TY - JOUR
T1 - Probabilistic models of concrete compressive strength and elastic modulus with rubber aggregates
AU - Nocera, Fabrizio
AU - Wang, Junsong
AU - Faleschini, Flora
AU - Demartino, Cristoforo
AU - Gardoni, Paolo
N1 - Funding Information:
This work has been partially supported by the Zhejiang University/University of Illinois at Urbana-Champaign Institute .
Publisher Copyright:
© 2022 Elsevier Ltd
PY - 2022/3/7
Y1 - 2022/3/7
N2 - The disposal of waste rubber products is a significant issue globally and it poses a serious threat to the environment creating long-term ecological problems. The possible use of rubber aggregates in concrete is a valid alternative to obtain a green construction material. This paper develops probabilistic models for the concrete Strength Reduction Factor (SRF) and Elastic modulus Reduction Factor (ERF) accounting for the amount of rubber aggregates as well as several variables defining the mix design. Three different rubber aggregate types are considered, namely fine and coarse replaced individually and fine and coarse replaced simultaneously. A total of 644 sets of concrete compressive strength and elastic modulus tests are collected from the literature for the model calibration. The paper presents a discussion about the formulation of the models, variance stabilizing transformations, model calibration, and model selection. Once formulated, we calibrate the probabilistic models using data from experimental tests. The unknown model parameters are estimated using a Bayesian approach implemented using A Markov Chain Monte Carlo (MCMC) simulation method. The proposed probabilistic models are used to evaluate the reliability of rubberized concrete structures. As an illustration, the proposed probabilistic models are used to estimate the reliability of an example column made of rubberized concrete under compressive axial force and of an example one-way slab made of rubberized concrete under distributed load.
AB - The disposal of waste rubber products is a significant issue globally and it poses a serious threat to the environment creating long-term ecological problems. The possible use of rubber aggregates in concrete is a valid alternative to obtain a green construction material. This paper develops probabilistic models for the concrete Strength Reduction Factor (SRF) and Elastic modulus Reduction Factor (ERF) accounting for the amount of rubber aggregates as well as several variables defining the mix design. Three different rubber aggregate types are considered, namely fine and coarse replaced individually and fine and coarse replaced simultaneously. A total of 644 sets of concrete compressive strength and elastic modulus tests are collected from the literature for the model calibration. The paper presents a discussion about the formulation of the models, variance stabilizing transformations, model calibration, and model selection. Once formulated, we calibrate the probabilistic models using data from experimental tests. The unknown model parameters are estimated using a Bayesian approach implemented using A Markov Chain Monte Carlo (MCMC) simulation method. The proposed probabilistic models are used to evaluate the reliability of rubberized concrete structures. As an illustration, the proposed probabilistic models are used to estimate the reliability of an example column made of rubberized concrete under compressive axial force and of an example one-way slab made of rubberized concrete under distributed load.
KW - Bayesian inference
KW - Concrete with rubber aggregates
KW - Probabilistic model
KW - Reliability analysis
KW - Sustainability
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U2 - 10.1016/j.conbuildmat.2021.126145
DO - 10.1016/j.conbuildmat.2021.126145
M3 - Article
AN - SCOPUS:85123029227
SN - 0950-0618
VL - 322
JO - Construction and Building Materials
JF - Construction and Building Materials
M1 - 126145
ER -