Earthquake-prone Countries Research Articles

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.

Proposing unsupervised clustering-based earthquake records selection framework for computationally efficient nonlinear response history analysis of structures equipped with multi-stage friction pendulum bearings

The design and analysis of base-isolated structures are critical for ensuring seismic performance and safety. Nevertheless, to effectively design and analyze base-isolated structures, it is essential to consider the structure's response under various ground motions that may occur during an earthquake. The nonlinear response history analysis (NRHA) is a common method for evaluating structures' seismic response under a specific set of ground motions. However, conducting this analysis for many earthquakes can be computationally expensive and time-consuming. Therefore, it is desirable to have a method for selecting a subset of earthquake records representative of the earthquake population. Accordingly, this study introduces a novel block-based framework based on the K-means unsupervised clustering techniques for efficient earthquake records' selection NRHA of base-isolated structures. The proposed approach aims to reduce the number of records required for investigations by identifying clusters of similar seismic signals and selecting representative records from each cluster for the NRHA. Additionally, the proposed framework serves a vital role in identifying the earthquake records that can be used as a training dataset for developing artificial neural network (ANN) models, enabling rapid response estimation of base-isolated structures. This dual functionality of the proposed method provides significant value for researchers and engineers working in earthquake-prone countries. This article presents two case studies to demonstrate the applicability and effectiveness of the proposed framework. The first case study focuses on selecting a subset of earthquake records from a suit that meets the ASCE 7–22 requirements for NRHA on base-isolated structures, aiming to achieve the close mean responses between the full suit and the subset of records. The second case study highlights the development of an ANN model for response estimation of such structures using the proposed framework to select suitable earthquakes as the training dataset, hence providing an adequate database to achieve high estimation results. In general, the study results highlight the capabilities of the proposed frameworks and the benefits of the K-means unsupervised clustering approach in addressing the gap in the literature and providing a robust method for earthquake record selection in various analysis scenarios.

Managing uncertainties in fault avoidance zone of urban areas: a case study of Karaj, Iran

Purpose This study aims to develop the application of the strategic choice approach (SCA) in Karaj City (Iran) as the case study for facilitating the decision-making process concerning uncertainties associated with determining fault trace, fault buffer zone and fault setback, as well as inherent uncertainties related to urban issues – known as wicked problems – which make a clear definition unachievable for them. Design/methodology/approach The SCA was recycled in this study to manage uncertain situations in planning. It is designed to deal with problems caused by uncertainty, insufficient knowledge and unpredictable policy outcomes. In combination with the risk-based planning approach, the paper proposes a new model to deal with uncertainty and hazard risk at the same time. Findings The results indicated that such decision-making tools are helpful for urban planners who impose changes in the fault zone to save lives and properties where the process seems problematic and ambiguous. Further analysis from the SCA development not only shows that urban planning restrictions should be applied gradually and in pace with the completion of fault displacement geological data but also reveals that defining the implementation process and institutional structure is as important as the preparation of binding fault zoning documents. Originality/value The paper will push forward global research and practice because the results can be generalized for use in other earthquake-prone countries, as the considerations and obstacles have a universal character and more specifically because many earthquake-prone countries have not started to define fault avoidance zone restrictions up to now.

Dynamic identification and seismic capacity of an innovative cleanroom with walkable ceiling system

AbstractPast earthquakes highlighted the vulnerability of cleanrooms, especially in earthquake-prone countries like Italy; the post-earthquake reconnaissance showed that damage to cleanrooms led to immeasurable economic losses. This study investigates the seismic performance of an innovative cleanroom, seismically designed and provided with innovative components. Full-scale shake table tests were performed on the cleanroom according to ICC-ES AC156 protocol; the cleanroom was tested under operating conditions. Both dynamic properties and seismic behavior of the specimen were assessed. The tests showed the excellent seismic behavior of the cleanroom, confirming that simple devices can significantly improve the seismic performance of nonstructural elements.

