Search Results (150)

This study develops a comprehensive workflow for the analytical seismic vulnerability and structural performance assessment of a special-importance steel building located in a region of elevated seismic hazard in southern Spain. The work addresses the need for reliable analytical methodologies for facilities that must remain operational during earthquakes. The proposed framework integrates a probabilistic seismic hazard assessment, including uniform hazard spectra and hazard disaggregation to identify control earthquakes. Additionally, an analytical vulnerability assessment under the Spanish seismic design code, NCSE-02, is performed. Operational modal analysis and nonlinear analysis are combined to retrofit the numerical model of the building and capture the building’s realistic seismic response. The resulting demand spectra are derived from site-specific ground-motion scenarios for Los Barrios (Cádiz, Spain). Retrofitting strategies are designed and assessed to ensure compliance with the code-defined performance requirements. Results indicate that the retrofitted model reproduces the building’s dynamic behaviour with improved reliability, and that the strengthening interventions enhance seismic performance while still allowing moderate damage in specific components. These findings highlight the importance of analytical vulnerability approaches and code-oriented retrofitting when evaluating the seismic performance and vulnerability of essential facilities. The study demonstrates that rigorous analytical methods provide a robust basis for defining seismic vulnerability in special-importance buildings and support improved decision-making for structural safety and resilience. Full article

Significant earthquakes can cause widespread infrastructure damage, social implications, and substantial economic losses. To mitigate these impacts, earthquake forecasting models have been developed to estimate earthquake occurrences and improve recovery efforts, with the Epidemic-Type Aftershock Sequence (ETAS) model being the most informative statistical framework for characterizing earthquake sequences. In this study, the ETAS model is used to estimate the model parameters for seismicity in Canada using the historical earthquake catalogue and to forecast long-term seismicity for seven different regions in Canada. Furthermore, the model is used to generate synthetic earthquake catalogues in order to assess its ability to replicate observed seismic patterns. The study identifies the southwestern region of Canada, associated with the coastal area of British Columbia, as being at the highest seismic risk, with a 66% exceedance probability for M7.5 events or above to occur in 30 years. In contrast, Alberta features the least seismic risk, with a 4% exceedance probability for events above 6.5 magnitude. For southeastern Canada, associated with Eastern Ontario and Southern Quebec, an exceedance probability of 74% for events above 6.0 magnitude poses the potential for significant damage due to the larger exposed population. Moreover, the resulting seismicity maps show the model’s capability for real-events analysis, but improvements are needed for further applications. Full article

On 7 January 2025, an Mw7.1 earthquake struck Dingri County, Tibet, causing severe damage in a high-altitude, sparsely instrumented region where traditional damage assessment methods are limited. To address this, we developed an integrated "source simulation–nighttime light validation" framework. First, a kinematic source model (constrained by InSAR and teleseismic data) and the Unified Seismic Tomography models for continental China lithosphere 2.0 (USTClitho2.0) velocity model were used with the curved-grid finite difference method to simulate high-resolution ground motion and intensity fields. Second, NASA Black Marble (VNP46A2) nighttime light data, processed with the Block-Matching and 3D filtering (BM3D) algorithm, were analyzed to compute pixel-level radiance changes and township-level total nighttime light loss rates (TNLR). The results reveal a high spatial consistency between simulated high-intensity zones and areas of significant light loss. For instance, Mangpu Township, within a simulated high-intensity zone, exhibited a TNLR of 44.7%. This demonstrates that nighttime light remote sensing can effectively validate physical simulations in areas lacking dense seismic networks. Our framework provides a novel, complementary methodology for rapid and reliable post-earthquake damage assessment in high-mountain, data-sparse regions. Full article

