@article {2020, title = {Reduced Basis Model Order Reduction for Navier-Stokes equations in domains with walls of varying curvature}, journal = {International Journal of Computational Fluid Dynamics}, volume = {34}, year = {2020}, pages = {119-126}, abstract = {

We consider the Navier-Stokes equations in a channel with a narrowing and walls of varying curvature. By applying the empirical interpolation method to generate an affine parameter dependency, the offline-online procedure can be used to compute reduced order solutions for parameter variations. The reduced order space is computed from the steady-state snapshot solutions by a standard POD procedure. The model is discretised with high-order spectral element ansatz functions, resulting in 4752 degrees of freedom. The proposed reduced order model produces accurate approximations of steady-state solutions for a wide range of geometries and kinematic viscosity values. The application that motivated the present study is the onset of asymmetries (i.e., symmetry breaking bifurcation) in blood flow through a regurgitant mitral valve, depending on the Reynolds number and the valve shape. Through our computational study, we found that the critical Reynolds number for the symmetry breaking increases as the wall curvature increases.

}, doi = {10.1080/10618562.2019.1645328}, url = {https://arxiv.org/abs/1901.03708}, author = {Martin W. Hess and Annalisa Quaini and Gianluigi Rozza} } @article {2020, title = {Reduced basis model order reduction for Navier{\textendash}Stokes equations in domains with walls of varying curvature}, journal = {International Journal of Computational Fluid Dynamics}, volume = {34}, year = {2020}, pages = {119-126}, abstract = {

We consider the Navier{\textendash}Stokes equations in a channel with a narrowing and walls of varying curvature. By applying the empirical interpolation method to generate an affine parameter dependency, the offline-online procedure can be used to compute reduced order solutions for parameter variations. The reduced-order space is computed from the steady-state snapshot solutions by a standard POD procedure. The model is discretised with high-order spectral element ansatz functions, resulting in 4752 degrees of freedom. The proposed reduced-order model produces accurate approximations of steady-state solutions for a wide range of geometries and kinematic viscosity values. The application that motivated the present study is the onset of asymmetries (i.e. symmetry breaking bifurcation) in blood flow through a regurgitant mitral valve, depending on the Reynolds number and the valve shape. Through our computational study, we found that the critical Reynolds number for the symmetry breaking increases as the wall curvature increases.

}, doi = {10.1080/10618562.2019.1645328}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85085233294\&doi=10.1080\%2f10618562.2019.1645328\&partnerID=40\&md5=e2ed8f24c66376cdc8b5485aa400efb0}, author = {Martin W. Hess and Annalisa Quaini and Gianluigi Rozza} } @article {2020, title = {A reduced order modeling technique to study bifurcating phenomena: Application to the gross-pitaevskii equation}, journal = {SIAM Journal on Scientific Computing}, year = {2020}, abstract = {

We propose a computationally efficient framework to treat nonlinear partial differential equations having bifurcating solutions as one or more physical control parameters are varied. Our focus is on steady bifurcations. Plotting a bifurcation diagram entails computing multiple solutions of a parametrized, nonlinear problem, which can be extremely expensive in terms of computational time. In order to reduce these demanding computational costs, our approach combines a continuation technique and Newton{\textquoteright}s method with a reduced order modeling (ROM) technique, suitably supplemented with a hyperreduction method. To demonstrate the effectiveness of our ROM approach, we trace the steady solution branches of a nonlinear Schr{\"o}dinger equation, called the Gross{Pitaevskii equation, as one or two physical parameters are varied. In the two-parameter study, we show that our approach is 60 times faster in constructing a bifurcation diagram than a standard full order method.

}, doi = {10.1137/20M1313106}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85096768803\&doi=10.1137\%2f20M1313106\&partnerID=40\&md5=47d6012d10854c2f9a04b9737f870592}, author = {Federico Pichi and Annalisa Quaini and Gianluigi Rozza} } @article {2020, title = {A Reduced Order technique to study bifurcating phenomena: application to the Gross-Pitaevskii equation}, journal = {SIAM Journal on Scientific Computing}, year = {2020}, abstract = {

We propose a computationally efficient framework to treat nonlinear partial differential equations having bifurcating solutions as one or more physical control parameters are varied. Our focus is on steady bifurcations. Plotting a bifurcation diagram entails computing multiple solutions of a parametrized, nonlinear problem, which can be extremely expensive in terms of computational time. In order to reduce these demanding computational costs, our approach combines a continuation technique and Newton{\textquoteright}s method with a Reduced Order Modeling (ROM) technique, suitably supplemented with a hyper-reduction method. To demonstrate the effectiveness of our ROM approach, we trace the steady solution branches of a nonlinear Schr{\"o}dinger equation, called Gross-Pitaevskii equation, as one or two physical parameters are varied. In the two parameter study, we show that our approach is 60 times faster in constructing a bifurcation diagram than a standard Full Order Method.

}, doi = {https://doi.org/10.1137/20M1313106}, url = {https://arxiv.org/abs/1907.07082}, author = {Federico Pichi and Annalisa Quaini and Gianluigi Rozza} }