Weighted Reduced Order Methods for Uncertainty Quantification in Computational Fluid Dynamics
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-55060-7_6
Reference34 articles.
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2. Ballarin, F., Sartori, A., Rozza, G.: RBniCS—reduced order modelling in FEniCS (2015). http://mathlab.sissa.it/rbnics
3. Carere, G., Strazzullo, M., Ballarin, F., Rozza, G., Stevenson, R.: A weighted pod-reduction approach for parametrized PDE-constrained optimal control problems with random inputs and applications to environmental sciences. Comput. Math. Appl. 102, 261–276 (2021)
4. Chen, P., Quarteroni, A., Rozza, G.: A weighted reduced basis method for elliptic partial differential equations with random input data. SIAM J. Numer. Anal. 51(6), 3163–3185 (2013)
5. Chen, P., Quarteroni, A., Rozza, G.: Comparison between reduced basis and stochastic collocation methods for elliptic problems. J. Sci. Comput. 59(1), 187–216 (2014)
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