Application prospects and challenges of intelligent technology in urban coastal soft soil engineering

SI Chuanqi; WANG Chen; LIANG Jiaxin; HUA Jian; LIANG Fayun

doi:10.11779/CJGE2024S20045

Volume 46 Issue S2

Turn off MathJax

Article Contents

Abstract

References

Chinese Journal of Geotechnical Engineering > 2024 > 46(S2): 216-220. > DOI: 10.11779/CJGE2024S20045

SI Chuanqi, WANG Chen, LIANG Jiaxin, HUA Jian, LIANG Fayun. Application prospects and challenges of intelligent technology in urban coastal soft soil engineering[J]. Chinese Journal of Geotechnical Engineering, 2024, 46(S2): 216-220. DOI: 10.11779/CJGE2024S20045

Citation:

PDF (2396 KB)

Application prospects and challenges of intelligent technology in urban coastal soft soil engineering

1.
College of Civil Engineering, Tongji University, Shanghai 200000, China
2.
College of Civil Engineering, Taiyuan University of Technology, Taiyuan 030024, China

More Information

Received Date: June 21, 2024

Graphical Abstract

Abstract

Abstract

Due to the high-quality urban development, the coastal areas are confronted with demands for urban renewal. These regions typically exhibit environmental sensitivity and complexity, while the conventional approaches often rely on manpower and resources, making it arduous to ensure extensive coverage, high efficiency and uninterrupted implementation. Consequently, the intelligent technology has emerged as a crucial means to tackle this issue. This study provides an overview of the current state of the intelligent technology in three key aspects: data perception, intelligent prediction, and visual interaction. The applications and challenges of contact and non-contact measurements, big data analysis and parametric modeling as well as the digital twin and interactive platform in soft soil engineering are summarized. It aims to facilitate a comprehensive understanding of the essence of the intelligent technology and its prospects while contributing towards fostering new quality productive forces.
- soft soil foundation,
- intelligent monitoring,
- data collection,
- model building

FullText(HTML)

References (33)

