循环湿化条件下粉土联合石灰改良弱膨胀土的动力累积变形特性

章定文; 刘文俊; 侯爵; 陈加富; 唐紫琼

doi:10.19818/j.cnki.1671-1637.2025.04.005

循环湿化条件下粉土联合石灰改良弱膨胀土的动力累积变形特性

doi: 10.19818/j.cnki.1671-1637.2025.04.005

章定文^{1, 2, 3, ,},
刘文俊^{1, 2, 3},
侯爵⁴,
陈加富⁴,
唐紫琼¹

1.
东南大学交通学院，江苏南京 211189
2.
交通运输部综合交通运输理论交通运输行业重点实验室 (南京现代综合交通实验室)，江苏南京 211100
3.
江苏省低碳与绿色岩土工程重点实验室，江苏南京 211189
4.
江苏省交通工程建设局，江苏南京 210017

基金项目:

国家重点研发计划 2023YFB2604800

详细信息

作者简介:
章定文(1978-)，男，湖南常德人，东南大学教授，工学博士，从事交通岩土工程研究

通讯作者:
ZHANG Ding-wen (1978-), male, professor, PhD, zhang@seu.edu.cn

中图分类号: U416.16
计量
- 文章访问数: 188
- HTML全文浏览量: 59
- PDF下载量: 29
- 被引次数: 0
出版历程
- 收稿日期: 2024-07-24
- 录用日期: 2025-05-06
- 修回日期: 2025-02-19
- 刊出日期: 2025-08-28

Dynamic cumulative deformation characteristics of weak expansive soil improved by silt and lime under cyclic wetting

ZHANG Ding-wen^{1, 2, 3
, ,},
LIU Wen-jun^{1, 2, 3},
HOU Jue⁴,
CHEN Jia-fu⁴,
TANG Zi-qiong¹

1.
School of Transportation, Southeast University, Nanjing 211189, Jiangsu, China
2.
Key Laboratory of Transport Industry of Comprehensive Transportation Theory (Nanjing Modern Multimodal Transportation Laboratory), Ministry of Transport, PRC, Nanjing 211100, Jiangsu, China
3.
Jiangsu Key Laboratory of Low Carbon and Sustainable Geotechnical Engineering, Nanjing 211189, Jiangsu, China
4.
Transportation Engineering Construction Bureau of Jiangsu Province, Nanjing 210017, Jiangsu, China

Funds:

National Key R&D Program 2023YFB2604800

Article Text (Baidu Translation)

摘要

摘要: 对不同掺入量粉土和石灰的改良膨胀土试样开展了物理力学特性及微观电镜扫描试验，分析其改良机理；在此基础上，采用GDS动三轴仪开展改良土动三轴试验，研究不同动应力幅值、含水率、循环湿化次数对改良膨胀土动力累积变形的影响规律，并构建了改良膨胀土累积变形预测模型。研究结果表明：掺入2.5%的低剂量石灰既可以通过“砂化”作用提高粉土和膨胀土的拌和性，又能提高单一粉土物理改良土的强度和水稳性；掺入粉土可改善膨胀土颗粒级配，增大土体孔隙率，抑制膨胀土的膨胀潜势，并提升改良土加州承载比(CBR)值；研究中采用40%粉土联合2.5%石灰改良膨胀土可满足公路路基填料各项指标要求；循环加载初期，改良土累积应变增长迅速，前2 000次循环加载后，改良膨胀土累积应变占79.3%，随后累积应变增长速率趋于稳定，呈塑性安定型；改良土最终累积应变与循环湿化次数成幂函数增长关系；最不利工况下最终累积应变小于1.0%，工后变形满足路基长期稳定性要求；构建的考虑动应力幅值、含水率及湿化次数影响的动力累积应变预测模型，可为粉土石灰改良膨胀土路基长期变形估算提供依据。
- 路基工程 /
- 膨胀土 /
- 湿化循环 /
- 改良机理 /
- 累积变形 /
- 复合改良 /
- 预测模型
Abstract: The physical and mechanical property and microscopic electron microscope scanning tests were conducted on improved expansive soil samples with different silt and lime content. The improvement mechanism was analyzed. The dynamic triaxial test of the improved soil was carried out using the GDS dynamic triaxial apparatus. The influence rules of different dynamic stresses, water content, and cyclic wetting times on the cumulative deformation of the improved soil were studied. A cumulative deformation prediction model of improved soil was constructed. The results show that the addition of 2.5% low-amount lime can not only enhance the mixing property of silt and expansive soil through sanding, but also improve the strength and water stability of single silt physically improved soil. The addition of silt can optimize the particle gradation of expansive soil, increase the porosity of the soil, inhibit the expansion potential of expansive soil, and improve the California bearing ratio (CBR) value of improved soil. The requirements of various indexes of highway subgrade filling can be met by employing 40% silt combined with 2.5% lime to improve expansive soil. At the initial stage of cyclic loading, the cumulative strain of the improved soil increases rapidly. After 2 000 cycles of loading, the cumulative strain of the improved expansive soil accounts for 79.3%, and then the growth rate of the cumulative strain tends to be stable, showing plastic stability. The final cumulative strain of the improved soil has a power function growth relationship with cyclic wetting times. Under the most unfavorable conditions, the final cumulative strain is less than 1.0%. The post-construction deformation meets the long-term stability requirements of the subgrade. A dynamic cumulative strain prediction model is constructed considering the influence of dynamic stress amplitude, water content, and humidification times, providing a reference for the long-term deformation prediction of silt-lime improved expansive soil subgrade.
- subgrade engineering /
- expansive soil /
- wetting cycle /
- improvement mechanism /
- cumulative deformation /
- composite improvement /
- prediction model

