Institution
National Institute of Technology, Karnataka
Education•Mangalore, Karnataka, India•
About: National Institute of Technology, Karnataka is a education organization based out in Mangalore, Karnataka, India. It is known for research contribution in the topics: Computer science & Corrosion. The organization has 5017 authors who have published 7057 publications receiving 70367 citations.
Topics: Computer science, Corrosion, Cloud computing, Microstructure, Alloy
Papers published on a yearly basis
Papers
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TL;DR: In this article, the performance of weathered steel slag coarse aggregates in GGBFS-FA based geopolymer concrete is evaluated and the flexural fatigue behavior of GGB FS-FA geopolym concrete with steel slags is also studied in detail.
Abstract: The present day research is focussed on development of alternative binder materials to Ordinary Portland Cement (OPC) due to huge emissions of green house gases associated with production of OPC. GGBFS-FA based geopolymer binders are an innovative alternative to OPC which can obtain high strengths apart from being eco-friendly; since its production does not involve high energy and also contributes to sustainability by using the industrial waste materials. Steel slag, an industrial by-product obtained from manufacture of steel can be identified as an alternative to natural aggregates for concrete production, since there is a possibility of acute shortage of natural aggregates in future. The present study is conducted to evaluate the performance of weathered steel slag coarse aggregates in GGBFS-FA based geopolymer concrete. GGBFS-FA geopolymer concrete with steel slag coarse aggregates are prepared by replacing natural granite aggregates at different replacement levels i.e. 0%, 25%, 50%, 75% and 100% (by volume) and various fresh and mechanical properties are studied. The flexural fatigue behaviour of GGBFS-FA geopolymer concrete with steel slag is also studied in detail. Efforts are also made to model the probabilistic distribution of fatigue data of GGBFS-FA geopolymer concrete at different stress levels using two parameters Weibull distribution. The results indicated that incorporation of steel slag in GGBFS-FA geopolymer concrete resulted in slight reduction in mechanical strength. The water absorption and volume of permeable voids displayed higher values with inclusion of steel slag. Reduction in number of cycles for fatigue failure was observed in geopolymer concrete mixes containing steel slag as compared to granite aggregates. Overall, the performance of steel slag was found to be satisfactory for structural and pavement application and steel slag can be recognised as new construction material.
47 citations
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TL;DR: It is concluded from the computed values of elastic constants that h-BN sheets, finite or infinite, satisfy Born's criterion for mechanical stability.
Abstract: Classical molecular dynamics simulations have been performed to analyze the elastic and mechanical properties of two-dimensional (2D) hexagonal boron nitride (h-BN) using a Tersoff-type interatomic empirical potential. We present a systematic study of h-BN for various system sizes. Young's modulus and Poisson's ratio are found to be anisotropic for finite sheets whereas they are isotropic for the infinite sheet. Both of them increase with system size in accordance with a power law. It is concluded from the computed values of elastic constants that h-BN sheets, finite or infinite, satisfy Born's criterion for mechanical stability. Due to the the strong in-plane sp2 bonds and the small mass of boron and nitrogen atoms, h-BN possesses high longitudinal and shear velocities. The variation of bending rigidity with system size is calculated using the Foppl-von Karman approach by coupling the in-plane bending and out-of-plane stretching modes of the 2D h-BN.
47 citations
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TL;DR: Identification of several clinically important bacterial species in the samples suggests that the workers at the treatment plant are exposed to opportunistic and infectious bacteria.
Abstract: Wastewater contains a variety of microorganisms, and unit operations in the plants could release these biological components into the air environment. These airborne biological particles could have adverse health effects on plant workers and the downwind population. This study provides a first report on the concentration and characterization of the airborne biological particles in six wastewater treatment plants in Mumbai, India. The study indicates that 49% and 27% of the samples exceed, respectively, the exposure limit for airborne endotoxin and bacteria in occupational settings. Endotoxin was identified as the single most important component of the particulate matter responsible for induction of proinflammatory indicator (tumor necrosis factor-α) in in vitro assay. Identification of several clinically important bacterial species in the samples suggests that the workers at the treatment plant are exposed to opportunistic and infectious bacteria. Principal component analysis was used to identify the grou...
47 citations
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TL;DR: It is shown that with the proposed control law the agent trajectories converge in a globally asymptotic manner to the centroidal Voronoi configuration.
Abstract: This paper addresses the problem of automated multiagent search in an unknown environment. Autonomous agents equipped with sensors carry out a search operation in a search space, where the uncertainty, or lack of information about the environment, is known a priori as an uncertainty density distribution function. The agents are deployed in the search space to maximize single step search effectiveness. The centroidal Voronoi configuration, which achieves a locally optimal deployment, forms the basis for the proposed sequential deploy and search strategy. It is shown that with the proposed control law the agent trajectories converge in a globally asymptotic manner to the centroidal Voronoi configuration. Simulation experiments are provided to validate the strategy.
46 citations
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TL;DR: A Genetic Algorithm based Wrapper Feature Selection technique is proposed for determining most-optimal lab events that contribute predominantly to mortality, even for large-scale patient cohorts, using an Extreme Learning Machine (ELM) based neural network designed for predicting patient-specific ICU mortality.
46 citations
Authors
Showing all 5100 results
Name | H-index | Papers | Citations |
---|---|---|---|
Ajay Kumar | 53 | 809 | 12181 |
Bhiksha Raj | 51 | 359 | 13064 |
Alexander P. Lyubartsev | 49 | 184 | 9200 |
Vijay Nair | 47 | 425 | 10411 |
Sukumar Mishra | 44 | 405 | 7905 |
Arun M. Isloor | 38 | 261 | 6272 |
Vinay Kumaran | 36 | 262 | 4473 |
M. C. Ray | 30 | 115 | 2662 |
Airody Vasudeva Adhikari | 30 | 119 | 2832 |
Ian R. Lane | 27 | 129 | 2947 |
D. Krishna Bhat | 26 | 95 | 1715 |
Anurag Kumar | 26 | 126 | 2276 |
Soma Biswas | 25 | 127 | 2195 |
Chandan Kumar | 25 | 66 | 1806 |
H.S. Nagaraja | 23 | 90 | 1609 |