Analisi e ottimizzazione termodinamica del sistema di generazione di potenza di un impianto solare a concentrazione ibrido

Impianto solare termodinamico a concentrazione per la produzione di energia elettrica.

A Low Consumption Real Time Environmental Monitoring System for Smart Cities based on ZigBee Wireless Sensor Network

Nowadays, there is an increasing interest in wireless sensor networks (WSN) for environmental monitoring systems because it can be used to improve the quality of life and living conditions are becoming a major concern to people. This paper describes the design and development of a real time monitoring system based on ZigBee WSN characterized by a lower energy consumption, low cost, reduced dimensions and fast adaptation to the network tree topology. The developed system encompasses an optimized sensing process about environmental parameters, low rate transmission from sensor nodes to the gateway, packet parsing and data storing in a remote database and real time visualization through a web server.

Analisi dei coefficienti di auto induzione di dispersione nelle macchine elettriche rotanti di tipo multifase

L’obiettivo di questa tesi è l’analisi e la modellizzazione dei flussi dispersi statorici nelle macchine multifase utilizzando la teoria dei vettori di spazio multipli. L’analisi ed il calcolo del coefficiente di auto induzione di dispersione statorica nei vari spazi è cruciale nella progettazione e nel controllo delle macchine elettriche multifase in quanto, per esempio, essa limita il ripple di corrente quando la macchina non è alimentata con una tensione perfettamente sinusoidale. Il fine è pertanto di giungere alla scrittura di un’equazione che leghi il generico vettore di spazio dei flussi dispersi ai vettori di spazio delle correnti che alimentano la macchina elettrica tramite una costante che contenga i coefficienti di auto e mutua induzione di dispersione in cava degli avvolgimenti statorici.

Creazione e sviluppo di un sistema di controllo in tempo reale per un sistema fuel cell

The control of a proton exchange membrane fuel cell system (PEM FC) for domestic heat and power supply requires extensive control measures to handle the complicated process. Highly dynamic and non linear behavior, increase drastically the difficulties to find the optimal design and control strategies. The objective is to design, implement and commission a controller for the entire fuel cell system. The fuel cell process and the control system are engineered simultaneously; therefore there is no access to the process hardware during the control system development. Therefore the method of choice was a model based design approach, following the rapid control prototyping (RCP) methodology. The fuel cell system is simulated using a fuel cell library which allowed thermodynamic calculations. In the course of the development the process model is continuously adapted to the real system. The controller application is designed and developed in parallel and thereby tested and verified against the process model. Furthermore, after the commissioning of the real system, the process model can be also better identified and parameterized utilizing measurement data to perform optimization procedures. The process model and the controller application are implemented in Simulink using Mathworks` Real Time Workshop (RTW) and the xPC development suite for MiL (model-in-theloop) and HiL (hardware-in-the-loop) testing. It is possible to completely develop, verify and validate the controller application without depending on the real fuel cell system, which is not available for testing during the development process. The fuel cell system can be immediately taken into operation after connecting the controller to the process.

Analisi di pH, ORP e DO finalizzata all'utilizzo di segnali indiretti per il monitoraggio e il controllo automatico di impianti di depurazione a fanghi attivi

Con il presente lavoro di tesi si è studiata la possibilità di estrarre informazioni sugli andamenti dei processi biologici dall’osservazione dei segnali di pH, potenziale di ossido riduzione (ORP) e ossigeno disciolto (DO) nelle vasche di processo di un impianto a fanghi attivi a flusso continuo (predenitro/nitro) per verificare la possibilità di utilizzare questo tipo di sonde per lo sviluppo di sistemi per il controllo automatico e la gestione intelligente, eventualmente remota, degli impianti di depurazione. Il lavoro di sperimentazione è stato svolto su un impianto pilota a flusso continuo con schema predenitro – nitro, costruito ed installato presso i laboratori della sede Enea di Bologna (Sezione ACS PROT IDR - Gestione Risorse Idriche). L’obiettivo primario della sperimentazione è stato quello di portare il sistema in uno stato stazionario di equilibrio, così da poter stabilire delle condizioni di funzionamento note e costanti, riscontrabili anche nei segnali di riferimento. Tali condizioni sono state definite prendendo come riferimento un impianto reale noto, funzionante in condizioni di processo costanti e medie, definendo contestualmente test sperimentali che riproducessero condizioni riscontrabili sullo stesso impianto reale. Le condizioni del sistema sono state monitorate costantemente, attraverso il monitoraggio giornaliero dei processi, effettuato con attività di campionamento e di analisi, osservando costantemente i segnali indiretti.

Enabling computationally intensive bioinformatics applications on the Grid platform

Bioinformatics is a recent and emerging discipline which aims at studying biological problems through computational approaches. Most branches of bioinformatics such as Genomics, Proteomics and Molecular Dynamics are particularly computationally intensive, requiring huge amount of computational resources for running algorithms of everincreasing complexity over data of everincreasing size. In the search for computational power, the EGEE Grid platform, world's largest community of interconnected clusters load balanced as a whole, seems particularly promising and is considered the new hope for satisfying the everincreasing computational requirements of bioinformatics, as well as physics and other computational sciences. The EGEE platform, however, is rather new and not yet free of problems. In addition, specific requirements of bioinformatics need to be addressed in order to use this new platform effectively for bioinformatics tasks. In my three years' Ph.D. work I addressed numerous aspects of this Grid platform, with particular attention to those needed by the bioinformatics domain. I hence created three major frameworks, Vnas, GridDBManager and SETest, plus an additional smaller standalone solution, to enhance the support for bioinformatics applications in the Grid environment and to reduce the effort needed to create new applications, additionally addressing numerous existing Grid issues and performing a series of optimizations. The Vnas framework is an advanced system for the submission and monitoring of Grid jobs that provides an abstraction with reliability over the Grid platform. In addition, Vnas greatly simplifies the development of new Grid applications by providing a callback system to simplify the creation of arbitrarily complex multistage computational pipelines and provides an abstracted virtual sandbox which bypasses Grid limitations. Vnas also reduces the usage of Grid bandwidth and storage resources by transparently detecting equality of virtual sandbox files based on content, across different submissions, even when performed by different users. BGBlast, evolution of the earlier project GridBlast, now provides a Grid Database Manager (GridDBManager) component for managing and automatically updating biological flatfile databases in the Grid environment. GridDBManager sports very novel features such as an adaptive replication algorithm that constantly optimizes the number of replicas of the managed databases in the Grid environment, balancing between response times (performances) and storage costs according to a programmed cost formula. GridDBManager also provides a very optimized automated management for older versions of the databases based on reverse delta files, which reduces the storage costs required to keep such older versions available in the Grid environment by two orders of magnitude. The SETest framework provides a way to the user to test and regressiontest Python applications completely scattered with side effects (this is a common case with Grid computational pipelines), which could not easily be tested using the more standard methods of unit testing or test cases. The technique is based on a new concept of datasets containing invocations and results of filtered calls. The framework hence significantly accelerates the development of new applications and computational pipelines for the Grid environment, and the efforts required for maintenance. An analysis of the impact of these solutions will be provided in this thesis. This Ph.D. work originated various publications in journals and conference proceedings as reported in the Appendix. Also, I orally presented my work at numerous international conferences related to Grid and bioinformatics.