Reliability Analysis of FRP-Confined Concrete at Ultimate using Conjugate Search Direction Method.

Polymers (Basel)

Division of Computational Mathematics and Engineering, Institute for Computational Science, Ton Duc Thang University, Ho Chi Minh City 800010, Vietnam.

Published: March 2020

In this paper compressive strength and ultimate strain results in the current database of fiber-reinforced polymer (FRP)-confined concrete are used to determine the reliability of their design space. The Lognormal, Normal, Frechet, Gumbel, and Weibull distributions are selected to evaluate the probabilistic characteristics of six FRP material categories. Following this, safety levels of the database are determined based on a probabilistic model. An iterative reliability method is developed with conjugate search direction for evaluating the reliability. The results show that Lognormal and Gumbel distributions provide best probability distribution for model errors of strength and strain enhancement ratios. The developed conjugate reliability method provides improved robustness over the existing reliability methods owing to its faster convergence to stable results. The results reveal that the part of the database containing normal strength concrete (NSC) heavily confined (i.e., actual confinement ratio (/) > 0.5) by low and normal modulus carbon fibers (i.e., fiber elastic modulus () ≤ 260 GPa) and moderately confined (i.e., 0.3 ≤ / ≤ 0.5) by aramid fibers exhibits a very high safety level. The segments of the database with a low and moderate safety level have been identified as i) NSC moderately and heavily confined by higher modulus glass fibers (i.e., > 60 GPa), ii) high strength concrete (HSC) moderately and heavily confined (i.e., / > 0.3) by glass fibers, iii) HSC lightly confined (i.e., / ≤ 0.2) by carbon fibers, and iv) HSC lightly confined by aramid fibers. Additional experimental studies are required on these segments of the database before they can be used reliably for design and modeling purposes.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7183259PMC
http://dx.doi.org/10.3390/polym12030707DOI Listing

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