Development of quantitative methods for sustainability assessment in process industry

The increasing aversion to technological risks of the society requires the development of inherently safer and environmentally friendlier processes, besides assuring the economic competitiveness of the industrial activities. The different forms of impact (e.g. environmental, economic and societal) are frequently characterized by conflicting reduction strategies and must be holistically taken into account in order to identify the optimal solutions in process design. Though the literature reports an extensive discussion of strategies and specific principles, quantitative assessment tools are required to identify the marginal improvements in alternative design options, to allow the trade-off among contradictory aspects and to prevent the “risk shift”. In the present work a set of integrated quantitative tools for design assessment (i.e. design support system) was developed. The tools were specifically dedicated to the implementation of sustainability and inherent safety in process and plant design activities, with respect to chemical and industrial processes in which substances dangerous for humans and environment are used or stored. The tools were mainly devoted to the application in the stages of “conceptual” and “basic design”, when the project is still open to changes (due to the large number of degrees of freedom) which may comprise of strategies to improve sustainability and inherent safety. The set of developed tools includes different phases of the design activities, all through the lifecycle of a project (inventories, process flow diagrams, preliminary plant lay-out plans). The development of such tools gives a substantial contribution to fill the present gap in the availability of sound supports for implementing safety and sustainability in early phases of process design. The proposed decision support system was based on the development of a set of leading key performance indicators (KPIs), which ensure the assessment of economic, societal and environmental impacts of a process (i.e. sustainability profile). The KPIs were based on impact models (also complex), but are easy and swift in the practical application. Their full evaluation is possible also starting from the limited data available during early process design. Innovative reference criteria were developed to compare and aggregate the KPIs on the basis of the actual sitespecific impact burden and the sustainability policy. Particular attention was devoted to the development of reliable criteria and tools for the assessment of inherent safety in different stages of the project lifecycle. The assessment follows an innovative approach in the analysis of inherent safety, based on both the calculation of the expected consequences of potential accidents and the evaluation of the hazards related to equipment. The methodology overrides several problems present in the previous methods proposed for quantitative inherent safety assessment (use of arbitrary indexes, subjective judgement, build-in assumptions, etc.). A specific procedure was defined for the assessment of the hazards related to the formations of undesired substances in chemical systems undergoing “out of control” conditions. In the assessment of layout plans, “ad hoc” tools were developed to account for the hazard of domino escalations and the safety economics. The effectiveness and value of the tools were demonstrated by the application to a large number of case studies concerning different kinds of design activities (choice of materials, design of the process, of the plant, of the layout) and different types of processes/plants (chemical industry, storage facilities, waste disposal). An experimental survey (analysis of the thermal stability of isomers of nitrobenzaldehyde) provided the input data necessary to demonstrate the method for inherent safety assessment of materials.