Application of a retrofit system to improve the seismic and energy performances of RC framed buildings

The need to renovate the existing building stock in earthquake-prone countries is now widely recognized. In this framework, this paper aims at investigating an innovative technology for the seismic, energy and architectural renovation of RC framed buildings. This technology combines the seismic resistance provided by steel trusses with the thermal performance of wood-based panels, which are both applied to the outer building envelope.In this paper, the proposed system is applied to a pilot building located in the city of Bucharest, in Romania, to examine its effectiveness and replicability. The pilot building is a five-storey apartment block located in a suburban neighborhood of the city and representative of many coeval buildings in Bucharest that are energy-intensive and earthquakes-prone since they were built before the enforcement of effective seismic and energy efficiency standards.The proposed retrofit methodology involves designing wood-based prefabricated panels and steel trusses according to criteria of structural strengthening and energy efficiency, standardization in manufacturing process, fast installation, and architectural integration. Furthermore, the parametric modeling in BIM environment of the above-mentioned components enables controlling their size, quantity, manufacturing, cost, and arrangement on the building façade to optimize the construction and installation processes.

Post-earthquake fire ignition model uncertainty in regional probabilistic shaking–fire cascading multi-hazard risk assessment: A study of earthquakes in Japan

Fires following earthquakes have significant impact on urban communities in earthquake-prone countries with wooden buildings, in addition to the main earthquake hazard of ground shaking. Regional-scale post-earthquake fire risk assessments are important for developing effective risk reduction strategies. Such risk assessments require the consideration of epistemic uncertainty, that is, uncertainty caused by lack of knowledge concerning the best models, in addition to aleatoric uncertainty. This study focused on epistemic uncertainty in post-earthquake fire ignition estimations, and incorporated it into risk assessments by using alternative empirical ignition models. The key objectives of this study were as follows: (1) correlating the probability of ignition per person to the ground motion intensity based on data for different past large earthquakes in Japan; (2) investigating the impact of using ignition models calibrated on different earthquake events in risk assessments through a realistic case study considering possible large earthquakes. A hierarchical Bayesian Poisson regression analysis revealed that the empirical relationship between the ignition probability and ground motion intensity greatly varies across six major large earthquakes in Japan from 1995 to 2022. Particularly, the effects of ignition prevention measures that have been widely implemented in households since the 1995 Kobe earthquake were inferred from much smaller ignition probabilities in approximately the last 10 years. The effects of this high epistemic uncertainty manifested as the large variability of the loss exceedance curve for a portfolio of buildings. These results indicate that the new ignition models can help to foster risk-informed decision-making under epistemic uncertainty.

Seismic risk-informed prioritisation of multi-span RC girder bridges considering knowledge-based uncertainty

In earthquake-prone countries, transport network managers need to perform extensive seismic risk assessments coping with a considerable number of bridges characterised by an unsatisfying knowledge level and designed in the past without anti-seismic requirements. This study proposes a framework for efficient risk assessment of multi-span girder bridges considering knowledge-based uncertainties. The framework is intended to be applied to risk-informed prioritisation of bridge portfolios. It is based on subsequent modules that involve the input of knowledge data, the simulation of knowledge-based uncertainties, simplified seismic analysis, fragility and loss assessment. The seismic vulnerability of a given bridge is represented by loss ratio percentiles related to a given seismic intensity measure which can be used to quantify the expected annual losses and the corresponding variability due to the influence of knowledge-based uncertainty. A case-study section demonstrates the framework for the widespread category of simply supported girder-reinforced concrete bridges. It addresses issues such as the use of optimal intensity measures, the required number of model realisations and discrepancies with respect to accurate nonlinear time-history analysis. Finally, an illustrative example of the proposed framework for eight case-study bridges in Southern Italy demonstrates its applicability for seismic risk-informed prioritisation of critical bridges and for directing in-depth knowledge data collections where needed.

