Performance Prediction and Optimization of High-Plasticity Clay Lime–Cement Stabilization Based on Principal Component Analysis and Principal Component Regression
High-plasticity clay soils pose significant challenges in geotechnical engineering due to their poor mechanical properties, such as low strength and high compressibility. Lime–cement stabilization offers a sustainable solution, but optimizing additive proportions requires advanced analytical approac...
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2025-06-01
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| author | Ibrahim Haruna Umar Zaharaddeen Ali Tarauni Abdullahi Balarabe Bello Hang Lin Jubril Izge Hassan Rihong Cao |
| author_facet | Ibrahim Haruna Umar Zaharaddeen Ali Tarauni Abdullahi Balarabe Bello Hang Lin Jubril Izge Hassan Rihong Cao |
| author_sort | Ibrahim Haruna Umar |
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| description | High-plasticity clay soils pose significant challenges in geotechnical engineering due to their poor mechanical properties, such as low strength and high compressibility. Lime–cement stabilization offers a sustainable solution, but optimizing additive proportions requires advanced analytical approaches to decipher complex soil-stabilizer interactions. This study investigates the stabilization of high-plasticity clay soil (CH) sourced from Kano, Nigeria, using lime (0–30%) and cement (0–8%) for thirty (30) sample combinations to optimize consolidation and strength properties. Geotechnical laboratory tests (consolidation and UCS) were evaluated per ASTM standards. Multivariate analysis integrated principal component analysis (PCA) with regression modeling (PCR) for sensitivity and causality assessment. Optimal stabilization (15% lime + 6% cement) significantly improved soil properties: void ratio reduced by 58% (0.60→0.25), porosity by 49.5% (0.38→0.19), UCS increased by 222.5% to 2670 kPa (28 days), preconsolidation stress by 206% (355.63→1088.92 kPa), and compressibility modulus by 16% (7048→10,474.28 kPa). PCR sensitivity analysis attributed 46% of UCS variance to PC1 (compressibility parameters: void ratio, porosity, compression index; β = 0.72). PCR Causality analysis shows improvment with curing (R<sup>2</sup>: 68.7% at 7 days→83.0% at 28 days; RMSE: 11.2→7.8 kPa). PCR establishes compressibility reduction as the dominant causal mechanism for strength gain, providing a robust framework for dosage optimization beyond empirical approaches. |
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| publishDate | 2025-06-01 |
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| spelling | doaj-art-18d39a69fb4f4b78bcf19a2176ebf3a82025-08-20T02:35:56ZengMDPI AGApplied Sciences2076-34172025-06-011513715010.3390/app15137150Performance Prediction and Optimization of High-Plasticity Clay Lime–Cement Stabilization Based on Principal Component Analysis and Principal Component RegressionIbrahim Haruna Umar0Zaharaddeen Ali Tarauni1Abdullahi Balarabe Bello2Hang Lin3Jubril Izge Hassan4Rihong Cao5School of Resources and Safety Engineering, Central South University, Changsha 410083, ChinaDepartment of Computer Engineering, Faculty of Engineering, Bayero University Kano, Kano 700241, NigeriaDepartment of Civil Engineering, Faculty of Engineering, Bayero University Kano, Kano 700241, NigeriaSchool of Resources and Safety Engineering, Central South University, Changsha 410083, ChinaDepartment of Geology, Faculty of Physical Sciences, Ahmadu Bello University Zaria, Zaria 810211, NigeriaSchool of Resources and Safety Engineering, Central South University, Changsha 410083, ChinaHigh-plasticity clay soils pose significant challenges in geotechnical engineering due to their poor mechanical properties, such as low strength and high compressibility. Lime–cement stabilization offers a sustainable solution, but optimizing additive proportions requires advanced analytical approaches to decipher complex soil-stabilizer interactions. This study investigates the stabilization of high-plasticity clay soil (CH) sourced from Kano, Nigeria, using lime (0–30%) and cement (0–8%) for thirty (30) sample combinations to optimize consolidation and strength properties. Geotechnical laboratory tests (consolidation and UCS) were evaluated per ASTM standards. Multivariate analysis integrated principal component analysis (PCA) with regression modeling (PCR) for sensitivity and causality assessment. Optimal stabilization (15% lime + 6% cement) significantly improved soil properties: void ratio reduced by 58% (0.60→0.25), porosity by 49.5% (0.38→0.19), UCS increased by 222.5% to 2670 kPa (28 days), preconsolidation stress by 206% (355.63→1088.92 kPa), and compressibility modulus by 16% (7048→10,474.28 kPa). PCR sensitivity analysis attributed 46% of UCS variance to PC1 (compressibility parameters: void ratio, porosity, compression index; β = 0.72). PCR Causality analysis shows improvment with curing (R<sup>2</sup>: 68.7% at 7 days→83.0% at 28 days; RMSE: 11.2→7.8 kPa). PCR establishes compressibility reduction as the dominant causal mechanism for strength gain, providing a robust framework for dosage optimization beyond empirical approaches.https://www.mdpi.com/2076-3417/15/13/7150high-plasticity clay soil stabilizationlime-cement admixtureconsolidation propertiesunconfined compressive strengthprincipal component analysis (PCA)principal component regression (PCR) |
| spellingShingle | Ibrahim Haruna Umar Zaharaddeen Ali Tarauni Abdullahi Balarabe Bello Hang Lin Jubril Izge Hassan Rihong Cao Performance Prediction and Optimization of High-Plasticity Clay Lime–Cement Stabilization Based on Principal Component Analysis and Principal Component Regression Applied Sciences high-plasticity clay soil stabilization lime-cement admixture consolidation properties unconfined compressive strength principal component analysis (PCA) principal component regression (PCR) |
| title | Performance Prediction and Optimization of High-Plasticity Clay Lime–Cement Stabilization Based on Principal Component Analysis and Principal Component Regression |
| title_full | Performance Prediction and Optimization of High-Plasticity Clay Lime–Cement Stabilization Based on Principal Component Analysis and Principal Component Regression |
| title_fullStr | Performance Prediction and Optimization of High-Plasticity Clay Lime–Cement Stabilization Based on Principal Component Analysis and Principal Component Regression |
| title_full_unstemmed | Performance Prediction and Optimization of High-Plasticity Clay Lime–Cement Stabilization Based on Principal Component Analysis and Principal Component Regression |
| title_short | Performance Prediction and Optimization of High-Plasticity Clay Lime–Cement Stabilization Based on Principal Component Analysis and Principal Component Regression |
| title_sort | performance prediction and optimization of high plasticity clay lime cement stabilization based on principal component analysis and principal component regression |
| topic | high-plasticity clay soil stabilization lime-cement admixture consolidation properties unconfined compressive strength principal component analysis (PCA) principal component regression (PCR) |
| url | https://www.mdpi.com/2076-3417/15/13/7150 |
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