PSI - Issue 64

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Available online at www.sciencedirect.com Structural Integrity Procedia 00 (2023) 000 – 000 Available online at www.sciencedirect.com ScienceDirect Structural Integrity Procedia 00 (2023) 000 – 000 Available online at www.sciencedirect.com ScienceDirect

www.elsevier.com/locate/procedia www.elsevier.com/locate/procedia

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Procedia Structural Integrity 64 (2024) 1295–1302

SMAR 2024 – 7th International Conference on Smart Monitoring, Assessment and Rehabilitation of Civil Structures Satellite monitoring of reinforced concrete buildings in areas affected by slow-moving landslides Annalisa Mele a , Chiara Di Muro b, *, Mohammad Amin Khalili b , Andrea Miano a , Massimo Ramondini c , Domenico Calcaterra b , Andrea Prota a , Diego Di Martire b a Department of Structures for Engineering and Architecture, University of Naples Federico II, Via Claudio 21, 80125, Naples, Italy b Department of Earth, Environment and Resources Sciences, University of Naples Federico II, Via Vicinale Cupa Cintia 21, 80126, Naples, Italy c Department of Civil, Architectural and Environmental Engineering, University of Naples Federico II, Via Claudio 21, 80125, Naples, Italy Abstract Slow-moving landslides are very spread phenomena in Italy and worldwide. The study of their impact on the existing structures is of great interest, since they can provoke more or less serious consequences for structures, facilities and human life safety. Traditional monitoring techniques on site are usually adopted for landslides. The innovative Differential Interferometry Synthetic Aperture Radar (DInSAR) techniques, based on the use of data derived from satellite images, constitute an advanced technology that allows to remotely monitor the deformation of large portions of land over long periods of time, with relatively low costs. These techniques are able to well capture displacements slowly evolving in time; for this reason, they fit very well with slow-moving landslides. This work follows a previous study by some of the authors, where the structural health monitoring of a reinforced concrete infilled building within a landslide-affected area was made. A finite element model of the structure was created, assuming a non-linear behavior for the structural elements, focusing on the elastic part up to yielding, while infills were modeled as diagonal struts. DInSAR data derived from the processing of COSMO-SkyMed images in the period 2012-2016 were used in order to investigate the evolution of the infills damage over the years. In this work, the monitoring period has been extended by processing new COSMO-SkyMed images, up to 2022. The prediction of the future expected displacements, shown in the previous study, has been now compared to the real displacements detected. According to them, the analysis of the expected damage on the infills has been checked. © 2024 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of SMAR 2024 Organizers SMAR 2024 – 7th International Conference on Smart Monitoring, Assessment and Rehabilitation of Civil Structures Satellite monitoring of reinforced concrete buildings in areas affected by slow-moving landslides Annalisa Mele a , Chiara Di Muro b, *, Mohammad Amin Khalili b , Andrea Miano a , Massimo Ramondini c , Domenico Calcaterra b , Andrea Prota a , Diego Di Martire b a Department of Structures for Engineering and Architecture, University of Naples Federico II, Via Claudio 21, 80125, Naples, Italy b Department of Earth, Environment and Resources Sciences, University of Naples Federico II, Via Vicinale Cupa Cintia 21, 80126, Naples, Italy c Department of Civil, Architectural and Environmental Engineering, University of Naples Federico II, Via Claudio 21, 80125, Naples, Italy Abstract Slow-moving landslides are very spread phenomena in Italy and worldwide. The study of their impact on the existing structures is of great interest, since they can provoke more or less serious consequences for structures, facilities and human life safety. Traditional monitoring techniques on site are usually adopted for landslides. The innovative Differential Interferometry Synthetic Aperture Radar (DInSAR) techniques, based on the use of data derived from satellite images, constitute an advanced technology that allows to remotely monitor the deformation of large portions of land over long periods of time, with relatively low costs. These techniques are able to well capture displacements slowly evolving in time; for this reason, they fit very well with slow-moving landslides. This work follows a previous study by some of the authors, where the structural health monitoring of a reinforced concrete infilled building within a landslide-affected area was made. A finite element model of the structure was created, assuming a non-linear behavior for the structural elements, focusing on the elastic part up to yielding, while infills were modeled as diagonal struts. DInSAR data derived from the processing of COSMO-SkyMed images in the period 2012-2016 were used in order to investigate the evolution of the infills damage over the years. In this work, the monitoring period has been extended by processing new COSMO-SkyMed images, up to 2022. The prediction of the future expected displacements, shown in the previous study, has been now compared to the real displacements detected. According to them, the analysis of the expected damage on the infills has been checked. © 2024 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of SMAR 2024 Organizers © 2024 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of SMAR 2024 Organizers

* Corresponding author. Tel.: +39 81 2532146. E-mail address: chiara.dimuro@unina.it * Corresponding author. Tel.: +39 81 2532146. E-mail address: chiara.dimuro@unina.it

2452-3216 © 2024 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of SMAR 2024 Organizers 2452-3216 © 2024 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of SMAR 2024 Organizers

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