@article {2022, title = {Driving bifurcating parametrized nonlinear PDEs by optimal control strategies: application to Navier{\textendash}Stokes equations with model order reduction}, journal = {ESAIM: M2AN}, volume = {56}, year = {2022}, month = {2022///}, pages = {1361 - 1400}, url = {https://doi.org/10.1051/m2an/2022044}, author = {Federico Pichi and Maria Strazzullo and F. Ballarin and Gianluigi Rozza} } @article {2021, title = {Hierarchical model reduction techniques for flow modeling in a parametrized setting}, journal = {Multiscale Modeling and Simulation}, volume = {19}, year = {2021}, pages = {267-293}, abstract = {

In this work we focus on two different methods to deal with parametrized partial differential equations in an efficient and accurate way. Starting from high fidelity approximations built via the hierarchical model reduction discretization, we consider two approaches, both based on a projection model reduction technique. The two methods differ for the algorithm employed during the construction of the reduced basis. In particular, the former employs the proper orthogonal decomposition, while the latter relies on a greedy algorithm according to the certified reduced basis technique. The two approaches are preliminarily compared on two-dimensional scalar and vector test cases.

}, doi = {10.1137/19M1285330}, author = {Matteo Zancanaro and F. Ballarin and Simona Perotto and Gianluigi Rozza} } @article {2021, title = {A Monolithic and a Partitioned, Reduced Basis Method for Fluid{\textendash}Structure Interaction Problems}, journal = {Fluids}, volume = {6}, year = {2021}, pages = {229}, abstract = {

The aim of this work is to present an overview about the combination of the Reduced Basis Method (RBM) with two different approaches for Fluid{\textendash}Structure Interaction (FSI) problems, namely a monolithic and a partitioned approach. We provide the details of implementation of two reduction procedures, and we then apply them to the same test case of interest. We first implement a reduction technique that is based on a monolithic procedure where we solve the fluid and the solid problems all at once. We then present another reduction technique that is based on a partitioned (or segregated) procedure: the fluid and the solid problems are solved separately and then coupled using a fixed point strategy. The toy problem that we consider is based on the Turek{\textendash}Hron benchmark test case, with a fluid Reynolds number Re=100.

}, issn = {2311-5521}, doi = {10.3390/fluids6060229}, url = {https://www.mdpi.com/2311-5521/6/6/229}, author = {Monica Nonino and F. Ballarin and Gianluigi Rozza} } @article {2021, title = {A Reduced Order Cut Finite Element method for geometrically parametrized steady and unsteady Navier{\textendash}Stokes problems}, journal = {Computer \& Mathematics With Applications}, year = {2021}, month = {2021/08/12/}, abstract = {

We focus on steady and unsteady Navier{\textendash}Stokes flow systems in a reduced-order modeling framework based on Proper Orthogonal Decomposition within a levelset geometry description and discretized by an unfitted mesh Finite Element Method. This work extends the approaches of [1], [2], [3] to nonlinear CutFEM discretization. We construct and investigate a unified and geometry independent reduced basis which overcomes many barriers and complications of the past, that may occur whenever geometrical morphings are taking place. By employing a geometry independent reduced basis, we are able to avoid remeshing and transformation to reference configurations, and we are able to handle complex geometries. This combination of a fixed background mesh in a fixed extended background geometry with reduced order techniques appears beneficial and advantageous in many industrial and engineering applications, which could not be resolved efficiently in the past.

}, keywords = {Cut Finite Element Method, Navier{\textendash}Stokes equations, Parameter{\textendash}dependent shape geometry, Reduced Order Models, Unfitted mesh}, isbn = {0898-1221}, url = {https://www.sciencedirect.com/science/article/pii/S0898122121002790}, author = {Efthymios N Karatzas and Monica Nonino and F. Ballarin and Gianluigi Rozza} } @conference { 20.500.11767_123375, title = {Reduced Order Methods for Parametrized Non-linear and Time Dependent Optimal Flow Control Problems, Towards Applications in Biomedical and Environmental Sciences}, booktitle = {Numerical Mathematics and Advanced Applications ENUMATH 2019}, volume = {139}, year = {2021}, pages = {841{\textendash}850}, publisher = {Springer}, organization = {Springer}, isbn = {978-3-030-55873-4}, doi = {10.1007/978-3-030-55874-1_83}, url = {https://arxiv.org/abs/1912.07886}, author = {Maria Strazzullo and Zakia Zainib and F. Ballarin and Gianluigi Rozza} } @conference {2021, title = {Reduced Order Methods for Parametrized Non-linear and Time Dependent Optimal Flow Control Problems, Towards Applications in Biomedical and Environmental Sciences}, booktitle = {Numerical Mathematics and Advanced Applications ENUMATH 2019}, year = {2021}, month = {2021//}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, address = {Cham}, abstract = {

