Search Results (68)

Reinforced concrete (RC)–masonry hybrid systems are commonly found in both historical renovations and modern constructions, particularly in seismic regions. While combining the ductility of RC with the mass and stiffness of masonry offers potential advantages, these systems often exhibit complex and unpredictable seismic behavior due to the differing mechanical characteristics of the two materials. This study aims to evaluate the benefits and drawbacks of RC–masonry hybrid systems by performing a comparative numerical analysis of three structural configurations. As a representative case study, the historical İsa Divanlı Mosque in Kahramanmaraş, Turkey—severely damaged during the 6 February 2023 earthquakes—is modeled under three scenarios: (Configuration A) full RC structure with shear walls, (Configuration B) unreinforced masonry, and (Configuration C) the existing hybrid form with an RC dome and slabs over masonry walls. Finite element models were developed for each case, and their seismic responses were analyzed under identical loading conditions. The maximum spectral displacements were 55.3 mm, 45.8 mm, and 59.5 mm for the RC, masonry, and hybrid configurations, respectively. The Normalized Displacement Index (NDI) values reached 0.666 mm/MPa for the RC and hybrid systems, while the masonry configuration remained at 0.528 mm/MPa, reflecting its brittle behavior. The findings highlight the influence of structural typology on seismic vulnerability and demonstrate the potential risks and disadvantages of hybrid systems. This study contributes to the understanding of hybrid structural behavior and offers recommendations for the design and retrofit of such systems in seismic regions. Full article

Assessing seismic vulnerability and prioritizing railway tunnels for seismic rehabilitation are critical components of railway infrastructure management, especially in seismically active regions. This study focuses on a railway network in Northwest Iran, consisting of 103 old masonry rock tunnels. The vulnerability of these tunnels is evaluated under 12 active faults as seismic sources. Fragility curves derived from the HAZUS methodology estimate the probability of various damage states under seismic intensities, including peak ground acceleration (PGA) and peak ground displacement (PGD). The expected values of the damage states are computed as the damage index (DI) to measure the severity of damage. A normalized prioritization index (NPI) is proposed, considering seismic vulnerability and life cycle damages in tunnel prioritizing. Finally, a detailed prioritization is provided in four classes. The results indicate that 10% of the tunnels are classified as priority, 33% as second priority, 40% as third priority, and 17% as fourth priority. This prioritization is necessary when there are budget limitations and it is not possible to retrofit all tunnels simultaneously. The main contribution of this study is the development of an integrated, data-driven framework for prioritizing the seismic rehabilitation of aging masonry railway tunnels, combining fragility-based vulnerability assessment with life-cycle damage considerations in a high-risk and data-limited region. The framework outlined in this study enables decision-making organizations to efficiently prioritize the tunnels based on vulnerability, which helps to increase seismic resilience. Full article

A framework for rapid seismic vulnerability assessment and disaster management of urban buildings was developed, incorporating structural information from Building Information Models (BIM) integrated into a Geographic Information System (GIS). The Critical Seismic Wall Index (CSWI) was evaluated for 252 undamaged and damaged buildings and compared with their seismic performance analyses. The seismic vulnerability of these buildings was determined based on site-specific seismic hazard analysis and compared with each building’s CSWI. This study demonstrates the use of BIM within a GIS workflow to enable rapid wall index calculation. Building on previous research that identifies a Critical Seismic Wall Index (CSWI) of 0.0025 as an indicator of a building’s seismic vulnerability, it further proposes a CSWI threshold of 0.004 for buildings with structural irregularities, based on the analysis of the studied building. The implementation of the integrated BIM–GIS methodology could enable rapid risk and damage assessment, as demonstrated in the investigated case studies. This study is significant because it provides a model for quickly assessing the seismic vulnerability of buildings, supporting resilience planning and sustainability, particularly in earthquake-prone regions, by prioritizing seismic risk by identification of high-risk buildings for demolition and prioritization of retrofit. Full article

