Prediction for ground settlement induced by box tunneling construction, the spatial variation of rock and soil mass in numerical simulation is ignored, resulting in inaccurate calculation results. Based on the traditional random field theory, this study introduces the data-driven random field theory and combines with ABAQUS numerical software, to establish a three-dimensional numerical model to consider the simulation method of spatial variability of soil parameters. Then, this method is applied to a box tunneling project in Suzhou City to generate geotechnical parameter random fields directly from sparse survey data samples. The results show that when the spatial variability of elastic modulus is incorporated, the ground settlement trend and law of box tunneling construction will not be changed, and the results are more valuable for reference. The results of stochastic finite element calculation based on data-driven random field are more consistent with the actual ground subsidence law, and the accuracy of the proposed calculation model is evaluated. The research results provide a more scientific numerical calculation method for the prediction of ground settlement caused by box tunneling construction.
Ruan Chencheng
,
Shi Peixin
,
Jia Pengjiao
,
Gui Lin
. Study on Ground Settlement Induced by Box Tunneling Construction Based on Data-Driven Random Field[J]. Chinese Journal of Underground Space and Engineering, 2024
, 20(S2)
: 931
-939
.
DOI: 10.20174/j.JUSE.2024.S2.49
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