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Jyeshtharaj B. Joshi

Researcher at Institute of Chemical Technology

Publications -  602
Citations -  20424

Jyeshtharaj B. Joshi is an academic researcher from Institute of Chemical Technology. The author has contributed to research in topics: Turbulence & Bubble. The author has an hindex of 65, co-authored 577 publications receiving 17852 citations. Previous affiliations of Jyeshtharaj B. Joshi include Bhabha Atomic Research Centre & National Chemical Laboratory.

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Wet air oxidation

TL;DR: Wet air oxidation (WAO), involving oxidation at high temperature (125-320 C) and pressure (0.5-20 MPa) conditions, is useful for the treatment of hazardous, toxic, and nonbiodegradable waste streams as mentioned in this paper.
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Bubble Formation and Bubble Rise Velocity in Gas−Liquid Systems: A Review

Abstract: The formation of gas bubbles and their subsequent rise due to buoyancy are very important fundamental phenomena that contribute significantly to the hydrodynamics in gas−liquid reactors. The rise o...
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Catalytic carbon dioxide hydrogenation to methanol: A review of recent studies

TL;DR: In this paper, a comprehensive overview of all the recent studies published during the past decade is presented, including thermodynamic considerations, innovations in catalysts, influences of reaction variables, overall catalyst performance, reaction mechanism and kinetics, and recent technological advances.
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Computational flow modelling and design of bubble column reactors

TL;DR: In this article, the authors reviewed the modelling efforts on the flow patterns published in the last 30 years with relatively more focus on the last 10 years, focusing on cylindrical bubble columns where results on flow pattern could be extended to the design.
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CFD simulation of bubble column—An analysis of interphase forces and turbulence models

TL;DR: In this paper, a laboratory scale bubble column with three different spargers (perforated plate, sintered plate and single hole) has been simulated using three different turbulence closure (k-ɛ, RSM and LES) models, with the purpose of critically comparing their predictions with experimental data.