Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Corrosion Level Prediction with Acoustic Emission Sensing and Crack Measurements
The prediction of corrosion levels in reinforced concrete (RC) structures is crucial for damage assessment and ensuring safety. However, obtaining this information is challenging due to the complex nature of the corrosion process and difficulties encountered during on-site inspections. This research aims to develop a novel approach to determine the corrosion degree across corroded RC elements based on acoustic emission (AE) sensing and crack measurements.
Data of multiple experimental programmes at KU Leuven have been combined in an elaborate data-set of six corroded beams, which all have been monitored by AE sensing and crack measurements. AE sensing continuously detects and localises elastic waves emitted by internal damage processes, providing information on the relative corrosion degree across a structure. However, several factors such as noise filtering, element size and wave velocity have a significant impact on the localisation process. Afterwards, targeted crack measurements can be performed on the area with highest AE activity. Crack measurements provide a straightforward technique for identifying visible damage and can be related to absolute corrosion levels through empirical relations. Since crack measurements are labour intensive and are limited to surfaced damage, and AE sensing can only assess damage in relative terms, the combination of both techniques offers significant benefits. When the influencing factors of the AE localisation are properly evaluated, results show that the predicted corrosion levels indeed match the actual mass losses of the rebars well, highlighting the potential of the combined AE and crack measurement technique as an efficient and accurate corrosion monitoring method.
Corrosion Level Prediction with Acoustic Emission Sensing and Crack Measurements
The prediction of corrosion levels in reinforced concrete (RC) structures is crucial for damage assessment and ensuring safety. However, obtaining this information is challenging due to the complex nature of the corrosion process and difficulties encountered during on-site inspections. This research aims to develop a novel approach to determine the corrosion degree across corroded RC elements based on acoustic emission (AE) sensing and crack measurements.
Data of multiple experimental programmes at KU Leuven have been combined in an elaborate data-set of six corroded beams, which all have been monitored by AE sensing and crack measurements. AE sensing continuously detects and localises elastic waves emitted by internal damage processes, providing information on the relative corrosion degree across a structure. However, several factors such as noise filtering, element size and wave velocity have a significant impact on the localisation process. Afterwards, targeted crack measurements can be performed on the area with highest AE activity. Crack measurements provide a straightforward technique for identifying visible damage and can be related to absolute corrosion levels through empirical relations. Since crack measurements are labour intensive and are limited to surfaced damage, and AE sensing can only assess damage in relative terms, the combination of both techniques offers significant benefits. When the influencing factors of the AE localisation are properly evaluated, results show that the predicted corrosion levels indeed match the actual mass losses of the rebars well, highlighting the potential of the combined AE and crack measurement technique as an efficient and accurate corrosion monitoring method.
Corrosion Level Prediction with Acoustic Emission Sensing and Crack Measurements
RILEM Bookseries
Banthia, Nemkumar (Herausgeber:in) / Soleimani-Dashtaki, Salman (Herausgeber:in) / Mindess, Sidney (Herausgeber:in) / Vandecruys, Eline (Autor:in) / Van Steen, Charlotte (Autor:in) / Martens, Constantijn (Autor:in) / Lombaert, Geert (Autor:in) / Verstrynge, Els (Autor:in)
Interdisciplinary Symposium on Smart & Sustainable Infrastructures ; 2023 ; Vancouver, BC, Canada
Smart & Sustainable Infrastructure: Building a Greener Tomorrow ; Kapitel: 102 ; 1166-1177
RILEM Bookseries ; 48
20.02.2024
12 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
| British Library Online Contents | 2018
| British Library Online Contents | 2018
| British Library Online Contents | 2018
Implementation of Acoustic Emission Source Recognition for Corrosion Severity Prediction
| British Library Online Contents | 2011