Ministry of Education
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Dr Harshal Akolekar

vidwan id: 265072
Male

Assistant Professor, Department of Mechanical Engineering
Indian Institute of Technology Jodhpur

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Expertise

  • Mechanical Engineering

Publications

Total Articles 22
Books 0
Proceedings 0

Publications

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Scopus

Citations 470
h-index 9

CrossRef

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Citations 21
h-index 2
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Professional Recognition

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Community & Membership

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Bio

Aerodynamics; Computational Fluid Dynamics; Machine Learning; Machine Learning; Submarine Hydrodynamics; Turbomachinery

Personal Details

  • Male
  • Assistant Professor , Indian Institute of Technology Jodhpur
  • NH-62, Nagaur Road, Karwar
Postdoctoral Fellow
Other Institute 2022
Ph.D.
Other Institute 2019
M.E. (Dist.)
Other Institute 2016
Assistant Professor Jan 2022 – Present
Indian Institute of Technology Jodhpur | Department of Mechanical Engineering

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Scholarly Work

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Scholarly Publications

Integration of machine learning and computational fluid dynamics to develop turbulence models for improved turbine wake mixing prediction

Open Access
Conference Paper
Year: 2020. Volume: 2C-2020 .
Authors: Akolekar H.D.;Zhao Y.;Sandberg R.D.;Pacciani R.
DOI 10.1115/GT2020-14732
4

Development and use of machine-learnt algebraic reynolds stress models for enhanced prediction of wake mixing in low-pressure turbines

Open Access
Article
Journal of Turbomachinery. Year: 2019. Volume: 141 , Issue: 4 .
Authors: Akolekar H.D.;Weatheritt J.;Hutchins N.;Sandberg R.D.;Laskowski G.;Michelassi V.
DOI 10.1115/1.4041753
46

Turbulence Model Development and Implementation for Low Pressure Turbines Using a Machine Learning Approach

Open Access
dissertation-thesis
Year: 2019.
Authors:

Machine-learnt turbulence closures for low-pressure turbines with unsteady inflow conditions

Open Access
Article
Journal of Turbomachinery. Year: 2019. Volume: 141 , Issue: 10 .
Authors: Akolekar H.D.;Sandberg R.D.;Hutchins N.;Michelassi V.;Laskowski G.
DOI 10.1115/1.4043907
22

CFD-ready Turbulence Models from Gene Expression Programming: Concepts

Open Access
conference-abstract
Year: 2019.
Authors:

Development and use of machine-learnt algebraic reynolds stress models for enhanced prediction of wake mixing in lpts

Open Access
Conference Paper
Year: 2018. Volume: 2C-2018 .
Authors: Akolekar H.D.;Weatheritt J.;Hutchins N.;Sandberg R.D.;Laskowski G.;Michelassi V.
DOI 10.1115/GT201875447
14