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Performance of ANN and M5P-tree to forecast the compressive strength of hand-mix cement-grouted sands modified with polymer using ASTM and BS standards and evaluate the outcomes using SI with OBJ assessments

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Abstract

The present article discusses the impact of the different grain sizes of sand on the ultimate stress of hand-mixed cement-grouted sand modified with polycarboxylate ether-based polymer using two different test standards (American Society for Testing and Materials (ASTM) and British Standards (BS)). The fresh and hardened properties of cement-grouted sands modified with polymer up to 0.16% (% wt. of dry cement) were tested and quantified. Five types of sand with different grain sizes were used in this study. Adding polymer decreased the water/cement ratio (\(w/c\)) by 21.9 to 54.1%, and it kept the flow time of the cement-based grout in the range of 18 to 23 s. The highest compression strength was achieved at seven and 28 days for the cement-grouted sand using the coarser-graded sand than finer-graded sand at low w/c varied between 0.50 and 0.53. The highest compression strength was obtained at high w/c ranged between 0.57 and 0.60 for the cement grout mixed with the fine-grained sands compared to coarse-grained sands. Adding polymer enhances the prismatic and cylindrical compressive strength significantly by 113 to 577% and 53 to 459% depending on mix proportion and curing period. Adding polymer creates an amorphous gel that fills the porous between the particles of the cement, which causes a reduction in the voids, porosity and enhanced the dry density of the cement; subsequently, the compression strength of the cement-grouted sands increased significantly. Several approaches such as linear regression, nonlinear regression (NLR), multiple linear regression, artificial neural network (ANN), and M5P-tress were employed to predict the compression strength of cement-grouted sand with a different grain size of sand, w/c, amount of polymer, and curing age. From the scatter index and OBJ assessments and based on training and testing datasets, the compressive strength of the cement-grouted sands can be predicted well by using NLR and ANN models. The compression strength following the BS standard was 71% larger than the compression strength of the same mix using the ASTM standard.

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Authors and Affiliations

  1. Department of Civil Engineering, Komar University of Science and Technology, Sulaymaniyah, Kurdistan-Region, Iraq

    Wael Mahmood

  2. Civil Engineering Department, College of Engineering, University of Sulaimani, Sulaymaniyah, Kurdistan, Iraq

    Ahmed Mohammed

  3. Engineering Department, American University of Iraq, Sulaimani, Kurdistan-Region, Iraq

    Ahmed Mohammed

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  1. Wael Mahmood
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Correspondence to Ahmed Mohammed.

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Mahmood, W., Mohammed, A. Performance of ANN and M5P-tree to forecast the compressive strength of hand-mix cement-grouted sands modified with polymer using ASTM and BS standards and evaluate the outcomes using SI with OBJ assessments. Neural Comput & Applic 34, 15031–15051 (2022). https://doi.org/10.1007/s00521-022-07349-4

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