Diff selection: Mark the radio boxes of the revisions to compare and hit enter or the button at the bottom.
Legend: (cur) = difference with latest revision, (prev) = difference with preceding revision, m = minor edit.
T. Lassila, A. Manzoni, A. Quarteroni, G. Rozza. Model Order Reduction in Fluid Dynamics: Challenges and Perspectives. DOI 10.1007/978-3-319-02090-7_9
F. Ballarin, A. Manzoni, A. Quarteroni, G. Rozza. Supremizer stabilization of POD-Galerkin approximation of parametrized steady incompressible Navier-Stokes equations. Int. J. Numer. Meth. Engng 102(5) (2014) DOI 10.1002/nme.4772
T. Iliescu, Z. Wang. Are the Snapshot Difference Quotients Needed in the Proper Orthogonal Decomposition?. SIAM J. Sci. Comput. 36(3) DOI 10.1137/130925141
M. Gunzburger, N. Jiang, M. Schneier. An Ensemble-Proper Orthogonal Decomposition Method for the Nonstationary Navier--Stokes Equations. SIAM J. Numer. Anal. 55(1) (2017) DOI 10.1137/16m1056444
T. Rebollo, E. Ávila, M. Mármol, F. Ballarin, G. Rozza. On a Certified Smagorinsky Reduced Basis Turbulence Model. SIAM J. Numer. Anal. 55(6) DOI 10.1137/17m1118233
D. Torlo, F. Ballarin, G. Rozza. Stabilized Weighted Reduced Basis Methods for Parametrized Advection Dominated Problems with Random Inputs. SIAM/ASA J. Uncertainty Quantification 6(4) DOI 10.1137/17m1163517
Z. Luo, F. Teng, Z. Di. A POD-based reduced-order finite difference extrapolating model with fully second-order accuracy for non-stationary Stokes equations. International Journal of Computational Fluid Dynamics 28(6-10) (2014) DOI 10.1080/10618562.2014.973407
J. Zokagoa, A. Soulaïmani. A POD-based reduced-order model for uncertainty analyses in shallow water flows. International Journal of Computational Fluid Dynamics 32(6-7) (2018) DOI 10.1080/10618562.2018.1513496
J. Baiges, R. Codina, S. Idelsohn. Reduced-Order Modelling Strategies for the Finite Element Approximation of the Incompressible Navier-Stokes Equations. (2014) DOI 10.1007/978-3-319-06136-8_9
A. Caiazzo, R. Guibert, I. Vignon-Clementel. A reduced-order modeling for efficient design study of artificial valve in enlarged ventricular outflow tracts. Computer Methods in Biomechanics and Biomedical Engineering 19(12) (2016) DOI 10.1080/10255842.2015.1133811
D. Silva, A. Coutinho. Practical implementation aspects of Galerkin reduced order models based on proper orthogonal decomposition for computational fluid dynamics. J Braz. Soc. Mech. Sci. Eng. 37(4) (2014) DOI 10.1007/s40430-014-0259-3
T. Sengupta, L. Lestandi, S. Haider, A. Gullapalli, M. Azaïez. Reduced order model of flows by time-scaling interpolation of DNS data. Adv. Model. and Simul. in Eng. Sci. 5(1) (2018) DOI 10.1186/s40323-018-0119-2
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