Computational methods for the analysis of protein structure and function

The vast majority of known proteins have not yet been experimentally characterized and little is known about their function. The design and implementation of computational tools can provide insight into the function of proteins based on their sequence, their structure, their evolutionary history and their association with other proteins. Knowledge of the three-dimensional (3D) structure of a protein can lead to a deep understanding of its mode of action and interaction, but currently the structures of <1% of sequences have been experimentally solved. For this reason, it became urgent to develop new methods that are able to computationally extract relevant information from protein sequence and structure. The starting point of my work has been the study of the properties of contacts between protein residues, since they constrain protein folding and characterize different protein structures. Prediction of residue contacts in proteins is an interesting problem whose solution may be useful in protein folding recognition and de novo design. The prediction of these contacts requires the study of the protein inter-residue distances related to the specific type of amino acid pair that are encoded in the so-called contact map. An interesting new way of analyzing those structures came out when network studies were introduced, with pivotal papers demonstrating that protein contact networks also exhibit small-world behavior. In order to highlight constraints for the prediction of protein contact maps and for applications in the field of protein structure prediction and/or reconstruction from experimentally determined contact maps, I studied to which extent the characteristic path length and clustering coefficient of the protein contacts network are values that reveal characteristic features of protein contact maps. Provided that residue contacts are known for a protein sequence, the major features of its 3D structure could be deduced by combining this knowledge with correctly predicted motifs of secondary structure. In the second part of my work I focused on a particular protein structural motif, the coiled-coil, known to mediate a variety of fundamental biological interactions. Coiled-coils are found in a variety of structural forms and in a wide range of proteins including, for example, small units such as leucine zippers that drive the dimerization of many transcription factors or more complex structures such as the family of viral proteins responsible for virus-host membrane fusion. The coiled-coil structural motif is estimated to account for 5-10% of the protein sequences in the various genomes. Given their biological importance, in my work I introduced a Hidden Markov Model (HMM) that exploits the evolutionary information derived from multiple sequence alignments, to predict coiled-coil regions and to discriminate coiled-coil sequences. The results indicate that the new HMM outperforms all the existing programs and can be adopted for the coiled-coil prediction and for large-scale genome annotation. Genome annotation is a key issue in modern computational biology, being the starting point towards the understanding of the complex processes involved in biological networks. The rapid growth in the number of protein sequences and structures available poses new fundamental problems that still deserve an interpretation. Nevertheless, these data are at the basis of the design of new strategies for tackling problems such as the prediction of protein structure and function. Experimental determination of the functions of all these proteins would be a hugely time-consuming and costly task and, in most instances, has not been carried out. As an example, currently, approximately only 20% of annotated proteins in the Homo sapiens genome have been experimentally characterized. A commonly adopted procedure for annotating protein sequences relies on the "inheritance through homology" based on the notion that similar sequences share similar functions and structures. This procedure consists in the assignment of sequences to a specific group of functionally related sequences which had been grouped through clustering techniques. The clustering procedure is based on suitable similarity rules, since predicting protein structure and function from sequence largely depends on the value of sequence identity. However, additional levels of complexity are due to multi-domain proteins, to proteins that share common domains but that do not necessarily share the same function, to the finding that different combinations of shared domains can lead to different biological roles. In the last part of this study I developed and validate a system that contributes to sequence annotation by taking advantage of a validated transfer through inheritance procedure of the molecular functions and of the structural templates. After a cross-genome comparison with the BLAST program, clusters were built on the basis of two stringent constraints on sequence identity and coverage of the alignment. The adopted measure explicity answers to the problem of multi-domain proteins annotation and allows a fine grain division of the whole set of proteomes used, that ensures cluster homogeneity in terms of sequence length. A high level of coverage of structure templates on the length of protein sequences within clusters ensures that multi-domain proteins when present can be templates for sequences of similar length. This annotation procedure includes the possibility of reliably transferring statistically validated functions and structures to sequences considering information available in the present data bases of molecular functions and structures.

Study of the thermal effects induced by magnetic resonance on endocardial leads: numerical models and experimental validation

