Search

• Large-scale shaking table tests were carried out for a subway station structure. • The isolation mechanism of Mini-NRB installed in the structure were studied. • Real-time monitoring of structure deformation was realized. • Mini-NRB reduces the bending moment of column by 60%–80% and shear force by 90%. A series of shaking-table tests of a subway station structure with mini natural rubber bearings (Mini-NRBs) installed at column ends were carried out for near-field earthquake motions. By comparing the dynamic response of the structure model with or without Mini-NRB, the isolation mechanism and effectiveness of Mini-NRB on the station model were studied. It is found that the Mini-NRB has an obvious isolation effect on the column of the structure. After installing Mini-NRB, the lateral stiffness of the column decreases greatly, which reduces the bending moment and shear force at the column end by 60%–80% and about 90% respectively under near-field earthquake excitation. The test data, real-time monitoring pictures, and ultimate structural seismic damage all show that Mini-NRB shares most of the lateral deformation of the column, so that the column is no longer a vulnerable spot of the subway station structure. In addition, Mini-NRB reduces the high frequency component of the middle plate response, thus reducing the peak acceleration response of the middle plate by 3%–10%. However, the lateral deformation of the structure and the internal force of the sidewall will increase. The lateral deformation of the structure with Mini-NRB increases by 30%–50% and the bending moment at the end of the side wall increases by 5%–25%. [ABSTRACT FROM AUTHOR]

• A lightweight nonlinear response prediction model is established based on 1D-CNN. • The performance of 1D-CNN is excellent. • The randomness of ground motions and soil parameters are considered simultaneously. • The calculation cost of stochastic seismic response has been significantly reduced. • A comprehensive stochastic dynamic analysis is conducted using PDEM. The randomness of ground motions and soil properties has a significant impact on the seismic response of underground structures. The probability density evolution method (PDEM) is a powerful stochastic dynamic analysis method. By decoupling the physical space and probability space, any number of random excitation variables can be incorporated into the dynamic system, thereby accurately capturing the time-varying evolution of structural dynamic response. However, due to the expensive computational cost of nonlinear time history analysis (NLTHA) of underground structures, the application of the PDEM that requires many calculation samples is severely limited. In view of this, this paper proposes a lightweight stochastic seismic response analysis method for the subway station structure based on deep learning and PDEM. Firstly, mathematical models of stochastic ground motions and random soil shear wave velocity profiles are constructed. Two types of random excitations are coupled using the high-dimensional space optimization point selection method. The one-dimensional convolutional neural network (1D-CNN) is used as a proxy model to map the free field's nonlinear time-history response to the subway station structure's nonlinear time-history response. The computational cost of stochastic dynamics analysis has been significantly reduced. Subsequently, the predicted results are combined with PDEM to conduct a comprehensive analysis and evaluation of the subway station structure's seismic response and seismic performance. The research results indicate that the proposed 1D-CNN model has superior predictive performance, with a computational cost of approximately 92.5% less than the traditional process. The evolution of the subway station structure's inter-storey drift ratio (IDR) is mainly influenced by stochastic ground motions. However, under the combined random excitation, the peak value of IDR is larger and its occurrence time is earlier, so the establishment of earthquake evacuation plans should refer to this working condition. Both the randomness of soil properties and the randomness of ground motions need to be considered, otherwise, underground structures' seismic performance will be overestimated. This study provides new technologies and directions for seismic analysis and design of underground structures. [ABSTRACT FROM AUTHOR]

• A new seismic barrier for underground structures is proposed to control the Rayleigh waves. • The soil acceleration response is reduced within the frequency range of 0.5–5 Hz. • The maximum layer drift of the subway station is reduced by over 40 %. • The internal forces of structural components are reduced by 70 % on average. • A novel index is proposed to evaluate the performance of seismic barriers. This research introduces a novel seismic mitigation approach for civil engineering constructions, utilizing seismic metamaterials, and particularly studies its application to underground structures. This approach involves the implementation of a regional seismic barrier, designed in the form of piles periodically clamped to a concrete foundation. The efficacy of this seismic barrier is explored through comprehensive numerical simulations. A wave propagation study is conducted to investigate the attenuation efficiency for Rayleigh waves in the frequency domain. Besides, dynamic analysis is performed on a two-layer and three-span subway station subjected to actual seismic recordings. The results from the wave propagation study reveal a notable reduction in acceleration response within the frequency range of 0.5 Hz–5 Hz when employing the seismic barrier, in contrast to the free-field scenario. Dynamic analysis demonstrates that the implementation of the proposed seismic barrier leads to a significant decrease in both the maximum layer drift and the structural internal forces of the subway station. Moreover, the relative displacement of soil proves to be a pertinent metric for evaluating the seismic control efficacy of the proposed barrier for underground structures. [ABSTRACT FROM AUTHOR]

• A novel seismic intensity measure for underground structures is proposed. • The seismic response characteristics of underground structures can be considered. • The rigidity degradation of the dynamic system can be considered. • The period range significantly affecting the seismic response for underground structures is obtained. The purpose of this study is to present a novel approach to constructing intensity measures (IMs) for underground structures using seismic response spectrums. The proposed IM takes the form of an integral of the product of the response spectrum and an arbitrary function that reflects the relative importance of each range of period to the seismic response of underground structures. To obtain the arbitrary function, an artificial neural network (ANN) technique is employed. To demonstrate the effectiveness of this method, we develop two different soil-subway station dynamic systems, referred to as Case I and Case II. Based on both cases, the probabilistic seismic demand model (PSDM) for the proposed IM and eight existing IMs are developed. The performance of the proposed IM is compared with that of the existing IMs in terms of their proficiency, practicality, and efficiency, as well as their ability to describe the probabilistic distribution of damage measure (DM). The results indicate that the proposed IM outperforms the existing IMs since it has the highest proficiency for both cases. Moreover, the fragility curves calculated using the proposed IM are more effective than those calculated using traditional IMs, with narrower uncertainty ranges, which can help reduce the uncertainty in evaluating seismic risk. Comparing the function solved by the ANN with the seismic response of subway stations under different periods of harmonic excitation, it can be found that the solved function and the seismic response reach their peak points at the same period. This finding suggests that the proposed IM can account for the interaction between the surrounding soil and underground structures, as well as the softening of soil layers during earthquakes, making it a suitable IM for underground structures. [ABSTRACT FROM AUTHOR]