Earthquake-prone Regions Research Articles

Comparative Study of Tube-In-Tube and Bundled Tube System in High Rise Buildings

This study evaluates the seismic performance of Tube-in-Tube and Bundled Tube structural systems for high-rise buildings, following IS 1893 standards. Key parameters, including storey displacement, drift, and shear, were assessed in Seismic Zones 3 and 5. In Seismic Zone 5, the Bundled Tube system reduces storey displacement by about 33% compared to the Tube-in-Tube system. Similarly, in Seismic Zone 3, displacements are lowered by 21-24%. The Tube-in-Tube system exhibits higher storey drift, particularly in Seismic Zone 5, where the Bundled Tube system offers a remarkable 85% reduction. In Seismic Zone 3, this reduction ranges from 45-50%. In terms of storey shear, the Bundled Tube system consistently outperforms the Tube-in-Tube system, reducing shear forces by 24-30% across both seismic zones. Overall, the Bundled Tube system proves to be more effective under seismic conditions, minimizing displacements, drifts, and shear forces, making it the superior choice for high-rise structures in earthquake-prone regions. This improvement in performance contributes to safer structural designs in compliance with IS 1893 standards.

Dynamic Behavior of Rectangular Tanks with Limited Freeboard Under Seismic Loads: Experimental, Analytical and Machine Learning Investigations

Abstract One of the most common types of fluid storage tanks are rectangular concrete tanks placed on the ground. Ensuring the seismic performance of these tanks is crucial as, besides damage and losses during a crisis, they can lead to other crises such as fires or toxic material leaks. One pivotal factor influencing the seismic behavior of these tanks is the height of the freeboard. A comprehensive understanding of how freeboard height impacts the impulsive and convective masses is essential for the effective design and dynamic analysis of rectangular tanks. While numerous numerical and experimental studies have explored this field, the influence of various filling levels, fluid properties, and tank geometries under seismic loading conditions requires further investigation. In this study, both an experimental model and a theoretical model were subjected to different tank fill levels, tank geometries, and various freeboard heights under the influence of different earthquake records. The results showed that tank height and geometry significantly affect the changes in impulsive and convective masses. Notably, in contrast to previous studies, our results demonstrate a nonlinear relationship between freeboard height and the variations in these masses. These new findings are crucial for refining current design practices and improving the resilience of rectangular tanks in earthquake-prone regions.

Improving mental health response in earthquake-prone regions: recommendations following the recent earthquake in Türkiye

We are members of Students’ Education, Empowerment and Development in Mental Health, a group of medical students and psychiatrists from around the globe under the Psychiatry, Medicine and Primary Care Section of the World Psychiatric Association. In this article, we put forward recommendations to help improve the mental health response in disaster-prone regions such as Türkiye. We recommend a three-step multi-tiered mental health response system that could significantly help to address the immediate, short-term and long-term mental health needs of communities directly affected by a disaster. The recommendation draws from the relevant literature and, most importantly, from our lived experiences of living in earthquake-prone countries.

Uncertainty-Aware Seismic Signal Discrimination using Bayesian Convolutional Neural Networks

Seismic signal classification plays a crucial role in mitigating the impact of seismic events on human lives and infrastructure. Traditional methods in seismic hazard assessment often overlook the inherent uncertainties associated with the prediction of this complex geological phenomenon. This work introduces a probabilistic framework that leverages Bayesian principles to model and quantify uncertainty in seismic signal classification by applying a Bayesian Convolutional Neural Network (BCNN). The BCNN was trained on a dataset that comprises waveforms detected in the Southern California region and achieved an accuracy of 99.1%. Monte Carlo Sampling subsequently creates a 95% prediction interval for probabilities that considers epistemic and aleatoric uncertainties. The ability to visualize both aleatoric and epistemic uncertainties provides decision-makers with information to determine the reliability of seismic signal classifications. Further, the use of Bayesian CNN for seismic signal classification provides a more robust foundation for decision-making and risk assessment in earthquake-prone regions.