We introduce reduced order methods as an efficient strategy to solve parametrized non-linear and time dependent optimal flow control problems governed by partial differential equations. Indeed, the optimal control problems require a huge computational effort in order to be solved, most of all in physical and/or geometrical parametrized settings. Reduced order methods are a reliable and suitable approach, increasingly gaining popularity, to achieve rapid and accurate optimal solutions in several fields, such as in biomedical and environmental sciences. In this work, we employ a POD-Galerkin reduction approach over a parametrized optimality system, derived from the Karush-Kuhn-Tucker conditions. The methodology presented is tested on two boundary control problems, governed respectively by (1) time dependent Stokes equations and (2) steady non-linear Navier-Stokes equations.

}, isbn = {978-3-030-55874-1}, doi = {https://doi.org/10.1007/978-3-030-55874-1_83}, url = {https://www.springerprofessional.de/en/reduced-order-methods-for-parametrized-non-linear-and-time-depen/19122676}, author = {Maria Strazzullo and Zakia Zainib and F. Ballarin and Gianluigi Rozza}, editor = {Fred J Vermolen and Cornelis Vuik} } @inbook {RozzaHessStabileTezzeleBallarin2020, title = {Basic ideas and tools for projection-based model reduction of parametric partial differential equations}, booktitle = {Model Order Reduction, Volume 2 Snapshot-Based Methods and Algorithms}, year = {2020}, pages = {1 - 47}, publisher = {De Gruyter}, organization = {De Gruyter}, address = {Berlin, Boston}, isbn = {9783110671490}, doi = {https://doi.org/10.1515/9783110671490-001}, url = {https://www.degruyter.com/view/book/9783110671490/10.1515/9783110671490-001.xml}, author = {Gianluigi Rozza and Martin W. Hess and Giovanni Stabile and Marco Tezzele and F. Ballarin} } @article {2020, title = {Certified Reduced Basis VMS-Smagorinsky model for natural convection flow in a cavity with variable height}, journal = {Computers and Mathematics with Applications}, volume = {80}, year = {2020}, pages = {973-989}, abstract = {

In this work we present a Reduced Basis VMS-Smagorinsky Boussinesq model, applied to natural convection problems in a variable height cavity, in which the buoyancy forces are involved. We take into account in this problem both physical and geometrical parametrizations, considering the Rayleigh number as a parameter, so as the height of the cavity. We perform an Empirical Interpolation Method to approximate the sub-grid eddy viscosity term that lets us obtain an affine decomposition with respect to the parameters. We construct an a posteriori error estimator, based upon the Brezzi{\textendash}Rappaz{\textendash}Raviart theory, used in the greedy algorithm for the selection of the basis functions. Finally we present several numerical tests for different parameter configuration.

}, doi = {10.1016/j.camwa.2020.05.013}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85085843368\&doi=10.1016\%2fj.camwa.2020.05.013\&partnerID=40\&md5=7c6596865ec89651319c7dd97159dd77}, author = {F. Ballarin and Rebollo, T.C. and E.D. {\'A}vila and Marmol, M.G. and Gianluigi Rozza} } @conference {HijaziAliStabileBallarinRozza2020, title = {The Effort of Increasing Reynolds Number in Projection-Based Reduced Order Methods: from Laminar to Turbulent Flows}, booktitle = {Lecture Notes in Computational Science and Engineering}, year = {2020}, pages = {245{\textendash}264}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, address = {Cham}, abstract = {

We present in this double contribution two different reduced order strategies for incompressible parameterized Navier-Stokes equations characterized by varying Reynolds numbers. The first strategy deals with low Reynolds number (laminar flow) and is based on a stabilized finite element method during the offline stage followed by a Galerkin projection on reduced basis spaces generated by a greedy algorithm. The second methodology is based on a full order finite volume discretization. The latter methodology will be used for flows with moderate to high Reynolds number characterized by turbulent patterns. For the treatment of the mentioned turbulent flows at the reduced order level, a new POD-Galerkin approach is proposed. The new approach takes into consideration the contribution of the eddy viscosity also during the online stage and is based on the use of interpolation. The two methodologies are tested on classic benchmark test cases.

