Editorial: Data-driven modeling and optimization in fluid dynamics: From physics-based to machine learning approaches
- DOI
- 10.3389/fphy.2022.1072691
- Published
- 12
- Container
- Frontiers in Physics
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.3389/fphy.2022.1072691,
title = {Editorial: Data-driven modeling and optimization in fluid dynamics: From physics-based to machine learning approaches},
author = {Michel Bergmann and Laurent Cordier and Traian Iliescu},
year = {2022},
journal = {Frontiers in Physics},
doi = {10.3389/fphy.2022.1072691},
url = {https://doi.org/10.3389/fphy.2022.1072691}
}RIS
TY - JOUR TI - Editorial: Data-driven modeling and optimization in fluid dynamics: From physics-based to machine learning approaches AU - Michel Bergmann AU - Laurent Cordier AU - Traian Iliescu PY - 2022 JO - Frontiers in Physics DO - 10.3389/fphy.2022.1072691 UR - https://doi.org/10.3389/fphy.2022.1072691 ER -
APA
Bergmann, M., Cordier, L., & Iliescu, T. (2022). Editorial: Data-driven modeling and optimization in fluid dynamics: From physics-based to machine learning approaches. Frontiers in Physics. https://doi.org/10.3389/fphy.2022.1072691