Crustal structures and anisotropy in southeastern China: Continental collision and intraplate earthquakes

This study investigates the role of crustal structures and anisotropy in southeastern China regarding intraplate earthquakes within the context of concentrated and perturbed tectonic stresses. The region is characterized by a complex multiphase tectonic history,including the ongoing collision between the Philippine Plate and the South China Sea margin. Utilizing the teleseismic receiver function method, we offer a comprehensive depiction of the crustal structures and layered anisotropy in Guangdong and Fujian, two earthquake-prone areas. Our results reveal that the crustal anisotropy is stratified into two layers, with a slow axis perpendicular to the orogenic belt in the upper-middle crust, whereas the fast axis aligns perpendicularly at lower crust levels. The lateral heterogeneity and anisotropy of the crustal structure emphasize both the boundary delineation and differential movement between continental blocks. The observed increase in density and intensity of intraplate earthquakes across this boundary supports our conclusion regarding a connection between decoupled crustal deformation and seismicity. Specifically, the foliation of metamorphic rocks during the Mesozoic collision generated orogen-parallel fabrics in the upper-middle crust, while ductile shearing resulted in orogen-perpendicular fast directions at lower crust levels. In contrast, mismatch evolution between continental blocks reactivated by present collision provides stress conditions conducive to earthquake occurrence in southeastern China. Our findings provide valuable insights into mechanisms behind intraplate earthquakes as well as tectonic evolution within continental collision zones.Plain Language SummaryThe mechanism of intraplate earthquakes is a topic of great interest in the study of continental collision and regional tectonic evolution. The controlling factors behind these earthquakes are highly complex and uncertain. In this study, we aim to investigate the role of crustal structures and anisotropy in southeastern China within the context of intraplate seismic activity. This region, which is currently experiencing a collision between the Philippine Plate and the South China Sea Margin, has a multiphase tectonic history that includes remnants of paleo-Pacific subduction. By utilizing the receiver function method, we provide a detailed picture of crustal structures and layered anisotropy in Guangdong and Fujian, two earthquake-prone regions in southeastern China. Our findings reveal that anisotropy in the crust can be stratified into two layers: an upper-middle crust and a lower crust with a slow axis and a fast axis, both perpendicular to the orogeny, respectively. The lateral heterogeneity and anisotropy of the crustal structure highlight the boundary and differential movement between the continental blocks. The enhanced density and intensity of the intraplate earthquakes across this boundary provide evidence for a connection between decoupled crustal deformation and seismicity. Specifically, our observations suggest that (1) the Mesozoic continental collision induced metamorphic foliation in the upper-middle crust, (2) ductile shearing is characteristic of the lower crust, and (3) ongoing collision has led to mismatch evolution between continental blocks, which creates stress conditions favorable for earthquake occurrence.

Edy App: Earthquake Mitigation Innovation Using GIS for Disaster Response in Pariaman, Indonesia

Pariaman City, located along the Semangko fault line and the subduction zone of the Indo-Australian and Eurasian plates, is highly vulnerable to earthquakes and tsunamis. The region's susceptibility to large earthquakes, followed by vertical deformations, highlights the need for effective disaster mitigation. In response, this study proposes the development of the Earthquake Buddy Application (EDY App), designed to assist with earthquake mitigation efforts. The EDY App leverages Geographic Information System (GIS) technology to map earthquake-prone areas, provide early warnings, suggest evacuation routes and Temporary Evacuation Sites (TES), and facilitate aid distribution. This Android-based mobile application focuses on four key aspects: education, mitigation, evacuation, and donation. Key features include an Earthquake Vulnerability Map, real-time early warnings, mitigation instructions, TES recommendations with distance and time estimations, emergency contact options, and donation channels. Built with React Native, PHP, and MySQL, and integrated with Google Maps API, the app is designed to be user-friendly and accessible to the public. The EDY App’s contribution to earthquake mitigation lies in its ability to create a disaster-aware community. By offering comprehensive information and support during critical moments, the app can potentially reduce casualties and enhance community preparedness in earthquake-prone regions like Pariaman. Through this innovation, it is expected that residents will be better equipped to respond to natural disasters, promoting a culture of safety and resilience.

