Repertory of best practices to mitigate the effects of climate change and expand the resilience of the Built Environment.

The way we live has revealed a lot about the choices made in the last decades. These choices are mostly based on a predatory socioeconomic structure, based on the pillars of anthropocentrism and inconsistent with the principles of global sustainability. This structure based on fossil fuels degrades the environment and directly and indirectly impacts the biomes. According to The International Energy Agency (2020), the sector was responsible for more than a third of global energy consumption and 40% of total GHG emissions into the atmosphere (directly and indirectly). This thesis presents the main effects of climate change observed in the built environment and at the urban territorial scale, through a review of the state of the art of the subject in the last decade (2010-2021). The thesis breaks down the projectual process seeking to identify how the architect and urban planner can mitigate the effects of climate change, adapting existing structures or in projects, and also promoting the expansion of the resilience of these building systems.

Digital 3D reconstruction as a research environment in art and architecture history: uncertainty classification and visualisation

The dissertation addresses the still not solved challenges concerned with the source-based digital 3D reconstruction, visualisation and documentation in the domain of archaeology, art and architecture history. The emerging BIM methodology and the exchange data format IFC are changing the way of collaboration, visualisation and documentation in the planning, construction and facility management process. The introduction and development of the Semantic Web (Web 3.0), spreading the idea of structured, formalised and linked data, offers semantically enriched human- and machine-readable data. In contrast to civil engineering and cultural heritage, academic object-oriented disciplines, like archaeology, art and architecture history, are acting as outside spectators. Since the 1990s, it has been argued that a 3D model is not likely to be considered a scientific reconstruction unless it is grounded on accurate documentation and visualisation. However, these standards are still missing and the validation of the outcomes is not fulfilled. Meanwhile, the digital research data remain ephemeral and continue to fill the growing digital cemeteries. This study focuses, therefore, on the evaluation of the source-based digital 3D reconstructions and, especially, on uncertainty assessment in the case of hypothetical reconstructions of destroyed or never built artefacts according to scientific principles, making the models shareable and reusable by a potentially wide audience. The work initially focuses on terminology and on the definition of a workflow especially related to the classification and visualisation of uncertainty. The workflow is then applied to specific cases of 3D models uploaded to the DFG repository of the AI Mainz. In this way, the available methods of documenting, visualising and communicating uncertainty are analysed. In the end, this process will lead to a validation or a correction of the workflow and the initial assumptions, but also (dealing with different hypotheses) to a better definition of the levels of uncertainty.

The assessment of change in rural landscape and the analysis of the driving forces. Proposal of a spatial model for the rural built environment

