In earthquake-prone regions, buildings are often damaged during seismic events but may still remain in use, owing to the high cost of replacement. The development of seismic capability assessment methods, therefore, becomes crucial. Taiwan’s National Centre for Research on Earthquake Engineering (NCREE) has developed a seismic assessment methodology, consisting of preliminary and detailed evaluations. The preliminary evaluation includes adjustable parameters to account for buildings with unique conditions, such as special shapes. Soft-story buildings are important examples. Failing to incorporate adjustment parameters for soft-story buildings could lead to an overestimation of their seismic capability. In this paper, a building information modelling (BIM)–based approach is demonstrated to automate the process of making preliminary evaluations of seismic capability. BIM can efficiently extract the required data and integrate eccentricity and rigidity ratio adjustments. The simplified model is also compared with the standard model to verify the validity of using elastic stiffness as a substitute for secant stiffness. The results show that, after adjustments, the preliminary evaluation closely aligns with the detailed evaluation, preventing overestimation of seismic capability. Furthermore, BIM also enhances automation, improves flexibility, and supports efficient information management.

Abstract Earthquake forecasting remains a fundamental challenge in statistical physics and geoscience due to the stochastic, clustered, and heavy-tailed nature of seismicity. A key limitation in current models is the lack of a rigorous characterization of extreme-event statistics in space–time–magnitude domains. In this Letter, we derive analytically the distribution of the largest event within a seismic cluster generated by a subcritical epidemic-type aftershock sequence model. Using a Neumann series expansion and a constructive bounding technique, we prove that the probability density η(t,x,y,m) decays as a power law in both time and space, η∼K(m)t−pr−ξ, under general heavy-tailed kernels with p > 1, ξ>2, and subcriticality condition |B(m)|<1. This result reveals the asymptotic structure of extreme seismic fluctuations and quantifies the decay rate of the most destructive events. Numerical simulations confirm our theory, providing a first-principles foundation for forecasting extreme events in earthquake-prone regions. Our findings have direct implications for probabilistic hazard assessment and represent a critical step toward predictive seismology grounded in statistical mechanics.

Abstract This study evaluates the quality of materials in reinforced concrete buildings and their compliance with relevant legislation and earthquake codes. In this scope, field observations of collapsed 400 reinforced concrete (RC) buildings in Kahramanmaraş, Adıyaman, Hatay and Gaziantep provinces, which are among the provinces affected by the Kahramanmaraş earthquakes, were conducted, general information and official documents about the buildings were collected, and detailed investigations including structural material properties were carried out. Some data was obtained from experimental studies conducted in the laboratory. The other part was obtained from reports. Differences were observed in the percentage distribution between the average compressive strength and the minimum compressive strength. In addition, factors such as the use of smooth, large-diameter stream aggregates, inappropriate granulometry, low material quality, poor workmanship, and insufficient compaction negatively impacted the building performance. Additionally, approximately 36% of the buildings were constructed with ribbed reinforcement, 31% with non-ribbed reinforcement, and 25% with both types of reinforcement. The use of ribbed reinforcement in buildings increased significantly after 1997 and its usage rate increased in the subsequent years. The findings of this study will contribute to a better understanding of the current building material deficiencies in earthquake-prone regions and provide information on strategies that should be developed in terms of building materials to improve the resilience of buildings with similar characteristics in other earthquake regions against future seismic events.