The Use of Fear Appeal to Promote Safe Behaviors Among People in the Event of an Earthquake

Earthquake, an unpredictable natural disaster, poses a significant threat to public health, causing physical, human, social, cultural, and economic damages [1]. Iran is among the world’s top 10 earthquake-prone countries—remembering earthquakes cause the greatest human casualties. Preparedness and safe behavior before and during earthquakes are crucially important to reduce the damage of earthquakes and prevent life-threatening incidents and property damage [2]. Each year, unexpected events affect 200 million people, resulting in economic losses of up to 3% of the affected countries’ GDP (gross domestic product). By observing safe behaviors during earthquakes, it is possible to reduce risks and prevent casualties and damages [3].

Seismic responses analysis of monopile offshore wind turbines in clays considering the long-term cyclic degradation effect

In marine environment, the monopile offshore wind turbines (MOWTs) are subjected to long-term horizontal cyclic loads caused by wind, waves and currents, which will lead to the stiffness degradation and plastic cumulative deformation of clays. The decrease of clays bearing capacity caused by long-term cyclic degradation effect is a threat to the safe use of MOWTs in earthquake-prone countries (such as some countries in the circum-Pacific seismic belt). A three-dimensional finite element model is established to research the seismic response analysis of MOWT in clays considering the long-term cyclic degradation effect. The cumulative deformation of pile-soil system after long-term cycle are obtained by adopting the stiffness degradation of clays through the USDFLD subroutine. On this basis, the dynamic response analysis of MOWT system under the combined action of seismic and environmental loads is carried out. The influence of long-term horizontal cyclic load number, long-term horizontal cyclic load amplitude, seismic intensity, soil strength, environmental loads and cyclic degradation parameter on the dynamic response of MOWT is analyzed. In the seismic design of MOWTs, the effects of long-term degradation and random wind, waves and other environmental loads should be considered.

Experimental investigation of mechanical behavior of lightweight RC elements under repeated loadings

Today, the use of lightweight structural concrete in earthquake-prone countries of the world has grown more and more. Therefore, it is important to study the behavior of this type of concrete against seismic loads. So far, many studies have been conducted on the behavior of reinforced concrete (RC) elements against cyclic loads caused by earthquakes, but recent observations show that many earthquakes occur consecutively. That is, structural elements and systems may experience several weak earthquakes or aftershocks during their lifetime. It is obvious that a structure that experiences several cyclic vibrations will suffer a degradation of strength and stiffness, and its behavior will change against subsequent earthquakes. The existing structural models consider the cyclic degradation resulting from the cyclic movement during an earthquake, but many of these models do not consider the effects of degradation caused by previous earthquakes; While this degradation can have significant effects on the behavior of structural elements. In this research, the degradation caused by cyclic loading in lightweight concrete structural elements was investigated first, and then their post-degradation behavior under different levels of degradation was studied; For this purpose, 12 specimens of lightweight RC beams and 4 specimens of lightweight RC columns were made with a scale of 50% and subjected to different uniform and cyclic loadings, and three levels of slight, moderate and extensive degradation were defined based on a number of constant fatigue cycles. Then, in the next step, the cyclic behavior of the specimens after degradation was tested in three levels of slight, moderate and extensive degradation. The results of the tests showed that with the increase in the degradation level, the amount of energy absorption of RC beams decreases; Especially in beams with extensive degradation level, the amount of beam energy absorption decreases by more than 40%. Comparing the cyclic behavior after the degradation of the damaged columns with the behavior of the intact specimen shows that the increase in the level of degradation reduces the ductility of the columns.

