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Prediction of compressive strength of BFRC using soft computing techniques

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Abstract

In this paper, the strength of basalt fiber reinforced concrete (BFRC) was investigated. Four percentages of basalt fiber (0.1%, 0.2%, 0.3%, and 0.4%) by volume fraction were added to concrete mix and BFRC cubes of 150 mm size were prepared and tested after 28 days curing age. It was found that the compressive strength of concrete with basalt fibers (1–4 percent) decreased in the range of 9.71–18.62 percent for M25. To predict the compressive strength of BFRC, three soft computing techniques, i.e., Random Forest (RF), Stochastic Random Tree, Artificial Neural Network (ANN) were applied for Nine inputs, i.e., Cement, Fine Aggregate, Coarse Aggregate, Water, Fly Ash, Superplasticizer, BF, length of Fiber, curing time, and which is Compressive Strength as output. The results showed correlation coefficient (CC) were (0.9938, 0.9755), (0.9985, 0.9342), and (0.9793, 0.7308) in training and testing stages, respectively, for RF, Stochastic RT and ANN. The Stochastic Random Tree was the outperforming model among the three applied ones. The sensitivity analysis showed that curing period is the most critical input in compressive strength.

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  1. Civil Engineering Department, Shoolini University, Solan, India

    Fadi Almohammed & Mohindra S. Thakur

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  1. Fadi Almohammed
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Correspondence to Fadi Almohammed.

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Almohammed, F., Thakur, M.S. Prediction of compressive strength of BFRC using soft computing techniques. Soft Comput 28, 1391–1408 (2024). https://doi.org/10.1007/s00500-023-08331-5

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