Reconstructing velocity and pressure from noisy sparse particle tracks using constrained cost minimization-Reference-Cited by-同舟云学术

Reconstructing velocity and pressure from noisy sparse particle tracks using constrained cost minimization

Published:2021-03-23 Issue:4 Volume:62 Page:
ISSN:0723-4864
Container-title:Experiments in Fluids
language:en
Short-container-title:Exp Fluids

Author:

Agarwal Karuna,Ram Omri,Wang Jin,Lu Yuhui,Katz Joseph^ORCID

Funder

Office of Naval Research

Publisher

Springer Science and Business Media LLC

Subject

Fluid Flow and Transfer Processes,General Physics and Astronomy,Mechanics of Materials,Computational Mechanics

Link

https://link.springer.com/content/pdf/10.1007/s00348-021-03172-0.pdf

Reference52 articles.

1. Agarwal K, Ram O, Katz J (2018) Cavitating structures at inception in turbulent shear flow. CAV18. https://doi.org/10.1115/1.861851_ch33

2. Agarwal K, Ram O, Wang J, Katz J (2019) Velocity and pressure reconstruction from sparse particle fields. ISPIV 2019

3. Aitken AC (1935) On least squares and linear combinations of observations. Proc R Soc Edinb 55:42–48. https://doi.org/10.1017/S0370164600014346

4. Albert A (1972) Regression and the Moore-Penrose pseudoinverse, 1st edn. Academic Press

5. Baur T, Kongeter J (1999) PIV with high temporal resolution for the determination of local pressure reductions from coherent turbulence phenomena. 3rd international workshop on particle image velocimetry, Santa Barbara, 16–18 September, 101–106

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