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Web of Science Core Collection® Times cited: 10 Crossref Cited-by Times cited: 13 OpenCitations.net Times cited: 7
OpenCitations.net - Citing documents:
M. Mohebujjaman, L. Rebholz, T. Iliescu. Physically constrained data‐driven correction for reduced‐order modeling of fluid flows. Int J Numer Meth Fluids 89(3) (2018) DOI 10.1002/fld.4684
O. San, R. Maulik. Extreme learning machine for reduced order modeling of turbulent geophysical flows. Phys. Rev. E 97(4) (2018) DOI 10.1103/physreve.97.042322
X. Xie, M. Mohebujjaman, L. Rebholz, T. Iliescu. Data-Driven Filtered Reduced Order Modeling of Fluid Flows. SIAM J. Sci. Comput. 40(3) DOI 10.1137/17m1145136
N. Akkari, F. Casenave, V. Moureau. Time Stable Reduced Order Modeling by an Enhanced Reduced Order Basis of the Turbulent and Incompressible 3D Navier–Stokes Equations. MCA 24(2) (2019) DOI 10.3390/mca24020045
A. Ferrer, J. Oliver, J. Cante, O. Lloberas-Valls. Vademecum-based approach to multi-scale topological material design. Adv. Model. and Simul. in Eng. Sci. 3(1) (2016) DOI 10.1186/s40323-016-0078-4
R. Reyes, R. Codina, J. Baiges, S. Idelsohn. Reduced order models for thermally coupled low Mach flows. Adv. Model. and Simul. in Eng. Sci. 5(1) (2018) DOI 10.1186/s40323-018-0122-7
S. Rahman, S. Ahmed, O. San. A dynamic closure modeling framework for model order reduction of geophysical flows. Physics of Fluids 31(4) DOI 10.1063/1.5093355