This paper analyses the role of landscape as a fundamental dimension of post-earthquake recovery in the inland areas of Central Italy, arguing that reconstruction must be understood not only as the repair of damaged buildings but as a broader territorial process affecting identity, spatial organization, and long-term settlement trajectories. In this sense, post-earthquake recovery is also interpreted as a strategic opportunity to reinforce coast–inland relationships, acknowledging the structural interdependence between inland Apennine areas and coastal urban systems. Drawing on insights from applied research conducted in the L’Aquila 2009 crater and on the conceptual framework developed within the PRIN TRIALS project, the paper discusses how seismic events accelerate pre-existing territorial dynamics and produce enduring transformations, particularly in the proximity landscapes surrounding historic centres. Rather than presenting empirical findings, the contribution offers a theoretical and operational framework aimed at integrating landscape considerations into reconstruction processes. It outlines key concepts such as landscape quality, transformative resilience, and permanent temporariness; reviews critical normative aspects linked to emergency procedures; and proposes a set of landscape-oriented guidelines and criteria for the contextual integration of reconstruction projects. These include landscape quality objectives, multiscalar readings of identity values, and operational tools such as visual-impact assessment, Project Reference Context analysis, and principles for managing transformations in peri-urban and historic environments. Overall, the paper argues that adopting a landscape-based perspective can strengthen territorial cohesion, support the sustainable redevelopment of historic centres and their surroundings, and embed post-earthquake reconstruction within broader coast–inland territorial strategies aimed at long-term resilience and balanced regional development in Apennine communities. Full article

Designing long-span cable-stayed bridges in high seismic hazard zones presents significant challenges due to their flexible structural systems, the influence of multi-support excitation, and the need to control large displacements while limiting seismic demands on critical components. These difficulties are further amplified in regions with complex geology and for bridges required to maintain high levels of post-earthquake serviceability. This study develops a low-damage seismic design approach for long-span cable-stayed bridges and demonstrates its application in the New Panama Canal Bridge. Probabilistic seismic hazard assessment and site response analyses are performed to generate spatially varying ground motions at the pylons and side piers. The pylons adopt a reinforced concrete configuration with embedded steel stiffeners for anchorage, forming a composite zone capable of efficiently transferring concentrated stay-cable forces. The lightweight main girder consists of a lattice-type steel framework connected to a high-strength reinforced concrete deck slab, providing both rigidity and structural efficiency. A coordinated girder–pylon restraint system—comprising vertical bearings, fuse-type restrainers, and viscous dampers—ensures controlled stiffness and effective energy dissipation. Nonlinear seismic analyses show that displacements of the girder remain well controlled under the Safety Evaluation Earthquake, and the dampers and bearings exhibit stable hysteretic behaviours. Cable tensions remain within 500–850 MPa, meeting minimal-damage performance criteria. Overall, the results demonstrate that low-damage seismic performance targets are achievable and that the proposed design approach enhances structural control and seismic resilience in long-span cable-stayed bridges. Full article

Slender structures such as minarets are highly susceptible to earthquake-induced damage in seismically active regions. Although various methods, including analytical and observational techniques, have been employed to study the seismic response of reinforced concrete (RC) minarets, the use of scaled physical models and shaking table testing remains limited. This research examines the numerical feasibility of employing scaled physical models for shaking table investigations of RC minarets under realistic laboratory constraints. A representative RC minaret with a height of 33.2 m was selected and a geometric scale ratio of 1:10 length was adopted. Established physical modeling approaches were evaluated through numerical implementation, with particular attention to similitude requirements, material properties, and laboratory limitations. Within this framework, the Artificial Mass Model (AMM) and the Neglected Gravity Model (NGM) were examined as candidate strategies for scaled modeling. Both approaches necessitate the use of a material with a reduced modulus of elasticity or an increased mass density relative to the prototype material. To satisfy these requirements, two micro-concrete mixes, designated as Mix-1 and Mix-2, incorporating partial replacement of the binder with lower-stiffness constituents such as plaster gypsum and fly ash, were developed and characterized. Numerical results indicate that both the AMM and NGM approaches are viable for modeling slender RC minaret structures. Although the AMM provides slightly higher accuracy in reproducing the prototype dynamic response, the NGM offers greater practical applicability by eliminating the need for additional artificial mass. Overall, this study presents a preliminary numerical feasibility assessment that supports the selection of appropriate physical modeling strategies and provides a rational basis for the subsequent execution of shaking table experiments. Full article

