The condition assessment of existing buildings with special reference to the analysis of degradation level has been extensively and fruitfully applied in the field of maintenance and monitoring. This paper presents a methodology for detecting structural degradation of the building that can be implemented in a decision support system consisting in a platform connected with smart devices. The proposed procedure is suitable for calculating the degradation of the building through a set of key performance indices and an optimized analytic hierarchy process. In addition, the methodology is calibrated through the well-known Tuutti model to consider the damage evolution of reinforcements’ corrosion. The results show that this calibration increases the accuracy of the assessment but reduces the robustness of the method. Moreover, an optimal calibration point is identified by exploiting the results of a set of case studies performed in Italy, Portugal, and Brazil. Finally, the method is compared with a similar approach for the degradation analysis developed in the University of Brasilia.

Structural Degradation Assessment of RC Buildings: Calibration and Comparison of Semeiotic-Based Methodology for Decision Support System

Valentino Sangiorgio
;
Giuseppina Uva;Fabio Fatiguso
2019-01-01

Abstract

The condition assessment of existing buildings with special reference to the analysis of degradation level has been extensively and fruitfully applied in the field of maintenance and monitoring. This paper presents a methodology for detecting structural degradation of the building that can be implemented in a decision support system consisting in a platform connected with smart devices. The proposed procedure is suitable for calculating the degradation of the building through a set of key performance indices and an optimized analytic hierarchy process. In addition, the methodology is calibrated through the well-known Tuutti model to consider the damage evolution of reinforcements’ corrosion. The results show that this calibration increases the accuracy of the assessment but reduces the robustness of the method. Moreover, an optimal calibration point is identified by exploiting the results of a set of case studies performed in Italy, Portugal, and Brazil. Finally, the method is compared with a similar approach for the degradation analysis developed in the University of Brasilia.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11589/161070
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