Strength of Sand Reinforced with Different Forms of Geogrid

Abstract

Abstract:

Based on the polyester welded biaxial geogrid (PET25-25), different forms of geogrid were designed, such as uniaxial, biaxial, triaxial and multiaxial ones. By means of triaxial compression tests, the strength property and failure modes of these forms were obtained. Besides, the influence of the space between transverse ribs in uniaxial geogrid on the strength and the configuration of reinforcement inside the basic geogrid element were studied. It can be seen from the test results that different forms of geogrid had different reinforcing effects; the multiaxial geogrid had the best reinforcing effect, consuming the greatest amount of material, 2.21 times of the basic geogrid element; biaxial geogrids performed better in reinforcing than uniaxial and triaxial ones; the comparison of uniaxial geogrids and triaxial ones were different in different confining pressures, that is, in low confining pressure, uniaxial geogrids performed better than triaxial ones, in contrast, in high confining pressure, triaxial ones did better. In addition, the reinforcing effect of uniaxial geogrids increased with the space of transverse rib decreasing; uniaxial geogrids mainly improved the cohesion of reinforced sand, however, other forms of geogrid mainly increased the friction angle.

Key words: geogrid, triaxial compression test, strength property, reinforcement

CLC Number:

TU 46

ZHOU Xiaofeng1,ZHANG Mengxi1,QIU Chengchun1,ZHU Hong2,WANG Jin2. Strength of Sand Reinforced with Different Forms of Geogrid[J]. Journal of Shanghai Jiaotong University, 2013, 47(09): 1377-1381.

References

［1］Jewell R A, Milligan G W E, Sarsby R W, et al. Interaction between soil and geogrids ［C］∥Proceedings of Symposium on Polymer Grid Reinforcement. London: Thomas Telford Ltd, 1984: 1829.

［2］Lopes M L, Ladeira M. Influence of the confinement, soil density and displacement rate on soilgeogrid interaction ［J］. Geotextiles and Geomembranes, 1996, 14(10): 543554.

［3］杨广庆, 李广信, 张保俭. 土工格栅界面摩擦特性试验研究［J］. 岩土工程学报, 2006, 28(8): 948952.

YANG Guangqing, LI Guangxin, ZHANG Baojian. Experimental studies on interface friction characteristics of geogrids ［J］. Chinese Journal of Geotechnical Engineering, 2006, 28(8): 948952.

［4］刘文白, 周健. 土工格栅与土界面作用特性试验研究［J］. 岩土力学, 2009, 30(4): 965971.

LIU Wenbai, ZHOU Jian. Experimental research on interface friction of geogrids and soil ［J］. Rock and Soil Mechanics, 2009, 30(4): 965971.

［5］Abdi M R, Arjomand M A. Pullout tests conducted on clay reinforced with geogrid encapsulated in thin layers of sand ［J］. Geotextiles and Geomembranes, 2011, 29(6): 588595.

［6］Dong Y L, Han J, Bai X H. Behavior of triaxial geogridreinforced bases under static loading geosynthetics for a challenging world ［C］∥Proceedings of the 9th International Conference on Geosynthetics. Brazil: Printed in So Paulo, 2010: 15471550.

［7］蔡春, 张孟喜, 赵岗飞, 等. 带加强肋单向土工格栅的拉拔试验［J］. 岩土力学, 2012, 33(1): 5359, 64.

CAI Chun, ZHANG Mengxi, ZHAO Gangfei, et al. Pullout test of uniaxial geogrid with strengthening ribs ［J］. Rock and Soil Mechanics, 2012, 33(1): 5359, 64.

［8］邱成春, 张孟喜, 魏伟. 面应变条件下网格状带齿加筋砂的强度分析［J］. 岩土力学, 2011, 32(S2):313318.

QIU Chengchun, ZHANG Mengxi, WEI Wei. Strength analysis of frictional failure of sand reinforced with gridrib reinforcement under plane strain condition ［J］. Rock and Soil Mechanics, 2011, 32(S2): 313318.

