Dynamic Characteristics Monitoring Changes of Damaged and Retrofitted RC Buildings

Gunaydin M., Adanur S., Altunisik A. C. , Mosallam A., Sevim B.

EXPERIMENTAL TECHNIQUES, 2021 (Journal Indexed in SCI) identifier identifier

  • Publication Type: Article / Article
  • Publication Date: 2021
  • Doi Number: 10.1007/s40799-021-00493-x
  • Keywords: Ambient vibration test, Carbon fiber reinforced polymer, Dynamic characteristics, Epoxy injection method, High-strength structural mortar, Stochastic subspace identification method, SEISMIC PERFORMANCE, FRAME, BEAMS, IDENTIFICATION, BEHAVIOR, JOINTS, REHABILITATION, DUCTILITY, STRENGTH, SLABS


This paper presents results of an experimental study that focuses on monitoring changes in dynamic characteristics of a damaged and retrofitted two-story reinforced concrete (RC) building model with poor detailing. In the study, ambient vibration tests are performed via four test setup protocols in order to monitor changes in dynamic characteristics before and after such setups. The four main test setups are: (i) undamaged (as-built) case (Setup # 1), (ii) damaged cases with different degrees of damages (Setup # 2), (iii) repaired case with different types of repair methods (Setup # 3), and (iv) strengthened case with externally bonded CFRP composite laminates (Setup # 4). In addition, a total of eight ambient vibration tests are conducted in order to assess the effects of degree of damage and associated retrofit systems on building's dynamic characteristics such as natural frequencies, mode shapes, and damping ratios. The Stochastic Subspace Identification (SSI) Method is used to identify the dynamic characteristics. Experimentally identified dynamic characteristics obtained from all setups are compared with each other in order to detect the effect of damage and repair applications on the structure's dynamic characteristics. Moreover, Modal Assurance Criterion (MAC) and Coordinate Modal Assurance Criterion (COMAC) are determined to examine the changes of stiffness of each RC building model.