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.

Elf magnetic field influence on ION Channels studied by Patch Clamp Technique: exposure set up and "Whole Cell" measurements on Potassium currents

The aim of this thesis was to study the effects of extremely low frequency (ELF) electromagnetic magnetic fields on potassium currents in neural cell lines ( Neuroblastoma SK-N-BE ), using the whole-cell Patch Clamp technique. Such technique is a sophisticated tool capable to investigate the electrophysiological activity at a single cell, and even at single channel level. The total potassium ion currents through the cell membrane was measured while exposing the cells to a combination of static (DC) and alternate (AC) magnetic fields according to the prediction of the so-called ‘ Ion Resonance Hypothesis ’. For this purpose we have designed and fabricated a magnetic field exposure system reaching a good compromise between magnetic field homogeneity and accessibility to the biological sample under the microscope. The magnetic field exposure system consists of three large orthogonal pairs of square coils surrounding the patch clamp set up and connected to the signal generation unit, able to generate different combinations of static and/or alternate magnetic fields. Such system was characterized in term of field distribution and uniformity through computation and direct field measurements. No statistically significant changes in the potassium ion currents through cell membrane were reveled when the cells were exposed to AC/DC magnetic field combination according to the afore mentioned ‘Ion Resonance Hypothesis’.

Influence of cultivar choice, sowing date and abiotic stresses on tocopherol content and composition in Camelina sativa (L.) Crantz

In Europe, the current demand for vegetable oils and the need to find alternative crops for the regions most affected by climate change (i.e., Mediterranean basin) may be a launchpad for camelina [Camelina sativa (L.) Crantz] to be steadily introduced in European cropping systems. Camelina is mainly known for the unique composition of its oil, with a fatty acids profile including more than 50% content of essential linoleic and linolenic fatty acids, and a high tocopherol content. Being tocopherols part of the vitamin E family of antioxidants, the added value of growing camelina in harsh environments could be the enhancement of tocopherol content in camelina oil, thus having a more stable and nutritionally valuable product. With the final purpose of fully valorize camelina as a tolerant, valuable-oil producing crop for the Mediterranean basin, the main aim of this study was to investigate whether and how sowing date, cultivar choice, and abiotic stresses can affect tocopherol content and composition in camelina oil. The results showed that cultivar choice and growing conditions influenced total tocopherol, γ-tocopherol, and α-tocopherol contents. Moreover, heat stress trial revealed that high temperature increased α-tocopherol content, while no effect was observed in total tocopherols and in γ-tocopherol content. Finally, drought increased total tocopherols in camelina, and in drought-sensitive lines an increase in α-tocopherol was observed. This study allowed to acquire awareness on camelina resistance to abiotic stresses, coupled with a better knowledge on tocopherol content and composition in relation to cultivar, sowing date, and abiotic stresses. This will have an impact for the introduction of camelina as an alternative crop in harsher environments, such as the Mediterranean basin, to produce an oil suitable for food, feed, and industrial applications.