[1]	YU Xinyi (禹鑫燚), WU Jiaxin (吴加鑫), XU Chengjun (许成军), LUO Huizhen (罗惠珍), OU Linlin∗ (欧林林). Adaptive Human-Robot Collaboration Control Based on Optimal Admittance Parameters [J]. J Shanghai Jiaotong Univ Sci, 2022, 27(5): 589-601.
[2]	LÜ Qibing (吕其兵), LIU Tianyuan (刘天元), ZHANG Rong (张荣), JIANG Yanan (江亚南), XIAO Lei (肖雷), BAO Jingsong∗ (鲍劲松). Generation Approach of Human-Robot Cooperative Assembly Strategy Based on Transfer Learning [J]. J Shanghai Jiaotong Univ Sci, 2022, 27(5): 602-613.
[3]	SHANG Xi, YANG Gewen, DAI Shaohuai, JIANG Yilin. Research on Resource Allocation Strategy of One-to-Many Radar Jamming Based on Reinforcement Learning [J]. Air & Space Defense, 2022, 5(1): 94-101.
[4]	ZHOU Yi, ZHOU Liangcai, DING Jiali, GAO Jianing. Power Network Topology Optimization and Power Flow Control Based on Deep Reinforcement Learning [J]. Journal of Shanghai Jiao Tong University, 2021, 55(S2): 7-14.
[5]	LI Peng, RUAN Xiaogang, ZHU Xiaoqing, CHAI Jie, REN Dingqi, LIU Pengfei. A Regionalization Vision Navigation Method Based on Deep Reinforcement Learning [J]. Journal of Shanghai Jiao Tong University, 2021, 55(5): 575-585.
[6]	JI Xiukun (冀秀坤), HAI Jintao (海金涛), LUO Wenguang (罗文广), LIN Cuixia (林翠霞), XIONG Yu(熊禹), OU Zengkai (殴增开), WEN Jiayan(文家燕). Obstacle Avoidance in Multi-Agent Formation Process Based on Deep Reinforcement Learning [J]. J Shanghai Jiaotong Univ Sci, 2021, 26(5): 680-685.
[7]	HE Linkun, ZHANG Ran, GONG Qinghai. Landing Guidance of Reusable Launch Vehicle Based on Reinforcement Learning [J]. Air & Space Defense, 2021, 4(3): 33-40.
[8]	CHEN Tao, ZHANG Ying, HUANG Xiangsong. Adaptive Interference Waveform Design Based on Reinforcement Learning [J]. Air & Space Defense, 2021, 4(2): 59-.
[9]	ZHANG Yun, Lü Runyan, CAI Yunze . Missile-Target Situation Assessment Model Based on Reinforcement Learning [J]. Journal of Shanghai Jiao Tong University(Science), 2020, 25(5): 561-568.
[10]	ZHANG Mengxi, MA Yuan, QIU Chengchun. Influence of Strengthened Node Arrangement on Pull-Out Characteristics of Biaxial Geogrid [J]. Journal of Shanghai Jiao Tong University, 2020, 54(12): 1307-1315.
[11]	TANG Jianhui,LI Ping,WANG Xinlang,JIN Yitong. Field Technological Test on Soft Ground Improvement by the In-Tube Deep Dynamic Compaction Method [J]. Journal of Shanghai Jiaotong University, 2019, 53(7): 812-818.
[12]	DI Chong,QI Kaiyue,WU Yue,SU Yu,LI Shenghong. A Double Competitive Scheme Based Learning Automata Algorithm [J]. Journal of Shanghai Jiaotong University, 2018, 52(10): 1292-1297.
[13]	Zhou Lai, Jin Xiaowei, Zheng Yikai. Researchon Operational Decision Support Based on Deep Reinforcement Learning [J]. Air & Space Defense, 2018, 1(1): 31-35.
[14]	QIU Chengchun1,ZHANG Mengxi2,WANG Yiming3. Analysis of Dynamic Response of Embankment Reinforced with Geogrid with Strengthening Nodes Based on PFC2D [J]. Journal of Shanghai Jiaotong University, 2015, 49(07): 957-960.
[15]	HOU Juan* (侯娟), ZHANG Meng-xi (张孟喜), LI Pei-pei (李培培). Simulation Study of Foundations Reinforced with Horizontal-Vertical Inclusions Using Particle Flow Code [J]. Journal of shanghai Jiaotong University (Science), 2013, 18(3): 311-316.