Earthquake Events Research Articles

Multi-layer non-hydrostatic free-surface flow model with kinematic seafloor for seismic tsunami generation

Earthquake induced tsunamis pose devastating threat to coastal communities worldwide. Accurate description of tsunami generation by kinematic fault rupture is of importance to investigate earthquake events and evaluate tsunami impacts. The paper develops a multi-layer non-hydrostatic model with a kinematic bottom boundary condition and conducts comprehensive validation to examine the model’s capability in resolving seismic tsunami generation. The two-dimensional governing equations of the multi-layer non-hydrostatic free-surface flow system equipped with kinematic seafloor displacement is first introduced in Cartesian coordinates. A combined finite difference and finite volume scheme is utilized to discretize the governing equations with flow variables arranged on a staggered Arakawa C-grid. Application of pressure correction technique to the discretized formulations yields Poisson-type equations from which the non-hydrostatic pressure is solved for the next time step to complete the temporal integration. Based on existing analytical solutions, four groups of tsunami generation cases considering broad ranges of source parameters, including horizontal scale, rise time, and rupture velocity, are designed to demonstrate performance of the proposed non-hydrostatic model with one-, two-, and three-layers as well as the hydrostatic one. Comparison of 59 generation cases including extreme scenarios indicates the non-hydrostatic model performs better than the hydrostatic model in reproducing the entire waveform and predicting the maximum wave amplitude. High modeling accuracy can be achieved through incorporation of more layers. The proposed multi-layer non-hydrostatic model is a powerful tool for investigating earthquake source mechanisms and evaluating coastal tsunami hazards.

Framework for lifecycle resilience assessment of earthquake-damaged coastal RC structures considering non-uniform corrosion

Reinforced concrete (RC) structures in seismic coastal areas often suffer from the coupled effects of corrosion and earthquakes due to prolonged exposure to harsh environmental conditions. Previous research on the seismic performance of buildings primarily focused on uniform corrosion(UC), disregarding the impact of varying concentrations of chloride-ions on corrosion rate. This discrepancy will overestimate the seismic performance of building structures. The framework proposed in this study aims to evaluate the resilience of RC structures to non-uniform story corrosion(NUSC). The framework encompasses an innovative functional recovery function and considers the influence of chloride-ions concentration on the corrosion rate, time-varying initial functional function, and degradation model for corroded reinforced concrete. NUSC model is established within the proposed framework via OpenSees software. The proposed framework integrates the seismic hazard, fragility, resilience, and recovery models. A nonlinear time history analysis method is employed to simulate the structural response to the seismic action. The findings demonstrate that NUSC leads to a reduction in seismic resilience by 7.3% and 10% compared to UC when considering service times of 35 and 55 years, respectively. This indicates an escalation in seismic risk as well as a decline in structural seismic capacity.

Effect of rubber particles on mechanical properties of calcareous sand under large displacement shear

To reveal the influence of rubber particles on the mechanical properties of calcareous sand under the large-displacement shear effects of earthquakes and waves, indoor ring shear tests were conducted on rubber particle-calcium sand mixtures. The effects of rubber particle size and content on the mechanical properties of calcareous sand were studied via indoor ring shear test. Then, based on PFC3D, a numerical model of a ring shear test that can restore the shape of calcareous sand particles is established, and a mesomechanical analysis of mixed sand is carried out. The results showed that the effect of the rubber particle content on the crushing characteristics and strength of calcareous sand was significant and that the effect of the particle size was small. The rubber content causes a gradual decrease in the peak strength and particle crushing rate and increases the deformation stability of the mixed sand. The softening coefficient and relative crushing rate were significantly reduced to 0.01–0.06 and 0.28–1.2%, respectively, at 40% rubber content. The numerical simulations and experimental results were in good agreement. An increase in the rubber content significantly influences chain development, which explains the macroscopic mechanical properties of mixed sand at the fine level.

