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Explosion resistance evaluation and damage prediction of middle partition walls in prefabricated frame tunnels

Zhen Huang, Yuzhu Zhou, Ziming Xiong and 3 more

Engineering Science and Technology, an International Journal · 2025

doi:10.1016/j.jestch.2025.102107 (opens in a new tab)

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Abstract

As the weak part of the assembled frame tunnel, the response evaluation of the middle partition wall under explosion load has attracted much attention. This study focuses on the dynamic response, post-disaster assessment, and damage prediction of the middle partition wall with different joint types (steel box joint, mortise-and-tenon joint, sleeve joint) in the prefabricated frame tunnel under blast load. Utilizing the CONWEP explosion load algorithm, three-dimensional refined models of the joints were established to analyze the failure modes and dynamic response characteristics of the middle partition wall subjected to explosive loads. The damage level of the middle partition wall was predicted by employing the deflection-span ratio damage assessment criterion and machine learning. The results show that the middle partition walls are damaged by a combination of bending and shear under explosive loads. The stiffness of the steel box type middle partition wall is the highest, and the damage at the structural joint is the least. When the explosive equivalent is less than 150 kg or the detonation distance is greater than 3 m, the displacement changes and explosion resistance of the three types of middle partition walls are equivalent. When the equivalent reaches 454 kg or the detonation distance is less than 3 m, the blast resistance and stability of the steel box type middle partition wall surpass those of the other types of middle partition walls. The probability of serious damage and collapse failure of the steel box type middle partition wall is less than that of the other two types of partition walls. In the case of low explosion intensity, the blast resistance of the middle walls of the three types of joints is equivalent.

Abstract licence: CC BY-NC-ND

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