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Mechanical characterization of marl soil treated by cement and lignosulfonate under freeze–thaw cycles: experimental studies and machine-learning modeling

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Abstract

Calcium carbonate-enriched marl is supposed to lose the bearing capacity while subjected to an increase/decrease in the moisture content and under the effect of multiple freeze–thaw (F-T) cycles. Investigating different weight percentages and curing periods, combination of ordinary Portland cement (OPC) and lignosulfonate is introduced as an efficient method to improve the mechanical strength of the marl soil under the effect of F-T cycles. In this regard, compaction, unconfined compressive strength, and direct shear tests were conducted. It was observed that although the addition of OPC (as the sole binder) can enhance the shear strength, the performance of samples under the action of F-T was not significantly improved. However, samples containing lignosulfonate showed a rectified behavior. Microstructural investigations exhibited the development of new intensity peaks for the calcium-aluminate-silicate-hydrate (C-A-S–H) products and elaborated a denser structure with a lower porosity, keeping the soil particles closer. Next, different intelligent approaches of machine learning (ML) were employed to provide cost-effective and accurate speedy tools. Among eight machine learning algorithms and advanced ensemble models, comparative study revealed the efficiency of gradient boosting model with coefficients of determinations of up to 98.5% for the prediction of UCS. Feature importance analysis suggested the duration of treatment and the cement content as the main contributing factors to the UCS. Highly accurate and efficient EPR-based models with coefficients of determination of higher than 99% were also proposed for the prediction of shear strength and shear stress parameters.

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Some or all data, models, or codes that support the findings of this study are available from the corresponding author upon reasonable request.

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Authors and Affiliations

  1. Department of Civil Engineering, University of Guilan, Rasht, Iran

    Ali Shafiei

  2. School of Engineering, RMIT University, Melbourne, Australia

    Mohammad Aminpour & Majidreza Nazem

  3. Department of Civil and Water Engineering, Laval University, Québec, Canada

    Hadi Hasanzadehshooiili

  4. Department of Civil Engineering, University of Guilan, Rasht, PO Code 4199613776, Iran

    Ali Ghorbani

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  2. Mohammad Aminpour
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Contributions

Ali Shafiei: investigation, visualization, and writing—original draft. Mohammad Aminpour: conceptualization, methodology, software, formal analysis, resources, data curation, visualization, and writing—review and editing. Hadi Hasanzadehshooiili: conceptualization, methodology, software, formal analysis, resources, data curation, visualization, and writing—review and editing. Ali Ghorbani: conceptualization, methodology, resources, validation, supervision, and writing—review and editing. Majidreza Nazem: writing—review and editing.

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Shafiei, A., Aminpour, M., Hasanzadehshooiili, H. et al. Mechanical characterization of marl soil treated by cement and lignosulfonate under freeze–thaw cycles: experimental studies and machine-learning modeling. Bull Eng Geol Environ 82, 200 (2023). https://doi.org/10.1007/s10064-023-03226-z

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