Integration of Machine learning and equal differential time method for enhanced hypocenter localization in earthquake early warning systems: application to dense seismic arrays in Taiwan

The Earthquake Early Warning System (EEWS) acts as a vital instrument for reducing seismic risks in regions with high seismic vulnerability. A rapid and accurate hypocenter estimation is pivotal for the EEWS, providing the groundwork for more reliable magnitude and intensity assessments necessary for effective earthquake warnings. This study presents an algorithm that integrates machine-learning-based (near) real-time phase picking with an Equal Differential Time (EDT) rapid hypocenter location algorithm, applying it to a 3D velocity model. The phase-picking model, refined through data augmentation, enhances the precision of phase detection in continuous recordings and simultaneous multiple events while ensuring the swift detection of the P-phase, which is critical for early earthquake warnings. Our rapid earthquake location method calculates theoretical P arrivals from potential hypocenters, which are grid points in a 3D velocity model, to stations that are close to their grid points, with the arrivals being stored by the station. As P arrivals are detected, the differences in arrival times across stations are utilized in EDT for estimating hypocenters. Furthermore, our earthquake location algorithm is adept at localizing multiple seismic events, a capability that can diminish the risk of unreported cases in scenarios where events occur in close temporal and spatial succession in high seismicity regions. We applied the algorithm to real waveform recordings of recent earthquakes in Taiwan that satisfied the early warning criteria. The results suggest that our algorithm consistently yields more reliable hypocenter estimates compared to those from the currently operational EEWS in Taiwan. Moreover, our algorithm succeeded in locating an earthquake that the current EEWS overlooked due to its failure to recognize P arrivals. These results showcase the potential of our algorithm to provide more accurate hypocenter estimates and to locate earthquake events with complex seismic recordings.Graphical

Study on the Effect of Burial Depth on Selection of Optimal Intensity Measures for Advanced Fragility Analysis of Horseshoe-Shaped Tunnels in Soft Soil

Seismic intensity measures (IMs) can directly affect the seismic risk assessment and the response characteristics of underground structures, especially when considering the key variable of burial depth. This means that the optimal seismic IMs must be selected to match the underground structure under different buried depth conditions. In the field of seismic engineering design, peak ground acceleration (PGA) is widely recognized as the optimal IM, especially in the seismic design code for aboveground structures. However, for the seismic evaluation of underground structures, the applicability and effectiveness still face certain doubts and discussions. In addition, the adverse effects of earthquakes on tunnels in soft soil are particularly prominent. This study aims to determine the optimal IMs applicable to different burial depths for horseshoe-shaped tunnels in soft soil using a nonlinear dynamic time history analysis method, and based on this, establish the seismic fragility curves that can accurately predict the probability of tunnel damage. The nonlinear finite element analysis model for the soil–tunnel interaction system was established. The effects of different burial depths on damage to horseshoe-shaped tunnels in soft soil were systematically studied. By adopting the incremental dynamic analysis (IDA) method and assessing the correlation, efficiency, practicality, and proficiency of the potential IMs, the optimal IMs were determined. The analysis indicates that PGA emerges as the optimal IM for shallow tunnels, whereas peak ground velocity (PGV) stands as the optimal IM for medium-depth tunnels. Furthermore, for deep tunnels, velocity spectral intensity (VSI) emerges as the optimal IM. Finally, the seismic fragility curves for horseshoe-shaped tunnels in soft soil were built. The proposed fragility curves can provide a quantitative tool for evaluating seismic disaster risk, and are of great significance for improving the overall seismic resistance and disaster resilience of society.

Assessing the Influence of Earthquakes on Sovereign Credit Risk: An Event Study on CDS Market Dynamics of Selected Countries

This study analyzes the effects of earthquakes on sovereign credit default risk. The study examines whether 20 major earthquakes that occurred in Türkiye, Mexico, Chile, South Africa, and Greece after 2010 have made a difference on CDS markets using the event analysis method. The results indicate that the earthquakes increased uncertainty in the CDS markets of all countries. These results prove that uncertainty about the ability of countries to repay their public debt has significantly changed compared to the pre-earthquake period.

