Title:
Prepublished: Uncertainty of Models for the Modulus of Elasticity of Concrete in the Colombian Code
Author(s):
Albert R. Ortiz and Julian Carrillo
Publication:
Materials Journal
Volume:
Issue:
Appears on pages(s):
Keywords:
aggregates; bayesian model updating; concrete's Modulus of elasticity; uncertainty quantification
DOI:
10.14359/51745620
Date:
2/3/2025
Abstract:
The Modulus of elasticity of concrete is typically estimated using numerical models that consider factors such as the compressive strength of the concrete, aggregate properties, unit weight of concrete, and water-cement ratio. The most used equation depends on the relationship between the compressive strength of the concrete and its Modulus of elasticity. However, this simplified formula may provide an inaccurate estimate of the Modulus of elasticity of concrete containing different types of aggregates under varying loading conditions. More sophisticated models can be used to accurately estimate the Modulus of elasticity for specific applications, such as expressions involving the unit weight of concrete. This study presents a probabilistic update to the expressions used for estimating the Modulus of elasticity of concrete based on an extensive database of over 2600 experimental tests from 20 different studies. Bayesian Inference was used to update the currently proposed models, allowing for the determination of the expressions representing the trends of the current database along with their associated uncertainties. The updated expressions were formulated considering either the compressive strength of concrete or both the compressive strength and the unit weight as input parameters. Expressions for estimating the Modulus of elasticity, considering the aggregate's origin, were also updated. This comprehensive approach enhances the accuracy and reliability of predicting the Modulus of elasticity, providing valuable insights and tools for concrete structures' design and structural reliability analysis.