ГРАДОСТРОИТЕЛЬНЫЕ ОСОБЕННОСТИ ВЫСОТНОГО СТРОИТЕЛЬСТВА В РЕСПУБЛИКЕ КРЫМ

The principles of design and construction of high-rise buildings in seismic areas, the influence of urban planning principles of designing such buildings on architecture and planning solutions of buildings, especially on the example of the Republic of Crimea, are considered. Based on the experience of previous studies, the author has identified the main types of seismic protection, features of their use, advantages and disadvantages that can be used when placing high-rise buildings in the design territories. The objectives of the study are determined by the development of earthquake-prone regions, in particular the Republic of Crimea, and the development of high-rise construction. The research methodology determines the ways to solve problems related to the design and construction of high-rise buildings and structures, taking into account the requirements of urban planning.

Seismic vulnerability assessment of buildings using rapid visual screening for hybrid UMNN-RFO approach

This chapter proposes a hybrid approach for seismic vulnerability assessment of buildings using rapid visual screening (RVS). The Unconstrained Monotonic Neural Network (UMNN) and Red Fox Optimisation (RFO) are combined to create the hybrid technique, thus, the term ‘UMNN-RFO approach’. The UMNN algorithm predicts the RVS score and the RFO algorithm optimizes the RVS score. The RVS methods via Google Maps are being used to examine the Andaman and Nicobar Islands because it is one of the main earthquake prone regions in the world. A score was given after a screening that looked at Reinforced Concrete moment-resisting frames, load-bearing structures, steel frames (SF) and wooden frames (WF). By then, the MATLAB platform will have the proposed model implemented. The proposed approach outperforms all current techniques, including Granular Computing Artificial Neural Network (GrC-ANN), Particle Swarm Optimization-Back Propagation Neural Network (PSO-BPNN) and Genetic Algorithm-Artificial Neural Network (GA-ANN). The proposed method’s accuracy is 90%, determination coefficient is 0.91 and the Root Mean Square error is 0.27%. From the result, the proposed method concluded that older structures are more likely to sustain greater damage shortly than more recently built ones based on the score.

Cyclic loading experiments on seismic performance of precast concrete superposed shear walls with CFST end columns

The seismic performance of precast concrete shear walls is a major concern when considering their application in earthquake-prone regions. To improve the seismic performance and constructability of conventional precast concrete superposed shear walls, an innovative design, termed Precast Concrete Superposed Shear Walls with CFST End Columns (PCSSWEC), has been proposed. Given the limited research on the seismic performance of PCSSWECs, cyclic loading experiments were conducted on three full-scale PCSSWEC specimens and one monolithic RC shear wall specimen. The design axial compression ratio (ACR) and the thickness of the steel tube were employed as research variables. Experimental observations and results gave a comprehensive view of the hysteretic behavior of PCSSWECs, reflecting a favorable seismic performance (in terms of failure modes, global and local damage, force-displacement responses, load-bearing capacity, stiffness and strength degradation, deformability, ductility, and energy dissipation capacity). The experiment also revealed significant differences between PCSSWECs and monolithic RC shear walls in concrete crack development and deformation characteristics, confirming that the CFST columns and the wall panel could work together until the failure phase. Moderately increasing the ACR (0.3–0.5) was beneficial for PCSSWECs. However, increasing the steel tube thickness (3.5 mm–5.0 mm) could lead to unfavorable degradation in strength and stiffness and weaken ductility. In addition, a simplified method was proposed to evaluate the flexural strength of PCSSWECs.

Seismic performance of precast UHPC pipe pile with two pile-cap beam connection types: An experimental and numerical study

To develop an effective pile foundation scheme for earthquake-prone regions, this study introduces a novel pile structure that integrates ultra-high-performance concrete (UHPC) with traditional prestressed high-strength concrete (PHC) pipe piles. The research focuses on assessing the impact of various connection forms between the pile and cap beam on the seismic performance of bridge substructures. Two 1/3-scale specimens were meticulously designed and tested: one featuring a cast-in-place (CIP) connection and the other incorporating precast assembly (PA) connection between the pipe pile and cap beam. Cyclic loading tests were conducted to evaluate the failure mode, lateral capacity, ductility, energy dissipation ability, residual displacement, rebar strain, curvature distribution and rotation of UHPC pipe piles with the two connection forms. The results indicate that the specimen with a CIP connection exhibits a higher horizontal load capacity and stronger energy dissipation ability, while the specimen with the PA connection displays superior self-centering ability, increased ductility, and causes less damage to the cap beam. Finally, finite element models were developed to analyze the effects of design parameters on the seismic performance of the pile connected by the two methods. This research may provide valuable design guidance for incorporating UHPC in pile foundations. To facilitate its practical implementation in engineering projects, further theoretical and experimental research is recommended in this paper.

