간행물
Journal of the Earthquake Engineering Society of Korea KCI 등재 한국지진공학회논문집
- 발행기관 한국지진공학회
- 자료유형 학술지
- 간기 격월간
- ISSN 1226-525x (Print)2234-1099 (Online)
- 수록기간 1997 ~ 2025
- 주제분류 공학 > 토목공학 공학 분류의 다른 간행물
- 십진분류KDC 531DDC 624
권호리스트/논문검색
제29권 제3호(통권 제165호) (2025년 5월) 6건
1.
2025.05
구독 인증기관 무료, 개인회원 유료
Existing reinforced concrete buildings with seismically deficient columns experience reduced structural capacity and lateral resistance due to increased axial loads from green remodeling or vertical extensions aimed at reducing CO2 emissions. Traditional performance assessment methods face limitations due to their complexity. This study aims to develop a machine learning-based model for rapidly assessing seismic performance in reinforced concrete buildings using simplified structural details and seismic data. For this purpose, simple structural details, gravity loads, failure modes, and construction years were utilized as input variables for a specific reinforced concrete moment frame building. These inputs were applied to a computational model, and through nonlinear time history analysis under seismic load data with a 2% probability of exceedance in 50 years, the seismic performance evaluation results based on dynamic responses were used as output data. Using the input-output dataset constructed through this process, performance measurements for classifiers developed using various machine learning methodologies were compared, and the best-fit model (Ensemble) was proposed to predict seismic performance.
4,200원
2.
2025.05
구독 인증기관 무료, 개인회원 유료
Our study experimentally evaluates the structural characteristics of a Cone-Shaped Friction Isolator (CFI) as part of research on sliding bearings. With its relatively simple configuration and effective restoring mechanism, the CFI has significant practical implications for structural engineering. We designed the shape and components of the CFI, and its operation and restoring mechanisms were theoretically reviewed. A prototype of the CFI was developed, and structural characteristic experiments were conducted, focusing on design parameters such as the cone’s inclination angle, the friction coefficient of the contact surface, the magnitude of the vertical load applied to the isolator, and the horizontal loading frequency. The experimental results provide valuable insights into the structural characteristics of devices in terms of critical shear force and restoring shear force.
4,000원
3.
2025.05
구독 인증기관 무료, 개인회원 유료
Our study develops a finite element analysis (FEA) model to evaluate the seismic performance of a two-story reinforced concrete (RC) school building and validates it through experiments. We developed a methodology that reflects failure modes from past experiments and validated it by comparing results at both the member (columns) and system (beam-column joints) levels. We created an FEA model for seismic-vulnerable RC moment frames using this methodology. This model incorporates bond-slip effects using three methods: Merged Nodes, Constrained Beam in Solid Penalty (CBISP), and Constrained Beam in Solid Friction (CBISF), which model the interaction between reinforcement and concrete. The approach provides a reliable tool for evaluating seismic performance and improves the accuracy of reinforced concrete frame evaluations.
4,000원
4.
2025.05
구독 인증기관 무료, 개인회원 유료
This study proposes an improved method for updating finite element models (FEM) by incorporating the random field characteristics of concrete material properties in reinforced concrete structures. Traditional FEM often assumes homogeneous material properties, which can lead to significant discrepancies between predicted and actual dynamic responses, especially in structures where the Young’s modulus (E) of concrete varies due to factors like curing conditions, material composition, and construction methods. We employed a Gaussian random field model and a system identification (SI) technique to address this limitation to optimize sensor placement. We developed an FEM updating method that incorporates the spatial variability of concrete elasticity. This optimization allowed for a more accurate capture of dynamic properties across various structural locations, resulting in FEM updates that reflect concrete’s inherent heterogeneity. The proposed method was validated through numerical examples, comparing dynamic response accuracy in models before and after updating. Results demonstrated that error values, measured in terms of maximum value error and normalized root mean squared Error (NRMSE), were significantly reduced in the updated models compared to the pre-update model. This approach effectively addresses the limitations of homogeneous assumptions in FEM.
4,000원
5.
2025.05
구독 인증기관 무료, 개인회원 유료
To characterize the breakdown process, we newly introduce and define a dimensionless number called breakdown zone Reynolds number Reb. Reb represents the relationship between shear frictional resistance and inertial force, equivalent to (Vr /Vs)2. Vr and Vs are rupture and shear wave velocities, respectively. Reb also characterizes the energy budget relationship, seismic energy radiation, and its efficiency. Based on Reb, particle motion can be categorized into two cases: a) Reb≪1 and b) Reb ~1 or Reb>1. For case a), since the inertial force is negligible compared to the shear frictional resistance, the particle motion can be viewed as the response of a linear time-invariant system with the stress drop as an input function, and its impulse response function (IRF) is the second type of modified Bessel function with zeroth order supposing linear phase characteristics. The IRF is quite similar to the regularized Yoffe function. The particle velocity spectrum can be characterized with the approximated spectral attenuation slope in the high frequency range of ∝ω-0.6. The attenuation slope, however, would be changed to ∝ω-1.0 if we consider the pre-slip and phase delay of the response. Then, generic omega-square model can model a finite source’s source time function (STF). On the other hand, case b) shows that IRF has the same form as Brune’s omega-square model, and its STF has steeper spectral attenuation like omega-cube model. This means that the spectral characteristics of STF may change with the rupture velocity. Furthermore, we newly define the ratio of source-controlled fmax to corner frequency f c as Stokes number Sk, a function of Reb and approximately proportional to Reb 3/2. Remarkably, Sk delineates a Reynolds number similarity which is comparable to that of isotropic turbulence. The aggregated results of spectral inversion analysis for more than 130 shallow earthquakes occurring in Japan show that the analyzed fmax/ f c (=Sk) follow the theoretical relationship, and it is also demonstrated that the non-self-similarity parameter ε proposed by Kanamori and Rivera is related to the scale dependence of Reb. Finally, Reb is compared to the inertial number I, a representative dimensionless number governing the behavior of granular suspension as a model for the interaction between fault gouge and pore-pressure in fault core. As a result, Reb is equivalent to I 2 as we consider the differences in length scale and density in each definition. Consequently, I is uniquely linked to Sk by Reb, corresponding to the Stokes number for granular suspension. Hence, it can be asserted that Reb and Sk introduced in this study are representative dimensionless numbers which characterize the whole breakdown process and the behavior of pulverized fault core.
4,600원
6.
2025.05
구독 인증기관 무료, 개인회원 유료
Seismically deficient reinforced concrete(RC) structures experience reduced structural capacity and lateral resistance due to the increased axial loads resulting from green retrofitting and vertical extensions. To ensure structural safety, traditional performance assessment methods are commonly employed. However, the complexity of these evaluations can act as a barrier to the application of green retrofitting and vertical extensions. This study proposes a methodology for rapidly calculating the allowable axial force range of RC buildings by leveraging simplified structural details and seismic wave information. The methodology includes three machine-learning-based models: (1) predicting column failure modes, (2) assessing seismic performance under current conditions, and (3) evaluating seismic performance under amplified mass conditions. A machine learning model was specifically developed to predict the seismic performance of an RC moment frame building using structural details, gravity loads, failure modes, and seismic wave data as input variables, with dynamic response-based seismic performance evaluations as output data. Classifiers developed using various machine learning methodologies were compared, and two optimal ensemble models were selected to effectively predict seismic performance for both current and increased mass scenarios.
4,500원