Earthquake-induced liquefaction poses significant risks to urban infrastructure, yet traditional regional assessment methods are hindered by sparse geotechnical data and high-cost exploration. Based on transfer learning, this study develops a rapid assessment procedure for regional probabilistic liquefaction, enabling efficient probabilistic liquefaction assessment. This study demonstrates the feasibility of utilizing transfer learning to integrate abundant source domain data with readily available seismic information and post-earthquake observation data. A novel regional liquefaction probability index is also introduced. Both the proposed procedure and index are validated through their application to the 1999 Chi-Chi earthquake case, illustrating practical utility. Case results for Yuanlin City show that the assessment, which identifies the southeastern area as most liquefaction-prone and is consistent with both the index (highest values in this area) and post-earthquake field observations, validates the procedure’s effectiveness. A simplified calculation method for the index is also provided, ensuring strong practical applicability. Full article

Over the past several decades, extensive research has advanced the understanding of liquefaction in clean sands and sand–silt mixtures under seismic loading. However, the influence of plastic (i.e., clayey) fines on the liquefaction behavior of sandy soils remains less well understood. This study investigates how the quantity and plasticity of fines affect both the susceptibility to liquefaction and the resulting failure mode. A series of stress-controlled cyclic triaxial tests were conducted on sand specimens containing varying proportions of non-plastic silt, kaolinite, and bentonite. Specimens were prepared at a constant relative density with fines content ranging from 0% to 37%. Two liquefaction modes were examined: flow liquefaction, characterized by sudden and large strains under undrained conditions, and cyclic mobility, which involves gradual strain accumulation without complete strength loss. The results revealed a clear relationship between soil plasticity and liquefaction mode. Specimens containing non-plastic fines or fines with a liquid limit (LL) below 20% and a plasticity index (PI) of 0 exhibited flow liquefaction. In contrast, specimens with LL > 20% and PI ≥ 7% consistently displayed cyclic mobility behavior. These findings help reconcile the apparent contradiction between laboratory studies, which often show increased liquefaction susceptibility with plastic fines, and field observations, where clayey soils frequently appear non-liquefiable. The study emphasizes the critical role of plasticity in determining liquefaction type, providing essential insight for seismic risk assessments and design practices involving fine-containing sandy soils. Full article

The reduction in disaster risk in urban regions due to natural hazards (e.g., earthquakes, landslides, floods, and tropical cyclones) is primarily a development matter that must be treated within the scope of a broader urban development framework. Natural hazard assessment is one of the turning points in mitigating disaster risk, which typically contributes to stronger urban resilience and more sustainable urban development. Regarding this challenge, our research proposes a new approach in the signal processing chain and feature extraction from microtremor data that focuses mainly on the Horizontal-to-Vertical Spectral Ratio (HVSR) so as to assess liquefaction potential as a natural hazard using AI. The key raw seismic features of site amplification and resonance are extracted from the data via bandpass filtering, Fourier Transformation (FT), the calculation of the HVSR, and smoothing through the use of moving averages. The main novelty is the integration of machine learning, particularly stacked ensemble learning, for liquefaction potential classification from imbalanced seismic datasets. For this approach, several models are used to consider class imbalance, enhancing classification performance and offering better insight into liquefaction risk based on microtremor data. Then, the paper proposes a liquefaction detection method based on deep learning with an autoencoder and stacked classifiers. The autoencoder compresses data into the latent space, underlining the liquefaction features classified by the multi-layer perceptron (MLP) classifier and eXtreme Gradient Boosting (XGB) classifier, and the meta-model combines these outputs to put special emphasis on rare liquefaction events. This proposed methodology improved the detection of an imbalanced dataset, although challenges remain in both interpretability and computational complexity. We created a synthetic dataset of 1000 samples using realistic feature ranges that mimic the Rif data region to test model performance and conduct sensitivity analysis. Key seismic and geotechnical variables were included, confirming the amplification factor (Af) and seismic vulnerability index ($K_g$) as dominant predictors and supporting model generalizability in data-scarce regions. Our proposed method for liquefaction potential classification achieves 100% classification accuracy, 100% precision, and 100% recall, providing a new baseline. Compared to existing models such as XGB and MLP, the proposed model performs better in all metrics. This new approach could become a critical component in assessing liquefaction hazard, contributing to disaster mitigation and urban planning. Full article

