Clustering dimensionless learning for multiple-physical-regime systems-Reference-Cited by-同舟云学术

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Clustering dimensionless learning for multiple-physical-regime systems

Published:2024-02 Issue: Volume:420 Page:116728
ISSN:0045-7825
Container-title:Computer Methods in Applied Mechanics and Engineering
language:en
Short-container-title:Computer Methods in Applied Mechanics and Engineering

Author:

Zhang Lei^ORCID,Xu Zhaoyue^ORCID,Wang Shizhao,He Guowei

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Reference32 articles.

1. Fluid Mechanics;White,1979

2. Learning dominant physical processes with data-driven balance models;Callaham;Nature Commun.,2021

3. The spread of oil slicks on a calm sea;Fay,1969

4. Data-driven dimensional analysis: algorithms for unique and relevant dimensionless groups;Constantine,2017

5. Data-driven dimensional analysis of heat transfer in irradiated particle-laden turbulent flow;Jofre;Int. J. Multiph. Flow,2020

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2. Using the Buckingham π Theorem for Multi-System Transfer Learning: A Case-Study with 3 Vehicles Sharing a Database;Electronics;2024-05-23

3. Data-driven dryout prediction in helical-coiled once-through steam generator: A physics-informed approach leveraging the Buckingham Pi theorem;Energy;2024-05

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