The decision-making process for the adaptive reuse of cultural heritage requires the evaluation of multiple criteria because of its multifaceted structure. The criteria determined through a literature review were weighted by experts and ranked according to their degree of importance via the DEMATEL method, which is a multicriteria decision-making technique. This study, conducted by integrating the importance levels of the criteria determined by the DEMATEL method with Geographic Information Systems (GIS) techniques, was applied to Yediocak Primary School, one of the significant buildings in Osmaniye, affected by the 2023 Kahramanmaraş Pazarcık Earthquake and heavily damaged during the event. The DEMATEL analysis demonstrated that economic value, regional potential, and compatibility with the new function are the primary cause-group criteria, whereas architectural, cultural, and social values are predominantly situated within the effect group. The spatial assessment yielded a low suitability score for the current primary school function (0.3954). The hybrid DEMATEL + GIS index (0.2598) confirmed that a building’s reuse as a high-occupancy school is constrained by seismic risk, its position on a heavily trafficked corridor, and relatively limited access to healthcare and emergency assembly areas. This study aimed to establish a new framework for the adaptive reuse of historic buildings. Full article

Liquefaction is a critical mechanism amplifying earthquake-induced damage, necessitating systematic hazard assessment through spatially distributed mapping. This study presents a nationwide liquefaction hazard assessment framework for South Korea, integrating site classification, liquefaction potential index (LPI) computation, and probabilistic damage evaluation. Sites across the Korean Peninsula were stratified into five geotechnical categories (S1–S5) based on soil characteristics. LPI values were computed incorporating site-specific amplification coefficients for nine bedrock acceleration levels corresponding to seismic recurrence intervals of 500, 1000, 2400, and 4800 years per Korean seismic design specifications. Subsurface characterization utilized standard penetration test (SPT) data from 121,821 boreholes, with an R-based analytical program enabling statistical processing and spatial visualization. Damage probability assessment employed Iwasaki’s LPI severity classification across site categories. Results indicate that at 0.10 g peak ground acceleration (500-year event), four regions exhibit severe liquefaction susceptibility. This geographic footprint expands to seven regions at 0.14 g (1000-year event) and eight regions at 0.18 g. For the 2400-year design basis earthquake (0.22 g), all eight identified high-risk zones reach critical thresholds simultaneously. Site-specific analysis reveals stark contrasts in vulnerability: S2 sites demonstrate 99% very low to low damage probability, whereas S3, S4, and S5 sites face 33%, 51%, and 99% severe damage risk, respectively. This study establishes a scalable, evidence-based framework enabling efficient large-scale liquefaction hazard assessment for governmental risk management applications. Full article

This study aims to demonstrate the presence of a pronounced coseismic increase in atmospheric methane concentrations during the 2024 Noto Peninsula Earthquake and to examine whether this increase may have originated from underground natural gas release. By analyzing hourly CH₄ data from the Ministry of the Environment’s monitoring network, this study shows that significant methane increases occurred only in areas with seismic intensity of 6– or greater, and that an exceptional anomaly—reaching 29 times the standard deviation of the past year—was recorded at the Nanao station. The validity of this anomaly was confirmed through consultation with local atmospheric officer, and high-time-resolution data (6 min values) were provided, verifying continuous instrument operation. Detailed analysis further shows that two major methane peaks occurred, each rising not immediately after the main shock but synchronously with two large aftershocks approximately 8 and 44 min later. Geological and hydrogeological information indicates the presence of water-soluble gas and unsaturated hydrocarbons beneath the Nanao region, suggesting that seismic shaking may have ruptured clay layers and released accumulated gas. Analyses of public reports and interviews with local officials show that alternative explanations—such as fire smoke, pipeline rupture, instrument malfunction, and gas-cylinder damage—were unlikely. These findings indicate that the observed methane anomaly was most likely caused by earthquake-synchronous underground gas release, suggesting that methane-release risk should be considered in post-earthquake fire-hazard assessments. Full article

