ORIGINAL RESEARCH article
Front. Mater.
Sec. Structural Materials
Volume 12 - 2025 | doi: 10.3389/fmats.2025.1621109
This article is part of the Research TopicAdvancing Eco-Friendly Construction: The Role of Biomass and Waste IntegrationView all 3 articles
Study on permanent deformation properties of construction waste soil under traffic loading
Provisionally accepted- 1Zhejiang Communications Investment Group Expressway Construction and Management Co., Ltd., Hang Zhou, China
- 2School of Traffic and Transportation Engineering, Changsha University of Science and Technology, Changsha, China
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The permanent deformation characteristics of subgrade filler under cyclic loading are the key factors affecting the long-term stability of subgrade and pavement performance. This study aims to systematically analyze the permanent deformation characteristics of construction waste soil as subgrade filler under cyclic loading through dynamic triaxial tests to optimize roadbed design and extend its service life. Results indicate that confining pressure, moisture content, and dynamic stress amplitude significantly affect permanent deformation. Specifically, increasing confining pressure from 60 kPa to 120 kPa reduces permanent deformation by 40%, while increasing moisture content from 0.8 to 1.2 times the optimum moisture content increases deformation by 36%. The dynamic stress amplitude is increased from 40 kPa to 130 kPa, and the deformation is increased by 263 %. Based on the experimental data, the prediction model of permanent deformation of subgrade filler is established, and the prediction accuracy and universality of the model are verified by comparing with the experimental data of this study and other existing literatures. The model can provide a scientific basis for subgrade design and help to select construction parameters reasonably, so as to effectively control the permanent deformation of subgrade and reduce maintenance costs.
Keywords: Construction waste soil, Subgrade filler, Dynamic triaxial test, Permanent deformation, Prediction model
Received: 30 Apr 2025; Accepted: 05 Jun 2025.
Copyright: © 2025 Li, ZHANG, Weng, Qin, Shang and Zhang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Chuang ZHANG, School of Traffic and Transportation Engineering, Changsha University of Science and Technology, Changsha, China
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