Earthquakes, as one of the most destructive natural hazards, pose significant threats to human lives and infrastructure. The aftermath of an earthquake often results in cascading events, including structural damages, floods, and landslides, leading to considerable loss of life and property. Factors influencing the severity of these disasters include population density, construction standards, and emergency preparedness. Effective emergency preparedness aims to minimize these losses during natural disasters. This research aimed at identifying and assessing the open public spaces available in three sampled wards – 1, 7 and 17 of Pokhara Metropolitan City. This research focused on the critical issues of earthquake preparedness in the city of Pokhara, a region at high risk of seismic activity. The study employed various research methods such as focus group discussions, questionnaire surveys, and map surveys to collect the data. ArcGIS was employed for assessing of the open spaces and mapping purposes. Despite being among the 20 most disaster-prone countries globally, Nepal lacks robust governance for disaster preparedness, particularly in Pokhara. Results revealed significant disparities in open space availability and holding capacities among the selected wards, with ward no. 17 having the lowest open space area followed by ward no. 1 and 7 relatively. Those wards have a total of 156,657.41 m2, 566,320 m2 and 84,103.29 m2 respectively. There was good road access to the most of the open spaces. However, basic facilities such as public toilets and drinking water are lacking in many areas. The findings also emphasize the need for policy review, careful selection of open spaces, maintenance of basic facilities, and the development of emergency evacuation plans. Public awareness campaigns are also recommended to sensitize residents of Pokhara about potential natural disasters, mitigation measures, and evacuation plans. This study contributes valuable insights to the broader field of disaster management and urban planning, particularly in earthquake-prone regions.

Seismic performance evaluation of high-rise buildings plays a crucial role in maintaining structural safety within earthquake-prone regions. The growing frequency and intensity of seismic activities worldwide require innovative approaches to structural design that focus on resilience, creating sustainable solutions and safety assurance. The conventional force-based methods fail to properly capture nonlinear structural behaviors. On the other hand, energy-based seismic analysis provides a better understanding of how seismic energy get absorbed and distributed within buildings that is to say, the pathways through which earthquake energy flows. This study analyzes the behavior of a 10-story reinforced concrete (RC) building using pushover analysis (POA) and response spectrum analysis (RSA) in ETABS, following the Bangladesh National Building Code (BNBC 2020). The building is modeled with typical gravity and lateral load-resisting systems, considering BNBC seismic code specifications. The POA provides insights into the nonlinear performance of the structure, identifying hinge locations and performance levels under increasing lateral loads. Meanwhile, RSA assesses building responses to seismic motions through vibration pattern studies. A comparative evaluation of base shear, story displacement and drift ratios is conducted to determine whether the structure meets BNBC safety limits. Results suggest that while response spectrum analysis is effective for preliminary design, pushover analysis offers deeper insight into potential failure mechanisms. This study emphasizes the significance of integrating both static and dynamic approaches for a comprehensive seismic evaluation of high-rise buildings.

Community-based disaster management is an essential strategy for enhancing the resilience of those residing in earthquake-prone regions. This initiative was undertaken by church communities to aid disaster preparedness by utilizing church facilities as temporary evacuation shelters. The primary aim was to ascertain the possibilities and fundamental prerequisites for enabling church facilities to function effectively as emergency shelters. The activities encompassed focus group discussions, direct observations of building conditions, and the development of a preliminary draft for a feasibility evaluation guideline. Furthermore, geographical capacity mapping and an inventory of accessible basic facilities were completed. This program establishes a foundation for creating a systematic and participatory evaluation framework, with the objective of enhancing the social function of churches in emergency response activities.

Enhancing seismic resilience in the built environment is essential for safeguarding structures in earthquake-prone regions. Inerter-based vibration control systems represent an important advancement in earthquake engineering, yet their effectiveness under pulse-like, near-fault ground motions has not been thoroughly evaluated. This study investigates the seismic response of building structures equipped with tuned mass damper inerter (TMDI) systems when subjected to intense, pulse-like excitations, with reference to the 2024 Noto earthquake in Japan (M w 7.6). Through comprehensive simulation of low, medium, and high-rise structural models, spanning fundamental periods of 0.5, 1.0, and 2.0 s, the research assesses TMDI performance across varying mass ratios. Results indicate notable reductions in seismic vulnerability and damage potential, with performance gains validated against HAZUS fragility benchmarks for comparable structures demonstrating up to 145% improvement in median PGA for slight damage and 167% for moderate damage states. The findings underscore the potential of TMDIs as scalable, innovative vibration control solutions, contributing to safer and more sustainable built environments in near-fault seismic regions worldwide.

