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.

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.