Spilt Tensile Strength of Fiber-Reinforced Recycled Aggregate Concrete Simulation Employing Tunned Random Forests Trees

Xiao Chen; Chen Xi; Min Xiao; Lang Wu

doi:10.56748/ejse.24756

Authors

Xiao Chen Jiangxi Science and Technology Normal University
Chen Xi Jiangxi Science and Technology Normal University
Min Xiao Jiangxi Science and Technology Normal University
Lang Wu Jiangxi Science and Technology Normal University

DOI:

https://doi.org/10.56748/ejse.24756

Keywords:

recycled aggregate concrete, fibers, spilt tensile strength, random forests, sensitivity analysis

Abstract

A significant quantity of waste concrete is produced each year due to the demand for concrete manufacturing, which drives the yearly need for raw materials. Recycled aggregate concrete has become a viable remedy as a result. It is vulnerable to breaking and has less strength since the hardened mortar is affixed to natural aggregates, which presents a problem. The goal of this research is to employ random forests (RF) frameworks to project the split tensile strength (STS) of fiber-reinforced recycled aggregate concrete (RAC). The RF framework uses the Chimp optimization algorithm (CHOA) and artificial hummingbird optimization (ARHA) to tweak hyperparameters and select the best-performing combination. A data set including 257 data points and 10 input variables was taken from peer-reviewed published research and arbitrarily split into three phases: testing, validating, and training. The RF-AR approach exhibited high reliability, with R² of 0.9942, 0.9824, and 0.9913 throughout the learning, validating, and assessment stages. RF-AR had higher results than RF-CH, with R² of 0.9796, 0.9566, and 0.9694, respectively. Considering the values of the Theil inequality coefficient (TIC), RF-AR depicted the lowest values at 0.0128, 0.0213, and 0.0171 concerning 0.0241, 0.0333, and 0.0318 related to RF-CH for the train, validation as well as test phases, in that order. The RF-AR strategy performed better, even if the RF-CH method was dependable in forecasting the STS of fiber-reinforced RAC, according to the previously stated reasoning and the data.

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