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CONTENTS
Volume 28, Number 5, May 2025
 

Abstract
The present study examines the seismic behavior of reinforced concrete core-walls with outrigger systems exposed to near-fault (NF) and far-fault (FF) strong ground motions using two different record scaling techniques: spectrum-matching (SM) and amplitude scaling (AS). The outrigger uses buckling restrained braces (BRB). The systems are first designed with seismic codes and the conventional response spectrum analysis (RSA) process. Nonlinear fiber element models for the core walls and nonlinear BRB elements for the outrigger are generated in order to conduct nonlinear time history analysis. The SM and AS methods are used to obtain appropriate records for nonlinear time history analysis. When compared to the SM approach, the AS procedure resulted in a greater requirement for curvature ductility at the upper level of the core-wall, and this problem is particularly significant for the near-fault ground motions. The reason for this difference is the changes in the ground motion characteristics due to SM procedure. For near-fault ground motions, changes in the ground motion characteristics are more severe. According to the obtained results, due to the change and reduction of responses of tall core-wall with outrigger by SM process in time history analysis, it is not recommended to use this scaling method in this structural system.

Key Words
BRB; core-wall; far-fault; near-fault; NLTHA; outrigger; plastic hinge; record scaling method; reinforced concrete

Address
Department of Civil Engineering, Mahdishahr Branch, Islamic Azad University, Mahdishahr, Iran

Abstract
A high-rise residential building with a shear wall structure system containing viscous damping walls and located in a high-intensity earthquake area was studied. The seismic performance target of the high-rise shear wall structure was proposed based on the performance-based seismic design method. The damping effect and seismic performance of the shear wall structures using viscous damping walls under frequent earthquake and rare earthquake action were studied by using elastic time history analysis and elastic-plastic time history analysis. Moreover, a performance design of the energy dissipation substructure was carried out. The results indicated that the drift angle of the energy dissipation structure satisfied the requirements of the specification limit. Most of the walls of the structure were only slightly damaged, while only the bottom part of the walls was in the moderate damage category, indicating that the seismic performance of the shear wall structure could be effectively improved by using viscous damping walls. The base shear of the energy dissipation structure was reduced by 12~28%, and the viscous damping walls could provide an additional damping ratio of 2.5~4.77% under frequent earthquake action. The hysteretic energy dissipation effect was obvious under rare earthquake action. By adopting the technical measures of steel-reinforced concrete beams and increasing the reinforcement ratio of substructure columns, the key components of the energy dissipation substructure under rare earthquake action could satisfy the predetermined seismic performance objective requirements.

Key Words
energy dissipation effect; high-rise shear wall structure; seismic performance; substructure performance design; viscous damping walls

Address
Xin Huang, Yong-kang Zhang and Yu Chen: School of Transportation Science and Engineering, Civil Aviation University of China, Tianjin 300300, China
Yang Lv: Tianjin Key Laboratory of Civil Structure Protection and Reinforcement, Tianjin Chengjian University, Tianjin 300384, China
Xu-dong Zhu: Tianjin architecture design institute, Tianjin 300074, China

Abstract
In seasonally frozen areas, freezing of topsoil is detrimental to the seismic response of bridge substructures and may cause bridge damage. In order to counter this problem, this paper proposes the use of a temperature-insensitive composite material (PolyBRuS) to replace the soil around the with the aim of preventing seismic damage brought about by the seasonally frozen soil, which is named as the replacement method. Firstly, a three-dimensional finite element model was built based on the model tests, and the results of the model tests were used for verification and calibration. Secondly, based on the finite element model, a time-history analysis of the seismic response of the bridge substructure was carried out to explore the nonlinear seismic response of the bridge foundation in different seasons and with or without replacement conditions. The result of numerical simulations showed that frozen soil significantly reduced the extent of the plastic zone of the soil under seismic loading and affected the seismic response of the bridge substructure, including an increase of foundation acceleration (19% increase), a decrease of foundation displacement (32% decrease), and an increase of foundation bending moment (10% increase). Notably, it can be found that the replacement method can reduce the seismic acceleration, increased column deformation (21% increase), and reduced column bending moment of the winter bridge foundations (9% decrease), consequently reducing the risk of seismic damage to the bridge substructure. Meanwhile, the compressive stress and compressive strain characteristics of the PolyBRuS material on the column side under seismic action are similar to those of unfrozen soil in summer. Above all, the adverse effects of surface freezing on bridge substructures can be effectively mitigated by the replacement method, and the bridge foundations will have similar seismic responses in winter and summer. This achievement has practical application prospects and is expected to provide a new seismic strategy for bridge engineering in seasonally frozen soil areas.

