Dimensionally consistent learning with Buckingham Pi-Reference-Cited by-同舟云学术

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Dimensionally consistent learning with Buckingham Pi

Published:2022-12-15 Issue:12 Volume:2 Page:834-844
ISSN:2662-8457
Container-title:Nature Computational Science
language:en
Short-container-title:Nat Comput Sci

Author:

Bakarji Joseph,Callaham Jared,Brunton Steven L.,Kutz J. Nathan

Funder

United States Department of Defense | United States Army | U.S. Army Research, Development and Engineering Command | Army Research Office

U.S. Department of Defense

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Computer Science Applications,Computer Science (miscellaneous)

Link

https://www.nature.com/articles/s43588-022-00355-5.pdf

Reference45 articles.

1. Barenblatt, G. I. Scaling, Self-Similarity, and Intermediate Asymptotics: Dimensional Analysis and Intermediate Asymptotics 14 (Cambridge Univ. Press, 1996).

2. Sterrett, S. G. Physically Similar Systems – A History of the Concept, pp 377–411 (Springer, 2017).

3. Buckingham, E. On physically similar systems; illustrations of the use of dimensional equations. Phys. Rev. 4, 345–376 (1914).

4. del Rosario, Z., Lee, M. & Iaccarino, G. Lurking variable detection via dimensional analysis. SIAM/ASA J. Uncertain. 7, 232–259 (2019).

5. Jofre, L., del Rosario, Z. R. & Iaccarino, G. Data-driven dimensional analysis of heat transfer in irradiated particle-laden turbulent flow. Int. J. Multiphase Flow 125, 103198 (2020).

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