In earthquake-prone regions, predicting the impact of seismic events on highway bridges is crucial for post-earthquake effective emergency response and recovery planning. This paper presents a methodology for a simplified seismic risk assessment of bridges using fragility curves that integrates updated ductility ratios of reinforced concrete bridge columns from literature based on experimental results on cyclic tests of reinforced concrete circular columns. The methodology considers two damage states (cover spalling and bar buckling) for bridge columns with seismic and non-seismic design considerations and then estimates displacement thresholds for each damage state. The Damage Margin Ratio (DMR) is introduced as an index defined by the ratio of the median Peak Ground Acceleration (PGA) for a specific damage state to the PGA that corresponds to the target seismic hazard probability of exceedance in 50 years that is typically defined in bridge design and evaluation codes and standards. The DMR is then compared to a user-specified Threshold Damage Margin Ratio (TDMR) to evaluate the level of risk at a specific threshold probability of exceedance of the damage state (5% and 10%). Comparative assessment is conducted for the relative seismic risk and performance of non-seismic and seismic bridges corresponding to the seismic hazard values at 10% and 2% probability of exceedance in 50 years for 7 urban centers in the province of Quebec as a case study demonstration of the methodology. The proposed methodology offers a rapid tool for screening and prioritizing bridges for detailed seismic evaluation. Full article

To analyze the impact of capacity uncertainty on the seismic collapse fragility of reinforced concrete (RC) frame structures, a fragility analysis framework based on seismic reliability methods is proposed. First, incremental dynamic analysis (IDA) curves are plotted by IDA under a group of natural seismic waves. Subsequently, collapse points are identified based on recommendations from relevant standards, yielding the probability distribution of the maximum inter-story drift ratios (MIDRs) at collapse points. Then, the distribution of the MIDRs under various intensity measures (IMs) of artificial seismic waves is calculated by using the fractional exponential moments-based maximum entropy method (FEM-MEM). Next, the structural failure probability is determined based on the combined performance index (CPI), and a seismic collapse fragility curve is plotted using the four-parameter shifted generalized lognormal distribution (SGLD) model. The results indicate that the collapse probability is lower considering the capacity uncertainty. Compared to deterministic MIDR limits of 1/25 and 1/50, the median values of the structure’s collapse resistance increased by 13.2% and 87.3%, respectively. Additionally, the failure probability obtained by considering the capacity uncertainty is lower than the results based on deterministic limits alone. These findings highlight the importance of considering capacity uncertainty in seismic risk assessments of RC frame structures. Full article

The transverse-direction post-seismic running safety of a longitudinally connected ballastless track-continuous girder bridge (LCBTCGB) system considering earthquake damage state (EDS) was studied. In this study, a simulation model of an LCBTCGB was established, and the post-earthquake damage law of the LCBTCGB was analyzed by selecting the ground motion that had the greatest influence from within the existing studies. The EDS of key interlayer components and the residual deformation law of each layer structure of the LCBTCGB system were defined. Subsequently, the residual deformations and EDS from the simulation model were imported into a coupled dynamic model of the train, track, and bridge. Evaluation of running safety evaluation after an earthquake was carried out with and without considering EDS, and a running safety guidance diagram for after an earthquake is provided. The results revealed that under conditions of rare earthquakes, without considering EDS, the running safety judgment after the earthquake were underestimated, and the risk increased by 13.6%. Following the designed earthquake, the running safety risk after the earthquake increased by 18.7% if EDS was not considered. The risk of the running safety index exceeding the limit did not increase linearly with earthquake intensity with and without considering EDS. When the EDS was considered, derailment coefficients and wheel axle lateral forces exceeded the safety limit value at an earthquake intensity of 0.2 g, whereas these limit values were only exceeded at an earthquake intensity of 0.3 g when EDS is ignored. When the earthquake intensity reached 0.5 g, the influence on the derailment coefficient was greater but the difference in the wheel axle lateral forces was not significant with or without considering EDS. It is suggested that EDS should be considered when post-seismic running safety of LCBTCGBs are analyzed; otherwise, it will lead to misjudgment of running safety after an earthquake. Full article