Magnetic resonance imaging (MRI) is today precluded to patients bearing active implantable medical devices AIMDs). The great advantages related to this diagnostic modality, together with the increasing number of people benefiting from implantable devices, in particular pacemakers(PM)and carioverter/defibrillators (ICD), is prompting the scientific community the study the possibility to extend MRI also to implanted patients. The MRI induced specific absorption rate (SAR) and the consequent heating of biological tissues is one of the major concerns that makes patients bearing metallic structures contraindicated for MRI scans. To date, both in-vivo and in-vitro studies have demonstrated the potentially dangerous temperature increase caused by the radiofrequency (RF) field generated during MRI procedures in the tissues surrounding thin metallic implants. On the other side, the technical evolution of MRI scanners and of AIMDs together with published data on the lack of adverse events have reopened the interest in this field and suggest that, under given conditions, MRI can be safely performed also in implanted patients. With a better understanding of the hazards of performing MRI scans on implanted patients as well as the development of MRI safe devices, we may soon enter an era where the ability of this imaging modality may be more widely used to assist in the appropriate diagnosis of patients with devices. In this study both experimental measures and numerical analysis were performed. Aim of the study is to systematically investigate the effects of the MRI RF filed on implantable devices and to identify the elements that play a major role in the induced heating. Furthermore, we aimed at developing a realistic numerical model able to simulate the interactions between an RF coil for MRI and biological tissues implanted with a PM, and to predict the induced SAR as a function of the particular path of the PM lead. The methods developed and validated during the PhD program led to the design of an experimental framework for the accurate measure of PM lead heating induced by MRI systems. In addition, numerical models based on Finite-Differences Time-Domain (FDTD) simulations were validated to obtain a general tool for investigating the large number of parameters and factors involved in this complex phenomenon. The results obtained demonstrated that the MRI induced heating on metallic implants is a real risk that represents a contraindication in extending MRI scans also to patient bearing a PM, an ICD, or other thin metallic objects. On the other side, both experimental data and numerical results show that, under particular conditions, MRI procedures might be consider reasonably safe also for an implanted patient. The complexity and the large number of variables involved, make difficult to define a unique set of such conditions: when the benefits of a MRI investigation cannot be obtained using other imaging techniques, the possibility to perform the scan should not be immediately excluded, but some considerations are always needed.

Experimental analysis of fiber reinforced cementitious matrix (FRCM) confined masonry columns

The increasing use of Fiber Reinforced methods for strengthening existing brick masonry walls and columns, especially for the rehabilitation of historical buildings, has generated considerable research interest in understanding the failure mechanism in such systems. This dissertation is aimed to provide a basic understanding of the behavior of solid brick masonry walls unwrapped and wrapped with Fiber Reinforced Cementitious Matrix Composites. This is a new type of composite material, commonly known as FRCM, featuring a cementitious inorganic matrix (binder) instead of the more common epoxy one. The influence of the FRCM-reinforcement on the load-carrying capacity and strain distribution during compression test will be investigated using a full-field optical technique known as Digital Image Correlation. Compression test were carried on 6 clay bricks columns and on 7 clay brick walls in three different configuration, casted using bricks scaled respect the first one with a ratio 1:2, in order to determinate the effects of FRCM reinforcement. The goal of the experimental program is to understand how the behavior of brick masonry will be improved by the FRCM-wrapping. The results indicate that there is an arching action zone represented in the form of a parabola with a varying shape according to the used configuration. The area under the parabolas is considered as ineffectively confined. The effectively confined area is assumed to occur within the region where the arching action had been fully developed.

Experimental Data on Fire-Resistance Behavior of Reinforced Concrete Structures with Example Calculations

This thesis selects concrete, steel and their relation as research subjects, mainly commentary and discusses the property changes of steel and concrete materials under and after high temperature.The differences and comparisons of reasearch methods and ways between different researchers and different papers,particularly for chinese researches and chinese papers,and partly for comparison between chinese papers methods and Euro-Amercian papers methods about Fire Resistance Behavior of Reinforced Concrete will be summarized and analyzed.The researches on fire-resistance behavior of reinforced concrete become more and more important all over the world. And I would find differences between Chinese researches results, between Chinese researches results and other countries researches results.

Characterisation of supramolecular structures by novel recoupling methods in solid-state NMR

