A Flow feature detection framework for large-scale computational data based on incremental proper orthogonal decomposition and data mining-Reference-Cited by-同舟云学术

A Flow feature detection framework for large-scale computational data based on incremental proper orthogonal decomposition and data mining

Published:2018-08-09 Issue:6-7 Volume:32 Page:261-277
ISSN:1061-8562
Container-title:International Journal of Computational Fluid Dynamics
language:en
Short-container-title:International Journal of Computational Fluid Dynamics

Author:

Robertson Eric D.¹,Wang Yi²^ORCID,Pant Kapil³,Grismer Matthew J.⁴,Camberos José A.⁴

Affiliation:

1. Munitions Aerodynamics Sciences Branch, Air Force Research Laboratory, Eglin Air Force Base, FL, USA

2. University of South Carolina, Columbia, SC, USA

3. CFD Research Corporation, Huntsville, AL, USA

4. Aerospace Systems Directorate, Air Force Research Laboratory, Wright-Patterson Air Force Base, OH, USA

Funder

Air Force Office of Scientific Research

Publisher

Informa UK Limited

Subject

Mechanical Engineering,Mechanics of Materials,Energy Engineering and Power Technology,Condensed Matter Physics,Aerospace Engineering,Computational Mechanics

Link

https://www.tandfonline.com/doi/pdf/10.1080/10618562.2018.1508657

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4. A general classification of three‐dimensional flow fields

5. Large-scale dynamics in the flow around a finite cylinder with a ground plate

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