The application of volumetric modular construction using Cross-Laminated Timber (CLT) has emerged as a sustainable and efficient alternative to traditional building methods, especially in residential and mid-rise structures. However, the widespread adoption of this technology remains limited due to the lack of standardized inter-modular connection systems. This paper presents a comprehensive state-of-the-art review of inter-modular connections used in volumetric CLT modular buildings. This review aims to evaluate the inter-modular connections by developing performance objectives and identifying gaps in knowledge of volumetric CLT inter-modular connections. It begins with an overview of global CLT modular construction trends, highlighting geographic distribution, structural demands, and environmental hazards such as seismic and wind exposure. Seven representative connection systems were identified from the literature and assessed using a multi-criteria framework comprising structural performance, manufacturing feasibility, on-site construction efficiency, and experimental and numerical evaluation. Each connection was scored according to defined evaluation metrics, and the results were provided to identify key strengths and limitations. The top-performing systems demonstrated superior resilience, modular adaptability, and validation through experimental testing and simulation. The paper identified critical research gaps, including limited performance data available for seismic applications, challenges in disassembly and reuse specifications, and the need for adaptable, damage-tolerant systems to enhance building structural performance. These findings provide a reference evaluation methodology for future development of inter-modular connections, to expand the applicability of volumetric CLT modular construction in moderate and high seismic and wind hazard regions. Full article

The end-of-life phase of a building, which includes demolition and waste disposal, represents a crucial aspect of sustainable construction. In Europe, construction and demolition (C&D) waste accounts for approximately 40% of the total waste generated in the EU, making its management a global challenge. The EU Construction & Demolition Waste Management Protocol (2024) emphasizes the importance of evaluating, before proceeding with the demolition of a building, whether renovation could be a more efficient solution, considering economic, environmental, and technical aspects. From an economic perspective, demolition costs vary depending on several factors, including project size, structural complexity, techniques employed (conventional or non-conventional), materials to be removed, and local regulations. In addition to the direct costs of the intervention, it is essential to consider indirect impacts, such as the management of construction and demolition (C&D) waste, the removal of hazardous substances, and potential environmental damage to be mitigated. This study analyzes a case located in Italy, in the municipality of Caivano (Metropolitan City of Naples, in Campania region), concerning a building that required energy efficiency improvements and seismic upgrades. The decision to demolish and rebuild proved to be economically more advantageous than renovation, while also allowing a 35% increase in volume, enabling the creation of a greater number of housing units. Through the analysis of this real case study, the aim is to highlight how investments in demolition, if properly planned, designed, assessed, and managed, can effectively contribute to building redevelopment, supporting the transition towards a sustainable construction model in line with the principles of the circular economy. Full article

This study presents a multi-factor coupled assessment of seismic disaster risk for approximately 635,000 individual building units in Ankang City, Shaanxi Province, China, utilizing a high-resolution dataset. The assessment methodology innovatively integrates the three core components of risk: seismic vulnerability V of load-bearing structures, site-specific seismic hazards R, and potential consequences C of damage, to formulate the Seismic Resilience Index I_SR = C·R·V. Crucially, the approach advances established risk assessment frameworks by enhancing the spatial resolution of the site influence coefficient R using a high-resolution national site classification map and detailed local geological data. The results reveal that the areas with the lowest I_SR values (indicating the lowest resilience and thus the highest risk) are predominantly concentrated in older residential districts of counties such as Ningshan, Hanyin, and Ziyang, where unreinforced masonry structures built prior to 1989 are widespread. The model assessment results align with expected structural performance characteristics, and the study concludes by offering quantified, priority-based recommendations for targeted structural intervention and seismic retrofitting in the identified highest-risk regions and building typologies. Full article

