A Contrast Analysis of Deformation Characteristics and Critical Dynamic Stress of Natural and Fiber-Binder Reinforced Subgrade Filler after Different Freeze-Thaw Cycles

Author:

Wang Jiahui1,Li Yan2,Ling Xianzhang34,Yang Ping1,Zhao Yingying4ORCID

Affiliation:

1. College of Civil Engineering, Nanjing Forestry University, Nanjing 210037, China

2. China 19th Metallurgical Group Corporation Limited, Chengdu 610031, China

3. School of Civil Engineering, Harbin Institute of Technology, Harbin 150090, China

4. School of Civil Engineering, Qingdao University of Technology, Qingdao 266033, China

Abstract

To investigate the dynamic stability of natural subgrade filler (NSF) and fiber-binder reinforced subgrade filler (RSF) under cyclic load after freeze–thaw (FT) cycles, a triaxial test was conducted to determine the correlation between cumulative plastic strain (CPS) and the quantity of loading cycles, as well as the evolution law of dynamic strength and critical dynamic stress (CDS) with different FT cycles. The CPS change in the NSF and RSF shows three states (stable, critical, and destructive) with increasing vibration times. However, both fillers have different failure forms, and the curve shapes of the CPS with loading cycle quantities before and after failure are also different. With the number of FT cycles increasing, the requisite dynamic stress threshold for NSF specimen failure decreases continuously. After three FT cycles, the anti-cumulative deformation ability of the NSF decreases by approximately 32%. The anti-cumulative deformation abilities of the NSF after seven and nine FT cycles, respectively, are similar. The amelioration measures could significantly enhance the FT resistance of the NSF. After zero, one, three, five, seven, and nine FT cycles, the requisite dynamic stress threshold for the RSF to reach destruction is increased 1.52, 1.89, 1.98, 2.32, 2.2, and 2.45 times, respectively, compared to that of the NSF. A mechanical model of critical dynamic stress of the NSF and RSF that considers the FT cycle was obtained using a multivariate nonlinear regression method.

Funder

China Postdoctoral Science Foundation

National Key Scientific Instrument and Equipment Development Projects of China

Central Government Guided Local Science and Technology Development Fund Project of China

Publisher

MDPI AG

Subject

General Materials Science

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