Direttore Vicario: Prof. Gabriele Grillo
Responsabile Gestionale: Dr.ssa Franca Di Censo


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Parola da cercare

Prossimi Seminari

  • Nonintrusive reduced order models using physics informed neural networks
    Jan S. Hesthaven, Chair of Computational Mathematics and Simulation Science, EPFL, Lausanne, CH
    giovedì 29 ottobre 2020 alle ore 14:00 precise, Online seminar:

Seminari Passati

  • Partial Differential Equations with Uncertainty: the Stochastic input case
    Raul Tempone, ICES, University of Texas at Austin
    lunedì 24 gennaio 2005 alle ore 14:30, Aula Seminari MOX - 6° piano dip di matematica
    The main aim of applied numerical simulations is to derive predictions. Since these predictions are the basis for decision making it is natural to question their accuracy, specially because in most of the cases there is uncertainty in data of the problem to solve.

    We consider numerical approximations of partial differential equations (PDE) with stochastic coefficients, which is one way to address uncertainty quantification for PDEs.

    We discuss efficient discretization strategies, give convergence results and present numerical results.
  • Economia ed Ambiente: lo sviluppo sostenibile
    G. Caiati, Univ. di Milano
    mercoledì 19 gennaio 2005 alle ore 12:30, aula T2.2
  • Some well-balanced Finite Volume solvers for Shallow Water Equations
    Tomás Chacón Rebollo, Universidad de Sevilla
    martedì 18 gennaio 2005 alle ore 11:00, Aula Seminari MOX-6° piano dip mat.
    The accurate computation of stationary solutions of hyperbolic systems with source terms has been found in the past years as closely related to the accurate computation of transient solutions. Numerical solvers that do not solve steady solutions up to second order, at least, yield transient solutions that present large errors that grow as time increases, unacceptable from the physical point of view.

    These solvers are called “well-balanced”, as the flow and source terms must balance each other, up to high precision, for steady solutions.This talk focus on the systematic derivation of numerical schemes satisfying this property.

    Starting from standard Finite Volume solvers that can be written in viscous form, we shall derive associated well-balanced solvers in a specific way: These compute all steady solutions up to second order, in all the domain but on a subdomain whose measure vanishes as the grid size goes to zero.

    We shall apply these solvers to Shallow Water equations with variable bottom and friction effects. In particular we shall present a numerical simulation of the toxic waste due to the breaking of Aznalcóllar mine pond in 1998.
  • Tecniche a basi ridotte per l'ottimizzazione in emodinamica
    Gianluigi Rozza, EPFL
    lunedì 17 gennaio 2005 alle ore 14:00, Aula Seminari MOX-6° piano dip di matematica
    In questo seminario viene descritto il metodo a basi ridotte per le equazioni di
    Stokes in domini parametrizzati, utilizzato per approssimare flussi sanguigni in
    un bypass coronarico. Lo scopo e' fornire (a) un'analisi di sensitivita' per
    grandezze geometriche rilevanti nelle configurazioni di bypass e (b) rapide e
    affidabili previsioni del comportamento di certe grandezze di interesse (indici
    di merito fluidodinamici legati per esempio a sforzi e vorticita').
    Le linee guida della ricerca vogliono (i) fornire indicazioni di progettazione
    per futuri bypass bioartificiali; (ii) sviluppare metodi nuemrici di
    ottimizzazione in biomeccanica e (iii) fornire una relazione input-output
    costituita da modelli con una complessita' e un costo computazionale piu' basso
    rispetto alla soluzione completa delle equazioni della meccanica dei fluidi
    tramite un metodo classico a elementi finiti.
    PDE parametrizzate, problema di Stokes generalizzato, metodi a basi ridotte,
    ottimizzazione di bypass, emodinamica.
  • Un viaggio attraverso la biologia computazionale
    G. Lancia, Univ. di Udine
    mercoledì 12 gennaio 2005 alle ore 12:30, aula T2.2
  • High Order Reconstruction Methods for Piecewise Smooth Functions
    Anne Gelb, Arizona state university
    giovedì 16 dicembre 2004 alle ore 11:30, Aula Seminari MOX - 6° piano dip. di Matematica
    It is well known that while spectral methods yield exponentially convergent approximations for smooth functions, the results for piecewise smooth functions are poor, with spurious oscillations developing near the discontinuities and a much reduced overall convergence rate. This behavior, known as the Gibbs phenomenon, is considered as one of the major drawbacks in the application of spectral methods. Specifically, unlike standard filtering, the convergence does not deteriorate as the discontinuities area approached. The most familar ad easily analyzed spectral reprojection method is the Gegenbauer reconstruction method. However it is apparent that the Gegenbauer reconstruction method is not robust and in particular it suffer from round off error. Methods to alleviate these difficulties have been recently developed. All high order recontruction methods require a-priori knowledge of the jump discontinuity locations, since these edges determine the intervarls of smoothness in which the spectral reprojection reconstruction method can be applied. The local edge detection method has been recently been developed to determine the location of edges on scattered grid point data. It can also be applied to detect the discontinuities in the derivates of functions. In this talk I discuss recent advances in edge detection and high order reconstruction methods. Examples include applications from medical imaging, where noise is an additional impediment to the reconstruction. Other spectral reprojection methods are briefly discussed.
  • Medicina, Sport, Ecologia: la Modellistica Matematico-Numerica nella vita di tutti i giorni
    A. Veneziani, Dip. di Matematica
    mercoledì 15 dicembre 2004 alle ore 12:30, Aula B.21
  • Intersecting longest cycles and paths
    Tudor Zamfirescu, Universität Dortmund, Germany
    venerdì 10 dicembre 2004 alle ore 10:30, Dipartimento di Matematica - Politecnico di Milano