}, isbn = {978-3-030-30705-9}, doi = {10.1007/978-3-030-30705-9_22}, author = {Saddam Hijazi and Shafqat Ali and Giovanni Stabile and F. Ballarin and Gianluigi Rozza} } @unpublished {2020, title = {POD-Galerkin Model Order Reduction for Parametrized Nonlinear Time Dependent Optimal Flow Control: an Application to Shallow Water Equations}, year = {2020}, abstract = {

In this work we propose reduced order methods as a reliable strategy to efficiently solve parametrized optimal control problems governed by shallow waters equations in a solution tracking setting. The physical parametrized model we deal with is nonlinear and time dependent: this leads to very time consuming simulations which can be unbearable e.g. in a marine environmental monitoring plan application. Our aim is to show how reduced order modelling could help in studying different configurations and phenomena in a fast way. After building the optimality system, we rely on a POD-Galerkin reduction in order to solve the optimal control problem in a low dimensional reduced space. The presented theoretical framework is actually suited to general nonlinear time dependent optimal control problems. The proposed methodology is finally tested with a numerical experiment: the reduced optimal control problem governed by shallow waters equations reproduces the desired velocity and height profiles faster than the standard model, still remaining accurate.

}, author = {Maria Strazzullo and F. Ballarin and Gianluigi Rozza} } @article {2020, title = {POD{\textendash}Galerkin Model Order Reduction for Parametrized Time Dependent Linear Quadratic Optimal Control Problems in Saddle Point Formulation}, journal = {Journal of Scientific Computing}, volume = {83}, year = {2020}, abstract = {

In this work we deal with parametrized time dependent optimal control problems governed by partial differential equations. We aim at extending the standard saddle point framework of steady constraints to time dependent cases. We provide an analysis of the well-posedness of this formulation both for parametrized scalar parabolic constraint and Stokes governing equations and we propose reduced order methods as an effective strategy to solve them. Indeed, on one hand, parametrized time dependent optimal control is a very powerful mathematical model which is able to describe several physical phenomena, on the other, it requires a huge computational effort. Reduced order methods are a suitable approach to have rapid and accurate simulations. We rely on POD{\textendash}Galerkin reduction over the physical and geometrical parameters of the optimality system in a space-time formulation. Our theoretical results and our methodology are tested on two examples: a boundary time dependent optimal control for a Graetz flow and a distributed optimal control governed by time dependent Stokes equations. With these two test cases the convenience of the reduced order modelling is further extended to the field of time dependent optimal control.

}, doi = {10.1007/s10915-020-01232-x}, author = {Maria Strazzullo and F. Ballarin and Gianluigi Rozza} } @article {2020, title = {Projection-based reduced order models for a cut finite element method in parametrized domains}, journal = {Computers and Mathematics with Applications}, volume = {79}, year = {2020}, pages = {833-851}, abstract = {

This work presents a reduced order modeling technique built on a high fidelity embedded mesh finite element method. Such methods, and in particular the CutFEM method, are attractive in the generation of projection-based reduced order models thanks to their capabilities to seamlessly handle large deformations of parametrized domains and in general to handle topological changes. The combination of embedded methods and reduced order models allows us to obtain fast evaluation of parametrized problems, avoiding remeshing as well as the reference domain formulation, often used in the reduced order modeling for boundary fitted finite element formulations. The resulting novel methodology is presented on linear elliptic and Stokes problems, together with several test cases to assess its capability. The role of a proper extension and transport of embedded solutions to a common background is analyzed in detail.

