Reinforced concrete (RC) columns exhibit cyclic damage, such as strength degradation, under cyclic lateral loading, such as earthquakes. Considering the cyclic damage, the nonlinear load-deformation response of RC columns can be simulated using a lumped plasticity model. Based on an experimental database, this study calibrates lumped plasticity model parameters for 371 rectangular and 290 circular RC columns. The model parameters for adequate flexural rigidity, plastic rotation capacity, post-capping rotation capacity, moment strength, and cyclic strength degradation parameter are adjusted to match each experimentally observed load-deformation response. We have developed predictive equations that accurately relate the model parameters to the design characteristics of RC columns through regression analyses, providing a reliable tool for engineers and researchers. To demonstrate their application, the proposed and existing models numerically simulate the earthquake response of a bridge pier in a metropolitan railway bridge. The pier is subjected to several ground motions, increasing intensity until collapse occurs. The proposed lumped plasticity model showed about 41% less vulnerable to collapse.
While the subduction zone earthquakes have long ground motion durations, the effects are also not covered in seismic design provisions. Additionally, the collapse risk of steel frame buildings subjected to long-duration ground motions from subduction earthquakes remains poorly understood. This paper presents the influence of ground motion duration on the collapse risk of steel frame buildings with special concentrically braced frames in chevron configurations. The steel buildings considered in this paper are designed at a site in Seattle, Washington, according to the requirements of modern seismic design provisions in the United States. For this purpose, the nonlinear dynamic analyses employ two sets of spectrally equivalent long and short-duration ground motions. Based on the use of high-fidelity structural models accounting for both geometric and material nonlinearities, the estimated collapse capacity for the modern code-compliant steel frame buildings is, on average, approximately 1.47 times the smaller value when considering long-duration ground motion record, compared to the short-duration counterpart. Due to the sensitivity to destabilizing P-Delta effects of gravity loads, the influence of ground motion duration on collapse risk is more profound for medium-to-high-rise steel frame buildings compared to the low-rise counterparts.
This study explores the seismic performance of steel diaphragm walls in underground structures, a critical aspect of structural engineering. The study focuses on the effects of slab diaphragm flexibility, an often overlooked factor in seismic design. Traditional seismic designs often assume the slab acts as a rigid diaphragm, leading to inaccuracies in predicting how forces are distributed between the slab and walls during an earthquake. To address this, the authors model steel diaphragm walls using equivalent cross-sections and analyze shear forces in both rigid and semi-rigid diaphragm scenarios. Results show that semi-rigid diaphragms reduce the shear forces on the exterior walls while increasing them on the internal core, thereby affecting the overall stiffness of the structure. The study emphasizes the importance of considering diaphragm flexibility in seismic design to achieve more accurate predictions of structural behavior and improve construction efficiency.
A seismic intensity map, which describes ground motion distribution due to an earthquake, is crucial for disaster evaluation after the event. The ShakeMap system, developed and disseminated by the USGS, is widely used to generate intensity maps in many countries. The system utilizes a semi-variogram model to interpolate the measured intensities at seismic stations spatially. However, the default semi-variogram model embedded in ShakeMap is based on data from high seismic regions, which may not be suitable for the Korean Peninsula, categorized as a low-to-moderate seismic region. To address this discrepancy, this study aims to develop the region-specific semi-variogram model using local records and a region-specific ground motion model (GMM). To achieve this, we followed these steps: 1) collected records from significant earthquake events in South Korea, 2) calculated residuals between the observed intensities and predictions by the GMM, and 3) created semi-variogram models using weighted least squares regression to better fit short separation distances for PGA, PGV, SA0.2, and SA1.0. We compared the developed semi-variogram models with conventional models embedded in ShakeMap. Validation tests showed that the region-specific semi-variogram model reduced the mean squared error of intensity predictions by approximately 3.5% compared to the conventional model.
Most reinforced concrete (RC) school buildings constructed in the 1980s have seismic vulnerabilities due to low transverse reinforcement ratios in columns and beam-column joints. In addition, the building structures designed for only gravity loads have the weak-columnstrong- beam (WCSB) system, resulting in low lateral resistance capacity. This study aims to investigate the lateral resistance capacities of a two-story, full-scale school building specimen through cyclic loading tests. Based on the experimental responses, load-displacement hysteresis behavior and story drift-strain relationship were mainly investigated by comparing the responses to code-defined story drift limits. The test specimen experienced stress concentration at the bottom of the first story columns and shear failure at the beam-column joints with strength degradation and bond failure observed at the life safety level specified in the code-defined drift limits for RC moment frames with seismic details. This indicates that the seismically vulnerable school building test specimen does not meet the minimum performance requirements under a 1,400-year return period earthquake, suggesting that seismic retrofitting is necessary.
Early warnings have been developed to provide rapid earthquake information, allowing people to prepare as much time as possible. However, since it takes several seconds for an earthquake warning to be issued, the blind zone is inevitable. To reduce the blind zone, information from a single observatory is used to operate an on-site earthquake warning. However, false and missed alarms are still high, requiring continued research and validation. This study predicted Peak Ground Acceleration (PGA) using the characteristic data to reduce false and missed alarms in on-site earthquake warnings. A machine learning prediction model was created using the initial P-wave parameters developed from the characteristic data to achieve this. Then, the model was used to predict the maximum ground acceleration in the southeastern region of the Korean Peninsula. The expected results for six target earthquakes were confirmed to have a standard deviation within 0.3 compared to the observed PGA and the values within ±2 sigma. This method is expected to help develop an on-site early warning system for earthquakes.