The study aimed to create statistical models that relate the angle of internal friction to predictor factors including median grain size (D50), effective overburden stress, and Standard Penetration Test (SPT-N) values for soil deposits at Rumuibekwe Bridge in the Niger Delta. A total of 16 SPT tests were conducted within depths of 0–30 m, and soil samples were collected at each stratum. Laboratory analyses included sieve tests for D50 and consolidated drained triaxial tests for internal friction angle determination. The soils were classified mainly as fine to medium sands with variable fines content, reflecting the heterogeneous depositional profile of the Niger Delta. Statistical regression models, both simple and multiple, were developed to connect predictor variables with the response variable. Effective overburden stress emerged as the most significant predictor (R² = 0.921), outperforming SPT-N (R² = 0.807), while D50 exhibited weak predictive capability. Model validation confirmed that effective stress–based models provide more reliable predictions of friction angle than conventional SPT-only correlations. The findings highlight the importance of localized, stress-dependent models for geotechnical design in complex soil environments.
Wissam et al. (Tue,) studied this question.