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논문 기본 정보

자료유형
학술저널
저자정보
Bibo Dai (Northeastern University) Zhi-jun Xu (Henan University of Technology) Jie Zeng (Chongqing Jianzhu College) Yousef Zandi (Islamic Azad University) Abouzar Rahimi (Islamic Azad University) Sara Pourkhorshidi (Sahand University of Technology) Mohamed Amine Khadimallah (Prince Sattam Bin Abdulaziz University) Xingdong Zhao (Northeastern University) Islam Ezz El-Arab (Tanta University)
저널정보
국제구조공학회 Steel and Composite Structures, An International Journal Steel and Composite Structures, An International Journal Vol.41 No.6
발행연도
2021.12
수록면
831 - 850 (20page)

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Surface subsidence caused by mining subsidence has an impact on neighboring structures and utilities. In other words, subsurface voids created by mining or tunneling activities induce soil movement, exposing buildings to physical and/or functional destruction. Soil-structure is evaluated employing probability distribution laws to account for their uncertainty and complexity to estimate structural vulnerability. In this study, to investigate the displacement field and surface settlement profile caused by mining subsidence, on the basis of a Winkler soil model, analytical equations for the moment?rotation response of soil during mining induced ground movements are developed. To define the full static moment?rotation response, an equation for the uplift-yield state is constructed and integrated with equations for the uplift- and yield-only conditions. The constructed model's findings reveal that the inverse of the factor of safety (x) has a considerable influence on the moment?rotation curve. The maximal moment?rotation response of the footing is defined by X = 0:6. Despite the use of Winkler model, the computed moment?rotation response results derived from the literature were analyzed through the ELM-SVM hybrid of Extreme Learning Machine (ELM) and Support Vector Machine (SVM). Also, Monte Carlo simulations are used to apply continuous random parameters to assess the transmission of ground motions to structures. Following the findings of RMSE and R2, the results show that the choice of probabilistic laws of input parameters has a substantial impact on the outcome of analysis performed.

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