On the identification of bridge decks aeroelastic coefficients: the covariance block hankel matrix method

Il seguente elaborato si concentra sull'identifi�cazione strutturale di sistemi soggetti a sollecitazioni aeroelastiche e nello speci�fico l'attenzione viene rivolta ad impalcati da ponte. Si analizzano i concetti principali caratterizzanti il campo dell'aeroelasticità indagando i fattori dominanti che entrano in gioco sul piano teorico. In seguito, si considera il metodo di identifi�cazione strutturale chiamato Covariance Block Hankel Matrix (CBHM) utilizzato come strumento di derivazione dei coeffi�cienti aeroelastici propri della struttura. Infi�ne, si indaga il comportamento di questo metodo di identi�ficazione al variare di una serie di parametri chiave e all'interno di diversi scenari, visionando risultati ottenuti tramite una serie di test eff�ettuati per provare l'a�dattabilità del metodo stesso al variare delle condizioni che caratterizzano il sistema.

Testing of subgrid scale (SGS) models for large-eddy simulation (LES) of turbulent channel flow

Sub-grid scale (SGS) models are required in order to model the influence of the unresolved small scales on the resolved scales in large-eddy simulations (LES), the flow at the smallest scales of turbulence. In the following work two SGS models are presented and deeply analyzed in terms of accuracy through several LESs with different spatial resolutions, i.e. grid spacings. The first part of this thesis focuses on the basic theory of turbulence, the governing equations of fluid dynamics and their adaptation to LES. Furthermore, two important SGS models are presented: one is the Dynamic eddy-viscosity model (DEVM), developed by \cite{germano1991dynamic}, while the other is the Explicit Algebraic SGS model (EASSM), by \cite{marstorp2009explicit}. In addition, some details about the implementation of the EASSM in a Pseudo-Spectral Navier-Stokes code \cite{chevalier2007simson} are presented. The performance of the two aforementioned models will be investigated in the following chapters, by means of LES of a channel flow, with friction Reynolds numbers $Re_\tau=590$ up to $Re_\tau=5200$, with relatively coarse resolutions. Data from each simulation will be compared to baseline DNS data. Results have shown that, in contrast to the DEVM, the EASSM has promising potentials for flow predictions at high friction Reynolds numbers: the higher the friction Reynolds number is the better the EASSM will behave and the worse the performances of the DEVM will be. The better performance of the EASSM is contributed to the ability to capture flow anisotropy at the small scales through a correct formulation for the SGS stresses. Moreover, a considerable reduction in the required computational resources can be achieved using the EASSM compared to DEVM. Therefore, the EASSM combines accuracy and computational efficiency, implying that it has a clear potential for industrial CFD usage.