References

[1]	丁智, 张霄, 梁发云, 等. 软土基坑开挖对邻近既有隧道影响研究及展望[J]. 中国公路学报, 2021, 34(3): 50-70. DING Zhi, ZHANG Xiao, LIANG Fayun, et al. Research and prospects regarding the effect of foundation pit excavation on an adjacent existing tunnel in soft soil[J]. China Journal of Highway and Transport, 2021, 34(3): 50-70. (in Chinese)
[2]	陈湘生, 洪成雨, 苏栋. 智能岩土工程初探[J]. 岩土工程学报, 2022, 44(12): 2151-2159. doi: 10.11779/CJGE202212001 CHEN Xiangsheng, HONG Chengyu, SU Dong. Intelligent geotechnical engineering[J]. Chinese Journal of Geotechnical Engineering, 2022, 44(12): 2151-2159. (in Chinese) doi: 10.11779/CJGE202212001
[3]	黎剑华, 张鸿, 刘优平, 等. 光纤Bragg光栅在公路软基沉降监测中的应用[J]. 中南大学学报(自然科学版), 2011, 42(5): 1442-1446. LI Jianhua, ZHANG Hong, LIU Youping, et al. Fiber Bragg grating monitoring technology applied in soft ground settlement of highway[J]. Journal of Central South University (Science and Technology), 2011, 42(5): 1442-1446. (in Chinese)
[4]	朱海琴, 胡玉婷, 毛学军, 等. 基于FBG传感技术的软基全断面沉降传感器研发[J]. 南昌工程学院学报, 2016, 35(4): 79-84. ZHU Haiqin, HU Yuting, MAO Xuejun, et al. Development of whole cross section settlement sensor for soft soil foundation based on FBG sensing technology[J]. Journal of Nanchang Institute of Technology, 2016, 35(4): 79-84. (in Chinese)
[5]	侯公羽, 李子祥, 胡涛, 等. 基于分布式光纤应变传感技术的隧道沉降监测研究[J]. 岩土力学, 2020, 41(9): 3148-3158. HOU Gongyu, LI Zixiang, HU Tao, et al. Study of tunnel settlement monitoring based on distributed optic fiber strain sensing technology[J]. Rock and Soil Mechanics, 2020, 41(9): 3148-3158. (in Chinese)
[6]	朱建军, 李志伟, 胡俊. InSAR变形监测方法与研究进展[J]. 测绘学报, 2017, 46(10): 1717-1733. ZHU Jianjun, LI Zhiwei, HU Jun. Research progress and methods of InSAR for deformation monitoring[J]. Acta Geodaetica et Cartographica Sinica, 2017, 46(10): 1717-1733. (in Chinese)
[7]	WU Y, LIU C, ZHANG Q, et al. Bibliometric analysis of interferometric synthetic aperture radar (InSAR) application in land subsidence from 2000 to 2021[J]. Journal of Sensors, 2022, 2022: 1-15.
[8]	WU S, ZHANG B, DING X, et al. Radar interferometry for urban infrastructure stability monitoring: from techniques to applications[J]. Sustainability, 2023, 15(19): 14654. doi: 10.3390/su151914654
[9]	邢学敏, 杨东, 张锐, 等. 基于雷达遥感对地观测技术的软土地区公路沉降监测方法[J]. 岩土工程学报, 2023, 45(10): 2172-2179. doi: 10.11779/CJGE20220813 XING Xuemin, YANG Dong, ZHANG Rui, et al. Monitoring method for subsidence of highways in soft soil areas based on radar remote sensing earth observation technique[J]. Chinese Journal of Geotechnical Engineering, 2023, 45(10): 2172-2179. (in Chinese) doi: 10.11779/CJGE20220813
[10]	赵超英, 刘晓杰, 张勤, 等. 甘肃黑方台黄土滑坡InSAR识别、监测与失稳模式研究[J]. 武汉大学学报(信息科学版), 2019, 44(7): 996-1007. ZHAO Chaoying, LIU Xiaojie, ZHANG Qin, et al. Study on InSAR recognition, monitoring and instability model of Heifangtai loess landslide in Gansu Province[J]. Geomatics and Information Science of Wuhan University, 2019, 44(7): 996-1007. (in Chinese)
[11]	孙懋珩, 王欣. 基于双目视觉的基坑位移监测方案[J]. 计算机工程与设计, 2015, 36(1): 273-276. SUN Maoheng, WANG Xin. Excavation displacement monitoring scheme based on binocular vision[J]. Computer Engineering and Design, 2015, 36(1): 273-276. (in Chinese)
