Andrea Alaimo

1. The prevailing aim in wind turbine design is to develop larger, more powerful systems that extend higher into the atmosphere to capture stronger and more consistent winds; however, increasing th...

This research explores the use of physiological signals derived from heart activity to assess mental effort during flight-related tasks. Data were collected through wearable sensors during simulations with varying cognitive demands. Specific indicators related to heart rate variability (HRV) were extracted and tested in different combinations to identify those most relevant for distinguishing levels of mental workload (WL). A Random Forest (RF) ensemble method is applied to classify two conditions, and its performance is examined under various settings, including model complexity and data partitioning strategies. Results showed that certain feature pairs significantly enhanced classification accuracy. The best features settings obtained from the RF are then used to train the other two decision trees-based classifiers, namely the AdaBoost and the XGBoost. Moreover, the decision trees models output is compared with predictions from a Kriging spatial interpolation technique, showing superior results in terms of reliability and consistency. This study highlights the potential of using heart-based physiological data and advanced classification techniques for developing intelligent support systems in aviation.

In this work a piezoelectric device is proposed for vibration damping on satellites solar panels. The structural arrangement proposed for the piezoelectric actuation system rely on a V configuration of piezoelectric stacks that are hinged to the main yoke structure. The numerical model of the satellite structure is defined in a Euler-Bernoulli beam finite element framework taking into account the electro-mechanical coupling with active elements by introducing their equivalent nodal piezoelectric loads. Different shunt circuits have been designed to suppress the vibrations of the solar panel carrying out a parametric study on the circuit main components parameters to find the best combination. Numerical simulations have been carried out in order to compare the performance of the designed vibration suppression systems proving the effectiveness of the proposed smart structure configuration.

This study proposes a piezoelectric device for vibration damping in satellite solar panels. The design features a structural arrangement with piezoelectric stacks configured in a V-shape and hinged to the main yoke structure. The satellite structure is modeled using an Euler–Bernoulli beam finite element framework, incorporating the electro-mechanical coupling of active elements through equivalent nodal piezoelectric loads. Various shunt circuits are designed to mitigate vibrations, with a parametric study conducted to optimize the key circuit parameters. Additionally, a filtered PID active suppression system is developed and tuned using a meta-heuristic algorithm to determine optimal controller gains. Numerical simulations are performed to evaluate and compare the effectiveness of the proposed vibration suppression systems, demonstrating the efficiency of the smart structure configuration and providing performance analysis.