Frequency-dependent response of snow in uniaxial compression and comparison with numerical simulation

La determinazione del modulo di Young è fondamentale nello studio della propagazione di fratture prima del rilascio di una valanga e per lo sviluppo di affidabili modelli di stabilità della neve. Il confronto tra simulazioni numeriche del modulo di Young e i valori sperimentali mostra che questi ultimi sono tre ordini di grandezza inferiori a quelli simulati (Reuter et al. 2013)⁠. Lo scopo di questo lavoro è stimare il modulo di elasticità studiando la dipendenza dalla frequenza della risposta di diversi tipi di neve a bassa densità, 140-280 kg m-3. Ciò è stato fatto applicando una compressione dinamica uniassiale a -15°C nel range 1-250 Hz utilizzando il Young's modulus device (YMD), prototipo di cycling loading device progettato all'Istituto per lo studio della neve e delle valanghe (SLF). Una risposta viscoelastica della neve è stata identificata a tutte le frequenze considerate, la teoria della viscoelasticità è stata applicata assumendo valida l'ipotesi di risposta lineare della neve. Il valore dello storage modulus, E', a 100 Hz è stato identificato come ragionevolmente rappresentativo del modulo di Young di ciascun campione neve. Il comportamento viscoso è stato valutato considerando la loss tangent e la viscosità ricavata dai modelli di Voigt e Maxwell. Il passaggio da un comportamento più viscoso ad uno più elastico è stato trovato a 40 Hz (~1.1•10-2 s-1). Il maggior contributo alla dissipazione è nel range 1-10 Hz. Infine, le simulazioni numeriche del modulo di Young sono state ottenute nello stesso modo di Reuter et al.. La differenza tra le simulazioni ed i valori sperimentali di E' sono, al massimo, di un fattore 5; invece, in Reuter et al.⁠, era di 3 ordini di grandezza. Pertanto, i nostri valori sperimentali e numerici corrispondono meglio, indicando che il metodo qui utilizzato ha portato ad un miglioramento significativo.

Models for the assessment of resilience in water distribution networks

The following thesis work focuses on the use and implementation of advanced models for measuring the resilience of water distribution networks. In particular, the functions implemented in GRA Tool, a software developed by the University of Exeter (UK), and the functions of the Toolkit of Epanet 2.2 were investigated. The study of the resilience and failure, obtained through GRA Tool and the development of the methodology based on the combined use of EPANET 2.2 and MATLAB software, was tested in a first phase, on a small-sized literature water distribution network, so that the variability of the results could be perceived more clearly and with greater immediacy, and then, on a more complex network, that of Modena. In the specific, it has been decided to go to recreate a mode of failure deferred in time, one proposed by the software GRA Tool, that is failure to the pipes, to make a comparison between the two methodologies. The analysis of hydraulic efficiency was conducted using a synthetic and global network performance index, i.e., Resilience index, introduced by Todini in the years 2000-2016. In fact, this index, being one of the parameters with which to evaluate the overall state of "hydraulic well-being" of a network, has the advantage of being able to act as a criterion for selecting any improvements to be made on the network itself. Furthermore, during these analyzes, was shown the analytical development undergone over time by the formula of the Resilience Index. The final intent of this thesis work was to understand by what means to improve the resilience of the system in question, as the introduction of the scenario linked to the rupture of the pipelines was designed to be able to identify the most problematic branches, i.e., those that in the event of a failure it would entail greater damage to the network, including lowering the Resilience Index.

Near Real-Time Detection Of Pipe Bursts in Water Distribution Systems

The research work presented in the thesis describes a new methodology for the automated near real-time detection of pipe bursts in Water Distribution Systems (WDSs). The methodology analyses the pressure/flow data gathered by means of SCADA systems in order to extract useful informations that go beyond the simple and usual monitoring type activities and/or regulatory reporting , enabling the water company to proactively manage the WDSs sections. The work has an interdisciplinary nature covering AI techniques and WDSs management processes such as data collection, manipulation and analysis for event detection. Indeed, the methodology makes use of (i) Artificial Neural Network (ANN) for the short-term forecasting of future pressure/flow signal values and (ii) Rule-based Model for bursts detection at sensor and district level. The results of applying the new methodology to a District Metered Area in Emilia- Romagna’s region, Italy have also been reported in the thesis. The results gathered illustrate how the methodology is capable to detect the aforementioned failure events in fast and reliable manner. The methodology guarantees the water companies to save water, energy, money and therefore enhance them to achieve higher levels of operational efficiency, a compliance with the current regulations and, last but not least, an improvement of customer service.