Λεπτομέρειες βιβλιογραφικής εγγραφής
| Τίτλος: |
Seismic Damage Assessment of Existing Planar Steel X- or V-Braced Frames Using the Hybrid " M and P " Technique. |
| Συγγραφείς: |
Makarios, Triantafyllos, Bakalis, Athanasios, Efthymiou, Evangelos |
| Πηγή: |
Applied Sciences (2076-3417); Oct2024, Vol. 14 Issue 19, p8638, 29p |
| Θεματικοί όροι: |
Eigenfrequencies, Steel |
| Περίληψη: |
The effectiveness of a hybrid technique for identifying seismic damage in planar, multistory, steel X- or V-braced frames is demonstrated here through an example of a six-story frame. This proposed technique, referred to as "M and P", combines the instrumental monitoring (M) with pushover analysis (P). According to the methodology, the diagram of stepping eigenfrequencies of the frame in the inelastic region is initially plotted against seismic roof displacement. The fundamental natural frequency, detected through monitoring, is then utilized in this key diagram to reveal the inelastic roof displacement that corresponds to the damage state of the steel-braced frame. This displacement is subsequently used as the target in the pushover analysis, facilitating the identification of seismic damage within the existing steel-braced frame. Finally, the damage image is correlated with the damage stiffness matrix of the frame at the same inelastic roof displacement. The investigation results indicate that combining instrumental monitoring with pushover analysis using the eigenfrequencies curves established by the "M and P" technique allows for accurate identification of the seismic damage potential in existing damaged steel-braced frames. The "M and P" technique is a straightforward method for immediate damage assessment in steel structures after damage occurs, regardless of the cause. [ABSTRACT FROM AUTHOR] |
|
Copyright of Applied Sciences (2076-3417) is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
| Βάση Δεδομένων: |
Complementary Index |