期刊
ACI STRUCTURAL JOURNAL
卷 119, 期 3, 页码 249-+出版社
AMER CONCRETE INST
DOI: 10.14359/51734495
关键词
artificial neural network (ANN); concrete columns; glass fiber-reinforced polymer (GFRP) bars; reliability analysis; slenderness limit
资金
- Dalhousie University
- Natural Sciences and Engineering Research Council (NSERC)
A reliability-based methodology is employed in this research to quantify the safety associated with the slenderness limit calculation of concrete columns reinforced with GFRP bars. Four alternative design equations are proposed and optimized to achieve a target reliability index.
The slenderness limits in ACI 318 and ACI 440 are based on a deterministic method of defining slender columns as columns whose second-order capacity is lower than 5% of their firstorder capacity. For the first time, a reliability-based methodology is developed and employed in this research to quantify the safety associated with existing expressions used to calculate the slenderness limit of concrete columns reinforced with glass fiberreinforced polymer (GFRP) bars, and to propose alternative reliability-based expressions to optimize the design based a predefined target reliability index. The method involves developing a novel artificial neural network (ANN) to conduct second-order analysis, conducting Monte Carlo simulation, and first-order reliability. Analysis results indicate a reliability index ranging from 3.99 to 4.53 for the existing expression in ACI 440. Four alternative design equations for calculating the slenderness limits were proposed and optimized to achieve a target reliability index ranging from 4.0 to 4.5.
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