Seismic vulnerability assessment of reinforced concrete (RC) structures is crucial in earthquake-prone regions to mitigate risks to life and property. This study proposes a systematic three-phase framework for enhanced seismic risk assessment: (1) Automation, (2) Evaluation, and (3) Predictive Modeling. For the Automation Phase, a web-based tool was developed to digitize and streamline the Turkish Rapid Visual Screening (RVS) procedure, eliminating manual calculation errors while improving efficiency. During the Evaluation Phase, we applied this tool to assess 600 buildings, classifying them into four distinct risk categories (no, low, moderate, and high risk) through standardized scoring. Finally, in the Predictive Modeling Phase we conducted correlation analysis to identify key seismic risk factors (e.g., building height showing a strong negative correlation, while soft-story mechanisms and short columns emerged as critical vulnerabilities) and implemented three machine learning models (XGBoost, Random Forest, and AdaBoost) for risk prediction, with XGBoost achieving superior accuracy. The framework’s validation confirmed the web tool’s reliability relative to conventional methods while revealing most buildings as low-risk, demonstrating how this integrated approach—combining automated screening, large-scale assessment, and data-driven prediction—provides a scalable solution for seismic risk mitigation in vulnerable regions.

Base shear is one of the main parameters in the analysis and design of earthquake-resistant building structures. This parameter is particularly important in the Special Moment Resisting Frame (SMRF) system, which is known for its high ductility and good energy dissipation capacity, making it widely applied to buildings in earthquake-prone areas. This study aims to analyze the magnitude of base shear in buildings with the SMRF system based on the provisions of SNI 1726:2019, taking into account several factors, including the total mass of the structure, the fundamental period, the importance factor of the building, soil conditions, as well as the seismic response coefficient modified by the response modification factor according to the structural system used. The research employed a numerical analysis approach using structural modeling software, where the design seismic forces were calculated based on the relevant seismic parameters. The results show that the base shear value is significantly influenced by the mass of the structure and the fundamental period of the building, as well as variations in response spectrum values due to different soil conditions. The analysis also highlights the importance of selecting appropriate importance factors and response modification factors to ensure both safety and efficiency in structural design. In conclusion, this study emphasizes that the implementation of the provisions in SNI 1726:2019 is crucial in determining accurate base shear values. This not only has implications for the structural resistance of buildings against seismic loads but also for occupant safety and the sustainability of building functions in earthquake-prone regions.

Indonesia faces a high earthquake risk due to its location at the convergence of major tectonic plates, necessitating earthquake-resistant building design that accounts for both structural and non-structural components, including infill walls. This study evaluates the effect of infill wall materials—clay bricks and lightweight bricks—on the seismic response of a four-story reinforced concrete frame building located on soft soil in Pekalongan City. The analysis was performed using the response spectrum method in ETABS. Two structural models were developed by representing the infill walls as uniformly distributed dead loads on beams, with each load corresponding to the wall material. The results show that the use of lightweight bricks reduces lateral and vertical forces at the ground floor by approximately 9–11% and decreases the maximum inter-story drift by up to 7.6% compared to clay bricks. In addition, the lightweight brick model exhibits a shorter fundamental vibration period, indicating increased structural stiffness due to reduced mass. All models satisfy the mass-participation requirements specified in the Indonesian seismic code. These findings indicate that lightweight bricks provide a more efficient alternative for infill walls and improve the seismic performance of mid-rise buildings in earthquake-prone regions.

This study proposes a novel braced corrugated shear panel (BCSP) system aimed at enhancing the seismic resilience of steel structures. In contrast to conventional flat shear panels, the BCSP incorporates stiffening ribs and corrugated geometry to improve deformability, delay local and global buckling, and increase lateral load-carrying capacity under cyclic loading. Metal shear panels are widely recognized for their stable hysteretic behavior, particularly in high seismic regions; nevertheless, their performance can be further improved through optimized geometry. This research examines the influence of corrugation orientation and angle on the behavior of BCSPs subjected to cyclic loading, demonstrating that replacing traditional thin ductile shear panels with a corrugated configuration significantly enhances structural response. The results show that horizontal corrugation provides superior strength, stiffness, and ductility compared to vertical or inclined corrugation, while the combined effect of bracing and corrugation increases lateral load-resisting capacity and facilitates easier post-earthquake replacement. Overall, BCSPs with horizontal corrugation exhibit optimal performance and high structural resilience in earthquake-prone regions, offering a promising advancement for future steel structure design.