This study investigates five cases of municipal solid waste (MSW) landfill slope failures in the USA, China, Sri Lanka, and Greece, with the aim of assessing the safety margins and reliability of these slopes. The stability and reliability of the landfill slopes were evaluated under both static and seismic loading conditions, using pre-failure geometries and geotechnical data, with analyses conducted in accordance with Eurocode 7, employing all three design approaches. Under static loading, the factors of safety were close to unity, and reliability indexes ranged from 1.0 to 2.8, both falling below the recommended values set by Eurocode. The landfill slopes failed to meet the stability criteria in Design Approaches 2 and 3, while in Design Approach 1, four out of five landfills met the criteria. Under seismic conditions, safety factors and reliability indexes were significantly lower than the prescribed criteria in all analyses. Sensitivity analyses revealed that in two cases, unit weight and friction angle were the dominant parameters, while cohesion was the dominant parameter in one case. The findings of this study underscore the importance of establishing minimum design requirements for MSW landfill slope stability to mitigate potential risks to public health and the environment. Full article

A procedure for a simplified evaluation of bridges is proposed based on census and visual inspections. The structural–foundational, seismic, landslide, and hydraulic risks are considered, the hazard, vulnerability, and exposure factors of which are quantified with an index that can assume integer values from 1 to 5. Polynomial functions are then defined combining these indices, calculating an index for each risk and finally a multi-risk index of attention. The procedure follows a mathematical approach, less influenced by subjective choices, leading to a more gradual and efficient classification that managers can directly utilize. Specific needs and requirements result in specific configuration and calibration of the mathematical model coefficients. In this study, the authors calibrated coefficients to obtain results that were compliant with the Italian guidelines for existing bridges. The procedure, tested on a set of 86 bridges, does not replace an accurate evaluation, which is necessary in some cases and represents a higher level of knowledge, nor does it claim to provide a definitive result. It provides a more efficient classification, useful for establishing a rational decision-making process to prioritize any subsequent retrofit interventions. Full article

An investigation of risk factors has been identified as a crucial aspect of the routine management of rockburst. However, the identification methods for principal impact factors and the examination of the relationship between seismic energy and other source parameters have not been extensively explored to conduct dynamic risk management. This study aims to quantify impact risk factors and discriminate hazardous high-energy seismic events. The analytic hierarchy process (AHP) and entropy weight method (EWM) are utilized to ascertain the primary control factors based on geotechnical data and nearly two months of seismic data from a longwall panel. Furthermore, the distribution law and correlation relationship among seismic source parameters are systematically analyzed. Results show that the effect of coal depth, coal seam thickness, coal dip, and mining speed covers the entire mining process, while the fault is only prominent in localized areas. There are varying degrees of log-positive correlations between seismic energy and other source parameters, and this positive correlation is more pronounced for hazardous high-energy seismic events. Utilizing the linear logarithmic relationship between seismic energy and other source parameters, along with the impact weights of dynamic risks, the comprehensive energy index for evaluating high-energy seismic events is proposed. The comprehensive energy index identification method proves to be more accurate by comparing with the high-energy seismic events based on energy criteria. The limitations and improvements of this method are also synthesized to obtaining a wide range of applications. Full article

