Biomasse e loro quantificazione economica per un efficiente uso dell'energia

Biomasses and their possible use as energy resource are of great interest today, and the general problem of energy resources as well. In the present study the key questions of the convenience, from both energy and economy standpoints, have been addressed without any bias: the problem has been handled starting from “philosophical” bases disregarding any pre-settled ideology or political trend, but simply using mathematical approaches as logical tools for defining balances in a right way. In this context quantitative indexes such as LCA and EROEI have been widely used, together with multicriteria methods (such as ELECTRE) as decision supporting tools. This approach permits to remove mythologies, such as the unrealistic concept of clean energy, or the strange idea of biomasses as a magic to solve every thing in the field of the energy. As a consequence the present study aims to find any relevant aspect potentially useful for the society, looking at any possible source of energy without prejudices but without unrealistic expectations too. For what concerns biomasses, we studied in great details four very different cases of study, in order to have a scenario as various as much we can. A relevant result is the need to use biomasses together with other more efficient sources, especially recovering by-products from silviculture activities: but attention should be paid to the transportation and environmental costs. Another relevant result is the very difficult possibility of reliable evaluation of dedicated cultures as sources for “biomasses for energy”: the problem has to be carefully evaluated case-by-case, because what seems useful in a context, becomes totally disruptive in another one. In any case the concept itself of convenience is not well defined at a level of macrosystem: it seems more appropriate to limit this very concept at a level of microsystem, considering that what sounds fine in a limited well defined microsystem may cause great damage in another slightly different, or even very similar, microsystem. This approach seems the right way to solve the controversy about the concept of convenience.

Design and implementation of a novel multi-constellation FPGA-based dual frequency GNSS receiver for space applications

The PhD activity described in the document is part of the Microsatellite and Microsystem Laboratory of the II Faculty of Engineering, University of Bologna. The main objective is the design and development of a GNSS receiver for the orbit determination of microsatellites in low earth orbit. The development starts from the electronic design and goes up to the implementation of the navigation algorithms, covering all the aspects that are involved in this type of applications. The use of GPS receivers for orbit determination is a consolidated application used in many space missions, but the development of the new GNSS system within few years, such as the European Galileo, the Chinese COMPASS and the Russian modernized GLONASS, proposes new challenges and offers new opportunities to increase the orbit determination performances. The evaluation of improvements coming from the new systems together with the implementation of a receiver that is compatible with at least one of the new systems, are the main activities of the PhD. The activities can be divided in three section: receiver requirements definition and prototype implementation, design and analysis of the GNSS signal tracking algorithms, and design and analysis of the navigation algorithms. The receiver prototype is based on a Virtex FPGA by Xilinx, and includes a PowerPC processor. The architecture follows the software defined radio paradigm, so most of signal processing is performed in software while only what is strictly necessary is done in hardware. The tracking algorithms are implemented as a combination of Phase Locked Loop and Frequency Locked Loop for the carrier, and Delay Locked Loop with variable bandwidth for the code. The navigation algorithm is based on the extended Kalman filter and includes an accurate LEO orbit model.

Intelligent Sensor Systems for Structural Health Monitoring Applications

The convergence between the recent developments in sensing technologies, data science, signal processing and advanced modelling has fostered a new paradigm to the Structural Health Monitoring (SHM) of engineered structures, which is the one based on intelligent sensors, i.e., embedded devices capable of stream processing data and/or performing structural inference in a self-contained and near-sensor manner. To efficiently exploit these intelligent sensor units for full-scale structural assessment, a joint effort is required to deal with instrumental aspects related to signal acquisition, conditioning and digitalization, and those pertaining to data management, data analytics and information sharing. In this framework, the main goal of this Thesis is to tackle the multi-faceted nature of the monitoring process, via a full-scale optimization of the hardware and software resources involved by the {SHM} system. The pursuit of this objective has required the investigation of both: i) transversal aspects common to multiple application domains at different abstraction levels (such as knowledge distillation, networking solutions, microsystem {HW} architectures), and ii) the specificities of the monitoring methodologies (vibrations, guided waves, acoustic emission monitoring). The key tools adopted in the proposed monitoring frameworks belong to the embedded signal processing field: namely, graph signal processing, compressed sensing, ARMA System Identification, digital data communication and TinyML.