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A critical assessment of existing prediction models on the shear capacity of recycled aggregate concrete beams

A critical assessment of existing prediction models on the shear capacity of recycled aggregate... The open literature evidently indicates that the shear capacity of reinforced concrete beams is adversely affected by the replacement of natural concrete aggregate by recycled concrete aggregate (RCA), and several equations for estimating the shear capacity were proposed. This paper provides a critical assessment of the existing prediction equations for estimating the shear capacity of RAC beams. The assessment is conducted utilizing Bayesian parameter estimation for comparison between the seventeen existing prediction models of the shear capacity of RAC beams. This robust assessment technique against false conclusions yields more informative and richer inferences than a mere comparison with the experimental shear capacities by providing a complete distribution of the mean and standard deviation of the quality of the prediction (i.e., test-to-predict shear values). A clear ranking of the existing prediction equations is performed based on the degree of conservatism and uniformity of the design provided by each of the shear strength prediction equations. This paper also directly addresses the significant parameters that influence the shear strength of RAC beams based on the grey correlation analysis (GCA) and check whether the existing prediction equations include these important parameters. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Innovative Infrastructure Solutions Springer Journals

A critical assessment of existing prediction models on the shear capacity of recycled aggregate concrete beams

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Publisher
Springer Journals
Copyright
Copyright © Springer Nature Switzerland AG 2022
ISSN
2364-4176
eISSN
2364-4184
DOI
10.1007/s41062-022-00839-3
Publisher site
See Article on Publisher Site

Abstract

The open literature evidently indicates that the shear capacity of reinforced concrete beams is adversely affected by the replacement of natural concrete aggregate by recycled concrete aggregate (RCA), and several equations for estimating the shear capacity were proposed. This paper provides a critical assessment of the existing prediction equations for estimating the shear capacity of RAC beams. The assessment is conducted utilizing Bayesian parameter estimation for comparison between the seventeen existing prediction models of the shear capacity of RAC beams. This robust assessment technique against false conclusions yields more informative and richer inferences than a mere comparison with the experimental shear capacities by providing a complete distribution of the mean and standard deviation of the quality of the prediction (i.e., test-to-predict shear values). A clear ranking of the existing prediction equations is performed based on the degree of conservatism and uniformity of the design provided by each of the shear strength prediction equations. This paper also directly addresses the significant parameters that influence the shear strength of RAC beams based on the grey correlation analysis (GCA) and check whether the existing prediction equations include these important parameters.

Journal

Innovative Infrastructure Solutions – Springer Journals

Published: Aug 1, 2022

Keywords: Bayesian parameter estimation; Shear capacity; Prediction equation; Critical assessment; Grey correlation analysis

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