Quaderni MOX
Pubblicazioni
del Laboratorio di Modellistica e Calcolo Scientifico MOX. I lavori riguardano prevalentemente il campo dell'analisi numerica, della statistica e della modellistica matematica applicata a problemi di interesse ingegneristico. Il sito del Laboratorio MOX è raggiungibile
all'indirizzo mox.polimi.it
Trovati 1153 prodotti
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06/2023 - 06/02/2023
Artoni, A.; Antonietti, P. F.; Mazzieri, I.; Parolini, N.; Rocchi, D.
A segregated finite volume - spectral element method for aeroacoustic problems | Abstract | | We propose a segregated Finite Volume (FV) - Spectral Element Method (SEM) for modelling aeroacoustic phenomena based on the Lighthill's acoustic analogy. First the fluid solution is computed employing a FV method. Then, the sound source term is projected onto the acoustic grid and the inhomogeneous Lighthill's wave equation is solved employing the SEM. The novel projection method computes offline the intersections between the acoustic and the fluid grids in order to preserve the accuracy. The proposed intersection algorithm is shown to be robust, scalable and able to efficiently compute the geometric intersection of arbitrary polyhedral elements.
We then analyse the properties of the projection error and we numerically assess the obtained theoretical estimates. Finally, we address two relevant aeroacoustic benchmarks, namely the corotating vortex pair and the noise induced by a laminar flow around a squared cylinder, to demonstrate in practice the effectiveness of the proposed approach. The flow computations are performed with OpenFOAM , an open-source finite volume library, while the inhomogeneous Lighthill's wave equation is solved with SPEED, an open-source spectral element library. |
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05/2023 - 14/01/2023
Fumagalli, I.; Vergara, C.
Novel approaches for the numerical solution of fluid-structure interaction in the aorta | Abstract | | The aorta is the artery that undergoes the most deformation during the heartbeat. This is associated with the strong Fluid-Structure Interaction (FSI) occurring between the blood flow and the aortic wall. Moreover, also the dynamics of the aortic valve is the result of a FSI process. In this work, we describe the mathematical formulation of both vascular and valve FSI problems and we review the most recent numerical strategies for their solution. Concerning vascular FSI, we consider a moving-domain approach encompassing an arbitrary Lagrangian-Eulerian formulation of the fluid equations, which is the most employed framework in hemodynamics applications. In this context, we provide a systematic description and comparison of different algorithms for the coupling between the fluid and the structure model. In terms of valve FSI, we report a survey on the different numerical methods for the treatment of surfaces immersed and moving in a fluid, with particular focus on unfitted methods, which are the most established for cardiac valve modeling, and the more recent promising family of Cut Finite Elements methods.
Aiming to point out the main difficulties specifically related to aortic FSI simulation in a patient-specific context, we also review strategies for the imposition of boundary conditions, the recovery of a zero-pressure configuration of the vessel wall, and the calibration and validation of computational models against clinical data. |
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04/2023 - 10/01/2023
Quarteroni, A.; Dede’, L.; Regazzoni, F.; Vergara, C.
A mathematical model of the human heart suitable to address clinical problems | Abstract | | In this paper, we present a mathematical model capable of simulating
the human cardiac function. We review the basic equations of the
model, their coupling, the numerical approach for the computer solution of this mathematical model, and a few examples of application to specific problems of clinical interest. |
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03/2023 - 05/01/2023
Africa, P.C.; Perotto, S.; de Falco, C.
Scalable Recovery-based Adaptation on Quadtree Meshes for Advection-Diffusion-Reaction Problems | Abstract | | We propose a mesh adaptation procedure for Cartesian quadtree meshes, to discretize scalar advection-diffusion-reaction problems.
The adaptation process is
driven by a recovery-based a posteriori estimator for the L^2-norm of the discretization error, based on suitable higher order approximations of both the solution and the associated gradient. In particular, a metric-based approach exploits the information furnished by the estimator to iteratively predict the new adapted mesh.
The new mesh adaptation algorithm is successfully assessed on different configurations, and turns out to perform well also when dealing with discontinuities in the data as well as in the presence of internal layers not
aligned with the Cartesian directions.
A cross-comparison with a standard
estimate--mark--refine approach and with other adaptive strategies available in the literature shows the remarkable accuracy and parallel scalability
of the proposed approach. |
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02/2023 - 05/01/2023
Boon, W. M.; Fumagalli, A.; Scotti, A.