The 2023 Mw 6.8 Morocco earthquake induced atmospheric and ionospheric anomalies

Earth observations through Global Navigation Satellite System (GNSS) and Remote Sensing (RS) technologies play a significant role in natural hazard surveillance, particularly in the context of earthquake prediction and detection. This study introduces a distinctive Deep Learning (DL) based approach to identify ionospheric and atmospheric precursors, utilizing data from multiple satellite sources and provides a comprehensive analysis of spatiotemporally varying precursors, contributing to the understanding and monitoring of seismic activity in earthquake-prone regions. In our investigation of the Morocco earthquake on September 08, 2023 (Mw 6.8), we analyzed various precursors including Total Electron Content (TEC), Air Pressure (AP), Relative Humidity (RH), Outgoing Longwave Radiation (OLR), and Air Temperature (AT). Our study aims to identify a synchronized anomalous window of potential earthquake precursors using Standard Deviation (STDEV), Continuous Wavelet Transform (CWT), and Long Short-Term Memory Inputs (LSTM) network. Both statistical and deep learning methods revealed abnormal fluctuations as precursors occurring within 8–9 days before the earthquake near the epicenter. Additionally, we detected geomagnetic anomalies in the ionosphere 6 days prior to and 4 days after the earthquake, coinciding with active geomagnetic storm days. This research underlined the importance of combining multiple earthquake precursors using statistical and deep learning approaches to support the understanding of the Lithosphere-Atmosphere-Ionosphere-Coupling (LAIC) phenomena.

Enhancing soil liquefaction risk assessment with metaheuristics and hybrid learning techniques

ABSTRACT Soil liquefaction has garnered significant research attention over several decades due to its profound impact on infrastructure systems in earthquake-prone regions. Given the limitations inherent in the assumptions and approximations of conventional methods, machine learning has emerged as a robust and efficient approach for predicting soil liquefaction potential. This study aims to develop a synergistic JS-CNN-XGB model, unifying the Jellyfish Search (JS) optimizer with a hybrid deep/machine learning model. This amalgamation leverages the feature extraction capabilities of the Convolutional Neural Network (CNN) alongside the classification prowess of the eXtreme Gradient Boosting (XGB) algorithm. The proposed model seamlessly integrates into a user-friendly prediction system, streamlining the liquefaction prediction process. Validation is achieved through case studies involving historical earthquake recordings with diverse classification ratios and varying input attribute quantities. Compared to existing studies, our proposed system showcases a notable 6.2% enhancement in overall liquefaction assessment accuracy, demonstrating improved detection capabilities in imbalanced and balanced datasets. In conclusion, this study underscores an automated system that presents a robust solution to the challenges posed by liquefaction potential assessment in geotechnical engineering.

Unlocking Resilience: Examining the Influence of Fluid Viscous Dampers on Seismic Performance of Reinforced-concrete Structures in Earthquake-prone Regions

Unlocking Resilience: Examining the Influence of Fluid Viscous Dampers on Seismic Performance of Reinforced-concrete Structures in Earthquake-prone Regions

Fundamental Frequency Prediction of Historic Masonry Towers Based on Artificial Neural Networks

ABSTRACT Historic masonry towers, with their brittle materials, slenderness, and distinctive shapes, are highly susceptible to lateral excitations. The urgency of preserving surviving ones in earthquake-prone regions has become apparent. There is a prioritization of identifying and reinforcing the most vulnerable masonry towers. Predictions are based on the earthquake spectrum specific to each region, effectively alerting to the seismic vulnerabilities of towers constructed within those areas. Rather than formulating relationships based on known geometrical parameters, this study relies on an Artificial Neural Network (ANN)-based model to promptly estimate the fundamental frequency of masonry towers. Measurements taken from 19 actual masonry towers are utilized for training the networks. Various distinct tower parameters as well as their combinations are considered. Only geometrical information is taken into account while material properties are not considered. The performances of ANNs are directly compared to some empirical equations. The ANN-based techniques are evaluated by testing with 20 different towers that are not considered in the training process. The proposed ANN tool demonstrates practicality and robustness when estimating the lowest frequency of masonry towers based only on geometrical information. The slenderness ratio that is rarely considered in existing equations remarkably enhances the accuracy of fundamental frequency anticipation.

