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AntarikshVishwakarma / Jet-Analysis-Module

Developing a module for preprocessing, PIV, post-processing and analysis of jets, aiming at quantify key parameters from experimental data like entrainment rates, diffusivity, spreading angle, self-similarity (planar or axisymmetric jets), etc
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Jet-Analysis-Module

Developing a module for preprocessing, PIV, post-processing and analysis of jets, with an aim to quantify key parameters from experimental data like entrainment rates, spreading angle, self-similarity (planar or axisymmetric jets). Upon completion the code can be extended to include other parameters like diffusivity.

Main steps of the project :

  1. Getting familiar with data acquisition and post processing

    • Post proceesing sample data from 2D jet example, and Experimental Database
    • Preprocessing PIV images using local tracer particle density to distinguish between fluid entrained in the jet from the surrounding
    • Processing unmasked and masked PIV images and comparing their results

  2. Reading, understanding and deriving the formulas for self-similarity and entrainment as a function of distance:

    • Chapter 5 Free shear flows from Turbulent Flows by Stephen B. Pope
    • Chapter 5 Exact solutions of Navier-Stokes Equations from Boundary Layer Theory by Hermann Schlichting
    • Chapter 4 Boundary Free Shear Flows from A First Course in Turbulence from Tennekes and Lumley
    • Chapter 3 Solutions of The Newtonian Viscous-Flow Equations from Viscous Fluid Flow by Frank M. White
    • "Mechanics of the Turbulent-Nonturbulent Interface of a Jet" by J. Westerweel, C. Fukushima, J. M. Pedersen, and J. C. R. Hunt Phys. Rev. Lett. 95, 174501 – Published 20 October 2005; Erratum Phys. Rev. Lett. 95, 199902 (2005)

  3. Implementing the above formulas in Python, using textbook examples and data from above links for verification

  4. Testing the code using different sets of data and flow conditions obtained from literature to make the code universal and applicable in different scenarios, The matrix on this website will be used to guide the search for relevant results in different flow conditions(http://piv.de/uncertainty/?page_id=44)

  5. Based on the success of the 2D code, it will be extended to 3D to incorporate PTV results as well

    • Using the technique mentioned on this website data will be analyzed from here.
    • The 2D algorithm will then be modified and incorporated on a copy of the OpenPTV codes
    • The final 3D code will also be tested on flow conditions similar to the 2D case

Datasets to check

  1. https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/EBCBZM