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Institution

National Institute of Technology, Karnataka

EducationMangalore, 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.


Papers
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Journal ArticleDOI
TL;DR: In this article, the frequency response of carbon nanotube reinforced magneto-electro-elastic (FG-CNTMEE) plates subjected to open and closed electro-magnetic circuit conditions was derived.

42 citations

Journal ArticleDOI
TL;DR: In this paper, the effect of current density on composition, surface morphology and phase structure were studied for explaining the magnetic and electrochemical properties of the nanocrystalline alloy, and the conditions responsible for peak magnetic property and corrosion resistance were optimized.

42 citations

Journal ArticleDOI
TL;DR: An iterative approach based on bilateral filtering is proposed for speckle reduction in multiframe OCT data and results on phantom images and real OCT retinal images demonstrate the effectiveness of the proposed filter.

42 citations

Journal ArticleDOI
TL;DR: In this article, the acid activated bentonite clay was incorporated into polyetherimide membranes and was extensively studied for its morphology, porosity, membrane hydraulic resistance and hydrophilic properties.
Abstract: The acid activated bentonite clay ranging from 1.0 to 4.0 wt% was incorporated into polyetherimide membranes and was extensively studied for its morphology, porosity, membrane hydraulic resistance and hydrophilic properties. The nanocomposite membrane has shown an increment in porosity, hydrophilicity and a reduction in hydraulic resistance. Elemental mapping studies confirmed the intercalation of activated bentonite clay within the polymer matrix. Studies have been conducted to analyse the permeate flux and rejection of Cu(ii), Ni(ii) and Cd(ii) ions by varying the pH and initial feed concentration. The results revealed that membranes with higher clay dosage showed enhanced flux and rejection, whereas lower rejection was observed in the case of lower pH and higher initial feed concentrations. It has also been demonstrated that the affinity of metal ions to form the hydration sphere and the adsorption capacity towards bentonite clay plays a vital role in the effective removal of metal ions. The membrane showed good rejection of heavy metal ions without any external chelating agent. The membranes showed maximum rejection of 69.3%, 76.2% and 82.5% for 250 ppm of Cd(ii), Ni(ii) and Cu(ii) ion solutions, respectively. The low level of heavy metal concentration in the permeate indicates that good quality water could be reclaimed for further reuse.

42 citations

Journal ArticleDOI
03 Oct 2018
TL;DR: In this article, the turning cutting tool inserts are coated with AlCN/AlC and FeCrN monolayer thin solid films using cathodic arc evaporation technique.
Abstract: Thin solid films are used in cutting tools in order to improve its performance, reduce tool wear and improve tool life. Cathodic arc evaporation is the state of art PVD technique widely accepted in industries for the development of thin solid films. The turning cutting tool inserts are coated with AlCN/AlC and FeCrN monolayer thin solid films using cathodic arc evaporation technique. Quality characteristics of thin films are estimated using Calo and VDI3198 tests. Thickness of the coatings are found to be 1.430 and 1.475 μm for AlCN/AlC and FeCrN coatings respectively and adhesion quality of HF1 is attained. Performance of the thin solid films are evaluated in machining MDN431 steel with range of cutting speed (59–118 m min−1), feed rate (0.062–0.125 mm/rev) and depth of cut (0.2–0.4 mm). Experiments are performed based on full factorial design and regression analysis. Optimization of the process parameters is carried out using combined techniques of desirability and Particle swarm optimisation (PSO). The objective of the study is to establish correlation between machining parameters with cutting force, tool wear and surface roughness. Optimal process parameter for least cutting force and surface roughness are obtained for coatings. ANN has been adopted to improve the coefficient of determination (CoD) and capability of predictive regression models. ANN trained model and mathematical regression models are adequate to predicted the responses, which follows the experimental data with minimum absolute error. The AlCN/AlC coatings exhibited lower cutting forces and surface roughness than FeCrN coated tools. Tool wear was reduced by 3.62 times in AlCN/AlC and 1.63 times in FeCrN coated tools compared to uncoated tool which is due to increased hardness and elastic modulus of the coating.

42 citations


Authors

Showing all 5100 results

NameH-indexPapersCitations
Ajay Kumar5380912181
Bhiksha Raj5135913064
Alexander P. Lyubartsev491849200
Vijay Nair4742510411
Sukumar Mishra444057905
Arun M. Isloor382616272
Vinay Kumaran362624473
M. C. Ray301152662
Airody Vasudeva Adhikari301192832
Ian R. Lane271292947
D. Krishna Bhat26951715
Anurag Kumar261262276
Soma Biswas251272195
Chandan Kumar25661806
H.S. Nagaraja23901609
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202351
2022175
2021938
2020893
2019838
2018740