, and (3) defining fault-tolerance scheme (voting or RRC) per job and defining its usage for each job. Experiments demonstrate significant savings in AET.

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Context-sensitive points-to analysis is critical for several program optimizations. However, as the number of contexts grows exponentially, storage requirements for the analysis increase tremendously for large programs, making the analysis non-scalable. We propose a scalable flow-insensitive context-sensitive inclusion-based points-to analysis that uses a specially designed multi-dimensional bloom filter to store the points-to information. Two key observations motivate our proposal: (i) points-to information (between pointer-object and between pointer-pointer) is sparse, and (ii) moving from an exact to an approximate representation of points-to information only leads to reduced precision without affecting correctness of the (may-points-to) analysis. By using an approximate representation a multi-dimensional bloom filter can significantly reduce the memory requirements with a probabilistic bound on loss in precision. Experimental evaluation on SPEC 2000 benchmarks and two large open source programs reveals that with an average storage requirement of 4MB, our approach achieves almost the same precision (98.6%) as the exact implementation. By increasing the average memory to 27MB, it achieves precision upto 99.7% for these benchmarks. Using Mod/Ref analysis as the client, we find that the client analysis is not affected that often even when there is some loss of precision in the points-to representation. We find that the NoModRef percentage is within 2% of the exact analysis while requiring 4MB (maximum 15MB) memory and less than 4 minutes on average for the points-to analysis. Another major advantage of our technique is that it allows to trade off precision for memory usage of the analysis.

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Pricing is an effective tool to control congestion and achieve quality of service (QoS) provisioning for multiple differentiated levels of service. In this paper, we consider the problem of pricing for congestion control in the case of a network of nodes under a single service class and multiple queues, and present a multi-layered pricing scheme. We propose an algorithm for finding the optimal state dependent price levels for individual queues, at each node. The pricing policy used depends on a weighted average queue length at each node. This helps in reducing frequent price variations and is in the spirit of the random early detection (RED) mechanism used in TCP/IP networks. We observe in our numerical results a considerable improvement in performance using our scheme over that of a recently proposed related scheme in terms of both throughput and delay performance. In particular, our approach exhibits a throughput improvement in the range of 34 to 69 percent in all cases studied (over all routes) over the above scheme.

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We propose for the first time two reinforcement learning algorithms with function approximation for average cost adaptive control of traffic lights. One of these algorithms is a version of Q-learning with function approximation while the other is a policy gradient actor-critic algorithm that incorporates multi-timescale stochastic approximation. We show performance comparisons on various network settings of these algorithms with a range of fixed timing algorithms, as well as a Q-learning algorithm with full state representation that we also implement. We observe that whereas (as expected) on a two-junction corridor, the full state representation algorithm shows the best results, this algorithm is not implementable on larger road networks. The algorithm PG-AC-TLC that we propose is seen to show the best overall performance.

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The problem of developing L2-stability criteria for feedback systems with a single time-varying gain, which impose average variation constraints on the gain is treated. A unified approach is presented which facilitates the development of such average variation criteria for both linear and nonlinear systems. The stability criteria derived here are shown to be more general than the existing results.

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Digital human modeling (DHM) involves modeling of structure, form and functional capabilities of human users for ergonomics simulation. This paper presents application of geometric procedures for investigating the characteristics of human visual capabilities which are particularly important in the context mentioned above. Using the cone of unrestricted directions through the pupil on a tessellated head model as the geometric interpretation of the clinical field-of-view (FoV), the results obtained are experimentally validated. Estimating the pupil movement for a given gaze direction using Listing's Law, FoVs are re-computed. Significant variation of the FoV is observed with the variation in gaze direction. A novel cube-grid representation, which integrated the unit-cube representation of directions and the enhanced slice representation has been introduced for fast and exact point classification for point visibility analysis for a given FoV. Computation of containment frequency of every grid-cell for a given set of FoVs enabled determination of percentile-based FoV contours for estimating the visual performance of a given population. This is a new concept which makes visibility analysis more meaningful from ergonomics point-of-view. The algorithms are fast enough to support interactive analysis of reasonably complex scenes on a typical desktop computer. (C) 2011 Elsevier Ltd. All rights reserved.