A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Interpretability Analysis of Shear Capacity in Reinforced Recycled Aggregate Concrete Beams Using Tree Models
https://orcid.org/https://orcid.org/0000-0002-4043-3957
Recycled aggregate concrete is an effective solution for efficiently managing municipal construction waste on a large scale. Shear bearing capacity (SBC) is significant for reinforced concrete structures, and it is essential to develop trustworthy calculation models for structural design. This paper proposes a tree model-based SBC assessment system that considers eight design parameters of reinforced recycled concrete beams (RRCBs). Evaluation results revealed that the extreme gradient boosting model yielded the highest prediction accuracy with an R2 of 0.960 and a mean absolute percentage error of 7.343%. To reduce the risk of black-box models, this study conducted feature importance calculations, sensitivity analyses and reliability validation of the prediction results. The findings demonstrated that increasing the hoop reinforcement ratio and beam width significantly improved the SBC of RRCB. The compressive strength and longitudinal reinforcement ratio had positive effects on the SBC, while longitudinal steel bar yield strength had no effect on the SBC. These analyses can be combined with physical mechanisms to better refine the performance design. Furthermore, a comparative study utilizing two commonly used standard formulas was conducted. The results indicated that the SBCs estimated using the tree model are more accurate than those calculated by the standard formulas.
Interpretability Analysis of Shear Capacity in Reinforced Recycled Aggregate Concrete Beams Using Tree Models
https://orcid.org/https://orcid.org/0000-0002-4043-3957
Recycled aggregate concrete is an effective solution for efficiently managing municipal construction waste on a large scale. Shear bearing capacity (SBC) is significant for reinforced concrete structures, and it is essential to develop trustworthy calculation models for structural design. This paper proposes a tree model-based SBC assessment system that considers eight design parameters of reinforced recycled concrete beams (RRCBs). Evaluation results revealed that the extreme gradient boosting model yielded the highest prediction accuracy with an R2 of 0.960 and a mean absolute percentage error of 7.343%. To reduce the risk of black-box models, this study conducted feature importance calculations, sensitivity analyses and reliability validation of the prediction results. The findings demonstrated that increasing the hoop reinforcement ratio and beam width significantly improved the SBC of RRCB. The compressive strength and longitudinal reinforcement ratio had positive effects on the SBC, while longitudinal steel bar yield strength had no effect on the SBC. These analyses can be combined with physical mechanisms to better refine the performance design. Furthermore, a comparative study utilizing two commonly used standard formulas was conducted. The results indicated that the SBCs estimated using the tree model are more accurate than those calculated by the standard formulas.
Interpretability Analysis of Shear Capacity in Reinforced Recycled Aggregate Concrete Beams Using Tree Models
https://orcid.org/https://orcid.org/0000-0002-4043-3957
Recycled aggregate concrete is an effective solution for efficiently managing municipal construction waste on a large scale. Shear bearing capacity (SBC) is significant for reinforced concrete structures, and it is essential to develop trustworthy calculation models for structural design. This paper proposes a tree model-based SBC assessment system that considers eight design parameters of reinforced recycled concrete beams (RRCBs). Evaluation results revealed that the extreme gradient boosting model yielded the highest prediction accuracy with an R2 of 0.960 and a mean absolute percentage error of 7.343%. To reduce the risk of black-box models, this study conducted feature importance calculations, sensitivity analyses and reliability validation of the prediction results. The findings demonstrated that increasing the hoop reinforcement ratio and beam width significantly improved the SBC of RRCB. The compressive strength and longitudinal reinforcement ratio had positive effects on the SBC, while longitudinal steel bar yield strength had no effect on the SBC. These analyses can be combined with physical mechanisms to better refine the performance design. Furthermore, a comparative study utilizing two commonly used standard formulas was conducted. The results indicated that the SBCs estimated using the tree model are more accurate than those calculated by the standard formulas.
Interpretability Analysis of Shear Capacity in Reinforced Recycled Aggregate Concrete Beams Using Tree Models
KSCE J Civ Eng
Li, Li (author) / Qin, Yapeng (author) / Zhang, Yang (author) / Xu, Kaidong (author) / Yang, Xiao-Mei (author)
KSCE Journal of Civil Engineering ; 28 ; 3430-3443
2024-08-01
14 pages
Article (Journal)
Electronic Resource
English
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