Comparison of Seismic Performance of Buildings with Conventional Slab and Flat Slab in Different Zones of Bangladesh

As usable land is scarce in Bangladesh, the demand for high-rise buildings has risen over the past few decades. Conventionally, reinforced cement concrete (RCC) structures in Bangladesh have been used for residential, educational, institutional & commercial purposes. Bangladesh is located in a relatively earthquake-prone region on the fault plane; it is of utmost importance to assess seismic conditions while constructing a structure. Three types of slabs have been analyzed: conventional RCC slab, flat slab with drop panel, and flat slab with drop panel & shear wall. Typically, a conventional RCC slab contains a beam, column & slab with a large thickness of the beam. To avoid this, a flat slab with a drop panel may be used, but it has some limitations. As it has no lateral support, a flat slab with a shear wall can be replaced to gain more stability. According to BNBC 2006, Bangladesh was divided into three seismic zones. However, according to BNBC 2020, it is revised into four seismic zones. Seismic comparisons of three models in four seismic zones have been conducted. Maximum story displacement, maximum story drift, overturning moment and story shear have been found after analyzing three different types of models located in different seismic zones. The maximum story displacement and maximum story drift for flat slabs are greater than conventional slabs and flat slabs with shear walls. Moreover, the displacement between conventional and flat slabs with shear walls varies a little. Maximum overturning moment and story shear: it appears that for the traditional slab, the value is maximum, the flat slab is minimum, and the flat slab with the shear wall is between those two. The model for flat slab has been found to be more flexible than conventional RCC slab and flat slab with the shear wall.

IM-based seismic reliability assessment of the pre-code masonry building stock in metropolitan area of Lisbon

Earthquakes have a long history of causing catastrophic damage to communities, resulting in structural collapses, loss of life, and economic turmoil. To enable informed decision-making and reduce the impact of these events in earthquake-prone regions, seismic risk studies provide relevant information to support stakeholders in the implementation of effective risk-based policies. The present work addresses the seismic reliability of the pre-code masonry building stock in the Metropolitan Area of Lisbon, which is the region of Portugal that faces the highest seismic risk due to the coexistence of moderate to high seismic hazard and highest demographic-economic exposure. The adopted general framework combines several hazard studies developed for the region under investigation and a synthetic database of masonry buildings representative of the pre-code building stock in Lisbon. Through analytical–numerical probabilistic approaches, new second-order hazard solutions with structural dependency are derived for the mean annual frequency of limit-state exceedance, which can be integrated into national application documents for Eurocode 8. In light of these results, the reliability assessment of the building stock is conducted in several Local Administrative Units by means of an improved SAC/FEMA formulation. The study represents the first comprehensive investigation of its kind in this region, providing essential information to define appropriate target safety level for code calibration and support future risk studies.

Estimating S-wave amplitude for earthquake early warning in New Zealand: Leveraging the first 3 seconds of P-Wave

This study addresses the critical question of predicting the amplitude of S-waves during earthquakes in Aotearoa New Zealand (NZ), a highly earthquake-prone region, for implementing an Earthquake Early Warning System (EEWS). This research uses ground motion parameters from a comprehensive dataset comprising historical earthquakes in the Canterbury region of NZ. It explores the potential to estimate the damaging S-wave amplitude before it arrives, primarily focusing on the initial P-wave signals. The study establishes nine linear regression relationships between P-wave and S-wave amplitudes, employing three parameters: peak ground acceleration, peak ground velocity, and peak ground displacement. Each relationship’s performance is evaluated through correlation coefficient (R), coefficient of determination (R²), root mean square error (RMSE), and 5-fold Cross-validation RMSE, aiming to identify the most predictive empirical model for the Canterbury context. Results using a weighted scoring approach indicate that the relationship involving P-wave Peak Ground Velocity (Pv) within a 3-second window strongly correlates with S-wave Peak Ground Acceleration (PGA), highlighting its potential for EEWS. The selected empirical relationship is subsequently applied to establish a P-wave amplitude (Pv) threshold for the Canterbury region as a case study from which an EEWS could benefit. The study also suggests future research exploring complex machine learning models for predicting S-wave amplitude and expanding the analysis with more datasets from different regions of NZ.

