Seminari Generali IAC 2023

Questi brevi workshop sono dedicati alle attività di ricerca in matematica applicata.

I seminari generali IAC sono l'occasione per ricercatori dell'istituto e non di presentare le loro ricerche a un pubblico più vasto di quello del proprio settore di riferimento nella matematica applicata. Il linguaggio scelto non è, infatti, strettamente tecnico e si favorisce la fruizione a un pubblico più esteso, per stimolare collaborazioni interdisciplinari.

Tutti i seminari sono trasmessi in streaming sul canale Youtube dell'istituto @CNRIAC.

I seminari si tengono sempre alle ore 14:30.

Di seguito il calendario dei seminari in programma.

11 gennaio - Stefano Zaghi, ricercatore dell'IAC

Titolo "Adaptive Mesh Refinement CFD Simulations in the Exascale Era".


A discussion concerning the reasons to develop a new Adaptive Mesh Refinement (AMR) CFD library, the challenges of leveraging modern exascale supercomputers' computational resources, and the author's current failures (with some, probably negligible, progress).

25 gennaio - Adriano Tiribocchi, ricercatore dell'IAC

Titolo "Modeling the collective properties of multi-core emulsions under confinement"


Multi-core emulsions are a class of soft fluids assembled from cluster configurations of deformable oil-water double droplets (cores), often employed as building-blocks for the realisation of devices of interest in biotechnology, drug delivery and tissue engineering. We use lattice Boltzmann simulations to study the physics of multi-core emulsions flowing in microfluidic channels and report numerical evidence of a surprisingly rich variety of driven non-equilibrium states, whose formation is caused by a dipolar fluid vortex triggered by the sheared structure of the flow carrier within the microchannel. If time permits, we will also discuss the translocation dynamics of emulsion drops with multiple close-packed inner droplets flowing within constrictions. Under such conditions, these liquid architectures display a number of non-trivial features, such as permanent shape deformations and memory-like effects, of particular relevance for the design of soft porous materials.

8 febbraio - Luca Galantucci, ricercatore dell'IAC

Titolo "Dissipation anomaly in a turbulent quantum fluid"


When the intensity of turbulence is increased (by increasing the Reynolds number, e.g. by reducing the viscosity of the fluid), the rate of the dissipation of kinetic energy decreases but does not tend asymptotically to zero: it levels off to a non-zero constant as smaller and smaller vortical flow structures are generated. This fundamental property, called the dissipation anomaly, is sometimes referred to as the zeroth law of turbulence. The question of what happens in the limit of vanishing viscosity (purely hypothetical in classical fluids) acquires a particular physical significance in the context of liquid helium, a quantum fluid which becomes effectively inviscid at low temperatures achievable in the laboratory. By performing numerical simulations and identifying the superfluid Reynolds number, here we show evidence for a superfluid analogue to the classical dissipation anomaly.
Our numerics indeed show that as the superfluid Reynolds number increases, smaller and smaller structures are generated on the quantized vortex lines on which the superfluid vorticity is confined, balancing the effect of weaker and weaker dissipation.


22 febbraio - Angela Monti, IAC-Bari

Titolo "Model Order Reduction for Turing pattern approximation in reaction-diffusion PDE systems "


We investigate a suitable application of Model Order Reduction (MOR) techniques for the numerical approximation of Turing patterns, that are stationary solutions of reaction-diffusion PDE (RD-PDE) systems. We will consider in particular the Proper Orthogonal Decomposition (POD) and the Dynamic Mode Decomposition (DMD). Both techniques present inaccurate approximations, therefore we will introduce two novel algorithms that aim at stabilizing the studied problem. In the first part of the talk we focus on the stabilization of the POD-DEIM technique. We show that solutions of surrogate models built by classical POD-DEIM exhibit an unstable error behaviour over the dimension of the reduced space. To overcome this drawback, we add a correction term that provides missing information to the reduced model and we apply the POD-DEIM technique to the corrected model. To further improve the computational efficiency, we propose an adaptive version of this algorithm in time that accounts for the peculiar dynamics of the RD-PDE in presence of Turing instability. We show the effectiveness of the proposed methods in terms of accuracy and computational cost for a selection of RD-PDE systems, i.e. FitzHugh-Nagumo, Schnakenberg and the morphochemical DIB models, with increasing degree of nonlinearity and more structured patterns. In the second part we show some preliminary results regarding a new adaptive algorithm based on Dynamic Mode Decomposition (DMD). DMD is a data-diven technique that allows to find the best linear fit for a given dataset. We propose to modify the method by splitting the time interval into several subintervals to keep a certain level of accuracy. Numerical results will show the efficiency of the shown method. This is a joint work with Alessandro Alla (Università Ca’ Foscari, Venezia) and Ivonne Sgura (Università del Salento, Lecce).



Data inizio