Seis-PnSn: A Global Million-Scale Benchmark Data Set of Pn and Sn Seismic Phases for Deep Learning

Abstract The seismic phases Pn and Sn play a crucial role in investigating the velocity and anisotropic characteristics of the uppermost mantle. However, manually annotating these phases can be time-intensive and prone to subjective interpretation. Consequently, the use of travel-time data for these seismic phases remains limited. Despite the potential of deep learning to address this challenge, the scarcity of extensive training data sets for Pn and Sn presents significant constraints. To address this challenge, our research compiled a global million-scale benchmark data set of Pn and Sn seismic phases, namely Seis–PnSn. The data set is derived from earthquake events with epicenter distances ranging from 1.8° to 18°. The high-quality travel-time data used in this study are all from the International Seismological Centre and span the period 2000 to 2019. The waveform data were sourced from data centers located in different regions of the world under the International Federation of Digital Seismograph Networks. By leveraging the unique attributes of this data set, we trained baseline models and explored the prevailing challenges in deep-learning-based Pn and Sn phase picking as the scope transitions from local to regional epicenter distances. Our results show that the performance of the model is considerably enhanced after training on the proposed data set. Our study is a significant complement to the data foundation for future data-driven Pn and Sn seismic phase-picking studies, which will contribute to enhancing our understanding of the uppermost mantle structure of Earth, for example, the seismic velocity, anisotropy, and attenuation characteristics.

Assessing “Invisible Loss” During Medium-Term Earthquake Recovery: The Case of Indonesia's 2016 Aceh Earthquakes

This study presents the results of a medium-term assessment of earthquake recovery, aiming to measure non-economic welfare losses resulting from the indirect impacts of earthquakes. While most earthquake assessments concentrate on the economic loss and damage caused by direct impacts of earthquakes, this study focuses on capturing these less visible non-economic losses. The 2016 Aceh earthquakes in Indonesia serve as the case study for this assessment. By applying the difference-in-differences method, we compared the changes in a range of non-economic welfare indicators in earthquake-affected and unaffected villages two years before (2014) and two years after (2018) the catastrophic earthquakes. In addition to administrative data, we tested the suitability of average monthly and annual night-time light data from the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument as an alternative way to capture non-economic welfare losses. The findings from administrative data suggested a significant deterioration in, poverty, access to healthcare and access to socio-economic services in earthquake-affected villages relative to unaffected villages in 2018, compared to 2014. The analysis of nightlights data revealed contrasting results, suggesting that disaster recovery assessments using nightlights may not accurately capture non-economic welfare changes on the ground. Our research indicates that the detrimental effects of earthquakes on non-economic welfare persisted for years following the initial devastation. Utilizing administrative data can help pinpoint the nature and extent of non-economic losses and inform the development of policies to aid in the effective recovery of affected communities.

Enhancing earthquakes and quarry blasts discrimination using machine learning based on three seismic parameters

Explosions and other artificial seismic sources remain a major risk to human survival. Seismicity catalogs often suffer from contamination, which hinders the differentiation of tectonic and non-tectonic events. To address this issue, an automated control system is developed employing machine learning (ML) techniques to discriminate between earthquakes and quarry blasts (QBs). By using ML approaches, such as probabilistic and statistical techniques, QBs can be differentiated from natural earthquakes. The proposed method utilizes latitude, longitude, and magnitude information to improve the performance. Evaluation measures, including R2, F1-score, MCC score, and others, are employed to assess the algorithm's effectiveness. Experimental results demonstrate the superiority of the suggested method, achieving a success rate of 97.21%. The developed algorithm has significant potential for enhancing seismic hazard assessment, supporting urban development planning, and promoting safer communities by accurately discriminating between man-made and natural earthquake events.

