Energy harvesting from piezoelectric devices embedded in a 3D printed wing

This thesis work has been carried out at Clarkson University in Potsdam NY, USA and involved the design of a low elongation wing, consisting of parts made by polylactide (PLA) using the fused deposition model (FDM) technology of Rapid Prototyping, then assembled together in a thin aluminum spar. The aim of the research is to evaluate the feasibility of collecting electrical energy by converting mechanical energy from the vibration of the wing flutter. With this aim piezoelectric stripes were glued in the inner part of the wing, as well as on the aluminum spar, as monomorphic configuration. During the phases of the project, particular attention was given to the geometry and the materials used, in order to trigger the flutter for low flow velocity. The CAD software SolidWorks® was used for the design of the wing and then the drawings were sent to the Clarkson machine shop in order to to produce the parts required by the wing assembly. FEM simulations were performed, using software MSC NASTRAN/PATRAN®, to evaluate the stiffness of the whole wing as well as the natural vibration modes of the structure. These data, in a first approximation, were used to predict the flutter speed. Finally, experimental tests in the Clarkson wind tunnel facility were carried out in order to validate the results obtained from FEM analysis. The power collected by the piezoelectrics under flutter condition was addressed by tuning the resistors downstream the electronic circuit of the piezoelectrics.

La stampante 3D DELTA WASP 3MT - Verso la fabbricazione personale

La tesi segue il progetto della Delta WASP 3MT, stampante 3D di grandi dimensioni. Il lavoro parte da una analisi del contesto che incontra i temi dell'artigianato digitale e dell'autoproduzione. Successivamente viene fatta una analisi dei requisiti e delle soluzioni tecniche implementabili sulla macchina per soddisfarli. A questa segue una illustrazione degli interventi sulle varie parti della macchina. Infine si espongono brevemente i punti chiave elaborati per la comunicazione della macchina, dal naming alla strategia nei punti vendita.

An Embedded In-Cabin Lightweight High-Performance 3D Gaze Estimation System

Gaze estimation has gained interest in recent years for being an important cue to obtain information about the internal cognitive state of humans. Regardless of whether it is the 3D gaze vector or the point of gaze (PoG), gaze estimation has been applied in various fields, such as: human robot interaction, augmented reality, medicine, aviation and automotive. In the latter field, as part of Advanced Driver-Assistance Systems (ADAS), it allows the development of cutting-edge systems capable of mitigating road accidents by monitoring driver distraction. Gaze estimation can be also used to enhance the driving experience, for instance, autonomous driving. It also can improve comfort with augmented reality components capable of being commanded by the driver's eyes. Although, several high-performance real-time inference works already exist, just a few are capable of working with only a RGB camera on computationally constrained devices, such as a microcontroller. This work aims to develop a low-cost, efficient and high-performance embedded system capable of estimating the driver's gaze using deep learning and a RGB camera. The proposed system has achieved near-SOTA performances with about 90% less memory footprint. The capabilities to generalize in unseen environments have been evaluated through a live demonstration, where high performance and near real-time inference were obtained using a webcam and a Raspberry Pi4.