Title: Big data mechanism of railway tunnel base void and degradation damage based on discrete element method

Authors: Baojin Ge; Lianjun Wang

Addresses: School of Civil Engineering, BeiJing JiaoTong University, Beijing, 100044, China ' School of Civil Engineering, BeiJing JiaoTong University, Beijing, 100044, China

Abstract: With the development of cities and the advancement of science and technology, it is no longer possible to meet the needs of modern society only by relying on ground engineering construction projects. People are paying more and more attention to the development and utilisation of underground space. This paper is based on the discrete element method to study railway tunnels, comprehensively using theoretical analysis, laboratory tests and numerical simulations and other research methods. Aiming at the deterioration of surrounding rock conditions and insufficient tunnels in the study area, the influence of the cavity after lining on the long-term safety and remaining life of the railway tunnel was studied. The experimental results show that as the degree of tunnel shortage increases, the thickness of the railway tunnel and the safety factor of the full section of the structure are significantly reduced, and they are approximately linear.

Keywords: discrete element method; deterioration of substrate shedding; damage detection; big data mechanism; railway tunnel; hole in foundation pit.

DOI: 10.1504/IJTPM.2022.122562

International Journal of Technology, Policy and Management, 2022 Vol.22 No.1/2, pp.141 - 158

Received: 03 Mar 2021
Accepted: 04 May 2021
Published online: 03 May 2022 *

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