Investigating the distribution characteristics of earthquake disaster risks in the Sichuan–Yunnan region is of great importance for enhancing government emergency response capabilities and achieving sustainable regional development. This study, based on disaster systems theory, constructs a seismic risk evaluation index system for the Sichuan–Yunnan region and employs the entropy method to determine the comprehensive risk index for earthquake disasters across 37 prefecture-level cities. The findings reveal the following: (1) High-risk areas for disaster-causing factors are located in the Hengduan Mountain region and the North–South Mountain Range Valley Region; medium-risk areas are distributed along the northwestern edge of the Sichuan Basin; low-risk areas are situated in the eastern part of the Sichuan Basin and the Yunnan Plateau. (2) High-risk disaster-prone environments are found in the Hengduan Mountain region; medium-risk areas are present on the Yunnan Plateau and the western part of the North–South Mountain Range Valley Region; low-risk areas are in the Sichuan Basin. (3) High-vulnerability areas include the central Sichuan Basin and Kunming on the Yunnan Plateau; medium-vulnerability areas are located in the eastern and western parts of the Sichuan Basin; low-vulnerability areas are in the less developed parts of the Yunnan Plateau, the North–South Mountain Range Valley Region, and the Hengduan Mountain region. (4) High-risk seismic disaster areas are concentrated in the developed regions of the Sichuan Basin and the Yunnan Plateau; medium-risk areas are concentrated in the western part of the North–South Mountain Range Valley Region; low-risk areas are sporadically distributed in the eastern parts of the Sichuan–Yunnan region. (5) The vulnerability of the population, economy, and lifeline systems significantly explain the variation in seismic risk levels, all exceeding 0.70; the synergistic effects of disaster-causing factor danger, disaster-prone environment stability, and disaster-prone environment sensitivity are the most pronounced, with explanatory power exceeding 0.85 after factor interaction. Full article

The Hindukush and Himalaya regions of Pakistan are chronically prone to several geological hazards such as landslides. Studying landslides in these regions is crucial for risk assessment and disaster management, as well as for determining the effects of adverse climatic conditions, infrastructure management, and increasing anthropogenic activities. High-relief mountains in these regions face severe challenges because of frequently occurring landslides and other natural hazards, especially during intensive rainfall seasons and seismic activity, which destroy infrastructure and cause injuries and deaths. Landslides in the Alpuri Valley (Hindukush) and the Neelum Valley (Himalaya) have been activated through high magnitude earthquakes, intensive rainfalls, snowfall, floods, and man-made activities. Landslide susceptibility mapping in these areas is essential for sustainable development as it enables proactive risk management, up-to-date decision-making, and effective responses to landslide hazards, ultimately safeguarding human lives, property, and the environment. In this study, the relative effect method was applied for landslide susceptibility modeling in both study areas to determine the capability to reduce the effects of landslides, and to improve the prediction accuracy of the method. The relative effect is a statistical model that has only been used for very limited time for landslide susceptibility with effective results. A total of 368 (Neelum Valley) and 89 (Alpuri Valley) landslide locations were identified, which were utilized to prepare the reliable landslide inventory using GIS. In order to evaluate the areas at risk for future landslides activities and determine their spatial relationship with landslide occurrences, the landslide inventory was developed with 17 landslide causative factors. These factors include slope gradient, slope aspect, geology, plan curvature, general curvature, profile curvature, elevation, stream power index, drainage density, terrain roughness index, distance from the roads, distance from the streams, distance from fault lines, normalized difference wetness index, land-use/land-cover, rainfall, and normalized difference vegetation index. Finally, the performance of the relative effect method was validated using the success and prediction curve rate. The AUC-validated result of the success rate curve in the Alpuri Valley is 74.75%, and 82.15% in the Neelum Valley, whereas, the AUC-validated result of the prediction rate curve of the model is 87.87% in the Alpuri Valley and 82.73% in the Neelum Valley. These results indicate the reliability of the model to produce a landslide susceptibility map, and apply it to other landslide areas. The model demonstrated a more effective result in the Alpuri Valley, having a smaller area. However, the results are also desirable and favorable in Neelum Valley, with it being a large area. It will assist in general landslide hazard management and mitigation, and further research studies related to future landslide susceptibility assessments in other parts of the region. Full article

This study describes the methodology employed to construct a seismic fragility function based on a pre-existing numerical model tailored for underground stations. Employing a dynamic numerical model, a comprehensive analysis encompassing 110 distinct cases was conducted, each varying in soil depth and classification. Seismic waves, conforming to the standard design spectrum, were utilized within these numerical analyses. The formulation of the fragility function within the constructed model follows a structured approach, segmented by damage indices and severity levels. This systematic breakdown serves to outline the fundamental framework for establishing the fragility function, providing insights into its development process. Subsequently, the derived fragility function underwent a rigorous comparative analysis against established seismic fragility functions from prior studies. This comparative assessment serves as a critical evaluation tool, allowing for an appraisal of the suitability and robustness of the newly developed fragility function in relation to existing benchmarks. Full article