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Ravi S. Srinivasan Jaya Lakshmanan Eddy Santosa Deepak Srivastav 《Energy and Buildings》2011,43(11):3289-3294
Benchmarking plug-load densities is essential to bypass arbitrary and/or incorrect inputs used in building energy analysis. As more building simulationists play a decision-making role for the design team, they tend to lean on building energy standards and guidelines for preliminary inputs such as plug-load densities. It is necessary for building energy standards and rating systems to implement plug-load density benchmarks to reward design teams in their efforts to reduce plug-load energy use. Using case study buildings, this paper establishes benchmark plug-load densities for K-12 schools under two new categories – classrooms with computers and classrooms without computers. Eighteen K-12 schools including 9 elementary, 2 middle, and 7 high schools are assessed for actual plug-load densities. For the same case study buildings, four existing approaches – NREL, COMNET, ASHRAE 90.1-1989, and Title-24 are evaluated for plug-load densities. Results show under- and over-estimation of plug-load densities over actual densities. The development of benchmark for K-12 schools will pave way for instituting targets for trimming plug-load densities in new and retrofit building projects. 相似文献
84.
G. M. Karthik P. Mastanaiah G. D. Janaki Ram Ravi Sankar Kottada 《Metallurgical and Materials Transactions B》2017,48(3):1416-1422
This work offers a fresh perspective on buttering, a technique often considered for fusion welding of dissimilar metals. For the first time, buttering was attempted in solid state using friction deposition. Using this new “friction buttering” technique, fusion welding of two different dissimilar metal pairs (austenitic stainless steel/borated stainless steel and Al-Cu-Mg/Al-Zn-Mg-Cu) was successfully demonstrated. The results show that friction buttering can simplify a tough dissimilar welding problem into a routine fusion welding task. 相似文献
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86.
For grading different types of renewable energy based electricity generation systems, a figure of merit has been proposed and evaluated. The figure of merit has been obtained by analyzing total energy utilization in constructing and installing the systems and by their respective electricity generation. The gross carbon emission has also been estimated for evaluation of figure of merit. This figure of merit clearly indicates that wind power is the most sustainable source for electricity generation, followed by small hydropower and solar photovoltaics. 相似文献
87.
Krishna P. Yagati Ravi N. Bathe Koteswararao V. Rajulapati K. Bhanu Sankara Rao G. Padmanabham 《Journal of Materials Processing Technology》2014,214(12):2949-2959
In this work, joining of aluminium alloy AA6061-T6 to Interstitial Free steel using pulsed gas metal arc welding process has been attempted. The effect of different surface conditions of steel (viz, galvanized, galvanealed and uncoated) and gap between the sheets on braze joint formation have been investigated. Galvanized steel surface showed good bead width, joint formation and lap shear strength compared to the other two combinations. Interface gap has not affected the wetting behaviour significantly but presence of a gap of 300 μm or so helped in escape of zinc vapour during the process there by avoiding formation of any crevice or macroporosity in the joint. Features and properties of the joint are characterized by metallography, fractography, energy dispersive spectroscopy (EDS) and lap shear tests. Load carrying capacity of Al-Galvanized steel was highest (222 N/mm of seam length) compared to other combinations, aided by better wetting due to presence of Zn on the surface and minimum porosity due to interfacial gap provided during brazing. 相似文献
88.
In the Platinum Group Minerals (PGM) industry, almost all UG2 deposits being currently developed are deep level and bankable feasibility studies must rely entirely on batch testwork of borecore samples. Since UG2 has a significant chromite (FeO·Cr2O3) content, minimising chromium oxide (Cr2O3) recovery into final concentrate has become a critical aspect of downstream smelting since % Cr2O3 in furnace feed has a practical upper limit of about 2.5%. In most cases concentrate is toll smelted but penalties are severe depending on chromite content. Together with PGMs, the characterisation of chromite floatability and prediction of recovery and concentrate grade in a production plant using bench-scale data is therefore a key component of UG2 ore analysis. The need to accurately predict chromite recovery and particularly to identify characteristics that indicate when % Cr2O3 in concentrate can be reduced has a significant impact on the project’s financials and subsequent plant design.The natural floatability of chromite is low and its passage into concentrate is almost entirely by entrainment in water carry-over into concentrate whereas PGMs are recovered by true flotation. Optimising flotation performance has to accommodate these two completely different flotation behaviours in an effort to reject chromite whilst at the same time maximise Platinum Group Minerals (PGM) recovery and grade.Incorporating extensive testwork conducted by Barrick Platinum South Africa and Northam and other plant data, the paper traces chromite, and to a lesser extent PGM, floatability in bench, pilot and plant scales and highlights that certain mechanisms of chromite entrainment are consistent irrespective of cell size and efficiency. 相似文献
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90.
This article presents a hybrid model involving artificial neural networks and biogeography-based optimization for long-term forecasting of India's sector-wise electrical energy demand. It involves socio-economic indicators, such as population and per capita gross domestic product, and uses two artificial neural networks, which are trained through a biogeography-based optimization algorithm with a goal of perfect mapping of the input–output data in the non-linear space through obtaining the global best weight parameters. The biogeography-based optimization based training of the artificial neural network improves the forecasting accuracy and avoids trapping in local optima besides enhancing the convergence to the lowest mean squared error at the minimum number of iterations than existing approaches. The model requires an input and the year of the forecast and predicts the sector-wise energy demand. Forecasts up to the year 2025 are compared with those of the regression model, the artificial neural network model trained by back-propagation, and the artificial neural network model trained by harmony search algorithm to exhibit its effectiveness. 相似文献