}, doi = {10.1016/j.camwa.2019.08.003}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85070900852\&doi=10.1016\%2fj.camwa.2019.08.003\&partnerID=40\&md5=2d222ab9c7832955d155655d3c93e1b1}, author = {Efthymios N Karatzas and F. Ballarin and Gianluigi Rozza} } @article {2020, title = {Reduced order methods for parametric optimal flow control in coronary bypass grafts, toward patient-specific data assimilation}, journal = {International Journal for Numerical Methods in Biomedical EngineeringInternational Journal for Numerical Methods in Biomedical EngineeringInt J Numer Meth Biomed Engng}, volume = {n/a}, year = {2020}, month = {2020/05/27}, pages = {e3367}, abstract = {

Abstract Coronary artery bypass grafts (CABG) surgery is an invasive procedure performed to circumvent partial or complete blood flow blockage in coronary artery disease. In this work, we apply a numerical optimal flow control model to patient-specific geometries of CABG, reconstructed from clinical images of real-life surgical cases, in parameterized settings. The aim of these applications is to match known physiological data with numerical hemodynamics corresponding to different scenarios, arisen by tuning some parameters. Such applications are an initial step toward matching patient-specific physiological data in patient-specific vascular geometries as best as possible. Two critical challenges that reportedly arise in such problems are: (a) lack of robust quantification of meaningful boundary conditions required to match known data as best as possible and (b) high computational cost. In this work, we utilize unknown control variables in the optimal flow control problems to take care of the first challenge. Moreover, to address the second challenge, we propose a time-efficient and reliable computational environment for such parameterized problems by projecting them onto a low-dimensional solution manifold through proper orthogonal decomposition-Galerkin.

}, keywords = {coronary artery bypass grafts, data assimilation, flow control, Galerkin methods, hemodynamics modeling, Optimization, patient-specific simulations, Proper orthogonal decomposition, reduced order methods}, isbn = {2040-7939}, doi = {https://doi.org/10.1002/cnm.3367}, url = {https://onlinelibrary.wiley.com/doi/10.1002/cnm.3367?af=R}, author = {Zakia Zainib and F. Ballarin and Stephen E. Fremes and Piero Triverio and Laura Jim{\'e}nez-Juan and Gianluigi Rozza} } @article {2020, title = {Stabilized reduced basis methods for parametrized steady Stokes and Navier{\textendash}Stokes equations}, journal = {Computers and Mathematics with Applications}, volume = {80}, year = {2020}, pages = {2399-2416}, abstract = {

It is well known in the Reduced Basis approximation of saddle point problems that the Galerkin projection on the reduced space does not guarantee the inf{\textendash}sup approximation stability even if a stable high fidelity method was used to generate snapshots. For problems in computational fluid dynamics, the lack of inf{\textendash}sup stability is reflected by the inability to accurately approximate the pressure field. In this context, inf{\textendash}sup stability is usually recovered through the enrichment of the velocity space with suitable supremizer functions. The main goal of this work is to propose an alternative approach, which relies on the residual based stabilization techniques customarily employed in the Finite Element literature, such as Brezzi{\textendash}Pitkaranta, Franca{\textendash}Hughes, streamline upwind Petrov{\textendash}Galerkin, Galerkin Least Square. In the spirit of offline{\textendash}online reduced basis computational splitting, two such options are proposed, namely offline-only stabilization and offline{\textendash}online stabilization. These approaches are then compared to (and combined with) the state of the art supremizer enrichment approach. Numerical results are discussed, highlighting that the proposed methodology allows to obtain smaller reduced basis spaces (i.e., neglecting supremizer enrichment) for which a modified inf{\textendash}sup stability is still preserved at the reduced order level.

}, doi = {10.1016/j.camwa.2020.03.019}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85083340115\&doi=10.1016\%2fj.camwa.2020.03.019\&partnerID=40\&md5=7ace96eee080701acb04d8155008dd7d}, author = {Shafqat Ali and F. Ballarin and Gianluigi Rozza} } @article {2019, title = {A POD-selective inverse distance weighting method for fast parametrized shape morphing}, journal = {International Journal for Numerical Methods in Engineering}, volume = {117}, year = {2019}, pages = {860-884}, abstract = {

Efficient shape morphing techniques play a crucial role in the approximation of partial differential equations defined in parametrized domains, such as for fluid-structure interaction or shape optimization problems. In this paper, we focus on inverse distance weighting (IDW) interpolation techniques, where a reference domain is morphed into a deformed one via the displacement of a set of control points. We aim at reducing the computational burden characterizing a standard IDW approach without significantly compromising the accuracy. To this aim, first we propose an improvement of IDW based on a geometric criterion that automatically selects a subset of the original set of control points. Then, we combine this new approach with a dimensionality reduction technique based on a proper orthogonal decomposition of the set of admissible displacements. This choice further reduces computational costs. We verify the performances of the new IDW techniques on several tests by investigating the trade-off reached in terms of accuracy and efficiency.