[12]	李丽萍, 郑晅. 基于双目立体视觉的隧道围岩形变监测系统[J]. 物联网技术, 2021, 11(3): 22-23. LI Liping, ZHENG Xuan. Tunnel surrounding rock deformation monitoring system based on binocular stereo vision[J]. Internet of Things Technologies, 2021, 11(3): 22-23. (in Chinese)
[13]	HE L, TAN J, HU Q, et al. Non-contact measurement of the surface displacement of a slope based on a smart binocular vision system[J]. Sensors (Basel), 2018, 18(9): E2890. doi: 10.3390/s18092890
[14]	HU Q, FENG Z, HE L, et al. Accuracy improvement of binocular vision measurement system for slope deformation monitoring[J]. Sensors, 2020, 20(7): 1994. doi: 10.3390/s20071994
[15]	郑健龙, 周驰晴, 张军辉. 双层地基一维固结特性研究综述[J]. 长沙理工大学学报(自然科学版), 2012, 9(1): 1-11. ZHENG Jianlong, ZHOU Chiqing, ZHANG Junhui. Summary of 1-D consolidation characteristics of double-layered ground[J]. Journal of Changsha University of Science & Technology (Natural Science), 2012, 9(1): 1-11. (in Chinese)
[16]	张冲, 刘钢, 赵明志, 等. 成宜高速某浅层软土上路堤填筑的稳定性分析[J]. 中外公路, 2021, 41(2): 19-25. ZHANG Chong, LIU Gang, ZHAO Mingzhi, et al. Stability analysis of embankment filling on a shallow soft soil of Chengyi Expressway[J]. Journal of China & Foreign Highway, 2021, 41(2): 19-25. (in Chinese)
[17]	ABIODUN O I, JANTAN A, OMOLARA A E, et al. Comprehensive review of artificial neural network applications to pattern recognition[J]. IEEE ACCESS, 2019, 7: 158820-158846. doi: 10.1109/ACCESS.2019.2945545
[18]	ZHANG Q, ZHU Y, MA R, et al. Prediction method of TBM tunneling parameters based on PSO-BI-LSTM model[J]. Frontiers in Earth Science, 2022, 10: 854807. doi: 10.3389/feart.2022.854807
[19]	潘秋景, 吴洪涛, 张子龙, 等. 基于多域物理信息神经网络的复合地层隧道掘进地表沉降预测[J]. 岩土力学, 2024, 45(2): 539-551. PAN Qiujing, WU Hongtao, ZHANG Zilong, et al. Prediction of tunneling-induced ground surface settlement within composite strata using multi-physics- informed neural network[J]. Rock and Soil Mechanics, 2024, 45(2): 539-551. (in Chinese)
[20]	周中, 张俊杰, 丁昊晖, 等. 基于GA-Bi-LSTM的盾构隧道下穿既有隧道沉降预测模型[J]. 岩石力学与工程学报, 2023, 42(1): 224-234. ZHOU Zhong, ZHANG Junjie, DING Haohui, et al. Settlement prediction model of shield tunnel under-crossing existing tunnel based on GA-Bi-LSTM[J]. Chinese Journal of Rock Mechanics and Engineering, 2023, 42(1): 224-234. (in Chinese)
[21]	林东, 郑俊杰, 薛鹏鹏, 等. 基于贝叶斯方法的软土深基坑不确定性位移反演分析[J]. 土木与环境工程学报(中英文), 2024, 46(3): 52-60. LIN Dong, ZHENG Junjie, XUE Pengpeng, et al. Probabilistic method for displacement back analysis of deep excavations in soft soil based on Bayesian method[J]. Journal of Civil and Environmental Engineering, 2024, 46(3): 52-60. (in Chinese)
[22]	王长虹, 吴昭欣, 王昆, 等. CPTU数据校准上海深层软土参数的随机力学-贝叶斯方法[J]. 岩土工程学报, 2023, 45(1): 75-84. doi: 10.11779/CJGE20211494 WANG Changhong, WU Zhaoxin, WANG Kun, et al. Stochastic mechanics-based Bayesian method for calibrating geotechnical parameters of Shanghai deep soft clay using CPTU data[J]. Chinese Journal of Geotechnical Engineering, 2023, 45(1): 75-84. (in Chinese) doi: 10.11779/CJGE20211494
