TY - JOUR
T1 - Redefining Soil Stabilization Strategies
T2 - A Stochastic Exploration of Nano-Modified Clays in Foundation Engineering
AU - Khalaf, Fawzi Kh
AU - Pauzi, Nur Irfah Mohd
AU - Fattah, Mohammed Y.
AU - Mostafa, Karim Sherif
AU - Sidek, Norbaya
AU - Hafez, Mohamed A.
N1 - Publisher Copyright:
©2025 NSP. Natural Sciences Publishing Cor.
PY - 2025/11/1
Y1 - 2025/11/1
N2 - This study investigates the probabilistic bearing capacity of soft clay stabilized with nanoclay, nano MgO, and nano SiO2 using Monte Carlo Simulation (MCS). A combination of triaxial and model footing tests provided the input parameters for the stochastic analysis. MCS was applied to quantify failure probability (Pf) and reliability index (β ), integrating corrected Terzaghi bearing capacity predictions through regression with experimental data. The results revealed that Nano MgO achieved the lowest Pf(4.5%) and highest β values, indicating superior strength and consistency. In contrast, Nano SiO2, despite its high deterministic performance, showed increased uncertainty with depth, while Nano Clay exhibited poor reliability (Pf> 59%). This study demonstrates that MCS provides critical insights into the variability and reliability of nano-treated soils, supporting performance-based geotechnical design under uncertainty.
AB - This study investigates the probabilistic bearing capacity of soft clay stabilized with nanoclay, nano MgO, and nano SiO2 using Monte Carlo Simulation (MCS). A combination of triaxial and model footing tests provided the input parameters for the stochastic analysis. MCS was applied to quantify failure probability (Pf) and reliability index (β ), integrating corrected Terzaghi bearing capacity predictions through regression with experimental data. The results revealed that Nano MgO achieved the lowest Pf(4.5%) and highest β values, indicating superior strength and consistency. In contrast, Nano SiO2, despite its high deterministic performance, showed increased uncertainty with depth, while Nano Clay exhibited poor reliability (Pf> 59%). This study demonstrates that MCS provides critical insights into the variability and reliability of nano-treated soils, supporting performance-based geotechnical design under uncertainty.
KW - Load–Settlement Behavior
KW - Monte Carlo Simulation (MCS)
KW - Probabilistic Geotechnics
KW - Terzaghi Model Correction
UR - https://www.scopus.com/pages/publications/105024832604
U2 - 10.18576/amis/190607
DO - 10.18576/amis/190607
M3 - Article
AN - SCOPUS:105024832604
SN - 1935-0090
VL - 19
SP - 1319
EP - 1333
JO - Applied Mathematics and Information Sciences
JF - Applied Mathematics and Information Sciences
IS - 6
ER -