}, doi = {10.1002/nme.5982}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85056396233\&doi=10.1002\%2fnme.5982\&partnerID=40\&md5=6aabcbdc9a0da25e36575a0ebfac034f}, author = {F. Ballarin and A. D{\textquoteright}Amario and Simona Perotto and Gianluigi Rozza} } @article {2019, title = {A reduced order variational multiscale approach for turbulent flows}, journal = {Advances in Computational Mathematics}, volume = {45}, year = {2019}, pages = {2349-2368}, abstract = {

The purpose of this work is to present different reduced order model strategies starting from full order simulations stabilized using a residual-based variational multiscale (VMS) approach. The focus is on flows with moderately high Reynolds numbers. The reduced order models (ROMs) presented in this manuscript are based on a POD-Galerkin approach. Two different reduced order models are presented, which differ on the stabilization used during the Galerkin projection. In the first case, the VMS stabilization method is used at both the full order and the reduced order levels. In the second case, the VMS stabilization is used only at the full order level, while the projection of the standard Navier-Stokes equations is performed instead at the reduced order level. The former method is denoted as consistent ROM, while the latter is named non-consistent ROM, in order to underline the different choices made at the two levels. Particular attention is also devoted to the role of inf-sup stabilization by means of supremizers in ROMs based on a VMS formulation. Finally, the developed methods are tested on a numerical benchmark.

}, doi = {10.1007/s10444-019-09712-x}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85068076665\&doi=10.1007\%2fs10444-019-09712-x\&partnerID=40\&md5=af0142e6d13bbc2e88c6f31750aef6ad}, author = {Giovanni Stabile and F. Ballarin and G. Zuccarino and Gianluigi Rozza} } @article {2019, title = {A Weighted POD Method for Elliptic PDEs with Random Inputs}, journal = {Journal of Scientific Computing}, volume = {81}, year = {2019}, pages = {136-153}, abstract = {

In this work we propose and analyze a weighted proper orthogonal decomposition method to solve elliptic partial differential equations depending on random input data, for stochastic problems that can be transformed into parametric systems. The algorithm is introduced alongside the weighted greedy method. Our proposed method aims to minimize the error in a L2 norm and, in contrast to the weighted greedy approach, it does not require the availability of an error bound. Moreover, we consider sparse discretization of the input space in the construction of the reduced model; for high-dimensional problems, provided the sampling is done accordingly to the parameters distribution, this enables a sensible reduction of computational costs, while keeping a very good accuracy with respect to high fidelity solutions. We provide many numerical tests to assess the performance of the proposed method compared to an equivalent reduced order model without weighting, as well as to the weighted greedy approach, in both low and high dimensional problems.

}, doi = {10.1007/s10915-018-0830-7}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85053798049\&doi=10.1007\%2fs10915-018-0830-7\&partnerID=40\&md5=5cad501b6ef1955da55868807079ee5d}, author = {L.Venturi and F. Ballarin and Gianluigi Rozza} } @article {2019, title = {Weighted Reduced Order Methods for Parametrized Partial Differential Equations with Random Inputs}, journal = {PoliTO Springer Series}, year = {2019}, pages = {27-40}, abstract = {

In this manuscript we discuss weighted reduced order methods for stochastic partial differential equations. Random inputs (such as forcing terms, equation coefficients, boundary conditions) are considered as parameters of the equations. We take advantage of the resulting parametrized formulation to propose an efficient reduced order model; we also profit by the underlying stochastic assumption in the definition of suitable weights to drive to reduction process. Two viable strategies are discussed, namely the weighted reduced basis method and the weighted proper orthogonal decomposition method. A numerical example on a parametrized elasticity problem is shown.

