Shear Strength of Internal Reinforced Concrete Beam-Column Joints: Intelligent Modeling Approach and Sensitivity Analysis

Joint Authors

Feng, De-Cheng
Fu, Bo

Source

Advances in Civil Engineering

Issue

Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-19, 19 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2020-08-25

Country of Publication

Egypt

No. of Pages

19

Main Subjects

Civil Engineering

Abstract EN

In this paper, an intelligent modeling approach is presented to predict the shear strength of the internal reinforced concrete (RC) beam-column joints and used to analyze the sensitivity of the influence factors on the shear strength.

The proposed approach is established based on the famous boosting-family ensemble machine learning (ML) algorithms, i.e., gradient boosting regression tree (GBRT), which generates a strong predictive model by integrating several weak predictors, which are obtained by the well-known individual ML algorithms, e.g., DT, ANN, and SVM.

The strong model is boosted as each weak predictor has its own weight in the final combination according to the performance.

Compared with the conventional mechanical-driven shear strength models, e.g., the well-known modified compression field theory (MCFT), the proposed model can avoid the complicated derivation process of shear mechanism and calibration of the involved empirical parameters; thus, it provides a more convenient, fast, and robust alternative way for predicting the shear strength of the internal RC joints.

To train and test the GBRT model, a total of 86 internal RC joint specimens are collected from the literatures, and four traditional ML models and the MCFT model are also employed as comparisons.

The results indicate that the GBRT model is superior to both the traditional ML models and MCFT model, as its degree-of-fitting is the highest and the predicting dispersion is the lowest.

Finally, the model is used to investigate the influences of different parameters on the shear strength of the internal RC joint, and the sensitivity and importance of the corresponding parameters are obtained.

American Psychological Association (APA)

Feng, De-Cheng& Fu, Bo. 2020. Shear Strength of Internal Reinforced Concrete Beam-Column Joints: Intelligent Modeling Approach and Sensitivity Analysis. Advances in Civil Engineering،Vol. 2020, no. 2020, pp.1-19.
https://search.emarefa.net/detail/BIM-1123966

Modern Language Association (MLA)

Feng, De-Cheng& Fu, Bo. Shear Strength of Internal Reinforced Concrete Beam-Column Joints: Intelligent Modeling Approach and Sensitivity Analysis. Advances in Civil Engineering No. 2020 (2020), pp.1-19.
https://search.emarefa.net/detail/BIM-1123966

American Medical Association (AMA)

Feng, De-Cheng& Fu, Bo. Shear Strength of Internal Reinforced Concrete Beam-Column Joints: Intelligent Modeling Approach and Sensitivity Analysis. Advances in Civil Engineering. 2020. Vol. 2020, no. 2020, pp.1-19.
https://search.emarefa.net/detail/BIM-1123966

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1123966