The Impacts of The Earthquake on The Cardiovascular System

Introduction: Various physiological and psychological effects of earthquakes can be seen on the human body, even without a direct physical impact from the earthquake. Both the experience of the earthquake process and the earthquake-related subsequent life changes cause stress through the activation of the sympathetic and parasympathetic systems in the body. This stress can affect various physiological processes, including the cardiovascular system. In this review, the effect of earthquakes on the cardiovascular system was aimed to be discussed in line with the available evidence. Discussion: There are studies showing that natural events such as earthquakes increase the incidence of adverse cardiac events, such as myocardial infarction, heart failure, hypertension, and sudden cardiac death, or cause existing cardiac diseases to worsen during these periods. However, there are also some evidences with conflicting results. Therefore, the effect of earthquakes on cardiovascular diseases has not been clearly demonstrated yet. Conclusion: Even survivors of earthquakes without physical injury are exposed to stress secondary to both internal and external factors. Studies indicate that individuals who are involved in the earthquake process may have adverse effects on cardiovascular health in the short and long term. Therefore, it is important to take necessary precautions and create appropriate conditions, especially in people with cardiovascular disease.

Assessment of Indoor and Soil-Gas Radon Concentration of a Quarry Site in Eiyekorin, Kwara State

The toxic health effect of human exposure to radon gas which is radioactive in nature has attracted extensive research attention worldwide. Since direct experiments on the effect of earthquakes on radon release are difficult to conduct, a possible alternative is to use man-made explosions as an earthquake surrogate and investigate the corresponding effect on radon concentration. This study aims at investigating the soil-gas radon concentration in an active quarry site and areas outside the quarry, and the infiltration of the gas into the indoor environment was measured in order to access the occupational exposure risk. Soil gas radon concentration was taken at 30 random locations within the quarry and areas outside the quarry using RAD7, likewise 10 indoor radon gas in offices and homes were measured using an active radon detector manufactured by Durridge Incorporation in USA and comparative analysis of the difference between the two locations were done. The mean of the soil-gas radon concentration in the quarry site is 24968.84 ± 6913.204Bq/m3 while that of outside the quarry is 9664.67 ± 4992.86 Bq/m3. The result shows higher values of radon-gas concentration in the quarry site compared with area outside the quarry and when compared to the International Commission on Radiation Protection (ICRP) suggested value of radon concentration in soil and sediment, which is in the range of 0.4 to 40 KBqm-3, result shows that most location within the study area are higher than these limits. Also, the radon in air indoor and outdoor was taken at the offices located within the quarry and occupational exposure risk was carried out. The average of radon in air indoor and outdoor was found to be 31.12 Bqm–3 and 10.12 Bqm–3 respectively with higher values found indoor. However, the values are found to be below the recommended value of 300 Bq/m3 by ICRP publication for homes and workplaces.

Utilization of Oil Palm Empty Fruit Bunch (EFB) Waste as a Mixing Material for In-terlocking Brick Production

The choice of building materials has a considerable influence on the reliability of a building. Conventional bricks, despite their frequent use, pose a challenge due to their weight, as they affect the load-bearing capacity of the building, unlike interlocking bricks, which have holes at the top and bottom for reinforcement, potentially reducing the effects of earthquakes. In this study, interlocking bricks made from a mixture of empty oil palm fruit stalks and sand with different sand replacements (0%, 2.5%, 5%, 7.5%, 10%, and 12.5%) are investigated. The research results consistently show that the average density of EFB fiber composite bricks with a density of 1.48 grams/cm³ is lower than that of standard composite bricks. Although the compressive strength of these bricks is initially lower than that of standard bricks, it increases with the substitution of part of the sand with EFB fibers, although not significantly, with the highest compressive strength observed at a substitution rate of 12.5%, reaching 5.201 MPa. Water absorption rates ranged from 13.97% to 21.99%, which increases compared to standard bricks but still meets the requirements. With ongoing research and innovation, EFB-based interlocking bricks have the potential to address environmental challenges and support sustainable and environmentally friendly building practices.

Probabilistic-based seismic fragility analysis of a ground-bridge structure system considering site liquefaction

Bridge structures are vulnerable to severe damage in previous earthquake events. Meanwhile, the earthquake-induced site liquefaction can significantly affect the seismic performance of bridge structures. Seismic fragility analysis is considered as an effective approach for evaluating seismic performance of bridge structural systems exposed to seismic hazards. This study aims to assess seismic fragility of a ground-bridge structure system considering site liquefaction. Based on the probabilistic seismic demand model (PSDM) and joint probabilistic seismic demand model (JPSDM), a holistic framework for fragility analysis considering site liquefaction is proposed to derive the liquefaction fragility as well as the structural system fragility. The system fragility surfaces obtained by the proposed method can reflect the influence of site properties on the damage exceeding probability of bridge structures. The results demonstrate an increasing probability of undergoing high-level damage states for the whole system containing highly loose sand under strong earthquakes, which may provide significant basis for probabilistic-based aseismic design.