}, doi = {10.1007/978-3-030-04870-9_2}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85084009379\&doi=10.1007\%2f978-3-030-04870-9_2\&partnerID=40\&md5=446bcc1f331167bbba67bc00fb170150}, author = {L. Venturi and D. Torlo and F. Ballarin and Gianluigi Rozza} } @inbook {tezzele2018combined, title = {Combined parameter and model reduction of cardiovascular problems by means of active subspaces and POD-Galerkin methods}, booktitle = {Mathematical and Numerical Modeling of the Cardiovascular System and Applications}, year = {2018}, pages = {185{\textendash}207}, publisher = {Springer}, organization = {Springer}, author = {Marco Tezzele and F. Ballarin and Gianluigi Rozza} } @article {doi:10.1137/17M1150591, title = {Model Reduction for Parametrized Optimal Control Problems in Environmental Marine Sciences and Engineering}, journal = {SIAM Journal on Scientific Computing}, volume = {40}, number = {4}, year = {2018}, pages = {B1055-B1079}, doi = {10.1137/17M1150591}, url = {https://doi.org/10.1137/17M1150591}, author = {Maria Strazzullo and F. Ballarin and Mosetti, R. and Gianluigi Rozza} } @article {2018, title = {Stabilized weighted reduced basis methods for parametrized advection dominated problems with random inputs}, journal = {SIAM-ASA Journal on Uncertainty Quantification}, volume = {6}, year = {2018}, pages = {1475-1502}, abstract = {

In this work, we propose viable and eficient strategies for stabilized parametrized advection dominated problems, with random inputs. In particular, we investigate the combination of the wRB (weighted reduced basis) method for stochastic parametrized problems with the stabilized RB (reduced basis) method, which is the integration of classical stabilization methods (streamline/upwind Petrov-Galerkin (SUPG) in our case) in the ofine-online structure of the RB method. Moreover, we introduce a reduction method that selectively enables online stabilization; this leads to a sensible reduction of computational costs, while keeping a very good accuracy with respect to high-fdelity solutions. We present numerical test cases to assess the performance of the proposed methods in steady and unsteady problems related to heat transfer phenomena.

}, doi = {10.1137/17M1163517}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85058246502\&doi=10.1137\%2f17M1163517\&partnerID=40\&md5=6c54e2f0eb727cb85060e988486b8ac8}, author = {D. Torlo and F. Ballarin and Gianluigi Rozza} } @article {2017, title = {On a certified smagorinsky reduced basis turbulence model}, journal = {SIAM Journal on Numerical Analysis}, volume = {55}, year = {2017}, pages = {3047-3067}, doi = {10.1137/17M1118233}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85039928218\&doi=10.1137\%2f17M1118233\&partnerID=40\&md5=221d9cd2bcc74121fcef93efd9d3d76c}, author = {Rebollo, T.C. and E.D. {\'A}vila and Marmol, M.G. and F. Ballarin and Gianluigi Rozza} } @article {2017, title = {Numerical modeling of hemodynamics scenarios of patient-specific coronary artery bypass grafts}, journal = {Biomechanics and Modeling in Mechanobiology}, volume = {16}, year = {2017}, pages = {1373-1399}, doi = {10.1007/s10237-017-0893-7}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85015065851\&doi=10.1007\%2fs10237-017-0893-7\&partnerID=40\&md5=c388f20bd5de14187bad9ed7d9affbd0}, author = {F. Ballarin and Elena Faggiano and Andrea Manzoni and Alfio Quarteroni and Gianluigi Rozza and Sonia Ippolito and Roberto Scrofani} } @inbook {BallarinRozzaMaday2017, title = {Reduced-order semi-implicit schemes for fluid-structure interaction problems}, booktitle = {Model Reduction of Parametrized Systems}, year = {2017}, pages = {149{\textendash}167}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, chapter = {Reduced-order semi-implicit schemes for fluid-structure interaction problems}, abstract = {

POD{\textendash}Galerkin reduced-order models (ROMs) for fluid-structure interaction problems (incompressible fluid and thin structure) are proposed in this paper. Both the high-fidelity and reduced-order methods are based on a Chorin-Temam operator-splitting approach. Two different reduced-order methods are proposed, which differ on velocity continuity condition, imposed weakly or strongly, respectively. The resulting ROMs are tested and compared on a representative haemodynamics test case characterized by wave propagation, in order to assess the capabilities of the proposed strategies.

