@article {2021,
	title = {On the comparison of LES data-driven reduced order approaches for hydroacoustic analysis},
	journal = {Computers \& Fluids},
	volume = {216},
	year = {2021},
	pages = {104819},
	abstract = {<p>In this work, Dynamic Mode Decomposition (DMD) and Proper Orthogonal Decomposition (POD) methodologies are applied to hydroacoustic dataset computed using Large Eddy Simulation (LES) coupled with Ffowcs Williams and Hawkings (FWH) analogy. First, a low-dimensional description of the flow fields is presented with modal decomposition analysis. Sensitivity towards the DMD and POD bases truncation rank is discussed, and extensive dataset is provided to demonstrate the ability of both algorithms to reconstruct the flow fields with all the spatial and temporal frequencies necessary to support accurate noise evaluation. Results show that while DMD is capable to capture finer coherent structures in the wake region for the same amount of employed modes, reconstructed flow fields using POD exhibit smaller magnitudes of global spatiotemporal errors compared with DMD counterparts. Second, a separate set of DMD and POD modes generated using half the snapshots is employed into two data-driven reduced models respectively, based on DMD mid cast and POD with Interpolation (PODI). In that regard, results confirm that the predictive character of both reduced approaches on the flow fields is sufficiently accurate, with a relative superiority of PODI results over DMD ones. This infers that, discrepancies induced due to interpolation errors in PODI is relatively low compared with errors induced by integration and linear regression operations in DMD, for the present setup. Finally, a post processing analysis on the evaluation of FWH acoustic signals utilizing reduced fluid dynamic fields as input demonstrates that both DMD and PODI data-driven reduced models are efficient and sufficiently accurate in predicting acoustic noises.</p>},
	keywords = {Dynamic mode decomposition, Ffowcs Williams and Hawkings, Hydroacoustics, Large eddy simulation, Model reduction, Proper orthogonal decomposition},
	issn = {0045-7930},
	doi = {https://doi.org/10.1016/j.compfluid.2020.104819},
	url = {https://www.sciencedirect.com/science/article/pii/S0045793020303893},
	author = {Mahmoud Gadalla and Marta Cianferra and Marco Tezzele and Giovanni Stabile and Andrea Mola and Gianluigi Rozza}
}
@article {GiustiStabileMarinoBorri2017,
	title = {Coupling effects on the dynamic response of moored floating platforms for offshore wind energy plants},
	journal = {Procedia engineering},
	volume = {199},
	year = {2017},
	pages = {3194{\textendash}3199},
	publisher = {Elsevier},
	doi = {10.1016/j.proeng.2017.09.527},
	author = {Giusti, Alessandro and Giovanni Stabile and Marino, Enzo and Claudio Borri}
}
@conference {MarinoLugniStabileBorriManuel2014,
	title = {Coupled dynamic simulations of offshore wind turbines: influence of wave modelling on the fatigue load assesment},
	booktitle = {XIII Conference of the Italian Association for Wind Engineering (In-Vento 2014)},
	year = {2014},
	author = {Marino, Enzo and Lugni, Claudio and Giovanni Stabile and Claudio Borri and Manuel, Lance}
}
@conference {MarinoLugniStabileBorri2014,
	title = {Coupled dynamic simulations of offshore wind turbines using linear, weakly and fully nonlinear wave models: the limitations of the second-order wave theory},
	booktitle = {9th International Conference on Structural Dynamics (EURODYN 2014)},
	year = {2014},
	author = {Marino, Enzo and Lugni, Claudio and Giovanni Stabile and Claudio Borri}
}
@inbook {MarinoStabileBorriLugni2013,
	title = {A comparative study about the effects of linear, weakly and fully nonlinear wave models on the dynamic response of offshore wind turbines},
	booktitle = {Research and Applications in Structural Engineering, Mechanics and Computation},
	year = {2013},
	pages = {389{\textendash}390},
	publisher = {CRC Press},
	organization = {CRC Press},
	author = {Marino, Enzo and Giovanni Stabile and Claudio Borri and Lugni, Claudio}
}
