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.

Scaled down physical properties of semiconductor nanowires for nanoelectronics scaling up

Semiconductor nanowires (NWs) are one- or quasi one-dimensional systems whose physical properties are unique as compared to bulk materials because of their nanoscaled sizes. They bring together quantum world and semiconductor devices. NWs-based technologies may achieve an impact comparable to that of current microelectronic devices if new challenges will be faced. This thesis primarily focuses on two different, cutting-edge aspects of research over semiconductor NW arrays as pivotal components of NW-based devices. The first part deals with the characterization of electrically active defects in NWs. It has been elaborated the set-up of a general procedure which enables to employ Deep Level Transient Spectroscopy (DLTS) to probe NW arrays’ defects. This procedure has been applied to perform the characterization of a specific system, i.e. Reactive Ion Etched (RIE) silicon NW arrays-based Schottky barrier diodes. This study has allowed to shed light over how and if growth conditions introduce defects in RIE processed silicon NWs. The second part of this thesis concerns the bowing induced by electron beam and the subsequent clustering of gallium arsenide NWs. After a justified rejection of the mechanisms previously reported in literature, an original interpretation of the electron beam induced bending has been illustrated. Moreover, this thesis has successfully interpreted the formation of NW clusters in the framework of the lateral collapse of fibrillar structures. These latter are both idealized models and actual artificial structures used to study and to mimic the adhesion properties of natural surfaces in lizards and insects (Gecko effect). Our conclusion are that mechanical and surface properties of the NWs, together with the geometry of the NW arrays, play a key role in their post-growth alignment. The same parameters open, then, to the benign possibility of locally engineering NW arrays in micro- and macro-templates.

Physico-chemical and microstructural properties of food dispersions

The macroscopic properties of oily food dispersions, such as rheology, mechanical strength, sensory attributes (e.g. mouth feel, texture and even flavour release) and as well as engineering properties are strongly determined by their microstructure, that is considered a key parameter in the understanding of the foods behaviour . In particular the rheological properties of these matrices are largely influenced by their processing techniques, particle size distribution and composition of ingredients. During chocolate manufacturing, mixtures of sugar, cocoa and fat are heated, cooled, pressurized and refined. These steps not only affect particle size reduction, but also break agglomerates and distribute lipid and lecithin-coated particles through the continuous phase, this considerably modify the microstructure of final chocolate. The interactions between the suspended particles and the continuous phase provide information about the existing network and consequently can be associated to the properties and characteristics of the final dispersions. Moreover since the macroscopic properties of food materials, are strongly determined by their microstructure, the evaluation and study of the microstructural characteristics, can be very important for a through understanding of the food matrices characteristics and to get detailed information on their complexity. The aim of this study was investigate the influence of formulation and each process step on the microstructural properties of: chocolate type model systems, dark milk and white chocolate types, and cocoa creams. At the same time the relationships between microstructural changes and the resulting physico-chemical properties of: chocolate type dispersions model systems dark milk and white chocolate were investigated.