Comparative study of the different models for the calculation of BLEVEs overpressure effects

The BLEVE, acronym for Boiling Liquid Expanding Vapour Explosion, is one of the most dangerous accidents that can occur in pressure vessels. It can be defined as an explosion resulting from the failure of a vessel containing a pressure liquefied gas stored at a temperature significantly above its boiling point at atmospheric pressure. This phenomenon frequently appears when a vessel is engulfed by a fire: the heat causes the internal pressure to raise and the mechanical proprieties of the wall to decrease, with the consequent rupture of the tank and the instantaneous release of its whole content. After the breakage, the vapour outflows and expands and the liquid phase starts boiling due to the pressure drop. The formation and propagation of a distructive schock wave may occur, together with the ejection of fragments, the generation of a fireball if the stored fluid is flammable and immediately ignited or the atmospheric dispersion of a toxic cloud if the fluid contained inside the vessel is toxic. Despite the presence of many studies on the BLEVE mechanism, the exact causes and conditions of its occurrence are still elusive. In order to better understand this phenomenon, in the present study first of all the concept and definition of BLEVE are investigated. A historical analysis of the major events that have occurred over the past 60 years is described. A research of the principal causes of this event, including the analysis of the substances most frequently involved, is presented too. Afterwards a description of the main effects of BLEVEs is reported, focusing especially on the overpressure. Though the major aim of the present thesis is to contribute, with a comparative analysis, to the validation of the main models present in the literature for the calculation and prediction of the overpressure caused by BLEVEs. In line with this purpose, after a short overview of the available approaches, their ability to reproduce the trend of the overpressure is investigated. The overpressure calculated with the different models is compared with values deriving from events happened in the past and ad-hoc experiments, focusing the attention especially on medium and large scale phenomena. The ability of the models to consider different filling levels of the reservoir and different substances is analyzed too. The results of these calculations are extensively discussed. Finally some conclusive remarks are reported.

Spatio-temporal variation of macrofaunal assemblages in the deep Blanes submarine canyon

The spatio-temporal variations in diversity and abundance of deep-sea macrofaunal assemblages (excluding meiofaunal taxa, as Nematoda, Copepoda and Ostracoda) from the Blanes Canyon (BC) and adjacent open slope are described. The Catalan Sea basin is characterized by the presence of numerous submarine canyons, which are globally acknowledged as biodiversity hot-spots, due to their disturbance regime and incremented conveying of organic matter. This area is subjected to local deep-sea fisheries activities, and to recurrent cold water cascading events from the shelf. The upper canyon (~900 m), middle slope (~1200 m) and lower slope (~1500 m) habitats were investigated during three different months (October 2008, May 2009 and September 2009). A total of 624 specimens belonging to 16 different taxa were found into 67 analyzed samples, which had been collected from the two study areas. Of these, Polychaeta, Mollusca and Crustacea were always the most abundant groups. As expected, the patterns of species diversity and evenness were different in time and space. Both in BC and open slope, taxa diversity and abundance are higher in the shallowest depth and lowest at -1500 m depth. This is probably due to different trophic regimes at these depths. The abundance of filter-feeders is higher inside BC than in the adjacent open slope, which is also related with an increment of predator polychaetes. Surface deposit-feeders are more abundant in the open slope than in BC, along with a decrement of filter-feeders and their predators. Probably these differences are due to higher quantities of suspended organic matter reaching the canyon. The multivariate analyses conducted on major taxa point out major differences effective taxa richness between depths and stations. In September 2009 the analyzed communities double their abundances, with a corresponding increase in richness of taxa. This could be related to a mobilizing event, like the release of accumulated food-supply in a nepheloid layer associated to the arrival of autumn. The highest abundance in BC is detected in the shallowest depth and in late summer (September), probably due to higher food availability caused by stronger flood events coming from Tordera River. The effects of such events seemed to involve adjacent open slope too. The nMDS conducted on major taxa abundance shows a slight temporal difference between the three campaigns samples, with a clear clustering between samples of Sept 09. All depth and all months were dominated by Polychaeta, which have been identified to family level and submitted to further analysis. Family richness have clearly minimum at the -1200 m depth of BC, highlighting the presence of a general impact affecting the populations in the middle slope. Three different matrices have been created, each with a different taxonomic level (All Taxa “AT”, Phylum Level “PL” and Polychaeta Families “PF”). Multivariate analysis (MDS, SIMPER) conducted on PL matrix showed a clear spatial differences between stations (BC and open slope) and depths. MDSs conducted on other two matrices (AT and PF) showed similar patterns, but different from PL analysis. A 2 nd stage analysis have been conducted to understand differences between different taxonomic levels, and PL level has been chosen as the most representative of variation. The faunal differences observed were explained by depth, station and season. All work has been accomplished in the Centre d’estudis avançats de Blanes (CEAB-CSIC), within the framework of Spanish PROMETEO project "Estudio Integrado de Cañones y Taludes PROfundos del MEdiTErráneo Occidental: un hábitat esencial", Ref. CTM2007-66316-C02- 01/MAR.

