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

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 (σ₃), 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 (σ₃), 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.

Keywords

Yellow river / Silt / Cyclic loading / Dynamic resilient modulus / Predicting model

References

[1] Wang SY, Liu JS, Ma TB. Dynamics and changes in spatial patterns of land use in Yellow River Basin, China. Land Use Policy, 2010, 27(2): 313-323.

[2] Xin Z, Ran L, Lu X. Soil erosion control and sediment load reduction in the Loess Plateau: policy perspectives. Int J Water Resour Dev, 2012, 28(2): 325-341.

[3] Milliman JD, Syvitski JP. Geomorphic/tectonic control of sediment discharge to the ocean: the importance of small mountainous rivers. J Geol, 1992, 100(5): 525-544.

[4] Chengrui M, Dregne HE. Silt and the future development of China's Yellow River. Geogr J, 2001, 167(1): 7-22.

[5] Yang D, Yu G, Xie Y, Zhan D, Li Z. Sedimentary records of large Holocene floods from the middle reaches of the Yellow River, China. Geomorphology, 2000, 33(1–2): 73-88.

[6] Liu X, Zhang M, Zhang H, Jia Y, Zhu C, Shan H. Physical and mechanical properties of loess discharged from the Yellow River into the Bohai Sea, China. Eng Geol, 2017, 227: 4-11.

[7] Zhang H, Liu X, Jia Y, Du Q, Sun Y, Yin P, Shan H. Rapid consolidation characteristics of Yellow River-derived sediment: geotechnical characterization and its implications for the deltaic geomorphic evolution. Eng Geol, 2020, 270105578

[8] Xiao J, Juang CH, Xu C, Li X, Wang L. Strength and deformation characteristics of compacted silt from the lower reaches of the Yellow River of China under monotonic and repeated loading. Eng Geol, 2014, 178: 49-57.

[9] Liu J, Xiao J. Experimental study on the stability of railroad silt subgrade with increasing train speed. J Geotech Geoenviron Eng, 2010, 136(6): 833.

[10] Wang Y, Cao T, Shao J, Song Y, Wan Y (2022) Experimental study on static characteristics of the Yellow River silt under (triaxial) consolidated undrained conditions. Mar Georesour Geotechnol 41:1-10

[11] Zhao RH, Hua LL, Liu HY, et al. . Feasibility study on Yellow River sediment used in subgrade filling of expressway. Yellow River, 2021, 43(2): 122

[12] Burczyk JM, Ksaibati K, Anderson-Sprecher R, Farrar M (1993) Factors influencing determination of a subgrade resilient modulus value. Transport Res Rec 1462(1):72–78

[13] Kabubo C, Thiong'o G, Kaluli J, Karatai TR (2017) Soil stabilization using rice husk ash and natural lime as an alternative to cutting and filling in road construction. J Construct Eng Manag 143(5):4016127.1

[14] De Freitas JB, De Rezende LR, De Fn Gitirana Jr G (2020) Prediction of the resilient modulus of two tropical subgrade soils considering unsaturated conditions. Eng Geol 270:105580

[15] Rahim AM, George K (2002) Automated dynamic cone penetrometer for subgrade resilient modulus characterization. Transport Res Rec 1806(1):70–77

[16] Elbagalati O, Elseifi MA, Gaspard K, Zhang Z. Development of an artificial neural network model to predict subgrade resilient modulus from continuous deflection testing. Can J Civ Eng, 2017, 44(9): 700-706.

[17] Nazzal MD, Mohammad LN (2010) Estimation of resilient modulus of subgrade soils using falling weight deflectometer. Transport Res Rec 2186(1):1–10

[18] Drumm EC, Boateng-Poku Y, Pierce TJ (1990) Estimation of subgrade resilient modulus from standard tests. J Geotech Eng 116(5):774–789

[19] Malla RB, Joshi S. Subgrade resilient modulus prediction models for coarse and fine-grained soils based on long-term pavement performance data. Int J Pavement Eng, 2008, 9(6): 431-444.

[20] Zhang J, Peng J, Zeng L, Li J, Li F. Rapid estimation of resilient modulus of subgrade soils using performance-related soil properties. Int J Pavement Eng, 2021, 22(6): 732-739.

[21] Liu X, Zhang X, Wang H, Jiang B (2019) Laboratory testing and analysis of dynamic and static resilient modulus of subgrade soil under various influencing factors. Construct Build Mater 195:178–186

[22] Muhammad N, Siddiqua S. Moisture-dependent resilient modulus of chemically treated subgrade soil. Eng Geol, 2021, 285106028

[23] Ghorbani B, Arulrajah A, Narsilio G, Horpibulsuk S, Bo MW. Development of genetic-based models for predicting the resilient modulus of cohesive pavement subgrade soils. Soils Found, 2020, 60(2): 398-412.

[24] Zhang J, Peng J, Zheng J, Dai L, Yao Y. Prediction of resilient modulus of compacted cohesive soils in South China. Int J Geomech, 2019, 19(7): 04019068.

[25] Rahman MM, Gassman SL. Effect of resilient modulus of undisturbed subgrade soils on pavement rutting. Int J Geotech Eng, 2019, 13(2): 152-161.

[26] Hossain MS (2009) Estimation of subgrade resilient modulus for Virginia soil. Transport Res Rec 2101(1):98–109

[27] Sadrossadat E, Heidaripanah A, Osouli S (2016) Prediction of the resilient modulus of flexible pavement subgrade soils using adaptive neuro-fuzzy inference systems. Construct Build Mater 123:235–247

[28] Sadrossadat E, Heidaripanah A, Osouli S. Prediction of the resilient modulus of flexible pavement subgrade soils using adaptive neuro-fuzzy inference systems. Constr Build Mater, 2016, 123: 235-247.

[29] Cheng X, Wang P, Li N, Liu Z, Zhou Y. Predicting the cyclic behaviour of suction anchors based on a stiffness degradation model for soft clays. Comput Geotech, 2020, 122103552

[30] Huang Z, Cai S, Hu R, Wang J, Jiang M, Gong J. Investigation of the effect of relative density on the dynamic modulus and damping ratio for coarse grained soil. Appl Sci, 2024, 14(15): 6847.

[31] Li N, Ma B, Wang H, Tang J, Wang X, Shao Z. Influence of loading frequency on mechanical properties of unbound granular materials via repeated load tests. Constr Build Mater, 2021, 301124098

[32] Wang J, Cai Y, Yang FJMG, Geotechnology (2013) Effects of initial shear stress on cyclic behavior of saturated soft clay. Mar Georesour Geotechnol 31(1):86–106

[33] Okur D, Ansal AJSD, Engineering E. Stiffness degradation of natural fine grained soils during cyclic loading. Soil Dyn Earthq Eng, 2007, 27(9): 843-854.

[34] Montgomery DC, Runger GC (2019) Applied statistics and probability for engineers. Wiley, Hoboken, NJ

Funding

Japan Science and Technology Agency(JPMJSP2136)

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The Author(s)