Neural network modelling of the wave-structure interaction processes

This thesis presents a new Artificial Neural Network (ANN) able to predict at once the main parameters representative of the wave-structure interaction processes, i.e. the wave overtopping discharge, the wave transmission coefficient and the wave reflection coefficient. The new ANN has been specifically developed in order to provide managers and scientists with a tool that can be efficiently used for design purposes. The development of this ANN started with the preparation of a new extended and homogeneous database that collects all the available tests reporting at least one of the three parameters, for a total amount of 16’165 data. The variety of structure types and wave attack conditions in the database includes smooth, rock and armour unit slopes, berm breakwaters, vertical walls, low crested structures, oblique wave attacks. Some of the existing ANNs were compared and improved, leading to the selection of a final ANN, whose architecture was optimized through an in-depth sensitivity analysis to the training parameters of the ANN. Each of the selected 15 input parameters represents a physical aspect of the wave-structure interaction process, describing the wave attack (wave steepness and obliquity, breaking and shoaling factors), the structure geometry (submergence, straight or non-straight slope, with or without berm or toe, presence or not of a crown wall), or the structure type (smooth or covered by an armour layer, with permeable or impermeable core). The advanced ANN here proposed provides accurate predictions for all the three parameters, and demonstrates to overcome the limits imposed by the traditional formulae and approach adopted so far by some of the existing ANNs. The possibility to adopt just one model to obtain a handy and accurate evaluation of the overall performance of a coastal or harbor structure represents the most important and exportable result of the work.

Design and fabrication of MOMS-based ultrasonic probes for minimally invasive endoscopic applications

A Micro-opto-mechanical systems (MOMS) based technology for the fabrication of ultrasonic probes on optical fiber is presented. Thanks to the high miniaturization level reached, the realization of an ultrasonic system constituted by ultrasonic generating and detecting elements, suitable for minimally invasive applications or Non Destructive Evaluation (NDE) of materials at high resolution, is demonstrated. The ultrasonic generation is realized by irradiating a highly absorbing carbon film patterned on silicon micromachined structures with a nanosecond pulsed laser source, generating a mechanical shock wave due to the thermal expansion of the film induced by optical energy conversion into heat. The short duration of the pulsed laser, together with an appropriate emitter design, assure high frequency and wide band ultrasonic generation. The acoustic detection is also realized on a MOMS device using an interferometric receiver, fabricated with a Fabry-Perot optical cavity realized by means of a patterned SU-8 and two Al metallization levels. In order to detect the ultrasonic waves, the cavity is interrogated by a laser beam measuring the reflected power with a photodiode. Various issues related to the design and fabrication of these acoustic probes are investigated in this thesis. First, theoretical models are developed to characterize the opto-acoustic behavior of the devices and estimate their expected acoustic performances. Tests structures are realized to derive the relevant physical parameters of the materials constituting the MOMS devices and determine the conditions theoretically assuring the best acoustic emission and detection performances. Moreover, by exploiting the models and the theoretical results, prototypes of acoustic probes are designed and their fabrication process developed by means of an extended experimental activity.

Sparse Signal Representation of Ultrasonic Signals for Structural Health Monitoring Applications

Assessment of the integrity of structural components is of great importance for aerospace systems, land and marine transportation, civil infrastructures and other biological and mechanical applications. Guided waves (GWs) based inspections are an attractive mean for structural health monitoring. In this thesis, the study and development of techniques for GW ultrasound signal analysis and compression in the context of non-destructive testing of structures will be presented. In guided wave inspections, it is necessary to address the problem of the dispersion compensation. A signal processing approach based on frequency warping was adopted. Such operator maps the frequencies axis through a function derived by the group velocity of the test material and it is used to remove the dependence on the travelled distance from the acquired signals. Such processing strategy was fruitfully applied for impact location and damage localization tasks in composite and aluminum panels. It has been shown that, basing on this processing tool, low power embedded system for GW structural monitoring can be implemented. Finally, a new procedure based on Compressive Sensing has been developed and applied for data reduction. Such procedure has also a beneficial effect in enhancing the accuracy of structural defects localization. This algorithm uses the convolutive model of the propagation of ultrasonic guided waves which takes advantage of a sparse signal representation in the warped frequency domain. The recovery from the compressed samples is based on an alternating minimization procedure which achieves both an accurate reconstruction of the ultrasonic signal and a precise estimation of waves time of flight. Such information is used to feed hyperbolic or elliptic localization procedures, for accurate impact or damage localization.