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Abstract

Prediction of soft soil sub-grades settlement has been a big challenge for geotechnical engineers that are responsible for the design of roadbed embankment. The characteristics of low strength, poor permeability, high water contents, and high compressibility are dominant in soft soils, which result in a huge settlement in the case of long-term loading. The settlement prediction in soft soil subgrades of Jiehui Expressway A1, Guangdong, China, is the focus of this study. For this purpose, the necessary data of settlement is collected throughout the project execution. The numerical analysis is conducted by using the Richards model based on Linear Least Squares Iteration (LLS-I) method to calculate and predict the expected settlement. The traditional settlement prediction methods, including the hyperbolic method, exponential curve method, and pearl curve method, are applied on field settlement data of soft soil subgrades of Jiehui Expressway A1. The results show that the Richards model based on Linear Least Squares Iteration (LLS-I) method has high precision, and it has proven to be a better option for settlement prediction of soft soil sub-grades. The model analysis indicates that the mean absolute percentage error (MAPE) can be minimized as compared to other soft soil sub-grades settlement prediction methods. Hence, Richards's model-based LLS-I method has a capability for simulation and settlement prediction of soft soil subgrades.
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Authors and Affiliations

Muhammad Nadeem
1
Muhammad Akbar
2
Pan Huali
3
Li Xiaoqing
1
Ou Guoqiang
3
Azka Amin
4

  1. Graduate Student School of Civil Engineering and Mechanics, HUST, Wuhan, China
  2. PhD, Research Scholar, Department of Geotechnical Engineering Institute of Mountain Hazards and Environment, Chinese Academy of Science, Chengdu, China
  3. Prof, PhD., Eng., Department of Geotechnical Engineering Institute of Mountain Hazards and Environment, Chinese Academy of Science, Chengdu, China
  4. Assistant Professor, Department of Business Administration Iqra University, Main Campus, Karachi, Pakistan

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