Key Words
bridge foundation; column-soil interaction; local replacement method; nonlinear seismic response; seasonally frozen soil

Address
Department of Civil Engineering, Dalian University of Technology, Dalian, Liaoning Province, PR China

Abstract
This study proposes an H-section dry support system for water tank foundation as a structural alternative to conventional concrete wet connections, addressing limitations such as extended curing times and limited height adjustability while ensuring seismic capacity. Static lateral loading tests on strong and weak axes of H-section confirmed the system's seismic performance such as strength and ductility, with deformation concentrated at lower joints rather than the column body. Differences in axis performance were linked to varying stress distribution patterns. A 3D finite element (FE) analysis using MIDAS Gen software was conducted on rectangular water tanks under gravity, hydrostatic and design seismic loads, with all evaluated connection arrangements meeting story drift and stability criteria. The system exceeded seismic lateral force requirements for non-structural components and low-rise buildings. It further offers improved maintenance efficiency through easy component replacement and height adjustability, reducing lifecycle costs and enhancing construction efficiency.

Key Words
construction efficiency; seismic resistance; steel H-section dry connection; structural performance analysis; water tank foundation

Address
Chaeyun Ahn, Jongwon Hong and Thomas H.-K. Kang: Department of Architecture and Architectural Engineering, Seoul National University,
1 Gwanak-ro, Gwanak-gu, Seoul 08826, Korea
Jang Keun Yoon: JK E&C, 11 Uisadang-daero 1-gil, Yeongdeungpo-gu, Seoul 07332, Korea

Abstract
Machine learning (ML) is increasingly used in bridge engineering. This study aims to investigate the feasibility and accuracy of ML in predicting the seismic response of reinforced concrete (RC) bridges affected by chloride ion corrosion. Considering the concrete durability damage, 48 seismic response influencing factors were carefully selected, 60 earthquake records were extracted from the PEER database, the Latin hypercubic sampling (LHS) method was applied to integrate the feature parameter data, and 1000 bridge numerical models were built on the Opensees platform to perform nonlinear dynamic time-history analysis to obtain the seismic response data. Three ML models (XGBoost, SVR, ANN) were developed based on the established dataset. The performance of the three ML models in predicting the peak displacement response at the top of the pier (PDTP), the peak shear response at the bottom of the pier (PSBP), and the peak bending moment response at the bottom of the pier (PMBP) under the effect of the earthquake were analyzed and compared. The results showed that the comprehensive performance of the three ML models was ranked as XGBoost>SVR>ANN. The tree-based and SHAP methods were combined to analyze the importance of features. The important features of the XGBoost model in predicting PDTP, PSBP, and PMBP were identified, respectively, among which the feature with the most significant influence on PDTP is the pier cross-section width, and the seismic ASI has the most significant influence on PSBP and PMBP. The SHAP method was used to interpret the decision-making process of the XGBoost model, most of the features were well interpreted, which proved that the XGBoost model developed in this study has good interpretability. The results can provide some help and reference for the subsequent related research.

Key Words
bridge engineering; chloride ion corrosion; concrete durability; machine learning; seismic response

Address
1) State Key Laboratory of Green Building, Xi'an University of Architecture and Technology, No. 13, Yanta Road, Xi'an, China, 2) School of Civil Engineering, Xi'an University of Architecture and Technology, No. 13, Yanta Road, Xi'an, China

Abstract
Traditional methods based on velocity pulse extraction struggle to accurately and efficiently identify the high-energy and changeable waveforms of near-fault ground motions. This paper explores the identification of near-fault ground motions using long and short-term memory (LSTM) neural networks. By utilising memory elements to process the ground motion time course, the approach offers improved accuracy and efficiency in identification. The 5356 non-near-fault ground motions and 154 near-fault ground motions in the PEER ground motion database were used as samples. Recognition is performed based on different neural network structures and preprocessed using different signal processing methods. In turn, the effects of various neural network structures and signal processing methods on the recognition results are compared. The results indicate that the prediction is significantly more accurate with one single hidden layer than with multiple hidden layers when using ground motion velocity time course as the neural network input. The training accuracy reaches a maximum of 93.07% with 95 neurons, and the test accuracy reaches a maximum of 92.65% with 100 neurons. When using the short-time Fourier transform to obtain the instantaneous frequency and spectral entropy of the signal as input to the neural network, the test accuracy reaches a maximum of 88.36% with 60 neurons. Further increasing the number of neurons does not improve the prediction effect. The ground motion is analyzed using the continuous wavelet transform with the 'db4' mother wavelet. The resulting wavelet coefficients are then used as inputs for the neural network. The neural network achieves the best prediction accuracy of 96.07% when the scale is set to 10 and the single hidden layer contains 400 neurons. The neural network for LSTM can effectively identify complex signals, such as those near fault ground motion, with appropriate preprocessing of input ground motion and neural network design.

Key Words
identification method; LSTM; near fault ground motion

Address
School of Management Science and Engineering, Shandong Technology and Business University, No. 191, Binhai Middle Road, Laishan District, Yantai City, Shandong China

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