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December 5, 2025Smart Construction and Sustainable Cities0 citationsOpen Access

Estimation and prediction of dynamic resilient modulus of Yellow River silt under long-term dynamic loading based on mathematical statistics method

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YCYu-Yuan ChenHHHemanta HazarikaYWYuke Wang

Key Points

  • The predictive model accurately estimates silt stability and mechanical properties under prolonged dynamic loading.
  • Results show a minimum dynamic resilient modulus value exceeding 64.4 MPa across all test conditions.
  • Statistical methods, including factor analysis and linear regression models, were applied via repeated load triaxial tests.
  • Findings highlight the potential for enhanced evaluation of embankment structures utilizing this silt material.

Abstract

Abstract Traversing the erosion-prone Loess Plateau, the Yellow River is notable for having the highest average sediment concentration globally. Given its local availability and cost-effectiveness, this silt has been commonly utilized as a construction material in the region. Nevertheless, a significant research gap remains regarding the assessment of its mechanical properties and stability. This investigation focuses on examining how stress states and physical characteristics influence the dynamic resilient modulus ( M r ) of Yellow River silt (YRS) under prolonged dynamic loading. To this end, repeated load triaxial (RLT) tests were performed, applying 10,000 loading cycles and varying key parameters including confining pressure ( σ ₃), relative density ( D r ), loading frequency ( f ), and cyclic stress ratio (CSR). Statistical methods were employed to determine the confidence intervals and distribution patterns of the M r values across these different test conditions. Results indicated that the silt exhibits cyclic hardening behavior under cyclic loading. The minimum recorded M r value exceeded 64.4 MPa across all tested scenarios. The influence of individual factors was quantified by using both power exponent and linear regression models. Furthermore, a comprehensive predictive model for estimating M r was developed, incorporating confining pressure ( σ ₃), relative density ( D r ), loading frequency ( f ), and cyclic stress ratio (CSR) through factor analysis and multivariate nonlinear regression. A comparison between measured and predicted M r values confirmed the model's applicability. These outcomes provide valuable insights into the mechanical evaluation and stability assessment of embankment structures built with YRS.

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Cite This Study

Chen et al. (2025) studied this question.

synapsesocial.com/papers/6932313d8e51979591dcee6chttps://doi.org/10.1007/s44268-025-00072-8
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