The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/caa059d2-7657-4301-a805-767e9ca98eab

Grille Guerra, Adrian; Andrea Sciacchitano; Fulvio Scarano (2024): Supporting data for: "Iterative modal reconstruction for sparse particle tracking data". Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/caa059d2-7657-4301-a805-767e9ca98eab.v1

Dataset

• Aerospace Engineering
• Engineering

data assimilation, lagrangian particle tracking, particle image velocimetry, proper orthogonal decomposition

CC BY 4.0

RefWorks, BibTeX, Reference Manager, Endnote, DataCite, NLM, DC, CFF

by Adrian Grille Guerra , Andrea Sciacchitano , Fulvio Scarano

The dataset in this repository complements the publication: Adrian Grille Guerra, Andrea Sciacchitano, Fulvio Scarano; Iterative modal reconstruction for sparse particle tracking data. Physics of Fluids 1 July 2024; 36 (7): 075107. https://doi.org/10.1063/5.0209527. The dataset contains the electronic supplementary material also available in the online version of the journal (three videos), a digital version of the figures of the publication in Matlab figure format, the full dataset discussed in the publication and also a sample code of the proposed methodology.

• 2024-07-02 first online, published, posted

4TU.ResearchData

video (.mp4), data figures (Matlab .fig), Matlab code (.m), Matlab data (.mat)

Iterative modal reconstruction for sparse particle tracking data

TU Delft, Faculty of Aerospace Engineering, Department of Flow Physics and Technology