Determining the impact of earthquakes on university students' hope and anxiety levels

ObjectivesThe seismic disturbances in Kahramanmaraş in February 2023 and their social effects highlight the potential adverse impacts on mental well-being, particularly anxiety and hopelessness. This study aimed to evaluate the hope and anxiety levels of university students studying health education and investigate the consequences of earthquakes on these emotions. MethodsA total of 398 students who were studying at Karabük University Vocational School of Health Services in May 2023 were selected through convenience sampling. Participants were assessed using the "Student Information Form," "State-Trait Anxiety Inventory (STAI)," and "Dispositional Hope Scale (DHS)." Confirmatory Factor Analysis (CFA) and reliability analysis were used to assess the scales' internal consistency. Descriptive statistics were used to determine anxiety and hope levels and independent t-tests were used to compare group differences. ResultsStudents who experienced an earthquake showed higher state anxiety (0.75 ± 0.12) than those who did not (0.71 ± 0.12). Additionally, students who suffered material (0.77 ± 0.12) and moral (0.76 ± 0.10) damage had significantly higher state anxiety levels (p < 0.05). There was also a statistically significant but weak negative correlation between DHS and state anxiety. ConclusionsThe findings of this study indicate that exposure to earthquakes is correlated with an increase in state anxiety levels, while higher levels of hope are associated with a decrease in state anxiety. This study provides valuable insights into the effects of earthquakes on students' mental well-being and emphasizes the significance of integrating the therapeutic potential of hope into their training programs.

Study on properties of reinforced concrete structures in seismic regions

This paper aims to explore the effects of earthquakes on the properties of medium-height reinforced concrete houses in China. The results demonstrated a significant decrease in ultrasonic resonance frequency, indicating structural damage, with reductions of 26.5 %, 30.2 %, and 37 % observed for earthquakes of magnitudes 5.0, 5.3, and 5.7, respectively. Similarly, the dynamic modulus of elasticity exhibited a reduction of over 50 %. Measurements of carbonation depth revealed values of 34.65 mm, 38.97 mm, and 46.12 mm for earthquakes of magnitudes 5.0, 5.3, and 5.7, respectively. Accordingly, the percentage of mass loss amounted to 22.17 %, 36.87 %, and 49.78 %. Furthermore, experiments identified the least favourable outcomes during maximum seismic activity, with a recorded peak stress of 447.3 MPa at a deformation of 0.63 mm. These findings contribute to a better understanding of the impact of seismic events on reinforced concrete structures and the associated corrosion mechanisms.

Finite element analysis and simplified envelope curve model for RC shear key under earthquake-tsunami actions

Coastal bridges are vulnerable to the compounded effects of earthquakes and subsequent tsunamis. Their limited lateral restraints can result in critical risks such as the deck unseating or overturning. To this end, reinforced concrete (RC) shear keys are often integrated to enhance the superstructure resilience. While previous studies have investigated their seismic performance, their effects under seismic-tsunami actions remains relatively unexplored yet. This study employed finite element (FE) analysis to examine shear key properties under such conditions, with emphasis on hysteretic curves, concrete damage, and strain evolution. The FE model was developed in accordance with precedent tests, and the modeling results were also compared with tests. A simplified envelope curve model was developed using both geometry and rebar configuration, with various damage states included to reckon their seismic damages after initial earthquakes. The proposed model was validated and aligned well with test results. Further, a framework was proposed to determine the envelope curve for bridges at different damage stages. This study aims to provide insights into the seismic-tsunami analysis on coastal bridges by considering their varying properties under seismic and tsunami actions.