This study explores the relationship between sustainable earthquake awareness and earthquake stress coping strategies among university students following the February 6, 2023, earthquake. A descriptive, cross-sectional study was conducted between March and April 2024, involving 239 university students. Following the STROBE checklist, data were collected using the Personal Information Form, Earthquake Stress Coping Scale (ESCS), and Sustainable Earthquake Awareness Scale (SEAS). Ethics approval was obtained, and data were gathered through face-to-face surveys. The average participant age was 21 years; 67.8% were women, and 20% had direct earthquake experience. Among participants, 67.4% reported negative academic impacts due to the earthquake. Higher SEAS scores were associated with higher income, prior earthquake experiences, having an emergency kit, securing belongings, and participation in earthquake training and drills. Higher ESCS social support-seeking scores correlated with higher income, earthquake preparedness training, drill participation, awareness of emergency meeting areas, and enrollment in the child development department. The findings highlight gaps in earthquake preparedness among university students while emphasizing the role of personal earthquake experiences in fostering awareness and adaptive coping strategies. Enhancing earthquake preparedness training could improve resilience among students in earthquake-prone regions.

Seismic slope instability poses a major hazard in earthquake-prone regions, where ground shaking can cause sudden slope failures resulting in severe damage and loss of life. Reliable assessment of seismic slope performance is therefore essential for geotechnical design. This study compares the Limit Equilibrium Method (LEM) and the Finite Element Method (FEM) in evaluating slope stability under pseudo-static and dynamic loading. The analysis investigates the effects of horizontal (kh) and vertical (kv) seismic coefficients, soil constitutive models, mesh refinement, and earthquake loading types on the Factor of Safety (FoS). Pseudo-static results show a clear reduction in stability with increasing seismic intensity. As the horizontal coefficient increases from kh=0.0 to kh=0.20, the FoS decreases from 1.706 to 0.945 in LEM and from 2.018 to 1.123 in FEM. Vertical acceleration further reduces FoS, especially when kv approx 0.75 kh. FEM consistently predicts higher stability than LEM, typically by 17-19%, due to its ability to model stress redistribution and deformation compatibility. Analyses of constitutive models and mesh refinement indicate close agreement between Mohr-Coulomb and Hardening Soil Small models, with differences generally within 1-3%, while finer meshes reduce FoS by 2-7% due to improved strain localization. Dynamic simulations show that time-history loading produces slightly higher FoS than pseudo-static analysis, whereas harmonic cyclic loading yields the lowest stability. These results highlight the importance of advanced numerical modeling and realistic seismic input in achieving reliable assessments of seismic slope stability.

This study addresses the vulnerability of reinforced concrete structures to multiple seismic events, considering the often-neglected effects of prior and subsequent shaking. The research emphasizes the need for a comprehensive evaluation of various structural systems to gauge the cumulative impact of multiple earthquakes, aiming to inform design processes for enhanced structural safety. The study specifically examines a mid-rise residential reinforced concrete building subjected to seven earthquake sequences, combining actual and artificial repeating events. The objective of the study is to investigate the response of an existing RC building structure located in Karachi, subjected to multiple shocks of earthquake. The scope of the current research covers the response evaluation of low to mid-rise RC building structures (engineered and non-engineered) located in Karachi. To this end, an FEM model has been developed with different sources of nonlinearities (Geometric and Material) and analyzed for recorded and simulated multiple sequences of earthquake. The research assesses the structure's response in terms of drifts, maximum displacements, and damage patterns. The results contribute valuable insights for understanding structural behavior under seismic conditions, with a specific emphasis on the percentage difference in displacement between the main shock and combined main shock and aftershock scenarios. The observed trends, including pronounced variations in displacement across different story levels, inform seismic vulnerability mitigation and retrofitting strategies, ultimately enhancing structural safety in earthquake-prone regions.