[23]	VARDAKOS S, GUTIERREZ M, XIA C C. Parameter identification in numerical modeling of tunneling using the differential evolution genetic algorithm (DEGA)[J]. Tunnelling and Underground Space Technology, 2012, 28: 109-123.
[24]	戴斌, 胡耘, 王惠生. 上海地区相邻基坑同步开挖影响分析与实践[J]. 岩土工程学报, 2021, 43(增刊2): 129-132. doi: 10.11779/CJGE2021S2031 DAI Bin, HU Yun, WANG Huisheng. Analysis and practice of influence of synchronous excavation of adjacent foundation pits in Shanghai Area[J]. Chinese Journal of Geotechnical Engineering, 2021, 43(S2): 129-132. (in Chinese) doi: 10.11779/CJGE2021S2031
[25]	唐洪祥, 崔家铭, 张雪, 等. 岩土体大变形分析的Cosserat-粒子有限元法[J]. 岩土工程学报, 2023, 45(3): 495-502. doi: 10.11779/CJGE20211244 TANG Hongxiang, CUI Jiaming, ZHANG Xue, et al. Cosserat-particle finite element method for large deformation analysis of rock and soil[J]. Chinese Journal of Geotechnical Engineering, 2023, 45(3): 495-502. (in Chinese) doi: 10.11779/CJGE20211244
[26]	王辉, 陈卫忠, 陈培帅, 等. 浅埋大跨小净距隧道断面形态及合理间距的优化研究[J]. 岩土力学, 2011, 32(增刊2): 641-646. WANG Hui, CHEN Weizhong, CHEN Peishuai, et al. Study of section morphology and reasonable distance optimization of large-span twin tunnels with small clear spacing in shallow rock mass[J]. Rock and Soil Mechanics, 2011, 32(S2): 641-646. (in Chinese)
[27]	TAO F, MA X, HU T, et al. Research on digital twin standard system[J]. Computer Intergraded Manufacturing Systems, 2019, 25(10), 2405–2418.
[28]	GRIEVES M, VICKERS J. Digital Twin: Mitigating Unpredictable, Undesirable Emergent Behavior in Complex Systems[M]. Cham: Springer International Publishing, 2017.
[29]	CHENG X, WANG C, LIANG F Y, et al. A preliminary investigation on enabling digital twin technology for operations and maintenance of urban underground infrastructure[J]. AI in Civil Engineering, 2024, 3(1): 4.
[30]	陈健, 盛谦, 陈国良, 等. 岩土工程数字孪生技术研究进展[J]. 华中科技大学学报(自然科学版), 2022, 50(8): 79-88. CHEN Jian, SHENG Qian, CHEN Guoliang, et al. Research progress in digital twin technology for geotechnical engineering[J]. Journal of Huazhong University of Science and Technology (Natural Science Edition), 2022, 50(8): 79-88. (in Chinese)
[31]	何满潮. 滑坡地质灾害远程监测预报系统及其工程应用[J]. 岩石力学与工程学报, 2009, 28(6): 1081-1090. HE Manchao. Real-time remote monitoring and forecasting system for geological disasters of landslides and its engineering application[J]. Chinese Journal of Rock Mechanics and Engineering, 2009, 28(6): 1081-1090. (in Chinese)
[32]	张斌, 冯其波, 杨婧, 等. 路基沉降远程自动监测系统的研发[J]. 中国铁道科学, 2012, 33(1): 139-144. ZHANG Bin, FENG Qibo, YANG Jing, et al. Development of remote automatic monitoring system for subgrade settlement[J]. China Railway Science, 2012, 33(1): 139-144. (in Chinese)
[33]	邬凯, 盛谦, 张勇慧, 等. 山区公路路基边坡地质灾害远程监测预报系统开发及应用[J]. 岩土力学, 2010, 31(11): 3683-3687. WU Kai, SHENG Qian, ZHANG Yonghui, et al. Development of real-time remote monitoring and forecasting system for geological disasters at subgrade slopes of mountainous highways and its application[J]. Rock and Soil Mechanics, 2010, 31(11): 3683-3687. (in Chinese)