Earthquake Effects Surveyed during the Nineteenth Century as Ecological Features of Chinookan Tidelands

Earthquake Effects Surveyed during the Nineteenth Century as Ecological Features of Chinookan Tidelands

Seismic collapse fragility analysis of steel moment-resisting frames (MRFs) with stiffness and strength deterioration considering the spectral shape of ground motion records

In this paper, the seismic collapse fragility analysis of special steel moment-resisting frame (MRF) buildings with strength and stiffness deterioration is comprehensively evaluated, taking into account the effect of record selection based on the spectral shape parameters. For this purpose, three special steel moment-resisting frame buildings, including 3, 10, and 20-story structures as representatives of low-rise, mid-rise, and high-rise buildings, are investigated. The modified bilinear Ibarra-Medina-Krawinkler (IMK) relation is used for modeling the concentrated plasticity and considering cyclic degradation in beams and columns under earthquake effects in Incremental Dynamic Analysis (IDA). The ground motion records are selected and categorized based on the three parameters, including the epsilon, SaRatio, and Np from a large database consisting of 2000 earthquake records. The records are divided into 7 groups using the epsilon parameter. The SaRatio and Np parameters further divide the records into 5 categories. Additionally, a randomly selected set of 200 earthquake records is used. The effects of hysteretic deterioration and spectral shape parameters of earthquake records on the median IDA curves, collapse fragility curves, and collapse capacity of the steel MRF structures are investigated. In addition to the hysteretic deterioration of steel structural members based on the results of the previous experiments, different values of the deterioration parameter (λ) are used in the nonlinear time history analyses to parametrically study the effect of deterioration on the collapse capacity. Finally, the effect of various parameters on the seismic collapse capacity of the structures in the form of Tornado diagrams is illustrated. The results demonstrate that the randomly selected records yield results close to the records sets with Np = 1, SaRatio = 1, and ε = 0. Furthermore, for a constant deterioration level, increasing epsilon and SaRatio, and decreasing Np lead to an increase in the collapse capacity of the structures. The results also show that the effect of deterioration on the collapse capacity of the buildings, especially the low-rise 3-story building, is significant.

Unveiling Temporal Cyclicities in Seismic b-Values and Major Earthquake Events in Japan by Local Singularity Analysis and Wavelet Methods

Studying the temporal characteristics of earthquake activity contributes to enhancing earthquake prediction capabilities. The seismic b-value is a key indicator describing the relationship between seismic frequency and magnitude. This study investigates the correlation between the occurrence of major earthquakes and seismic b-values using earthquake activity records in Japan from 1990 to 2023. Local singularity analysis and wavelet analysis of earthquake frequency and b-value time series reveal significant 5-year periodic features in seismic activity in Japan. Furthermore, our research identifies that this periodicity is also prominent in major earthquakes with magnitudes of 7 and above. Additionally, through a detailed analysis of the cross-correlation between seismic b-values and the occurrence time of major earthquakes, we uncover a notable pattern: major earthquakes often occur approximately two years after the peak of seismic b-values. This discovery offers a new perspective on earthquake prediction and may play a crucial role in future earthquake early warning systems.

EARTHQUAKE SIMULATOR FOR BEHAVIOURAL EDUCATION OF THE POPULATION

The practical exercises on seismic simulator in conditions close to real are irreplaceable, no matter the theoretical training one receives. The latter appear to be the most important prerequisite for attaining knowledge and skills, and acquiring behavioural habits of people for the events of strong earthquakes. Hence, physical simulator platforms realizing scenarios of earthquakes and the vibrations thereof have been in use for several years in some countries. The current article discloses the drawbacks of the existing simulators and, first and foremost, of how these simulators reproduce oscillations far different from the real seismic waveforms. Such simulators do not provide the complete experience during the training process. The paper describes the advantages of the presented simulator – adequate simulation of real seismic oscillations having the correct amplitudes, frequencies and waveforms varying in broad boundaries. Thus efficient and effective education of children and the seniors in effects of a strong and tangible earthquake exhibiting various amplitudes, phases and frequencies of the seismic waves can be made possible.