Abstract Seismicity de-clustering involves categorizing seismic events in a catalog into mainshocks, aftershocks, foreshocks, and background events. Achieving accurate de-clustering is essential for interpreting seismic activity patterns and assessing geological risks. This study addresses the challenge of effectively separating these events in earthquake-prone regions through the development of a modified Multi-objective Adaptive Guided Differential Evolution (mMOAGDE) algorithm. The mMOAGDE algorithm introduces innovative features such as adaptive control parameters and three distinct mutation phases to improve diversity and exploration in the solution space. By utilizing Strength Pareto instead of crowding distance and incorporating an archive control mechanism to maintain a constant size of non-dominated solutions, the algorithm achieves a balance between exploration and exploitation. Furthermore, a binary version of mMOAGDE integrates logical adaptive guided exploration to enhance the separation of seismic events. The algorithm evaluates two objective functions, Global Moran’s Index (GMI) and Allan Factor (AF), in spatial and temporal domains to de-cluster seismic catalogs. Applied to 30 years of earthquake data from regions including Southern California, Indonesia, Iran, and Japan, the mMOAGDE is benchmarked against established algorithms such as ANSGA-III, CMOPSO, MOEA/D-UR, and FLEA. The results demonstrate that the de-clustered catalogs yield GMI values within the desired range (-1 to 1) and maximize AF values. Validation through cumulative plots, $$\lambda$$ -plots, Allan factor plots, and inter-event time versus inter-event distance plots confirms the algorithm’s effectiveness in distinguishing aftershocks from background seismicity. This research highlights the potential of the mMOAGDE algorithm as a powerful tool for seismicity de-clustering, offering significant insights into earthquake dynamics and enhancing seismic risk assessment methodologies.

ABSTRACT Historical masonry bridges in many developing countries are highly vulnerable to seismic damage due to their construction without consideration of regional earthquake risks. This study investigates the seismic behavior of a historical masonry arch bridge that remains in active use. A detailed Finite Element Model (FEM) of the structure was developed using ABAQUS software based on original architectural drawings. Nonlinear time-history analyses were performed using 110 ground motion records to determine seismic demands. Mid-span lateral displacements were used to define damage states under varying seismic intensity levels, based on multiple scaled ground motion records. Analytical fragility curves were derived to estimate the probability of exceeding specific damage levels under varying seismic intensities. To complement the global vulnerability assessment, the Concrete Damaged Plasticity (CDP) model was employed to evaluate localized damage patterns, including tensile and compressive failure mechanisms. Results revealed that damage tends to concentrate at the arch bases and span ends, aligning with stress concentrations under seismic loads. The study provides a comprehensive framework for assessing the seismic performance of historical masonry bridges and highlights the necessity of structure-specific evaluations. The methodology and findings are applicable to similar masonry bridge typologies in other earthquake-prone regions, supporting future conservation and retrofitting strategies.

Seismic risk assessment is essential for reducing earthquake-related damage in urban areas. Accurate recognition of building features is a key factor in evaluating seismic vulnerability, yet traditional manual inspection methods are inefficient and prone to error. This study proposes a deep learning-based framework using convolutional neural networks for automated instance segmentation of building features to support seismic risk estimation in Lima, Peru, a seismically active region with diverse architectural styles. Leveraging state-of-the-art models like Mask R-CNN, the framework identifies and segments structural components such as walls, windows, and columns from building imagery. By integrating geospatial data and remote sensing technologies, the proposed approach enhances seismic risk evaluations through automated, scalable, and precise feature recognition. Despite challenges such as occlusions, varying lighting conditions, and architectural diversity, the model aims to adapt through specialized training tailored to Lima’s urban landscape, contributing to more efficient disaster preparedness and response in earthquake-prone regions.

