Probabilistic approaches in civil engineering: generation of random fields and structural identification with genetic algorithms

The inherent stochastic character of most of the physical quantities involved in engineering models has led to an always increasing interest for probabilistic analysis. Many approaches to stochastic analysis have been proposed. However, it is widely acknowledged that the only universal method available to solve accurately any kind of stochastic mechanics problem is Monte Carlo Simulation. One of the key parts in the implementation of this technique is the accurate and efficient generation of samples of the random processes and fields involved in the problem at hand. In the present thesis an original method for the simulation of homogeneous, multi-dimensional, multi-variate, non-Gaussian random fields is proposed. The algorithm has proved to be very accurate in matching both the target spectrum and the marginal probability. The computational efficiency and robustness are very good too, even when dealing with strongly non-Gaussian distributions. What is more, the resulting samples posses all the relevant, welldefined and desired properties of “translation fields”, including crossing rates and distributions of extremes. The topic of the second part of the thesis lies in the field of non-destructive parametric structural identification. Its objective is to evaluate the mechanical characteristics of constituent bars in existing truss structures, using static loads and strain measurements. In the cases of missing data and of damages that interest only a small portion of the bar, Genetic Algorithm have proved to be an effective tool to solve the problem.

Innovative Homogeneous and Heterogeneous Systems for Electrochemically Generated Luminescence Investigations: Towards One-Dimensional ECL

My research PhD work is focused on the Electrochemically Generated Luminescence (ECL) investigation of several different homogeneous and heterogeneous systems. ECL is a redox induced emission, a process whereby species, generated at electrodes, undergo a high-energy electron transfer reaction to form excited states that emit light. Since its first application, the ECL technique has become a very powerful analytical tool and has widely been used in biosensor transduction. ECL presents an intrinsically low noise and high sensitivity; moreover, the electrochemical generation of the excited state prevents scattering of the light source: for all these characteristics, it is an elective technique for ultrasensitive immunoassay detection. The majority of ECL systems involve species in solution where the emission occurs in the diffusion layer near to the electrode surface. However, over the past few years, an intense research has been focused on the ECL generated from species constrained on the electrode surface. The aim of my work is to study the behavior of ECL-generating molecular systems upon the progressive increase of their spatial constraints, that is, passing from isolated species in solution, to fluorophores embedded within a polymeric film and, finally, to patterned surfaces bearing “one-dimensional” emitting spots. In order to describe these trends, I use different “dimensions” to indicate the different classes of compounds. My thesis was mostly developed in the electrochemistry group of Bologna with the supervision of Prof Francesco Paolucci and Dr Massimo Marcaccio. With their help and also thanks to their long experience in the molecular and supramolecular ECL fields and in the surface investigations using scanning probe microscopy techniques, I was able to obtain the results herein described. Moreover, during my research work, I have established a new collaboration with the group of Nanobiotechnology of Prof. Robert Forster (Dublin City University) where I spent a research period. Prof. Forster has a broad experience in the biomedical field, especially he focuses his research on film surfaces biosensor based on the ECL transduction. This thesis can be divided into three sections described as follows: (i) in the fist section, homogeneous molecular and supramolecular ECL-active systems, either organic or inorganic species (i.e., corannulene, dendrimers and iridium metal complex), are described. Driving force for this kind of studies includes the search for new luminophores that display on one hand higher ECL efficiencies and on the other simple mechanisms for modulating intensity and energy of their emission in view of their effective use in bioconjugation applications. (ii) in the second section, the investigation of some heterogeneous ECL systems is reported. Redox polymers comprising inorganic luminophores were described. In such a context, a new conducting platform, based on carbon nanotubes, was developed aimed to accomplish both the binding of a biological molecule and its electronic wiring to the electrode. This is an essential step for the ECL application in the field of biosensors. (iii) in the third section, different patterns were produced on the electrode surface using a Scanning Electrochemical Microscopy. I developed a new methods for locally functionalizing an inert surface and reacting this surface with a luminescent probe. In this way, I successfully obtained a locally ECL active platform for multi-array application.