The presented study carried out an analysis on rural landscape changes. In particular the study focuses on the understanding of driving forces acting on the rural built environment using a statistical spatial model implemented through GIS techniques. It is well known that the study of landscape changes is essential for a conscious decision making in land planning. From a bibliography review results a general lack of studies dealing with the modeling of rural built environment and hence a theoretical modelling approach for such purpose is needed. The advancement in technology and modernity in building construction and agriculture have gradually changed the rural built environment. In addition, the phenomenon of urbanization of a determined the construction of new volumes that occurred beside abandoned or derelict rural buildings. Consequently there are two types of transformation dynamics affecting mainly the rural built environment that can be observed: the conversion of rural buildings and the increasing of building numbers. It is the specific aim of the presented study to propose a methodology for the development of a spatial model that allows the identification of driving forces that acted on the behaviours of the building allocation. In fact one of the most concerning dynamic nowadays is related to an irrational expansion of buildings sprawl across landscape. The proposed methodology is composed by some conceptual steps that cover different aspects related to the development of a spatial model: the selection of a response variable that better describe the phenomenon under study, the identification of possible driving forces, the sampling methodology concerning the collection of data, the most suitable algorithm to be adopted in relation to statistical theory and method used, the calibration process and evaluation of the model. A different combination of factors in various parts of the territory generated favourable or less favourable conditions for the building allocation and the existence of buildings represents the evidence of such optimum. Conversely the absence of buildings expresses a combination of agents which is not suitable for building allocation. Presence or absence of buildings can be adopted as indicators of such driving conditions, since they represent the expression of the action of driving forces in the land suitability sorting process. The existence of correlation between site selection and hypothetical driving forces, evaluated by means of modeling techniques, provides an evidence of which driving forces are involved in the allocation dynamic and an insight on their level of influence into the process. GIS software by means of spatial analysis tools allows to associate the concept of presence and absence with point futures generating a point process. Presence or absence of buildings at some site locations represent the expression of these driving factors interaction. In case of presences, points represent locations of real existing buildings, conversely absences represent locations were buildings are not existent and so they are generated by a stochastic mechanism. Possible driving forces are selected and the existence of a causal relationship with building allocations is assessed through a spatial model. The adoption of empirical statistical models provides a mechanism for the explanatory variable analysis and for the identification of key driving variables behind the site selection process for new building allocation. The model developed by following the methodology is applied to a case study to test the validity of the methodology. In particular the study area for the testing of the methodology is represented by the New District of Imola characterized by a prevailing agricultural production vocation and were transformation dynamic intensively occurred. The development of the model involved the identification of predictive variables (related to geomorphologic, socio-economic, structural and infrastructural systems of landscape) capable of representing the driving forces responsible for landscape changes.. The calibration of the model is carried out referring to spatial data regarding the periurban and rural area of the study area within the 1975-2005 time period by means of Generalised linear model. The resulting output from the model fit is continuous grid surface where cells assume values ranged from 0 to 1 of probability of building occurrences along the rural and periurban area of the study area. Hence the response variable assesses the changes in the rural built environment occurred in such time interval and is correlated to the selected explanatory variables by means of a generalized linear model using logistic regression. Comparing the probability map obtained from the model to the actual rural building distribution in 2005, the interpretation capability of the model can be evaluated. The proposed model can be also applied to the interpretation of trends which occurred in other study areas, and also referring to different time intervals, depending on the availability of data. The use of suitable data in terms of time, information, and spatial resolution and the costs related to data acquisition, pre-processing, and survey are among the most critical aspects of model implementation. Future in-depth studies can focus on using the proposed model to predict short/medium-range future scenarios for the rural built environment distribution in the study area. In order to predict future scenarios it is necessary to assume that the driving forces do not change and that their levels of influence within the model are not far from those assessed for the time interval used for the calibration.

Speleogenesis and secondary cave minerals in quartz-sandstone and quartzite environment

The main objective of this research is to improve the comprehension of the processes controlling the formation of caves and karst-like morphologies in quartz-rich lithologies (more than 90% quartz), like quartz-sandstones and metamorphic quartzites. In the scientific community the processes actually most retained to be responsible of these formations are explained in the “Arenisation Theory”. This implies a slow but pervasive dissolution of the quartz grain/mineral boundaries increasing the general porosity until the rock becomes incohesive and can be easily eroded by running waters. The loose sands produced by the weathering processes are then evacuated to the surface through processes of piping due to the infiltration of waters from the fracture network or the bedding planes. To deal with these problems we adopted a multidisciplinary approach through the exploration and the study of several cave systems in different tepuis. The first step was to build a theoretical model of the arenisation process, considering the most recent knowledge about the dissolution kinetics of quartz, the intergranular/grain boundaries diffusion processes, the primary diffusion porosity, in the simplified conditions of an open fracture crossed by a continuous flow of undersatured water. The results of the model were then compared with the world’s widest dataset (more than 150 analyses) of water geochemistry collected till now on the tepui, in superficial and cave settings. All these studies allowed verifying the importance and the effectiveness of the arenisation process that is confirmed to be the main process responsible of the primary formation of these caves and of the karst-like superficial morphologies. The numerical modelling and the field observations allowed evaluating a possible age of the cave systems around 20-30 million of years.

