Performance of High-Grade Concrete with Full Substitution of Aggregates by Recycled Concrete

Meinhold, U; Mellmann, Günter; Maultzsch, Matthias

doi:10.14359/10775

SP-202: Third Canmet/Aci International Symposium: Sustainable Development of Cement and Concrete 2001

DOI: 10.14359/10775

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Performance of High-Grade Concrete with Full Substitution of Aggregates by Recycled Concrete

U Meinhold¹,

Günter Mellmann²,

Matthias Maultzsch³

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Interpretable machine learning model for evaluating mechanical properties of concrete made with recycled concrete aggregate

Nguyen,

Phan,

Nguyen

et al. 2023

Structural Concrete

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The main objective of this paper is to use the data‐driven approach to predict and evaluate the mechanical properties of concrete made with recycled concrete aggregate (RCA), including compressive strength and elastic modulus. Using 358 data samples, including 10 input variables, 10 popular machine learning (ML) algorithms are introduced to select the best ML performance model for predicting RCA concrete's compressive strength and elastic modulus. Gradient Boosting and Categorial Boosting have the best performance in predicting the compressive strength of RCA concrete, with R2 = 0.9112, RMSE = 5.3464 MPa, MAE = 4.0845 MPa, and R2 = 0.9175, RMSE = 5.1520 MPa, MAE = 3.7567 MPa, respectively. Light Gradient Boosting and Categorial Boosting have the best performance in predicting the elastic modulus of RCA concrete, with R2 = 0.8775, RMSE = 2.3560 GPa, MAE = 1.8330 GPa, and R2 = 0.9300, RMSE = 2.3560 MPa, MAE = 1.2589 MPa, respectively. Based on the Shapley Additive Explanation analysis, the influence of main factors on compressive strength and elastic modulus of RCA concrete values has been analyzed qualitatively and quantitatively. RCA replacement level and cement/sand ratio slightly affect compressive strength but have a dominant influence on the elastic modulus of RCA concrete.

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Interpretable machine learning model for evaluating mechanical properties of concrete made with recycled concrete aggregate

Nguyen,

Phan,

Nguyen

et al. 2023

Structural Concrete

View full text Add to dashboard Cite

show abstract

Mechanical properties of concrete with recycled coarse aggregate

Rahal

2007

Building and Environment

643

211

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Interactions of aqueous Cu, Zn and Pb ions with crushed concrete fines

Coleman

Lee

Slipper

2005

Journal of Hazardous Materials

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Performance of High-Grade Concrete with Full Substitution of Aggregates by Recycled Concrete

Cited by 4 publications

References 0 publications

Interpretable machine learning model for evaluating mechanical properties of concrete made with recycled concrete aggregate

Interpretable machine learning model for evaluating mechanical properties of concrete made with recycled concrete aggregate

Mechanical properties of concrete with recycled coarse aggregate

Interactions of aqueous Cu, Zn and Pb ions with crushed concrete fines

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