A multi-objective genetic algorithm optimisation using variable speed pumps in water distribution systems

Due to its practical importance and inherent complexity, the optimisation of distribution networks for supplying drinking water has been the subject of extensive study for the past 30 years. The optimization is governed by sizing the pipes in the water distribution network (WDN) and / or optimises specific parts of the network such as pumps, tanks etc. or try to analyse and optimise the reliability of a WDN. In this thesis, the author has analysed two different WDNs (Anytown City and Cabrera city networks), trying to solve and optimise a multi-objective optimisation problem (MOOP). The main two objectives in both cases were the minimisation of Energy Cost (€) or Energy consumption (kWh), along with the total Number of pump switches (TNps) during a day. For this purpose, a decision support system generator for Multi-objective optimisation used. Its name is GANetXL and has been developed by the Center of Water System in the University of Exeter. GANetXL, works by calling the EPANET hydraulic solver, each time a hydraulic analysis has been fulfilled. The main algorithm used, was a second-generation algorithm for multi-objective optimisation called NSGA_II that gave us the Pareto fronts of each configuration. The first experiment that has been carried out was the network of Anytown city. It is a big network with a pump station of four fixed speed parallel pumps that are boosting the water dynamics. The main intervention was to change these pumps to new Variable speed driven pumps (VSDPs), by installing inverters capable to diverse their velocity during the day. Hence, it’s been achieved great Energy and cost savings along with minimisation in the number of pump switches. The results of the research are thoroughly illustrated in chapter 7, with comments and a variety of graphs and different configurations. The second experiment was about the network of Cabrera city. The smaller WDN had a unique FS pump in the system. The problem was the same as far as the optimisation process was concerned, thus, the minimisation of the energy consumption and in parallel the minimisation of TNps. The same optimisation tool has been used (GANetXL).The main scope was to carry out several and different experiments regarding a vast variety of configurations, using different pump (but this time keeping the FS mode), different tank levels, different pipe diameters and different emitters coefficient. All these different modes came up with a large number of results that were compared in the chapter 8. Concluding, it should be said that the optimisation of WDNs is a very interested field that has a vast space of options to deal with. This includes a large number of algorithms to choose from, different techniques and configurations to be made and different support system generators. The researcher has to be ready to “roam” between these choices, till a satisfactory result will convince him/her that has reached a good optimisation point.

Divergence patterns in Fucus seaweeds (Phaeophyceae) in the northern Baltic Sea and in the Tjongspollen area

To be able to interpret patterns of biodiversity it is important to understand the processes by which new species evolve and how closely related species remain reproductively isolated and ecologically differentiated. Divergence and differentiation can vary during speciation and it can be seen in different stages. Groups of closely related taxa constitute important case studies to understand species and new biodiversity formation. However, it is important to assess the divergence among them at different organismal levels and from an integrative perspective. For this purpose, this study used the brown seaweeds genus Fucus as a model to study speciation, as they constitute a good opportunity to study divergence at different stages. We investigated the divergence patterns in Fucus species from two marginal areas (northern Baltic Sea and the Tjongspollen area), based on phenetic, phylogenetic and biological taxonomical criteria that are respectively characterised by algal morphology, allele frequencies of five microsatellite loci and levels of secondary polyphenolic compounds called phlorotannins. The results from this study showed divergence at morphological and genetic levels to certain extent but complete lack of divergence at biochemical level (i.e. constitutive phlorotannin production) in the Baltic Sea or Norway. Morphological divergence was clearly evident in Tjongspollen (Norway) among putative taxa as they were identified in the field and this divergence corresponds with their neutral genetic divergence. In the Baltic, there are some distinguishable patterns in the morphology of the swedish and finnish individuals according to locality to certain extent but not among putative taxa within localities. Likewise, these morphological patterns have genetic correspondence among localities but not within each locality. At the biochemical level, measured by the phlorotannin contents there were neither evidence of divergence in Norway or the Baltic Sea nor any discernable aggregation pattern among or within localities. Our study have contributed with further understanding of the Baltic Sea Fucus system and its intriguingly rapid and recent divergence as well as of the Tjongspollen area systems where formally undescribed individuals have been observed for the first time; in fact they appear largely differentiated and they may well warrant a new species status. In current times, climate change threatens, peripheral ecosystems, biodiversity, and increased knowledge of processes generating and maintaining biodiversity in those ecosystems seem particularly important and needed.

Studies of CMS data access patterns with machine learning techniques

This thesis presents a study of the Grid data access patterns in distributed analysis in the CMS experiment at the LHC accelerator. This study ranges from the deep analysis of the historical patterns of access to the most relevant data types in CMS, to the exploitation of a supervised Machine Learning classification system to set-up a machinery able to eventually predict future data access patterns - i.e. the so-called dataset “popularity” of the CMS datasets on the Grid - with focus on specific data types. All the CMS workflows run on the Worldwide LHC Computing Grid (WCG) computing centers (Tiers), and in particular the distributed analysis systems sustains hundreds of users and applications submitted every day. These applications (or “jobs”) access different data types hosted on disk storage systems at a large set of WLCG Tiers. The detailed study of how this data is accessed, in terms of data types, hosting Tiers, and different time periods, allows to gain precious insight on storage occupancy over time and different access patterns, and ultimately to extract suggested actions based on this information (e.g. targetted disk clean-up and/or data replication). In this sense, the application of Machine Learning techniques allows to learn from past data and to gain predictability potential for the future CMS data access patterns. Chapter 1 provides an introduction to High Energy Physics at the LHC. Chapter 2 describes the CMS Computing Model, with special focus on the data management sector, also discussing the concept of dataset popularity. Chapter 3 describes the study of CMS data access patterns with different depth levels. Chapter 4 offers a brief introduction to basic machine learning concepts and gives an introduction to its application in CMS and discuss the results obtained by using this approach in the context of this thesis.