Skip to main content
Log in

Computer vision-based automated stiffness loss estimation for seismically damaged non-ductile reinforced concrete moment frames

  • Original Article
  • Published:
Bulletin of Earthquake Engineering Aims and scope Submit manuscript

Abstract

A novel automated image processing-based methodology is proposed for quantification of stiffness degradation in non-ductile reinforced concrete moment frames after a seismic event. A database of 264 surface crack patterns from quasi-static experiments on 61 non-ductile beam-column subassemblies at various damage levels is used for development and verification of the methodology. The reference databank includes a wide range of structural and geometric parameters. Multifractal dimensions of the images of non-ductile beam-column joints are considered as the mathematical complexity indices of the surface crack patterns. Five predictive equations are developed for estimating the updated stiffness of damaged non-ductile reinforced concrete moment frames following an earthquake. The equations are obtained using symbolic regression method and their input parameters vary based on the accessibility of the characteristic parameters of the beam-column joint. The effectiveness of the proposed empirical equations is shown for a sample specimen at a variety of damage levels. Results reveal that the multifractal dimensions of the surface crack maps are highly correlated with the stiffness loss in the non-ductile reinforced concrete beam-column joints. The stiffness based damage index obtained by the proposed predictive equations can be used for post-earthquake system identification, stability assessment, or subsequent seismic analysis of the damaged structure.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

Download references

Funding

The authors have not disclosed any funding.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Mohammadjavad Hamidia.

Ethics declarations

Conflict of interest

The authors have no relevant financial or non-financial interests to disclose.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Hamidia, M., Ganjizadeh, A. Computer vision-based automated stiffness loss estimation for seismically damaged non-ductile reinforced concrete moment frames. Bull Earthquake Eng 20, 6635–6658 (2022). https://doi.org/10.1007/s10518-022-01408-w

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10518-022-01408-w

Keywords

Navigation