In this work, solid-state NMR methods suitable for the investigation of supramolecular systems were developed and improved. In this context, special interest was focussed on non-covalent interactions responsible for the formation of supramolecular structures, such as pi-pi interacions and hydrogen-bonds. In the first part of this work, solid-state NMR methods were presented that provide information on molecular structure and motion via the investigation of anisotropic interactions, namely quadrupole and dipole-dipole couplings, under magic-angle spinning conditions. A two-dimensional 2H double quantum experiment was developed, which is performed under off magic-angle conditions and correlates 2H isotropic chemical shifts with quasistatic DQ-filtered line shapes. From the latter, the quadrupole coupling parameters of samples deuterated at multiple sites can be extracted in a site-selective fashion. Furthermore, 7Li quadrupole parameters of lithium intercalated into TiO2 were determined by NMR experiments performed under static and MAS conditions, and could provide information on the crystal geometry. For the determination of 7Li-7Li dipole-dipole couplings, multiple-quantum NMR experiments were performed. The 1H-13C REREDOR experiment was found to be capable of determining strong proton-carbon dipole-dipole couplings with an accuracy of 500~Hz, corresponding to a determination of proton-carbon chemical-bond lengths with picometer accuracy In the second part of this work, solid-state NMR experiments were combined with quantum-chemical calculations in order to aid and optimise the interpretation of experimental results. The investigations on Calix[4]hydroquinone nanotubes have shown that this combined approach can provide information on the presence of disordered and/or mobile species in supramolecular structures. As a second example, C3-symmetric discs arranging in helical columnar stacks were investigated. In these systems, 1H chemical shifts experience large pi-shifts due to packing effects, which were found to be long-ranged. Moreover, quantum-chemical calculations revealed that helicity in these systems is induced by the propeller-like conformation of the core of the molecules.

Hybrid constraint programming and metaheuristic methods for large scale optimization problems

This work presents hybrid Constraint Programming (CP) and metaheuristic methods for the solution of Large Scale Optimization Problems; it aims at integrating concepts and mechanisms from the metaheuristic methods to a CP-based tree search environment in order to exploit the advantages of both approaches. The modeling and solution of large scale combinatorial optimization problem is a topic which has arisen the interest of many researcherers in the Operations Research field; combinatorial optimization problems are widely spread in everyday life and the need of solving difficult problems is more and more urgent. Metaheuristic techniques have been developed in the last decades to effectively handle the approximate solution of combinatorial optimization problems; we will examine metaheuristics in detail, focusing on the common aspects of different techniques. Each metaheuristic approach possesses its own peculiarities in designing and guiding the solution process; our work aims at recognizing components which can be extracted from metaheuristic methods and re-used in different contexts. In particular we focus on the possibility of porting metaheuristic elements to constraint programming based environments, as constraint programming is able to deal with feasibility issues of optimization problems in a very effective manner. Moreover, CP offers a general paradigm which allows to easily model any type of problem and solve it with a problem-independent framework, differently from local search and metaheuristic methods which are highly problem specific. In this work we describe the implementation of the Local Branching framework, originally developed for Mixed Integer Programming, in a CP-based environment. Constraint programming specific features are used to ease the search process, still mantaining an absolute generality of the approach. We also propose a search strategy called Sliced Neighborhood Search, SNS, that iteratively explores slices of large neighborhoods of an incumbent solution by performing CP-based tree search and encloses concepts from metaheuristic techniques. SNS can be used as a stand alone search strategy, but it can alternatively be embedded in existing strategies as intensification and diversification mechanism. In particular we show its integration within the CP-based local branching. We provide an extensive experimental evaluation of the proposed approaches on instances of the Asymmetric Traveling Salesman Problem and of the Asymmetric Traveling Salesman Problem with Time Windows. The proposed approaches achieve good results on practical size problem, thus demonstrating the benefit of integrating metaheuristic concepts in CP-based frameworks.

