Machine learning-based study on the mechanical properties and embankment settlement prediction model of nickel-iron slag modified soil

Nickel-iron slag, a byproduct of industrial processes in China with an annual production exceeding 400,000 tons, is considered an industrial waste material. This study focuses on the rational utilization of nickel-iron slag by investigating its mechanical properties and road performance as a roadbed fill material. Initially, a detailed analysis of the grading curve of pure nickel-iron slag was conducted, leading to the proposal of various modification schemes for nickel-iron slag. Subsequently, static triaxial tests were performed on nickel-iron slag-clay mixtures to explore the impact of different factors on the stress-strain curve of nickel- iron slag-modified soil. Utilizing these discoveries, a formula for the molar Coulomb shear strength of nickel-iron slag-modified soil was derived. In addition, a numerical simulation study of a nickel-iron slagreinforced embankment was conducted, integrating field tests. This aimed to investigate the variations in the compression layer sedimentation-thickness ratio and settlement factor of nickel-iron slag-modified soil reinforced embankment under different filling heights and slope rates. The results informed the development of a prediction model for the settlement ratio of nickel-iron slag-modified soil-reinforced embankment. Key findings indicate that pure nickel-iron slag exhibits poorly graded gravel sand characteristics, and optimal gradation is achieved when clay doping ranges from 30% to 40%. As the clay content increases, the stress- strain curve of nickel-iron slag-clay transitions from strain-hardening to strain-softening. Furthermore, the stress-strain curve of nickel-iron slag-cement-clay exhibits strain-softening, and the shear strength fitting formula demonstrates high computational accuracy with a small error range. Numerical simulations reveal that the sink-thickness ratio and settlement factor are minimally affected by the slope rate. The sink-thickness ratio increases with the elevation of filling height, while the settlement factor fluctuates within a small range. The proposed sink-thickness ratio prediction model exhibits high accuracy and strong generalization capabilities. This comprehensive study provides valuable insights into the efficient utilization of nickel-iron slag in construction and road engineering.