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Flavia De Luca

Publications and source records attributed to Flavia De Luca.

2 recordsLinked to original sources

Structural Vibration Control of Offshore Wind Turbines Using Tuned Mass Damper Inerter in OpenFAST: Implementation, Validation, and Illustration

The tuned mass damper inerter (TMDI) is a passive vibration absorber that suppresses structural vibrations by leveraging the inertance property of inerter devices. Previous studies have demonstrated TMDI effectiveness in wind turbines, but relied on simplified structural models. To date, no study has implemented multi-directional TMDIs within aero-hydro-servo-elastic tools such as OpenFAST to enable independent vibration control across multiple turbine components, including the tower, blades, and substructure. This paper addresses this gap by implementing the TMDI in OpenFAST. The governing equations of motion are derived and implemented within the Structural Control (StC) Module, supporting arbitrary TMDI connectivity and independent multi-directional configurations across turbine components. Verification against independent numerical models confirms the implementation's accuracy across all supported configurations. An application study examines the IEA 15MW reference wind turbine equipped with a tower-top TMDI under combined wind-wave loading. Optimal tuning is performed using a simplified two-degree-of-freedom model, with modal properties extracted from an OpenSeesPy finite element model of the IEA 15MW. Results show that TMDIs with secondary mass up to 100 times smaller than a conventional TMD achieve matching or superior vibration suppression in the fore-aft and side-side directions, in terms of peak and standard deviation of tower-top displacement and acceleration. Notably, TMDI stroke is markedly reduced compared to the TMD, better suiting the spatially constrained wind turbine environment. These results support the practical merit of lightweight TMDIs for wind turbine vibration control, with the OpenFAST implementation enabling performance-driven design under realistic loading conditions.

math.OC

Social media usage reveals how regions recover after natural disaster

The challenge of nowcasting and forecasting the effect of natural disasters (e.g. earthquakes, floods, hurricanes) on assets, people and society is of primary importance for assessing the ability of such systems to recover from extreme events. Traditional disaster recovery estimates, such as surveys and interviews, are usually costly, time consuming and do not scale. Here we present a methodology to indirectly estimate the post-emergency recovery status ('downtime') of small businesses in urban areas looking at their online posting activity on social media. Analysing the time series of posts before and after an event, we quantify the downtime of small businesses for three natural disasters occurred in Nepal, Puerto Rico and Mexico. A convenient and reliable method for nowcasting the post-emergency recovery status of economic activities could help local governments and decision makers to better target their interventions and distribute the available resources more effectively.

physics.soc-ph