Toxoplasma gondii in animals and the environment

Toxoplasma gondii is an obligate intracellular parasite capable of infecting virtually all warm-blooded species, including humans, but cats are the only definitive hosts. Humans or animals acquire T. gondii infection by ingesting food or water contaminated with sporulated oocysts or by ingesting tissue cysts containing bradyzoites. Toxoplasmosis has the highest human incidence among zoonotic parasitic diseases, but it is still considered an underreported zoonosis. The importance of T. gondii primary infection in livestock is related to the ability of the parasite to produce tissue cysts in infected animals, which may represent important sources of infection for humans. Consumption of undercooked mutton and pork are considered important sources of human Toxoplasma gondii. The first aim of this thesis was to develop a rapid and sensitive in- house indirect ELISA for the detection of antibodies against T. gondii in sheep sera. ROC-curve analysis showed high discriminatory power (AUC=0.999) and high sensitivity (99.4%) and specificity (99.8%) of the method. The ELISA was used to test a batch of sheep sera (375) collected in the Forli-Cesena district. The overall prevalence was estimated at 41.9% demonstrating that T. gondii infection is widely distributed in sheep reared in Forli-Cesena district. Since the epidemiological impact of waterborne transmission route of T.gondii to humans is now thought to be more significant than previously believed, the second aim of the thesis was to evaluate PCR based methods for detecting T. gondii DNA in raw and finished drinking water samples collected in Scotland. Samples were tested using a quantitative PCR on 529 bp repetitive elements. Only one raw water sample (0.3%), out of the 358 examined, tested T. gondii positive demonstrating that there is no evidence that tap water is a source of Toxoplasma infection in Scotland.

Improvement of The Driver Simulator Control and Comparison Between Driver-Road-Vehicle Interaction in Real and Simulated Environment

The present doctoral thesis discusses the ways to improve the performance of driving simulator, provide objective measures for the road safety evaluation methodology based on driver’s behavior and response and investigates the drivers' adaptation to the driving assistant systems. The activities are divided into two macro areas; the driving simulation studies and on-road experiments. During the driving simulation experimentation, the classical motion cueing algorithm with logarithmic scale was implemented in the 2DOF motion cueing simulator and the motion cues were found desirable by the participants. In addition, it found out that motion stimuli could change the behaviour of the drivers in terms of depth/distance perception. During the on-road experimentations, The driver gaze behaviour was investigated to find the objective measures on the visibility of the road signs and reaction time of the drivers. The sensor infusion and the vehicle monitoring instruments were found useful for an objective assessment of the pavement condition and the drivers’ performance. In the last chapter of the thesis, the safety assessment during the use of level 1 automated driving “ACC” is discussed with the simulator and on-road experiment. The drivers’ visual behaviour was investigated in both studies with innovative classification method to find the epochs of the distraction of the drivers. The behavioural adaptation to ACC showed that drivers may divert their attention away from the driving task to engage in secondary, non-driving-related tasks.

Exploiting the environment for structural health monitoring: Strategies, algorithms, and technologies

A densely built environment is a complex system of infrastructure, nature, and people closely interconnected and interacting. Vehicles, public transport, weather action, and sports activities constitute a manifold set of excitation and degradation sources for civil structures. In this context, operators should consider different factors in a holistic approach for assessing the structural health state. Vibration-based structural health monitoring (SHM) has demonstrated great potential as a decision-supporting tool to schedule maintenance interventions. However, most excitation sources are considered an issue for practical SHM applications since traditional methods are typically based on strict assumptions on input stationarity. Last-generation low-cost sensors present limitations related to a modest sensitivity and high noise floor compared to traditional instrumentation. If these devices are used for SHM in urban scenarios, short vibration recordings collected during high-intensity events and vehicle passage may be the only available datasets with a sufficient signal-to-noise ratio. While researchers have spent efforts to mitigate the effects of short-term phenomena in vibration-based SHM, the ultimate goal of this thesis is to exploit them and obtain valuable information on the structural health state. First, this thesis proposes strategies and algorithms for smart sensors operating individually or in a distributed computing framework to identify damage-sensitive features based on instantaneous modal parameters and influence lines. Ordinary traffic and people activities become essential sources of excitation, while human-powered vehicles, instrumented with smartphones, take the role of roving sensors in crowdsourced monitoring strategies. The technical and computational apparatus is optimized using in-memory computing technologies. Moreover, identifying additional local features can be particularly useful to support the damage assessment of complex structures. Thereby, smart coatings are studied to enable the self-sensing properties of ordinary structural elements. In this context, a machine-learning-aided tomography method is proposed to interpret the data provided by a nanocomposite paint interrogated electrically.