Comparing Different Approaches for Clustering Categorical Data

There are different ways to do cluster analysis of categorical data in the literature and the choice among them is strongly related to the aim of the researcher, if we do not take into account time and economical constraints. Main approaches for clustering are usually distinguished into model-based and distance-based methods: the former assume that objects belonging to the same class are similar in the sense that their observed values come from the same probability distribution, whose parameters are unknown and need to be estimated; the latter evaluate distances among objects by a defined dissimilarity measure and, basing on it, allocate units to the closest group. In clustering, one may be interested in the classification of similar objects into groups, and one may be interested in finding observations that come from the same true homogeneous distribution. But do both of these aims lead to the same clustering? And how good are clustering methods designed to fulfil one of these aims in terms of the other? In order to answer, two approaches, namely a latent class model (mixture of multinomial distributions) and a partition around medoids one, are evaluated and compared by Adjusted Rand Index, Average Silhouette Width and Pearson-Gamma indexes in a fairly wide simulation study. Simulation outcomes are plotted in bi-dimensional graphs via Multidimensional Scaling; size of points is proportional to the number of points that overlap and different colours are used according to the cluster membership.

Variabilità spaziale dei parametri di modelli afflussi-deflussi

L’invarianza spaziale dei parametri di un modello afflussi-deflussi può rivelarsi una soluzione pratica e valida nel caso si voglia stimare la disponibilità di risorsa idrica di un’area. La simulazione idrologica è infatti uno strumento molto adottato ma presenta alcune criticità legate soprattutto alla necessità di calibrare i parametri del modello. Se si opta per l’applicazione di modelli spazialmente distribuiti, utili perché in grado di rendere conto della variabilità spaziale dei fenomeni che concorrono alla formazione di deflusso, il problema è solitamente legato all’alto numero di parametri in gioco. Assumendo che alcuni di questi siano omogenei nello spazio, dunque presentino lo stesso valore sui diversi bacini, è possibile ridurre il numero complessivo dei parametri che necessitano della calibrazione. Si verifica su base statistica questa assunzione, ricorrendo alla stima dell’incertezza parametrica valutata per mezzo di un algoritmo MCMC. Si nota che le distribuzioni dei parametri risultano in diversa misura compatibili sui bacini considerati. Quando poi l’obiettivo è la stima della disponibilità di risorsa idrica di bacini non strumentati, l’ipotesi di invarianza dei parametri assume ancora più importanza; solitamente infatti si affronta questo problema ricorrendo a lunghe analisi di regionalizzazione dei parametri. In questa sede invece si propone una procedura di cross-calibrazione che viene realizzata adottando le informazioni provenienti dai bacini strumentati più simili al sito di interesse. Si vuole raggiungere cioè un giusto compromesso tra lo svantaggio derivante dall’assumere i parametri del modello costanti sui bacini strumentati e il beneficio legato all’introduzione, passo dopo passo, di nuove e importanti informazioni derivanti dai bacini strumentati coinvolti nell’analisi. I risultati dimostrano l’utilità della metodologia proposta; si vede infatti che, in fase di validazione sul bacino considerato non strumentato, è possibile raggiungere un buona concordanza tra le serie di portata simulate e osservate.

Homogeneous analysis of a sample of Open Clusters in the context of the BOCCE project and the Gaia-ESO Survey

The open clusters (OC) are gravitationally bound systems of a few tens or hundreds of stars. In our Galaxy, the Milky Way, we know about 3000 open clusters, of very different ages in the range of a few millions years to about 9 Gyr. OCs are mainly located in the Galactic thin disc, with distances from the Galactic centre in the range 4-22 kpc and a height scale on the disc of about 200 pc. Their chemical properties trace those of the environment in which they formed and the metallicity is in the range -0.5<[Fe/H]<+0.5 dex. Through photometry and spectroscopy it is possible to study relatively easily the properties of the OCs and estimate their age, distance, and chemistry. For these reasons they are considered primary tracers of the chemical properties and chemical evolution of the Galactic disc. The main subject of this thesis is the comprehensive study of several OCs. The research embraces two different projects: the Bologna Open Cluster Chemical Evolution project (BOCCE) and the Gaia-ESO Survey. The first is a long-term programme, aiming at studying the chemical evolution of the Milky Way disc by means of a homogeneous sample of OCs. The latter is a large public spectroscopy survey, conducted with the high-resolution spectrograph FLAMES@VLT and targeting about 10^5 stars in different part of the Galaxy and 10^4 stars in about 100 OCs. The common ground between the two projects is the study of the properties of the OCs as tracers of the disc's characteristics. The impressive scientific outcome of the Gaia-ESO Survey and the unique framework of homogeneity of the BOCCE project can propose, especially once combined together, a much more accurate description of the properties of the OCs. In turn, this will give fundamental constraints for the interpretation of the properties of the Galactic disc.