Non-Destructive Evaluation (NDE) methods allow the acquisition of a wide range of information related to the structural performance of bridges and viaducts. Consequently, the outcomes from NDE inspections are often considered in risk assessment procedures to collect detailed information about specific parameters involved in the assessment process. As an example, the defectiveness of bridges and viaducts, usually determined after a thorough visual inspection, commonly plays a key role in assessing the vulnerability of the assets and, therefore, in determining their structural risk conditions. In common practice, the planning of NDE inspections is usually borne by the authority responsible for the bridge inventory according to the prescriptions of a selected Standard and the outcomes from past risk assessments. Due to their recurrence in time and the large number of assets they commonly involve, NDE inspections represent costly operations for management authorities, both in terms of time and economic resources. Considering this, their planning should account for the expenses for their execution in addition to the outcomes from the risk classification of the assets. This paper presents a new NDE bridge inspection prioritization method that considers both risk and cost evaluations to establish inspection priorities within bridge inventories. The information gain criterion is adopted to refine the outcomes from risk assessment and prioritization process. Contemporary, the implementation of the methodology in a GIS framework, together with the use of spatial interpolation methods for data analysis, ensure high interoperability and the rendering of macro-level informative risk maps and inspection plans.
KEYWORDS: Resistance, Structural health monitoring, Sensors, Electrodes, Data acquisition, Carbon, Nanocomposites, Scanning electron microscopy, Control systems, Data modeling
Monitoring a building’s structural performance is critical for the identification of incipient damages and the optimization of maintenance programs. The characteristics and spatial deployment of any sensing system plays an essential role in the reliability of the monitored data and, therefore, on the actual capability of the monitoring system to reveal early-stage structural damage. A promising strategy for enhancing the quality of a structural health monitoring system is the use of sensors fabricated using materials exhibiting similar mechanical properties and durability as those of the construction materials. Based on this philosophy, the authors have recently proposed the concept of "smart-bricks" that are nanocomposite clay bricks capable of transducing a change in volumetric strain into a change in a selected electrical property. Such brick-like sensors could be easily placed at critical locations within masonry walls, being an integral part of the structure itself. The sensing is enabled through the dispersion of fillers into the constitutive material. Examples of fillers include titania, carbon-based particles, and metallic microfibers. In this paper, experimental tests are conducted on bricks doped with different types of carbon-based fillers, tested both as standalone sensors and within small wall systems. Results show that mechanical properties as well as the smart brick’s strain sensitivity depend on the type of filler used. The capability of the bricks to work as strain monitoring sensors within small masonry specimens is also demonstrated.
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