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Assessment of RC frame capacity subjected to a loss of corner column

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68378297%3A_____%2F22%3A00559946" target="_blank" >RIV/68378297:_____/22:00559946 - isvavai.cz</a>

  • Result on the web

    <a href="https://doi.org/10.1061/(ASCE)ST.1943-541X.0003423" target="_blank" >https://doi.org/10.1061/(ASCE)ST.1943-541X.0003423</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1061/(ASCE)ST.1943-541X.0003423" target="_blank" >10.1061/(ASCE)ST.1943-541X.0003423</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Assessment of RC frame capacity subjected to a loss of corner column

  • Original language description

    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.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    20101 - Civil engineering

Result continuities

  • Project

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2022

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Journal of Structural Engineering-Asce

  • ISSN

    0733-9445

  • e-ISSN

    1943-541X

  • Volume of the periodical

    148

  • Issue of the periodical within the volume

    9

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    15

  • Pages from-to

    04022122

  • UT code for WoS article

    000825795000011

  • EID of the result in the Scopus database

    2-s2.0-85133502328