期刊
CANADIAN JOURNAL OF CIVIL ENGINEERING
卷 -, 期 -, 页码 -出版社
CANADIAN SCIENCE PUBLISHING
DOI: 10.1139/cjce-2021-0432
关键词
code calibration; reliability analysis; slenderness limit; concrete columns; GFRP bars; artificial neural network; second-order analysis
The design provisions for internal GFRP-RC columns are being considered for updates by design committees due to advancements in understanding their behavior. This study proposes optimized reliability-based slenderness limits for CSA S806 and CSA S6 using a novel reliability-based approach that incorporates artificial intelligence and a comprehensive experimental database.
The design provisions for internal glass fiber-reinforced polymer (GFRP) reinforced concrete (RC) columns have been recently under consideration by design committees in Canada and around the world due to new advancements in understanding the behavior of GFRP-RC columns. The slenderness limit is a critical design parameter differentiating between the first- and secondorder analyses of GFRP-RC columns. The existing slenderness limits in design standards were calibrated using deterministic approaches. In this study, a novel reliability-based approach was utilized to quantify the reliability index associated with the slenderness limit to calibrate and propose optimized reliability-based slenderness limits for CSA S806 and CSA S6, for the first time. The method takes the advantage of artificial intelligence and incorporates a comprehensive experimental database.
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