This study presents a methodology for determining the optimal placement of sensors along the height of buildings to minimize uncertainty in reconstructing structural response at non-instrumented floors. Recent advancements in sensing technology have expanded the application of sensor data in earthquake and structural engineering, including model validation, post-event damage assessment, and structural health monitoring. However, to lower the costs of sensor installation and maintenance—particularly at the regional scale—it is essential to strategically place sensors to maximize the value of the collected data. Because the optimal sensor configuration depends on the specific objectives of an instrumentation project, there is no universal solution to the sensor placement problem. In this study, we focus on identifying sensor locations that allow for accurate interpolation of structural responses at non-instrumented floors with minimal prediction uncertainty. This objective supports the primary goal of the California Strong Motion Instrumentation Program (CSMIP), which is to collect structural response data with the highest possible accuracy and the lowest uncertainty. The proposed method is limited to stationary excitations (e.g., ambient vibrations or distant earthquakes) and to buildings with uniform mass and stiffness distributions along their height. Under these assumptions, a Gaussian Process Regression (GPR) model is used to quantify response prediction uncertainty and minimize the total uncertainty across the building height by placing sensors at the most informative locations. The GPR model is based on a simple shear-flexural beam representation, which effectively approximates the building using very few parameters—parameters that can be estimated from limited building information. The proposed method is verified and validated using both simulated and real data. Finally, a table is proposed that can be used by strong motion networks to facilitate more quantitative decision-making regarding sensor placement. While assumptions used in this study may seem restrictive, they strike a practical balance between accuracy and simplicity for large-scale applications such as CSMIP. The extension of this work to non-stationary excitations and general building types by training the GPR model on recorded seismic data rather than random vibration theory is under development. Full article

Urban infrastructure in seismic zones demands efficient and scalable tools for damage prediction. This study introduces an attention-integrated progressive transfer learning (PTL) framework for the seismic vulnerability assessment (SVA) of reinforced concrete (RC) frame buildings. Traditional simulation-based vulnerability models are computationally expensive and dataset-specific, limiting their adaptability. To address this, we leverage a pretrained artificial neural network (ANN) model based on nonlinear static pushover analysis (NSPA) and Monte Carlo simulations for a 4-story RC frame, and extended its applicability to 2-, 8-, and 12-story configurations via PTL. An attention mechanism is incorporated to prioritize critical features, enhancing interpretability and classification accuracy. The model achieves 95.64% accuracy across five damage categories and an R² of 0.98 for regression-based damage index predictions. Comparative evaluation against classical and deep learning models demonstrates superior generalization and computational efficiency. The proposed framework reduced retraining requirements across varying building heights, shows potential adaptability to other structural typologies, and maintains high predictive fidelity, making it a practical AI solution for structural risk evaluation in seismically active regions. Full article

Ground settlement is a multifaceted geological phenomenon driven by natural and man-made forces, posing a significant impediment to sustainable urban development. Thus, ground settlement susceptibility (GSS) mapping has emerged as a critical tool for understanding and mitigating cascading hazards in seismically active and anthropogenically modified sedimentary basins. Here, we develop an integrated framework for assessing GSS in the Pohang region, South Korea, by integrating Persistent Scatterer Interferometric Synthetic Aperture Radar (PSInSAR)-derived vertical land motion (VLM) data with seismological, geotechnical, and topographic parameters (i.e., peak ground acceleration (PGA), effective shear-wave velocity (V_s³⁰), site period (T_s), general amplification factor (A_F), seismic vulnerability index (K_g), soil depth, topographic slope, and landform classes) through ensemble machine learning models such as Random Forest (RF), XGBoost, and Decision Tree (DT). Analysis of 56 Sentinel-1 SLC images (2017–2023) revealed persistent subsidence concentrated in Quaternary alluvium, reclaimed coastal plains, and basin-fill deposits. Among the tested models, RF achieved the best performance and strongly agreed with field evidence of sand boils, liquefaction, and structural damage from the 2017 Pohang earthquake. The very-high-susceptibility zones exhibited mean subsidence rates of −3.21 mm/year, primarily within soft sediments (V_s³⁰ < 360 m/s) and areas of thick alluvium deposits. Integration of the optimal RF-based GSS index with regional building inventories revealed that nearly 65% of existing buildings fell within high- to very-high-susceptibility zones. The proposed framework demonstrates that integrating PSInSAR and ensemble learning provides a robust and transferable approach for quantifying ground settlement hazards and supporting risk-informed urban planning in seismically active and complex geological coastal environments. Full article