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Ankur Miglani

Researcher at Indian Institute of Technology Indore

Publications -  37
Citations -  549

Ankur Miglani is an academic researcher from Indian Institute of Technology Indore. The author has contributed to research in topics: Computer science & Combustion. The author has an hindex of 11, co-authored 26 publications receiving 357 citations. Previous affiliations of Ankur Miglani include Purdue University & Indian Institute of Science.

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Combustion and heat transfer characteristics of nanofluid fuel droplets: A short review

TL;DR: In this paper, the authors study the thermodynamic properties of high energy density fuels containing reactive metallic nanoparticles (NPs) at the droplet scale and understand how their interaction changes as a function of droplet size, NP type, NP concentration and the type of base fuel.
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Insight into instabilities in burning droplets

TL;DR: In this paper, self-induced boiling in burning functional pendant droplets can produce severe volumetric shape oscillations, and the degree of droplet deformation depends on the frequency and intensity of these bubble expulsion events.
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Effect of Particle Concentration on Shape Deformation and Secondary Atomization Characteristics of a Burning Nanotitania Dispersion Droplet

TL;DR: Secondary atomization characteristics of burning bicomponent (ethanol-water) droplets containing titania nanoparticles (NPs) were studied experimentally at atmospheric pressure under normal gravity as discussed by the authors.
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Sphere to ring morphological transformation in drying nanofluid droplets in a contact-free environment

TL;DR: The buckling instability induced morphological transition in an acoustically levitated, heated nanosuspension droplet using dynamic energy balance is elucidated and the droplet vaporization is observed to deviate from the classical D(2)-law.
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Deep CNN-based damage classification of milled rice grains using a high-magnification image dataset

TL;DR: In this article , a machine vision system is developed to first construct a dataset of 8048 high-magnification (4.5 x) images of damaged rice refractions, that are obtained through the on-field collection.