WEPA: Wind energy potential assessment-spatial decision support system

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.

Comparative Assessment of Techniques for Bioresource Monitoring Using GIS and Remote Sensing

Growing concern over the status of global and regional bioenergy resources has necessitated the analysis and monitoring of land cover and land use parameters on spatial and temporal scales. The knowledge of land cover and land use is very important in understanding natural resources utilization, conversion and management. Land cover, land use intensity and land use diversity are land quality indicators for sustainable land management. Optimal management of resources aids in maintaining the ecosystem balance and thereby ensures the sustainable development of a region. Thus sustainable development of a region requires a synoptic ecosystem approach in the management of natural resources that relates to the dynamics of natural variability and the effects of human intervention on key indicators of biodiversity and productivity. Spatial and temporal tools such as remote sensing (RS), geographic information system (GIS) and global positioning system (GPS) provide spatial and attribute data at regular intervals with functionalities of a decision support system aid in visualisation, querying, analysis, etc., which would aid in sustainable management of natural resources. Remote sensing data and GIS technologies play an important role in spatially evaluating bioresource availability and demand. This paper explores various land cover and land use techniques that could be used for bioresources monitoring considering the spatial data of Kolar district, Karnataka state, India. Slope and distance based vegetation indices are computed for qualitative and quantitative assessment of land cover using remote spectral measurements. Differentscale mapping of land use pattern in Kolar district is done using supervised classification approaches. Slope based vegetation indices show area under vegetation range from 47.65 % to 49.05% while distance based vegetation indices shoes its range from 40.40% to 47.41%. Land use analyses using maximum likelihood classifier indicate that 46.69% is agricultural land, 42.33% is wasteland (barren land), 4.62% is built up, 3.07% of plantation, 2.77% natural forest and 0.53% water bodies. The comparative analysis of various classifiers, indicate that the Gaussian maximum likelihood classifier has least errors. The computation of talukwise bioresource status shows that Chikballapur Taluk has better availability of resources compared to other taluks in the district.

Multi-Mode Phonon-Controlled Field Emission from Carbon Nanotubes: Modeling and Experiments

The main idea proposed in this paper is that in a vertically aligned array of short carbon nanotubes (CNTs) grown on a metal substrate, we consider a frequency dependent electric field, so that the mode-specific propagation of phonons, in correspondence with the strained band structure and the dispersion curves, take place. We perform theoretical calculations to validate this idea with a view of optimizing the field emission behavior of the CNT array. This is the first approach of its kind, and is in contrast to the the conventional approach where a DC bias voltage is applied in order to observe field emission. A first set of experimental results presented in this paper gives a clear indication that phonon-assisted control of field emission current in CNT based thin film diode is possible.

Modeling the Field Emission Current Fluctuation in Carbon Nanotube Thin Films

Owing to their distinct properties, carbon nanotubes (CNTs) have emerged as promising candidate for field emission devices. It has been found experimentally that the results related to the field emission performance show variability. The design of an efficient field emitting device requires the analysis of the variabilities with a systematic and multiphysics based modeling approach. In this paper, we develop a model of randomly oriented CNTs in a thin film by coupling the field emission phenomena, the electron-phonon transport and the mechanics of single isolated CNT. A computational scheme is developed by which the states of CNTs are updated in time incremental manner. The device current is calculated by using Fowler-Nordheim equation for field emission to study the performance at the device scale.

Ce(0.67)Fe(0.33)O(2-delta) and Ce(0.65)Fe(0.33)Pt(0.02)O(2-delta): New water gas shift (WGS) catalysts

Ce(0.65)Fe(0.33)Pt(0.02)O(2-delta) and Ce(0.67)Fe(0.33)O(2-delta) have been synthesized by a new low temperature sonochemical method using diethylenetriamine as a complexing agent. Due to the substitution of Fe and Pt ions in CeO(2), lattice oxygen is activated in Ce(0.67)Fe(0.33)O(2-delta) and Ce(0.65)Fe(0.33)Pt(0.02)O(2-delta). Hydrogen uptake studies show strong reduction peaks at 125 C in Ce(0.65)Fe(0.33)Pt(0.02)O(2-delta) against a hydrogen uptake peak at 420 degrees C in Ce(0.67)Fe(0.33)O(2-delta). Fe substituted ceria, Ce(0.67)Fe(0.33)O(2-delta) itself acts as a catalyst for CO oxidation and water gas shift (WGS) reactions at moderate temperatures. The rate of CO conversion in WGS with Pt free Ce(0.65)Fe(0.33)O(2-delta) is 2.8 mu mol g(-1) s(-1) at 450 C and with Pt substituted Ce(0.65)Fe(0.33)Pt(0.02)O(2-delta) is 4.05 mu mol g(-1) s(-1) at 275 degrees C. Due to the synergistic interaction of the Pt ion with Ce and Fe ions in Ce(0.65)Fe(0.33)Pt(0.02)O(2-delta), the catalyst showed much higher activity for CO oxidation and WGS reactions compared to Ce(0.67)Fe(0.33)O(2-delta). A reverse WGS reaction does not occur over Ce(0.65)Fe(0.33)Pt(0.02)O(2-delta). The catalyst also does not deactivate even when operated for a long time. Nearly 100% conversion of CO to CO(2) with 100% H(2) selectivity is observed in WGS reactions even up to 550 degrees C. (C) 2011 Elsevier B.V. All rights reserved.

Discrimination of Nuclear Grade Steel Samples Subjected to Different Heat Treatment Procedures Based on Acoustic Emission (AE) Data Profiling at Crack Initiation

The present work is an attempt to study crack initiation in nuclear grade, 9Cr-1Mo ferritic steel using AE as an online NDE tool. Laboratory experiments were conducted on 5 heat treated Compact Tension (CT) specimens made out of nuclear grade 9Cr-1Mo ferritic steel by subjecting them to cyclic tensile load. The CT Specimens were of 12.5 mm thickness. The Acoustic emission test system was setup to acquire the data continuously during the test by mounting AE sensor on one of the surfaces of the specimen. This was done to characterize AE data pertaining to crack initiation and then discriminate the samples in terms of their heat treatment processes based on AE data. The AE signatures at crack initiation could conclusively bring to fore the heat treatment distinction on a sample to sample basis in a qualitative sense.Thus, the results obtained through these investigations establish a step forward in utilizing AE technique as an on-line measurement tool for accurate detection and understanding of crack initiation and its profile in 9Cr-1Mo nuclear grade steel subjected to different processes of heat treatment.