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Institution

Padmasri Dr. B. V. Raju Institute of Technology

About: Padmasri Dr. B. V. Raju Institute of Technology is a based out in . It is known for research contribution in the topics: AC power & Nusselt number. The organization has 426 authors who have published 393 publications receiving 1741 citations. The organization is also known as: Padmasri Dr. B.V Raju Institute of Technology.


Papers
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Journal ArticleDOI
TL;DR: In this paper, the effects of thermal radiation and surface roughness on the complex dynamics of water conveying alumina and copper oxide nanoparticles, in the case where the thermophysical properties of the resulting mixture vary meaningfully with the volume fraction of solid nanomaterials, as well as with the Brownian motion and thermophoresis microscopic phenomena.
Abstract: Sequel to the fact that hybrid nanofluidic systems (e.g. scalable micro-/nanofluidic device) exhibit greater thermal resistance with increasing nanoparticle concentration, little is known on the significance of thermal radiation, surface roughness and linear stability of water conveying alumina and copper oxide nanoparticles. This study presents the effects of thermal radiation and surface roughness on the complex dynamics of water conveying alumina and copper oxide nanoparticles, in the case where the thermophysical properties of the resulting mixture vary meaningfully with the volume fraction of solid nanomaterials, as well as with the Brownian motion and thermophoresis microscopic phenomena. Based on the linear stability theory and normal mode analysis method, the basic partial differential equations governing the transport phenomenon were non-dimensionalized to obtain the simplified stability equations. The optimum values of the critical thermal Rayleigh number depicting the onset of thermo-magneto-hydrodynamic instabilities were obtained using the power series method and the Chock–Schechter numerical integration. The increase in the strength of Lorentz forces, thermal radiation and surface roughness has a stronger stabilizing impact on the appearance of convection cells. On the contrary, the stability diminishes with the increasing values of the volumetric fraction and diameter of nanomaterials. The partial substitution of the alumina nanoparticles by the copper oxide nanomaterials in the mixture stabilizes importantly the hybrid nanofluidic medium.

225 citations

Journal ArticleDOI
TL;DR: In this paper, the authors reviewed the technologies implemented for removal of ammonia and its associated compounds from wastewater based on physicochemical methods and biochemical treatment methods like biological treatment, membrane filtration, ion exchange, chemical precipitation, adsorption and some other technologies such as photocatalytic oxidation, aeration, and air stripping.

121 citations

Proceedings ArticleDOI
29 Mar 2018
TL;DR: The purpose of this paper presents an emerged survey of actual literatures on feature extraction methods since past five years, and described some of existing methodology of feature extraction.
Abstract: Deep learning is presently an effective research area in machine learning technique and pattern classification association. This has achieved big success in the areas of application namely computer vision, speech recognition, and NLP. This paper gives the impact of feature extraction that used in a deep learning technique such as Convolutional Neural Network (CNN). The purpose of this paper presents an emerged survey of actual literatures on feature extraction methods since past five years. As the raising of application demand increases, a large study and analysis in the feature extraction field became very efficient. In this paper, we presented a detailed study on deep learning, and a described some of existing methodology of feature extraction.

90 citations

Journal ArticleDOI
TL;DR: In this paper, the authors investigated radiative magnetohydrodynamic mixed convection boundary layer flow of nanofluids over a nonlinear inclined stretching/shrinking sheet in the presence of heat source/sink and viscous dissipation.

82 citations


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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20225
2021112
202054
201935
201828
201739