Seismic vulnerability assessment of tunnels in algeria: An innovative hierarchical approach

Tunnels are crucial components of civil infrastructure, serving as vital transportation routes for the public. In Algeria, where many tunnels are located in seismic zones, they face considerable risks from earthquakes, which can potentially impair their operational integrity. The susceptibility of these tunnels to seismic hazards underscores the need for robust assessment frameworks to evaluate their vulnerability. This study introduces a novel hierarchical framework for assessing tunnel vulnerability, drawing on global seismic data and experience. By integrating the Analytic Hierarchy Process (AHP) with the Vulnerability Index (VI), we categorized tunnels into three vulnerability levels. This approach enabled the development of seismic scenarios to forecast their performance during future earthquakes. The methodology was applied to numerous tunnels across Algeria, yielding insightful results that align with observations from post-seismic assessments. By systematically analyzing various influencing parameters, including geological conditions, structural design, and operational factors, the study enhances our understanding of tunnel resilience in seismic contexts. Ultimately, this research contributes to proactive risk management strategies for tunnel infrastructure, aiming to mitigate potential damages and ensure their continued functionality in earthquake-prone regions like Algeria. By refining our assessment methods and predictive capabilities, we strive to bolster the resilience of critical urban infrastructure against seismic risks.

A novel seismic vulnerability assessment for the urban roadway by using interval valued fermatean fuzzy analytical hierarchy process

AbstractSeismic activity poses significant challenges to urban road infrastructure, often resulting in road closures due to the combined effects of damaged buildings and affected road networks. In contrast, the resilience of roads is crucially important for all kinds of relief activities after an earthquake in this context, this study outlines a methodological framework for assessing the vulnerability of urban road infrastructure to seismic activity. By integrating various criteria within an Interval-valued Fermatean fuzzy Analytic Hierarchy Process framework, the approach offers a comprehensive analysis of vulnerability, considering both quantitative and qualitative factors. This method is a weighting method that has not been used before in MCDM studies in the field of earthquakes. A risk factor is obtained for each road section by using this comprehensive analysis of the vulnerability. This integrated approach considers the interplay between damaged buildings, road networks, and disaster response mechanisms, thereby enhancing the ability to anticipate and respond to seismic events effectively. The study conducts a case study in Istanbul, Turkey, a seismic-prone area, to validate the effectiveness of the proposed methodology. Key findings indicate that the approach can identify and quantify vulnerabilities within the transport network, enabling the identification of high-risk areas for necessary mitigation measures. Moreover, the methodology’s validity is confirmed through a validation study in Gölbaşı district, Adıyaman, Türkiye, which experienced severe damage during earthquakes on 6 February 2023 earthquakes. By providing a structured and comprehensive vulnerability analysis, the research aims to contribute to the resilience of urban infrastructure, particularly in earthquake-prone regions.

Structural response of half-scale pumice concrete masonry building: shake table/ambient vibration tests and FE analysis

Seismic performance evaluation of masonry structures is of paramount importance for ensuring the safety and resilience of buildings in earthquake-prone regions. There are limited number of studies on pumice elements in the literature. In addition, there are almost no studies investigating the earthquake behavior of pumice masonry building as a whole structure. In this context, a comprehensive understanding of their seismic response and dynamic characteristics has been lacking. To address this knowledge gap, a shake-table experimental campaign was undertaken, wherein half-scale pumice masonry building was exposed to simulated seismic forces. To enhance the experimental findings, numerical simulations were performed to confirm and expand our comprehension of how the pumice masonry structure responds to dynamic forces. Integrating both experimental and numerical outcomes provides a holistic understanding of how pumice masonry buildings behave during seismic events. At the end of the experimental study, the frequency values of the pumice model were observed to decrease up to 23.5% in the modes compared to the undamaged state. In the numerical model, this value decreases up to 19.85%. For the undamaged and damaged model, the first three experimental mode shapes were similar to the numerical mode shapes. Both experimental and numerical results show that the expected damages occur in the same regions. These results show that nonlinear FE models can be helpful in determining potential damage model locations. The findings have implications for the seismic design and retrofitting of similar traditional masonry buildings, facilitating the development of resilient and sustainable engineering solutions in seismic-prone regions.