Institution
Indian Institute of Technology Bombay
Education•Mumbai, India•
About: Indian Institute of Technology Bombay is a education organization based out in Mumbai, India. It is known for research contribution in the topics: Catalysis & Computer science. The organization has 16756 authors who have published 33588 publications receiving 570559 citations.
Topics: Catalysis, Computer science, Thin film, Population, Heat transfer
Papers published on a yearly basis
Papers
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TL;DR: In this article, the authors present experimental results on buoyancy-induced convection in aluminum metal foams of different pore densities and porosities and show that compared to a heated surface, the heat transfer coefficients in these heat sinks are five to six times higher.
Abstract: In this paper, we present our recent experimental results on buoyancy-induced convection in aluminum metal foams of different pore densities [corresponding to 5, 10, 20, and 40 pores per in. (PPI)] and porosities (0.89-0.96). The results show that compared to a heated surface, the heat transfer coefficients in these heat sinks are five to six times higher. However, when compared to commercially available heat sinks of similar dimensions, the enhancement is found to be marginal. The experimental results also show that for a given pore size, the heat transfer rate increases with porosity, suggesting the dominant role played by conduction in enhancing heat transfer. On the other hand, if the porosity is held constant, the heat transfer rate is found to be lower at higher pore densities. This can be attributed to the higher permeability with the larger pores, which allows higher entrainment of air through the porous medium. New empirical correlations are proposed for the estimation of Nusselt number in terms of Rayleigh and Darcy numbers. We also report our results on novel finned metal foam heat sinks in natural convection. Experiments were conducted on aluminum foams of 90% porosity with 5 and 20 PPI with one, two, and four aluminum fins inserted in the foam. All of these heat sinks were fabricated in-house. The results show that the finned metal foam heat sinks are superior in thermal performance compared to the normal metal foam and conventional finned heat sinks. The heat transfer increases with an increase in the number of fins. However, the relative enhancement is found to decrease with each additional fin. The indication is that there exists an optimum number of fins beyond which the enhancement in heat transfer, due to increased surface area, is offset by the retarding effect of overlapping thermal boundary layers. Similar to normal metal foams, the 5 PPI samples are found to give higher values of h compared to the 20 PPI samples due to higher permeability of the porous medium. Future work is planned to arrive at the optimal heat sink configuration for even larger enhancement in heat transfer.
115 citations
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TL;DR: In this paper, the performance of multiple tuned mass dampers (MTMD) for suppressing the dynamic response of a base-excited structure in a specific mode is investigated, where the base excitation is modelled as a stationary white noise random process.
115 citations
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TL;DR: In this paper, an effort has been made to summarize the developments so far, assess the effectiveness of various heat transfer techniques and draw some inferences from the study which can contribute to a more effective design of heat transfer systems.
115 citations
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TL;DR: In this article, a statistical downscaling technique for projections of all-India monsoon rainfall at a resolution of 0.5° in latitude/longitude was proposed, which can capture individual station means, the spatial patterns of the standard deviations, and cross correlation between station rainfalls.
Abstract: [1] Climate change impacts assessment involves downscaling of coarse-resolution climate variables simulated by general circulation models (GCMs) using dynamic (physics-based) or statistical (data-driven) approaches. Here we use a statistical downscaling technique for projections of all-India monsoon rainfall at a resolution of 0.5° in latitude/longitude. The present statistical downscaling model utilizes classification and regression tree, and kernel regression and develops a statistical relationship between large-scale climate variables from reanalysis data and fine-resolution observed rainfall, and then applies the relationship to coarse-resolution GCM outputs. A GCM developed by the Canadian Centre for Climate Modeling and Analysis is employed for this study with its five ensemble runs for capturing intramodel uncertainty. The model appears to effectively capture individual station means, the spatial patterns of the standard deviations, and the cross correlation between station rainfalls. Computationally expensive dynamic downscaling models have been applied for India. However, our study is the first to attempt statistical downscaling for the entire country at a resolution of 0.5°. The downscaling model seems to capture the orographic effect on rainfall in mountainous areas of the Western Ghats and northeast India. The model also reveals spatially nonuniform changes in rainfall, with a possible increase for the western coastline and northeastern India (rainfall surplus areas) and a decrease in northern India, western India (rainfall deficit areas), and on the southeastern coastline, highlighting the need for a detailed hydrologic study that includes future projections regarding water availability which may be useful for water resource policy decisions.
115 citations
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TL;DR: This review highlights the various protocols developed over the years for selective installation of suitable functional groups at the para-position of arenes thereby transforming them into value-added organic cores.
115 citations
Authors
Showing all 17055 results
Name | H-index | Papers | Citations |
---|---|---|---|
Jovan Milosevic | 152 | 1433 | 106802 |
C. N. R. Rao | 133 | 1646 | 86718 |
Robert R. Edelman | 119 | 605 | 49475 |
Claude Andre Pruneau | 114 | 610 | 45500 |
Sanjeev Kumar | 113 | 1325 | 54386 |
Basanta Kumar Nandi | 112 | 572 | 43331 |
Shaji Kumar | 111 | 1265 | 53237 |
Josep M. Guerrero | 110 | 1197 | 60890 |
R. Varma | 109 | 497 | 41970 |
Vijay P. Singh | 106 | 1699 | 55831 |
Vinayak P. Dravid | 103 | 817 | 43612 |
Swagata Mukherjee | 101 | 1048 | 46234 |
Anil Kumar | 99 | 2124 | 64825 |
Dhiman Chakraborty | 96 | 529 | 44459 |
Michael D. Ward | 95 | 823 | 36892 |