TY - JOUR

T1 - Multi-source data integration and multi-scale modeling framework for progressive prediction of complex geological interfaces in tunneling

AU - Wang, Jingxiao

AU - Li, Peinan

AU - Zhuang, Xiaoying

AU - Li, Xiaojun

AU - Jiang, Xi

AU - Wu, Jun

N1 - Funding Information: This work was supported by the National Natural Science Foundation of China, China (Grant No. 41827807), the “Social Development Project of Science and Technology Commission of Shanghai Municipality, China (Grant No. 21DZ1201105)”, “The Fundamental Research Funds for the Central Universities, China (Grant No. 21D111320)”, and the “Systematic Project of Guangxi Key Laboratory of Disaster Prevention and Engineering Safety, China (Grant No. 2022ZDK018)”.

PY - 2024/4

Y1 - 2024/4

N2 - A reliable geological model plays a fundamental role in the efficiency and safety of mountain tunnel construction. However, regional models based on limited survey data represent macroscopic geological environments but not detailed internal geological characteristics, especially at tunnel portals with complex geological conditions. This paper presents a comprehensive methodological framework for refined modeling of the tunnel surrounding rock and subsequent mechanics analysis, with a particular focus on natural space distortion of hard-soft rock interfaces at tunnel portals. The progressive prediction of geological structures is developed considering multi-source data derived from the tunnel survey and excavation stages. To improve the accuracy of the models, a novel modeling method is proposed to integrate multi-source and multi-scale data based on data extraction and potential field interpolation. Finally, a regional-scale model and an engineering-scale model are built, providing a clear insight into geological phenomena and supporting numerical calculation. In addition, the proposed framework is applied to a case study, the Long-tou mountain tunnel project in Guangzhou, China, where the dominant rock type is granite. The results show that the data integration and modeling methods effectively improve model structure refinement. The improved model's calculation deviation is reduced by about 10% to 20% in the mechanical analysis. This study contributes to revealing the complex geological environment with singular interfaces and promoting the safety and performance of mountain tunneling.

AB - A reliable geological model plays a fundamental role in the efficiency and safety of mountain tunnel construction. However, regional models based on limited survey data represent macroscopic geological environments but not detailed internal geological characteristics, especially at tunnel portals with complex geological conditions. This paper presents a comprehensive methodological framework for refined modeling of the tunnel surrounding rock and subsequent mechanics analysis, with a particular focus on natural space distortion of hard-soft rock interfaces at tunnel portals. The progressive prediction of geological structures is developed considering multi-source data derived from the tunnel survey and excavation stages. To improve the accuracy of the models, a novel modeling method is proposed to integrate multi-source and multi-scale data based on data extraction and potential field interpolation. Finally, a regional-scale model and an engineering-scale model are built, providing a clear insight into geological phenomena and supporting numerical calculation. In addition, the proposed framework is applied to a case study, the Long-tou mountain tunnel project in Guangzhou, China, where the dominant rock type is granite. The results show that the data integration and modeling methods effectively improve model structure refinement. The improved model's calculation deviation is reduced by about 10% to 20% in the mechanical analysis. This study contributes to revealing the complex geological environment with singular interfaces and promoting the safety and performance of mountain tunneling.

KW - Geological modeling

KW - Mountain tunnel

KW - Multi-source data

KW - Progressive prediction

KW - Tunnel portals

UR - http://www.scopus.com/inward/record.url?scp=85175009109&partnerID=8YFLogxK

U2 - 10.1016/j.undsp.2023.08.006

DO - 10.1016/j.undsp.2023.08.006

M3 - Article

AN - SCOPUS:85175009109

VL - 15

SP - 1

EP - 25

JO - Underground Space (China)

JF - Underground Space (China)

SN - 2096-2754

ER -