Mixed and multipoint finite element methods for rotation-based poroelasticity | Abstract | | This work proposes a mixed finite element method for the Biot poroelasticity equations that employs the lowest-order Raviart-Thomas finite element space for the solid displacement and piecewise constants for the fluid pressure. The method is based on the formulation of linearized elasticity as a weighted vector Laplace problem. By introducing the solid rotation and fluid flux as auxiliary variables, we form a four-field formulation of the Biot system, which is discretized using conforming mixed finite element spaces. The auxiliary variables are subsequently removed from the system in a local hybridization technique to obtain a multipoint rotation-flux mixed finite element method. Stability and convergence of the four-field and multipoint mixed finite element methods are shown in terms of weighted norms, which additionally leads to parameter-robust preconditioners. Numerical experiments confirm the theoretical results. |
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01/2023 - 05/01/2023
Zingaro, A.; Bucelli, M.; Piersanti, R.; Regazzoni, F.; Dede', L.; Quarteroni, A.
An electromechanics-driven fluid dynamics model for the simulation of the whole human heart | Abstract | | We introduce a multiphysics and geometric multiscale computational model, suitable to describe the hemodynamics of the whole human heart, driven by a four-chamber electromechanical model. We first present a study on the calibration of the biophysically detailed RDQ20 activation model (Regazzoni et al., 2020) that is able to reproduce the physiological range of hemodynamic biomarkers. Then, we demonstrate that the ability of the force generation model to reproduce certain microscale mechanisms, such as the dependence of force on fiber shortening velocity, is crucial to capture the overall physiological mechanical and fluid dynamics macroscale behavior. This motivates the need for using multiscale models with high biophysical fidelity, even when the outputs of interest are relative to the macroscale. We show that the use of a high-fidelity electromechanical model, combined with a detailed calibration process, allows us to achieve a remarkable biophysical fidelity in terms of both mechanical and hemodynamic quantities. Indeed, our electromechanical-driven CFD simulations -- carried out on an anatomically accurate geometry of the whole heart -- provide results that match the cardiac physiology both qualitatively (in terms of flow patterns) and quantitatively (when comparing in silico results with biomarkers acquired in vivo). Moreover, we consider the pathological case of left bundle branch block, and we investigate the consequences that an electrical abnormality has on cardiac hemodynamics thanks to our multiphysics integrated model. The computational model that we propose can faithfully predict a delay and an increasing wall shear stress in the left ventricle in the pathological condition. The interaction of different physical processes in an integrated framework allows us to faithfully describe and model this pathology, by capturing and reproducing the intrinsic multiphysics nature of the human heart. |
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85/2022 - 28/11/2022
Lurani Cernuschi , A.; Masci, C.; Corso, F.; Muccini, C.; Ceccarelli, D.; San Raffaele Hospital Galli, L.; Ieva, F.; Paganoni, A.M.; Castagna, A.
A neural network approach to survival analysis for modelling time to cardiovascular diseases in HIV patients with longitudinal observations | Abstract | | At the end of 2021, 38.4 million People were Living With HIV (PLWH)
worldwide. The advent of Anti Retroviral Therapy (ART) has significantly reduced the mortality and increased life expectancy of PLWH. Nowadays, the management of people with HIV on virological suppression is partly focused on the onset of comorbidities, such as the occurrence of CardioVascular Diseases (CVDs). In this study, we analyse the 15-year CVD risk in PLWH, following a survival analysis approach based on Neural Networks (NNs). We adopt a NN-based deep learning approach to flexibly model and predict the time to a CVD event, relaxing the linearity
and the proportional-hazard assumptions typical of the COX model and
including time-varying features. Results of this approach are compared
to the ones obtained via more classical survival analysis methods, both
in terms of predictive performance and interpretability, in order to
explore the potential of deep learning approaches in modelling survival
data with time-varying features. |
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84/2022 - 28/11/2022
Ciaramella, G.; Gambarini, M.; Miglio, E.
A preconditioner for free-surface hydrodynamics BEM | Abstract | | A preconditioner for the boundary element method applied to linear hydrodynamics is proposed. In particular, the problem of computing wave loads on large arrays of floating objects using a source-distribution BEM is considered. The preconditioner is based on block-Jacobi iterations combined with a coarse correction. Each vector of the coarse space is constant on the surface of one of the bodies, and zero on the others. An algorithm for the efficient construction of the coarse space using hierarchical matrices is presented. The method is implemented by integration with the hierarchical matrices interface of an existing BEM code. In combination with GMRES, scalability in terms of number of iterations is achieved and demonstrated by extensive numerical experiments. |
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