The routes of the Mediterranean Sea circulation

The Mediterranean Sea is a semi-enclosed basin connected to the Atlantic Ocean through the narrow and shallow Strait of Gibraltar and further subdivided in two different sub-basins, the Eastern Mediterranean and the Western Mediterranean, connected through the Stait of Sicily. On annual basis, a net heat budget of −7 W/m2, combined with exceeding evaporation over precipation and runoff together with wind stress, is responsible for the antiestuarine character of the zonal thermoaline circulation. The outflow at Gibraltar Strait is mainly composed of Levantine Intermediate Water (LIW) and deep water masses formed in the Western Mediterranean Sea. The aim of this thesis is to validate and quantitatively assess the main routes of water masses composing the ouflow at Gibraltar Strait, using for the first time in the Mediterranean Sea a lagrangian interpretation of the eulerian velocity field produced from an eddy-resolving reanalysis dataset, spanning from 2000 to 2012. A lagrangian model named Ariane is used to map out three-dimensional trajectories in order to describe the pathways of water mass transport from the Strait of Sicily, the Gulf of Lyon and the Northern Tyrrhenian Sea to the Gibraltar Strait. Numerical experiments were carried out by seeding millions of particles in the Strait of Gibraltar and following them backwards in time to track the origins of water masses and transport exchanged between the different sections of the Mediterranean. Finally, the main routes of the intermediate and deep water masses are reconstructed from virtual particles trajectories, which highlight the role of the Western Mediterranean Deep Water (WMDW) as the main contributor to the Gibraltar Strait outflow. For the first time, the quantitative description of the flow of water masses coming from the Eastern Mediterranean towards the Gibraltar Strait is provided and a new route that directly links the Northern Tyrrhenian Sea to Gibralatr Strait has been detected.

Substructuring approache in state space models for dynamic system parameters identification

In the recent decade, the request for structural health monitoring expertise increased exponentially in the United States. The aging issues that most of the transportation structures are experiencing can put in serious jeopardy the economic system of a region as well as of a country. At the same time, the monitoring of structures is a central topic of discussion in Europe, where the preservation of historical buildings has been addressed over the last four centuries. More recently, various concerns arose about security performance of civil structures after tragic events such the 9/11 or the 2011 Japan earthquake: engineers looks for a design able to resist exceptional loadings due to earthquakes, hurricanes and terrorist attacks. After events of such a kind, the assessment of the remaining life of the structure is at least as important as the initial performance design. Consequently, it appears very clear that the introduction of reliable and accessible damage assessment techniques is crucial for the localization of issues and for a correct and immediate rehabilitation. The System Identification is a branch of the more general Control Theory. In Civil Engineering, this field addresses the techniques needed to find mechanical characteristics as the stiffness or the mass starting from the signals captured by sensors. The objective of the Dynamic Structural Identification (DSI) is to define, starting from experimental measurements, the modal fundamental parameters of a generic structure in order to characterize, via a mathematical model, the dynamic behavior. The knowledge of these parameters is helpful in the Model Updating procedure, that permits to define corrected theoretical models through experimental validation. The main aim of this technique is to minimize the differences between the theoretical model results and in situ measurements of dynamic data. Therefore, the new model becomes a very effective control practice when it comes to rehabilitation of structures or damage assessment. The instrumentation of a whole structure is an unfeasible procedure sometimes because of the high cost involved or, sometimes, because it’s not possible to physically reach each point of the structure. Therefore, numerous scholars have been trying to address this problem. In general two are the main involved methods. Since the limited number of sensors, in a first case, it’s possible to gather time histories only for some locations, then to move the instruments to another location and replay the procedure. Otherwise, if the number of sensors is enough and the structure does not present a complicate geometry, it’s usually sufficient to detect only the principal first modes. This two problems are well presented in the works of Balsamo [1] for the application to a simple system and Jun [2] for the analysis of system with a limited number of sensors. Once the system identification has been carried, it is possible to access the actual system characteristics. A frequent practice is to create an updated FEM model and assess whether the structure fulfills or not the requested functions. Once again the objective of this work is to present a general methodology to analyze big structure using a limited number of instrumentation and at the same time, obtaining the most information about an identified structure without recalling methodologies of difficult interpretation. A general framework of the state space identification procedure via OKID/ERA algorithm is developed and implemented in Matlab. Then, some simple examples are proposed to highlight the principal characteristics and advantage of this methodology. A new algebraic manipulation for a prolific use of substructuring results is developed and implemented.

Gravitational microscope in MACSJ1206: unveiling galaxy cluster member mass distribution

Gravitational lensing is a powerful tool to investigate the properties of the distribution of matter, be it barionic or dark. In this work we take advantage of Strong Gravitational Lensing to infer the properties of one of the galaxy-scale substructures that makes up the cluster MACSJ1206. It is relatively easy to model the morphology of the visible components of a galaxy, while the morphology of the dark matter distribution cannot be so easily constrained. Being sensitive to the whole mass, strong lensing provides a way to probe DM distribution, and this is the reason why it is the best tool to study the substructure. The goal of this work consists of performing an analysis of the substructure previously mentioned, an early type galaxy (ETG), by analyzing the highly magnified Einstein ring around it, in order to put stringent constraints on its matter distribution, that, for an ETG, is commonly well described by an isothermal profilele. This turns out to be interesting for three main different reasons. It is well known that galaxies in clusters are subject to interaction processes, both dynamic and hydrodynamic, that can significantly modify the distribution of matter within them. Therefore, finding a different profile from the one usually expected could be a sign that the galaxy has undergone processes that have changed its structure. Studying the mass distribution also means studying the dark matter component, which not only still presents great questions today, but which is also not obviously distributed in the same way as in an isolated galaxy. What emerges from the analysis is that the total mass distribution of the galaxy under examination turns out to have a slope much steeper than the isothermal usually expected.

Stellar mass loss from the Fornax dwarf spheroidal galaxy

Dwarf galaxies often experience gravitational interactions from more massive companions. These interactions can deform galaxies, turn star formation on or off, or give rise to mass loss phenomena. In this thesis work we propose to study, through N-body simulations, the stellar mass loss suffered by the dwarf spheroid galaxy (dSph) Fornax orbiting in the Milky Way gravitational potential. Which is a key phenomenon to explain the mass budget problem: the Fornax globular clusters together have a stellar mass comparable to that of Fornax itself. If we look at the stellar populations which they are made of and we apply the scenarios of stellar population formation we find that, originally, they must have been >= 5 times more massive. For this reason, they must have lost or ejected stars through dynamic interactions. However, as presented in Larsen et al (2012), field stars alone are not sufficient to explain this scenario. We may assume that some of those stars fell into Fornax, and later were stripped by Milky Way. In order to study this solution we built several illustrative single component simulations, with a tabulated density model using the P07ecc orbit studied from Battaglia et al (2015). To divide the single component into stellar and dark matter components we have defined a posterior the probability function P(E), where E is the initial energy distribution of the particles. By associating each particle with a fraction of stellar mass and dark matter. In this way we built stellar density profiles without repeating simulations. We applied the method to Fornax using the profile density tables obtained in Pascale et al (2018) as observational constraints and to build the model. The results confirm the results previously obtained with less flexible models by Battaglia et al (2015). They show a stellar mass loss < 4% within 1.6 kpc and negligible within 3 kpc, too small to solve the mass budget problem.