}, doi = {10.1007/978-3-319-58786-8_10}, author = {F. Ballarin and Gianluigi Rozza and Yvon Maday}, editor = {Peter Benner and Mario Ohlberger and Anthony Patera and Gianluigi Rozza and Karsten Urban} } @conference {2016, title = {Advances in geometrical parametrization and reduced order models and methods for computational fluid dynamics problems in applied sciences and engineering: overview and perspectives}, booktitle = {Proceedings of the ECCOMAS Congress 2016, VII European Conference on Computational Methods in Applied Sciences and Engineering,}, year = {2016}, month = {06/2016}, publisher = {ECCOMAS}, organization = {ECCOMAS}, address = {Crete, Greece}, abstract = {

Several problems in applied sciences and engineering require reduction techniques in order to allow computational tools to be employed in the daily practice, especially in iterative procedures such as optimization or sensitivity analysis. Reduced order methods need to face increasingly complex problems in computational mechanics, especially into a multiphysics setting. Several issues should be faced: stability of the approximation, efficient treatment of nonlinearities, uniqueness or possible bifurcations of the state solutions, proper coupling between fields, as well as offline-online computing, computational savings and certification of errors as measure of accuracy. Moreover, efficient geometrical parametrization techniques should be devised to efficiently face shape optimization problems, as well as shape reconstruction and shape assimilation problems. A related aspect deals with the management of parametrized interfaces in multiphysics problems, such as fluid-structure interaction problems, and also a domain decomposition based approach for complex parametrized networks. We present some illustrative industrial and biomedical problems as examples of recent advances on methodological developments.