Machine-learning methods for structure prediction of β-barrel membrane proteins

Different types of proteins exist with diverse functions that are essential for living organisms. An important class of proteins is represented by transmembrane proteins which are specifically designed to be inserted into biological membranes and devised to perform very important functions in the cell such as cell communication and active transport across the membrane. Transmembrane β-barrels (TMBBs) are a sub-class of membrane proteins largely under-represented in structure databases because of the extreme difficulty in experimental structure determination. For this reason, computational tools that are able to predict the structure of TMBBs are needed. In this thesis, two computational problems related to TMBBs were addressed: the detection of TMBBs in large datasets of proteins and the prediction of the topology of TMBB proteins. Firstly, a method for TMBB detection was presented based on a novel neural network framework for variable-length sequence classification. The proposed approach was validated on a non-redundant dataset of proteins. Furthermore, we carried-out genome-wide detection using the entire Escherichia coli proteome. In both experiments, the method significantly outperformed other existing state-of-the-art approaches, reaching very high PPV (92%) and MCC (0.82). Secondly, a method was also introduced for TMBB topology prediction. The proposed approach is based on grammatical modelling and probabilistic discriminative models for sequence data labeling. The method was evaluated using a newly generated dataset of 38 TMBB proteins obtained from high-resolution data in the PDB. Results have shown that the model is able to correctly predict topologies of 25 out of 38 protein chains in the dataset. When tested on previously released datasets, the performances of the proposed approach were measured as comparable or superior to the current state-of-the-art of TMBB topology prediction.

Methods for the Quantification of Motor Stability for the Assessment of Fall Risk

The research field of the Thesis is the evaluation of motor variability and the analysis of motor stability for the assessment of fall risk. Since many falls occur during walking, a better understanding of motor stability could lead to the definition of a reliable fall risk index aiming at measuring and assessing the risk of fall in the elderly, in the attempt to prevent traumatic events. Several motor variability and stability measures are proposed in the literature, but still a proper methodological characterization is lacking. Moreover, the relationship between many of these measures and fall history or fall risk is still unknown, or not completely clear. The aim of this thesis is hence to: i) analyze the influence of experimental implementation parameters on variability/stability measures and understand how variations in these parameters affect the outputs; ii) assess the relationship between variability/stability measures and long- short-term fall history. Several implementation issues have been addressed. Following the need for a methodological standardization of gait variability/stability measures, highlighted in particular for orbital stability analysis through a systematic review, general indications about implementation of orbital stability analysis have been showed, together with an analysis of the number of strides and the test-retest reliability of several variability/stability numbers. Indications about the influence of directional changes on measures have been provided. The association between measures and long/short-term fall history has also been assessed. Of all the analyzed variability/stability measures, Multiscale entropy and Recurrence quantification analysis demonstrated particularly good results in terms of reliability, applicability and association with fall history. Therefore, these measures should be taken in consideration for the definition of a fall risk index.

Power Transient Analysis of Experimental Devices for Jules Horowitz Material Testing Reactor (JHR)

The objective of this thesis is the power transient analysis concerning experimental devices placed within the reflector of Jules Horowitz Reactor (JHR). Since JHR material testing facility is designed to achieve 100 MW core thermal power, a large reflector hosts fissile material samples that are irradiated up to total relevant power of 3 MW. MADISON devices are expected to attain 130 kW, conversely ADELINE nominal power is of some 60 kW. In addition, MOLFI test samples are envisaged to reach 360 kW for what concerns LEU configuration and up to 650 kW according to HEU frame. Safety issues concern shutdown transients and need particular verifications about thermal power decreasing of these fissile samples with respect to core kinetics, as far as single device reactivity determination is concerned. Calculation model is conceived and applied in order to properly account for different nuclear heating processes and relative time-dependent features of device transients. An innovative methodology is carried out since flux shape modification during control rod insertions is investigated regarding the impact on device power through core-reflector coupling coefficients. In fact, previous methods considering only nominal core-reflector parameters are then improved. Moreover, delayed emissions effect is evaluated about spatial impact on devices of a diffuse in-core delayed neutron source. Delayed gammas transport related to fission products concentration is taken into account through evolution calculations of different fuel compositions in equilibrium cycle. Provided accurate device reactivity control, power transients are then computed for every sample according to envisaged shutdown procedures. Results obtained in this study are aimed at design feedback and reactor management optimization by JHR project team. Moreover, Safety Report is intended to utilize present analysis for improved device characterization.