Real-time monitoring of building movement is essential to mitigate structural damage risks, particularly in earthquake-prone regions. The application of Internet of Things (IoT) technology enables continuous and efficient measurement of structural deformation and inclination through the integration of smart sensors and cloud-based systems. The primary objective of this study is to evaluate the performance of a MEMS-based IoT sensor system in detecting displacement and angular changes in building structures. An experimental laboratory test was conducted by comparing the readings of accelerometer, gyroscope, and inclinometer sensors with standard measuring instruments. Results indicate an average measurement error of 1.58%, a response time of 2.34 seconds, and data transmission reliability of 97.8%, demonstrating high accuracy and stability. The integration of sensors, an ESP32 microcontroller, and a cloud computing platform shows strong potential for implementation as an effective IoT-based Structural Health Monitoring (SHM) system, supporting the development of resilient and sustainable smart infrastructure

Purpose This study aims to quantify the effects of damper design parameters, building height, and seismic input types on the seismic response of reinforced concrete frames retrofitted with tension-compression resilient slip friction dampers. Despite their growing application, the performance of these dampers across different structural configurations and earthquake scenarios remains underexplored. By addressing this gap, the research seeks to provide data-driven insights to optimize retrofit strategies and enhance seismic resilience. The goal is to inform future design standards and contribute to more effective implementation of friction-based damping systems in earthquake-prone regions. Design/methodology/approach This study presents a parametric investigation using nonlinear time-history analysis in OpenSeesPy to assess the seismic performance of reinforced concrete moment-resisting frames retrofitted with tension-compression resilient slip friction dampers. Three damper configurations with varying friction thresholds and stiffness levels are evaluated across 3-, 5-, and 7-story building frames. Sixty ground motion records are considered, equally divided into pulse-like near-fault, non-pulse-like near-fault and far-field categories. Key structural response parameters, including peak roof displacement, interstory drift ratios, base shear forces and roof acceleration, are examined. The study aims to clarify how damper properties and structural characteristics influence seismic response outcomes. Findings The study reveals that damper effectiveness significantly depends on the interplay between damper properties, building height and earthquake type. Retrofitted frames exhibited substantial reductions in peak roof displacement, interstory drift and base shear compared to the unretrofitted model, particularly under near-fault pulse-like motions. Damper configurations with moderate friction thresholds and balanced stiffness offered optimal performance across scenarios. Additionally, taller frames benefited more noticeably from damping interventions. These results emphasize the importance of tailored damper parameterization for different structural and seismic contexts, providing robust evidence to guide the seismic retrofit of existing reinforced concrete structures using friction-based systems. Originality/value This study provides a novel contribution by systematically evaluating the seismic performance of reinforced concrete frames retrofitted with tension-compression resilient slip friction dampers under a wide range of structural configurations and earthquake types. Unlike previous research that focused on limited scenarios, this work integrates multiple damper designs, building heights, and categorized ground motion records to offer statistically robust insights.

The Sichuan–Yunnan region, a primary seismic-prone zone on the Qinghai–Tibet Plateau, has experienced heightened seismic exposure due to rapid urbanisation. In order to address the issue of disaster risks and to promote sustainable urban development, this study establishes an integrated urban seismic resilience evaluation framework based on the DPSIR (Driving–Pressure–State–Impact–Response) model. The CRITIC–AHP combined weighting method was utilised to determine indicator weights, and data from 37 prefecture-level cities (2010, 2015, 2020) were analysed to reveal spatial–temporal evolution patterns and correlations. The results demonstrate a consistent improvement in regional seismic resilience, with the overall index increasing from 0.501 in 2010 to 0.526 in 2020. Sichuan exhibited a “decline-then-rise” trend (0.570 to 0.566 to 0.585), while Yunnan demonstrated continuous growth (0.517 to 0.557). The spatial pattern underwent an evolution from “west–low, central–eastern–high” to “south–high, north–low”, with over half of the cities attaining relatively high resilience by 2020. Chengdu and Kunming have been identified as dual high-resilience cores, diffusing resilience outward to neighbouring regions. In contrast, mountainous areas such as Garze and Aba have been found to exhibit low resilience levels, primarily due to high seismic stress and limited socioeconomic capacity. Subsystem analysis has revealed divergent resilience pathways across provinces, while spatial autocorrelation has demonstrated fluctuating global Moran’s I values and temporary local clustering. This research provides a scientific foundation for seismic disaster mitigation and offers a transferable analytical framework for enhancing urban resilience in earthquake-prone regions globally.