Supplements (0)

Cited By

Cited by

Periodical cited type(19)

1.	张伟丽，李明依，李俊，钱程，陈宗武. 基于MICP技术的固化黏土抗侵蚀性能研究. 安全与环境工程. 2025(01): 201-210+232 .
2.	高瑜，邢家伟，王晓荣，韩红伟，樊促遥. 核磁共振作用下微生物矿化风沙土材料的微观孔隙. 科学技术与工程. 2025(05): 2066-2073 .
3.	王东星，许凤丽，泮晓华，商武锋，吴章平，郭克诚. GGBS-MICP协同固化淤泥质砂土工程特性研究. 岩石力学与工程学报. 2025(05): 1349-1362 .
4.	朱文羲，邓华锋，李建林，肖瑶，熊雨，程雷. 木质素磺酸钙增强花岗岩残积土微生物固化效果研究. 土木工程学报. 2024(03): 123-132 .
5.	徐志平，贾卓龙，晏长根，王逸凡. 聚丙烯纤维加筋黄土边坡防护原位测试及改进策略. 人民黄河. 2024(04): 111-116 .
6.	耿会岭，赵卫全，赵永刚，杨晓东，于凡. 生物诱导碳酸钙沉淀在改善土壤侵蚀中的应用. 水利水电技术(中英文). 2024(03): 11-23 .
7.	蒋钊，彭劼，许鹏旭，卫仁杰，李亮亮. 微生物结合碳纤维加固钙质砂的高强度试验研究. 土木与环境工程学报(中英文). 2024(05): 64-73 .
8.	付贵永，肖杨，史金权，周航，刘汉龙. 干湿循环下EICP联合黄原胶加固钙质粉土劣化特性试验研究. 岩土工程学报. 2024(11): 2341-2351 . 本站查看
9.	郑宏扬，王瑞，刘宇佳，唐朝生. 基于生物碳化活性氧化镁技术抑制土体干缩开裂的试验研究. 高校地质学报. 2024(06): 705-713 .
10.	袁童，雷学文，艾东，安然，陈昶，陈欣. 椰壳纤维-MICP复合改良膨胀土强度特性. 水利与建筑工程学报. 2023(03): 105-111 .
11.	赵卫全，张银峰，李娜，耿会岭，严俊. 微生物改良膨胀土的胀缩性及耐水性试验研究. 中国水利水电科学研究院学报(中英文). 2023(04): 350-359 .
12.	杜掀，郑涛，卢超波，杨庭伟，姜洪亮. 不同类型纤维对MICP处理钙质砂物理力学性能的影响. 西部交通科技. 2023(01): 60-63 .
13.	胡其志，霍伟严，马强，陶高梁. MICP联合纤维加筋黄土的力学性能及水稳性研究. 人民长江. 2023(08): 227-232+248 .
14.	张婧，杨四方，张宏，曹函，陆爱灵，唐卫平，廖梦飞. 碳中和背景下MICP技术深化与应用. 现代化工. 2023(11): 75-79+84 .
15.	张建伟，赵聪聪，尹悦，石磊，边汉亮，韩智光. 紫外诱变产脲酶菌株加固粉土的试验研究. 岩土工程学报. 2023(12): 2500-2509 . 本站查看
16.	陈欣，安然，汪亦显，陈昶. 胶结液浓度对MICP固化残积土力学性能影响及机理研究. 水利与建筑工程学报. 2023(06): 100-106+149 .
17.	贺桂成，唐孟媛，李咏梅，李春光，张志军，伍玲玲. 改性黄麻纤维联合微生物胶结铀尾砂的抗渗性能试验研究. 岩土力学. 2023(12): 3459-3470 .
18.	黄安国，何稼，邵应峰. EICP联合纤维加固边坡表层抗侵蚀试验研究. 河南科学. 2022(09): 1411-1421 .
19.	申春妮，方祥位，胡丰慧，姚志华，李洋洋. 珊瑚砂地基中微生物珊瑚砂桩承载特性试验研究. 岩土工程学报. 2022(S1): 68-73 . 本站查看

Other cited types(19)

Get Citation

PDF

XML

Article views (109) PDF downloads (27) Cited by(38)

Application prospects and challenges of intelligent technology in urban coastal soft soil engineering

Abstract

References

Cited by

Periodical cited type(19)

Other cited types(19)

Catalog

Related

Application prospects and challenges of intelligent technology in urban coastal soft soil engineering

Abstract

References

Cited by

Periodical cited type(19)

Other cited types(19)

Catalog

Related

Export File

Citation

Format

Content