Coarse-graining methods and polymer dynamics

This thesis studies molecular dynamics simulations on two levels of resolution: the detailed level of atomistic simulations, where the motion of explicit atoms in a many-particle system is considered, and the coarse-grained level, where the motion of superatoms composed of up to 10 atoms is modeled. While atomistic models are capable of describing material specific effects on small scales, the time and length scales they can cover are limited due to their computational costs. Polymer systems are typically characterized by effects on a broad range of length and time scales. Therefore it is often impossible to atomistically simulate processes, which determine macroscopic properties in polymer systems. Coarse-grained (CG) simulations extend the range of accessible time and length scales by three to four orders of magnitude. However, no standardized coarse-graining procedure has been established yet. Following the ideas of structure-based coarse-graining, a coarse-grained model for polystyrene is presented. Structure-based methods parameterize CG models to reproduce static properties of atomistic melts such as radial distribution functions between superatoms or other probability distributions for coarse-grained degrees of freedom. Two enhancements of the coarse-graining methodology are suggested. Correlations between local degrees of freedom are implicitly taken into account by additional potentials acting between neighboring superatoms in the polymer chain. This improves the reproduction of local chain conformations and allows the study of different tacticities of polystyrene. It also gives better control of the chain stiffness, which agrees perfectly with the atomistic model, and leads to a reproduction of experimental results for overall chain dimensions, such as the characteristic ratio, for all different tacticities. The second new aspect is the computationally cheap development of nonbonded CG potentials based on the sampling of pairs of oligomers in vacuum. Static properties of polymer melts are obtained as predictions of the CG model in contrast to other structure-based CG models, which are iteratively refined to reproduce reference melt structures. The dynamics of simulations at the two levels of resolution are compared. The time scales of dynamical processes in atomistic and coarse-grained simulations can be connected by a time scaling factor, which depends on several specific system properties as molecular weight, density, temperature, and other components in mixtures. In this thesis the influence of molecular weight in systems of oligomers and the situation in two-component mixtures is studied. For a system of small additives in a melt of long polymer chains the temperature dependence of the additive diffusion is predicted and compared to experiments.

Numerical methods for the dispersion analysis of Guided Waves

The use of guided ultrasonic waves (GUW) has increased considerably in the fields of non-destructive (NDE) testing and structural health monitoring (SHM) due to their ability to perform long range inspections, to probe hidden areas as well as to provide a complete monitoring of the entire waveguide. Guided waves can be fully exploited only once their dispersive properties are known for the given waveguide. In this context, well stated analytical and numerical methods are represented by the Matrix family methods and the Semi Analytical Finite Element (SAFE) methods. However, while the former are limited to simple geometries of finite or infinite extent, the latter can model arbitrary cross-section waveguides of finite domain only. This thesis is aimed at developing three different numerical methods for modelling wave propagation in complex translational invariant systems. First, a classical SAFE formulation for viscoelastic waveguides is extended to account for a three dimensional translational invariant static prestress state. The effect of prestress, residual stress and applied loads on the dispersion properties of the guided waves is shown. Next, a two-and-a-half Boundary Element Method (2.5D BEM) for the dispersion analysis of damped guided waves in waveguides and cavities of arbitrary cross-section is proposed. The attenuation dispersive spectrum due to material damping and geometrical spreading of cavities with arbitrary shape is shown for the first time. Finally, a coupled SAFE-2.5D BEM framework is developed to study the dispersion characteristics of waves in viscoelastic waveguides of arbitrary geometry embedded in infinite solid or liquid media. Dispersion of leaky and non-leaky guided waves in terms of speed and attenuation, as well as the radiated wavefields, can be computed. The results obtained in this thesis can be helpful for the design of both actuation and sensing systems in practical application, as well as to tune experimental setup.