}, author = {Filippo Salmoiraghi and F. Ballarin and Giovanni Corsi and Andrea Mola and Marco Tezzele and Gianluigi Rozza}, editor = {Papadrakakis, M. and Papadopoulos, V. and Stefanou, G. and Plevris, V.} } @article {2016, title = {A fast virtual surgery platform for many scenarios haemodynamics of patient-specific coronary artery bypass grafts}, year = {2016}, institution = {Submitted}, abstract = {A fast computational framework is devised to the study of several configurations of patient-specific coronary artery bypass grafts. This is especially useful to perform a sensitivity analysis of the haemodynamics for different flow conditions occurring in native coronary arteries and bypass grafts, the investigation of the progression of the coronary artery disease and the choice of the most appropriate surgical procedure. A complete pipeline, from the acquisition of patientspecific medical images to fast parametrized computational simulations, is proposed. Complex surgical configurations employed in the clinical practice, such as Y-grafts and sequential grafts, are studied. A virtual surgery platform based on model reduction of unsteady Navier Stokes equations for blood dynamics is proposed to carry out sensitivity analyses in a very rapid and reliable way. A specialized geometrical parametrization is employed to compare the effect of stenosis and anastomosis variation on the outcome of the surgery in several relevant cases.}, url = {http://urania.sissa.it/xmlui/handle/1963/35240}, author = {F. Ballarin and Elena Faggiano and Andrea Manzoni and Gianluigi Rozza and Alfio Quarteroni and Sonia Ippolito and Roberto Scrofani and Carlo Antona} } @article {2016, title = {Isogeometric analysis-based reduced order modelling for incompressible linear viscous flows in parametrized shapes}, number = {AMOS Advanced Modelling and Simulation in Engineering Sciences}, year = {2016}, institution = {Springer, AMOS Advanced Modelling and Simulation in Engineering Sciences}, abstract = {In this work we provide a combination of isogeometric analysis with reduced order modelling techniques, based on proper orthogonal decomposition, to guarantee computational reduction for the numerical model, and with free-form deformation, for versatile geometrical parametrization. We apply it to computational fluid dynamics problems considering a Stokes flow model. The proposed reduced order model combines efficient shape deformation and accurate and stable velocity and pressure approximation for incompressible viscous flows, computed with a reduced order method. Efficient offine-online computational decomposition is guaranteed in view of repetitive calculations for parametric design and optimization problems. Numerical test cases show the efficiency and accuracy of the proposed reduced order model.}, url = {http://urania.sissa.it/xmlui/handle/1963/35199}, author = {Filippo Salmoiraghi and F. Ballarin and Luca Heltai and Gianluigi Rozza} } @article {11943, title = {POD{\textendash}Galerkin monolithic reduced order models for parametrized fluid-structure interaction problems}, journal = {International Journal Numerical Methods for Fluids}, year = {2016}, publisher = {Wiley}, abstract = {In this paper we propose a monolithic approach for reduced order modelling of parametrized fluid-structure interaction problems based on a proper orthogonal decomposition (POD){\textendash}Galerkin method. Parameters of the problem are related to constitutive properties of the fluid or structural problem, or to geometrical parameters related to the domain configuration at the initial time. We provide a detailed description of the parametrized formulation of the multiphysics problem in its components, together with some insights on how to obtain an offline-online efficient computational procedure through the approximation of parametrized nonlinear tensors. Then, we present the monolithic POD{\textendash}Galerkin method for the online computation of the global structural displacement, fluid velocity and pressure of the coupled problem. Finally, we show some numerical results to highlight the capabilities of the proposed reduced order method and its computational performances}, doi = {10.1002/fld.4252}, author = {F. Ballarin and Gianluigi Rozza} } @article {2015, title = {Fast simulations of patient-specific haemodynamics of coronary artery bypass grafts based on a POD-Galerkin method and a vascular shape parametrization}, year = {2015}, abstract = {In this work a reduced-order computational framework for the study of haemodynamics in three-dimensional patient-specific configurations of coronary artery bypass grafts dealing with a wide range of scenarios is proposed. We combine several efficient algorithms to face at the same time both the geometrical complexity involved in the description of the vascular network and the huge computational cost entailed by time dependent patient-specific flow simulations. Medical imaging procedures allow to reconstruct patient-specific configurations from clinical data. A centerlines-based parametrization is proposed to efficiently handle geometrical variations. POD{\textendash}Galerkin reduced-order models are employed to cut down large computational costs. This computational framework allows to characterize blood flows for different physical and geometrical variations relevant in the clinical practice, such as stenosis factors and anastomosis variations, in a rapid and reliable way. Several numerical results are discussed, highlighting the computational performance of the proposed framework, as well as its capability to perform sensitivity analysis studies, so far out of reach.}, url = {http://urania.sissa.it/xmlui/handle/1963/34623}, author = {F. Ballarin and Elena Faggiano and Sonia Ippolito and Andrea Manzoni and Alfio Quarteroni and Gianluigi Rozza and Roberto Scrofani} } @article {2015, title = {Supremizer stabilization of POD-Galerkin approximation of parametrized Navier-Stokes equations}, number = {International Journal for Numerical Methods in Engineering;Volume 102, issue 5; pp.1136-1161;}, year = {2015}, publisher = {Wiley}, abstract = {In this work, we present a stable proper orthogonal decomposition{\textendash}Galerkin approximation for parametrized steady incompressible Navier{\textendash}Stokes equations with low Reynolds number.}, doi = {10.1002/nme.4772}, url = {http://urania.sissa.it/xmlui/handle/1963/34701}, author = {F. Ballarin and Andrea Manzoni and Alfio Quarteroni and Gianluigi Rozza} } @article {2014, title = {Shape Optimization by Free-Form Deformation: Existence Results and Numerical Solution for Stokes Flows}, number = {Journal of scientific computing;volume 60; issue 3; pages 537-563;}, year = {2014}, publisher = {Springer}, abstract = {Shape optimization problems governed by PDEs result from many applications in computational fluid dynamics. These problems usually entail very large computational costs and require also a suitable approach for representing and deforming efficiently the shape of the underlying geometry, as well as for computing the shape gradient of the cost functional to be minimized. Several approaches based on the displacement of a set of control points have been developed in the last decades, such as the so-called free-form deformations. In this paper we present a new theoretical result which allows to recast free-form deformations into the general class of perturbation of identity maps, and to guarantee the compactness of the set of admissible shapes. Moreover, we address both a general optimization framework based on the continuous shape gradient and a numerical procedure for solving efficiently three-dimensional optimal design problems. This framework is applied to the optimal design of immersed bodies in Stokes flows, for which we consider the numerical solution of a benchmark case study from literature.}, doi = {10.1007/s10915-013-9807-8}, url = {http://urania.sissa.it/xmlui/handle/1963/34698}, author = {F. Ballarin and Andrea Manzoni and Gianluigi Rozza and Sandro Salsa} }