Number of the records: 1
Assessment of RC frame capacity subjected to a loss of corner column
- 1.
SYSNO ASEP 0559946 Document Type J - Journal Article R&D Document Type Journal Article Subsidiary J Článek ve WOS Title Assessment of RC frame capacity subjected to a loss of corner column Author(s) Guo, M. (CN)
Huang, H. (CN)
Zhang, Wei (UTAM-F) RID, ORCID, SAI
Xue, C. (CN)
Huang, M. (CN)Number of authors 5 Article number 04022122 Source Title Journal of Structural Engineering-Asce. - : American Society of Civil Engineers - ISSN 0733-9445
Roč. 148, č. 9 (2022)Number of pages 15 s. Publication form Print - P Language eng - English Country US - United States Keywords progressive collapse ; corner column ; reinforced concrete (RC) structure ; machine learning ; peak resistance capacity ; shapely additive explanations (SHAP) values OECD category Civil engineering Method of publishing Limited access Institutional support UTAM-F - RVO:68378297 UT WOS 000825795000011 EID SCOPUS 85133502328 DOI 10.1061/(ASCE)ST.1943-541X.0003423 Annotation In this paper, three one-third scale reinforced concrete (RC) beam-column-slab structure specimen tests were conducted to investigate the collapse mechanisms under a loss of the corner column, including a frame with slab (S-COR), a frame with slab and secondary beams (SS-COR), and a frame without slab (NS-COR). The slab and secondary beam’s contributions were investigated by comparing the SS-COR and NS-COR, SS-COR, and S-COR specimens. The results show that the RC slab significantly enhanced the load resistance. Only a slight increase in peak resistance capacity of the SS-COR specimen was observed, while the ductility improved obviously due to the existence of secondary beams. The failure mode of the SS-COR frame is different from that of the S-COR frame: No concrete failure line occurs on the slab bottom, and the cracks develop entirely on the slab top. Moreover, based on the test results, finite element models (FE) were updated by adapting the OpenSeespy, which shows a good fit between the test curves and simulation results. Finally, 1,000 samples considering the uncertainty parameters were generated using Monte Carlo sampling to better understand the effect of uncertainty on the structure response. Data-driven models based on machine learning were used to predict the peak resistance capacity of the RC structures with slab and secondary beams. Workplace Institute of Theoretical and Applied Mechanics Contact Kulawiecová Kateřina, kulawiecova@itam.cas.cz, Tel.: 225 443 285 Year of Publishing 2023 Electronic address https://doi.org/10.1061/(ASCE)ST.1943-541X.0003423
Number of the records: 1