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<p>Soil plasticity and strength characteristics are critical factors influencing foundation stability, particularly in heterogeneous subsurface conditions. This study investigates the relationship between Plasticity Index (PI) and Unconfined Compressive Strength (UCS) of soils at a proposed building site in Bamgbola, southwestern Nigeria, to improve geotechnical decision-making for foundation design. A total of 108 disturbed soil samples were collected from 36 trial pits at depths of 0.5&#xa0;m, 1.0&#xa0;m, and 1.5&#xa0;m. Laboratory analyses including grain size distribution, moisture content, Atterberg limits, and unconfined compression tests were conducted, while spatial modelling was performed using GIS-based trend surface analysis. Results show that the soil is predominantly slightly silty gravel–sand with low fines content. Moisture content increases with depth (19.01–21.27%), alongside increases in PI (15.14–18.22%) and UCS (1278–2076 KPa). Spatial analysis reveals a direct PI–UCS relationship at 0.5&#xa0;m but inverse relationships at deeper layers. Regression analysis indicates a weak and non-significant relationship (R² &lt; 0.10; <i>p</i> &gt; 0.05), suggesting that PI alone is not a reliable predictor of UCS due to soil heterogeneity. The findings highlight the importance of site-specific geotechnical characterization and caution against the use of generalized empirical models for foundation design in mixed soils. The integrated spatial and statistical approach adopted in this study provides a practical framework for evaluating subsurface variability and improving foundation performance. This study demonstrates that the PI–UCS relationship is highly site-dependent in coarse-dominated soils, challenging the applicability of generalized predictive models. The results provide practical guidance for foundation design by integrating spatial variability with geotechnical parameters for improved engineering decision-making.</p>

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Preconstruction investigation of soil plasticity index and unconfined compressive strength of a hypothetical building site

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月21日

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  • Kayode Olayemi Ajibero,
  • Chikezie Aleke,
  • Odunayo Tope Ojo,
  • Oluwakemi Omolara Olukayode

摘要

Soil plasticity and strength characteristics are critical factors influencing foundation stability, particularly in heterogeneous subsurface conditions. This study investigates the relationship between Plasticity Index (PI) and Unconfined Compressive Strength (UCS) of soils at a proposed building site in Bamgbola, southwestern Nigeria, to improve geotechnical decision-making for foundation design. A total of 108 disturbed soil samples were collected from 36 trial pits at depths of 0.5 m, 1.0 m, and 1.5 m. Laboratory analyses including grain size distribution, moisture content, Atterberg limits, and unconfined compression tests were conducted, while spatial modelling was performed using GIS-based trend surface analysis. Results show that the soil is predominantly slightly silty gravel–sand with low fines content. Moisture content increases with depth (19.01–21.27%), alongside increases in PI (15.14–18.22%) and UCS (1278–2076 KPa). Spatial analysis reveals a direct PI–UCS relationship at 0.5 m but inverse relationships at deeper layers. Regression analysis indicates a weak and non-significant relationship (R² < 0.10; p > 0.05), suggesting that PI alone is not a reliable predictor of UCS due to soil heterogeneity. The findings highlight the importance of site-specific geotechnical characterization and caution against the use of generalized empirical models for foundation design in mixed soils. The integrated spatial and statistical approach adopted in this study provides a practical framework for evaluating subsurface variability and improving foundation performance. This study demonstrates that the PI–UCS relationship is highly site-dependent in coarse-dominated soils, challenging the applicability of generalized predictive models. The results provide practical guidance for foundation design by integrating spatial variability with geotechnical parameters for improved engineering decision-making.