Experimental investigation of the reactions 25 Mg(alpha,n)28 Si, 26 Mg(alpha,n)29 Si, 18 O(alpha,n)21 Ne and their impact on stellar nucleosynthesis

In der vorliegenden Dissertation werden die Kernreaktionen 25Mg(alpha,n)28Si, 26Mg(alpha,n)29Si und 18O(alpha,n)21Ne im astrophysikalisch interessanten Energiebereich von E alpha = 1000 keV bis E alpha = 2450 keV untersucht.rnrnDie Experimente wurden am Nuclear Structure Laboratory der University of Notre Dame (USA) mit dem vor Ort befindlichen Van-de-Graaff Beschleuniger KN durchgeführt. Hierbei wurden Festkörpertargets mit evaporiertem Magnesium oder anodisiertem Sauerstoff mit alpha-Teilchen beschossen und die freigesetzten Neutronen untersucht. Zum Nachweis der freigesetzten Neutronen wurde mit Hilfe von Computersimulationen ein Neutrondetektor basierend auf rn3He-Zählrohren konstruiert. Weiterhin wurden aufgrund des verstärkten Auftretens von Hintergrundreaktionen verschiedene Methoden zur Datenanalyse angewendet.rnrnAbschliessend wird mit Hilfe von Netzwerkrechnungen der Einfluss der Reaktionen 25Mg(alpha,n)28Si, 26Mg(alpha,n)29Si und 18O(alpha,n)21Ne auf die stellare Nukleosynthese untersucht.rn

Experimental assessment of environmental decay effects in masonry via non destructive diagnostic techniques and mechanical tests

Environmental decay in porous masonry materials, such as brick and mortar, is a widespread problem concerning both new and historic masonry structures. The decay mechanisms are quite complex dependng upon several interconnected parameters and from the interaction with the specific micro-climate. Materials undergo aesthetical and substantial changes in character but while many studies have been carried out, the mechanical aspect has been largely understudied while it bears true importance from the structural viewpoint. A quantitative assessment of the masonry material degradation and how it affects the load-bearing capacity of masonry structures appears missing. The research work carried out, limiting the attention to brick masonry addresses this issue through an experimental laboratory approach via different integrated testing procedures, both non-destructive and mechanical, together with monitoring methods. Attention was focused on transport of moisture and salts and on the damaging effects caused by the crystallization of two different salts, sodium chloride and sodium sulphate. Many series of masonry specimens, very different in size and purposes were used to track the damage process since its beginning and to monitor its evolution over a number of years Athe same time suitable testing techniques, non-destructive, mini-invasive, analytical, of monitoring, were validated for these purposes. The specimens were exposed to different aggressive agents (in terms of type of salt, of brine concentration, of artificial vs. open-air natural ageing, …), tested by different means (qualitative vs. quantitative, non destructive vs. mechanical testing, punctual vs. wide areas, …), and had different size (1-, 2-, 3-header thick walls, full-scale walls vs. small size specimens, brick columns and triplets vs. small walls, masonry specimens vs. single units of brick and mortar prisms, …). Different advanced testing methods and novel monitoring techniques were applied in an integrated holistic approach, for quantitative assessment of masonry health state.

Novel investigation methods in Computational Social Dynamics and Complex Systems

In this thesis the evolution of the techno-social systems analysis methods will be reported, through the explanation of the various research experience directly faced. The first case presented is a research based on data mining of a dataset of words association named Human Brain Cloud: validation will be faced and, also through a non-trivial modeling, a better understanding of language properties will be presented. Then, a real complex system experiment will be introduced: the WideNoise experiment in the context of the EveryAware european project. The project and the experiment course will be illustrated and data analysis will be displayed. Then the Experimental Tribe platform for social computation will be introduced . It has been conceived to help researchers in the implementation of web experiments, and aims also to catalyze the cumulative growth of experimental methodologies and the standardization of tools cited above. In the last part, three other research experience which already took place on the Experimental Tribe platform will be discussed in detail, from the design of the experiment to the analysis of the results and, eventually, to the modeling of the systems involved. The experiments are: CityRace, about the measurement of human traffic-facing strategies; laPENSOcosì, aiming to unveil the political opinion structure; AirProbe, implemented again in the EveryAware project framework, which consisted in monitoring air quality opinion shift of a community informed about local air pollution. At the end, the evolution of the technosocial systems investigation methods shall emerge together with the opportunities and the threats offered by this new scientific path.