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The present research paper properly focuses on the dynamics and failure mechanisms of the masonry "Apennine Church" of Santissimo Crocifisso in Pretare, municipality of Arquata del Tronto in the province of Ascoli Piceno (Marche region, Central Italy). Such a peculiar structural type traditionally characterizes the intense seismic area of Central Italy, unfortunately almost totally damaged by the recent shock sequence of 2016. Advanced numerical modeling through discontinuous and continuous approaches were here utilized to have an insight into the dynamic properties and behavior of the structure under strong nonlinear dynamic excitations. In the discrete element approach, the non-smooth contact dynamics method, implemented in LMGC90©, was applied, adopting a full 3D detailed discretization. The church was schematized as an arrangement of rigid blocks, subjected to sliding by friction and perfect plastic collisions, with a null restitution coefficient. In the finite element approach, the concrete damaged plasticity model available in Midas FEA NX© was involved. This model allows reproducing the tensile cracking, the compressive crushing, and the degradation of the material under cyclic loads. Finally, the numerical analyses provided a valuable picture of the actual behavior of the church, thus giving useful hints for future strengthening interventions. [ABSTRACT FROM AUTHOR]

During recent years, the availability of innovative monitoring instrumentation has been a fundamental component in the development of efficient and reliable early warning systems (EWS). In fact, the potential to achieve high sampling frequencies, together with automatic data transmission and elaboration are key features for a near-real time approach. This paper presents a case study located in Central Italy, where the realization of an important state route required a series of preliminary surveys. The monitoring system installed on site included manual inclinometers, automatic modular underground monitoring system (MUMS) inclinometers, piezometers, and geognostic surveys. In particular, data recorded by innovative instrumentation allowed for the detection of major slope displacements that ultimately led to the landslide collapse. The implementation of advanced tools, featuring remote and automatic procedures for data sampling and elaboration, played a key role in the critical event identification and prediction. In fact, thanks to displacement data recorded by the MUMS inclinometer, it was possible to forecast the slope failure that was later confirmed during the following site inspection. Additionally, a numerical analysis was performed to better understand the mechanical behavior of the slope, back-analyze the monitored event, and to assess the stability conditions of the area of interest. [ABSTRACT FROM AUTHOR]