HTML全文

图 1 膨胀土和粉土级配曲线

Figure 1. Grading curves of expansive soil and silt

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图 2 不同粉土和石灰掺入量条件下改良膨胀土的物理力学指标

Figure 2. Physical and mechanical indexes of improved expansive soil with different content of silt and lime

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图 3 500倍扫描电镜照片对比

Figure 3. Comparison of 500 times SEM photos

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图 4 试样增湿脱湿过程

Figure 4. Wetting and dewetting process of samples

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图 5 试样含水率测试点

Figure 5. Test points of sample moisture content

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图 6 试样内部含水率标准差随时间变化曲线

Figure 6. Curves of standard deviation of moisture content in samples changing with time

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图 7 循环荷载加载

Figure 7. Cyclic loading

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图 8 GDS动三轴试验系统

Figure 8. GDS dynamic triaxial test system

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图 9 含水率w_op、σ_d=60 kPa下累积应变增长曲线

Figure 9. Cumulative strain growth curve under water content w_op and σ_d=60 kPa

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图 10 不同幅值动应力下改良土累积应变发展曲线

Figure 10. Cumulative strain growth curves with different dynamic stresses

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图 11 不同含水率下累积应变增长曲线

Figure 11. Cumulative strain growth curves under different water content

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图 12 最终累积应变与循环湿化次数关系曲线

Figure 12. Relationship curves between final cumulative strain and cyclic wetting times

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图 13 归一化最终累积应变与含水率关系曲线

Figure 13. Relationship between normalized ultimate cumulative strain and water content

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图 14 归一化最终累积应变与湿化次数关系曲线

Figure 14. Relationship between normalized ultimate cumulative strain and wetting times

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图 15 累积应变预测模型验证(n=10)

Figure 15. Verification of cumulative strain prediction model (n=10)

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表 1 膨胀土和粉土基本物理参数

Table 1. Basic physical parameters of expansive soil and silt

土体类别	土粒相对密度	液限/%	塑限/%	塑性指数	自由膨胀率_/%
膨胀土	2.73	54.1	28.8	25.3	55
粉土	2.70	32.3	25.0	7.3

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表 2 累积应变预测模型拟合结果

Table 2. Fitting results of cumulative strain prediction model

湿化次数	含水率	拟合参数			决定系数R²
湿化次数	含水率	a₁	b₁	m₁	决定系数R²
0	w_op	0.056	0.118	0.727	0.994
0	w_op+4%	0.074	0.116	0.737	0.995
0	w_op+8%	0.097	0.116	0.753	0.993
1	w_op	0.099	0.115	0.751	0.981
1	w_op+4%	0.112	0.115	0.739	0.991
1	w_op+8%	0.095	0.116	0.726	0.984
5	w_op	0.105	0.117	0.751	0.965
5	w_op+4%	0.120	0.119	0.730	0.993
5	w_op+8%	0.164	0.115	0.734	0.990
10	w_op	0.181	0.116	0.746	0.972
10	w_op+4%	0.221	0.119	0.735	0.983
10	w_op+8%	0.262	0.117	0.732	0.969

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