Updated indicators of seismic risk for the territory of the Irkutsk region and the Republic of Buryatia

For all earthquake prone countries, including the Russian Federation, seismic risk assessment is periodically updated. The need for updating is increasing due to changes in assessments of hazard level and vulnerability properties of the elements at risk. For the earthquake prone regions of the Russian Federation classified as the priority development zones, risk indicators updating should increase the effectiveness of preventive measures implementation aimed at risk reduction. Calculations show that the development of risk maps, as well as the subsequent planning and implementation of preventive measures tied to the place marked on the map as the most dangerous, can reduce possible social and economic losses by 20-30%. The article describes the issues of updating seismic risk indicators for the territory of the Irkutsk region and the Republic of Buryatia. For the considered areas, which are included in the advanced development program, the actual values of seismic hazard and building vulnerability were used. The procedure for assessing and mapping risk indicators with the geographic information system “Extremum” application is given. Examples of thematic maps are presented, illustrating rather high estimates of individual risk for 6% of the territory of the Irkutsk region and 39% of the territory of the Republic of Buryatia. The results of the study indicate the need and importance of ensuring the seismic safety of the population in the framework of planning measures for the advanced development of territories.

Experimental study on the in-plane response of cast-in-situ reinforced concrete sandwich walls under combined vertical and horizontal load

Cast-in-situ Reinforced Concrete Sandwich Panel (cRCSP) technology represents a viable and increasingly popular solution for the construction sector to face recent crucial challenges, such as great housing demand or environmental sustainability. Recently, cRCSP-based buildings are being widely used also in earthquake-prone countries, like Italy. Nevertheless, so far, the available studies in the literature studies focused on the seismic response of this structural typology are not-exhaustive and, besides, relevant structural technical codes do not provide specific design rules. The present study deals with an experimental campaign carried out on four full-scale cRCSP walls subjected to increasing in-plane cyclic lateral loading. Two wall configurations have been considered different for shape and openings: the first has no openings and a squat profile; the second has a central door-type opening and a square profile. Two levels of uniformly distributed vertical load have been applied and kept constant during the test. Materials, specimens, and test set-up are described. The main experimental outcomes in terms of recorded force-displacement curves and observed damage states are discussed in detail. In particular, different failure modes and seismic performances have been observed.

Earthquake early warning systems based on low-cost ground motion sensors: A systematic literature review

Earthquake early warning system (EEWS) plays an important role in detecting ground shaking during an earthquake and alerting the public and authorities to take appropriate safety measures, reducing possible damages to lives and property. However, the cost of high-end ground motion sensors makes most earthquake-prone countries unable to afford an EEWS. Low-cost Microelectromechanical systems (MEMS)-based ground motion sensors are becoming a promising solution for constructing an affordable yet reliable and robust EEWS. This paper contributes to advancing Earthquake early warning (EEW) research by conducting a literature review investigating different methods and approaches to building a low-cost EEWS using MEMS-based sensors in different territories. The review of 59 articles found that low-cost MEMS-based EEWSs can become a feasible solution for generating reliable and accurate EEW, especially for developing countries and can serve as a support system for high-end EEWS in terms of increasing the density of the sensors. Also, this paper proposes a classification for EEWSs based on the warning type and the EEW algorithm adopted. Further, with the support of the proposed EEWS classification, it summarises the different approaches researchers attempted in developing an EEWS. Following that, this paper discusses the challenges and complexities in implementing and maintaining a low-cost MEMS-based EEWS and proposes future research areas to improve the performance of EEWSs mainly in 1) exploring node-level processing, 2) introducing multi-sensor support capability, and 3) adopting ground motion-based EEW algorithms for generating EEW.

Improving Emergency Training for Earthquakes through Immersive Virtual Environments and Anxiety Tests: A Case Study

Because of the occurrence of severe and large magnitude earthquakes each year, earthquake-prone countries suffer considerable financial damages and loss of life. Teaching essential safety measures will lead to a generation that can perform basic procedures during an earthquake, which is an essential and effective solution in preventing the loss of life in this natural disaster. In recent years, Virtual Reality (VR) technology has been a tool used to educate people on safety matters. This paper evaluates the effect of education and premonition on the incorrect decision-making of residents under the stressful conditions of an earthquake. For this purpose, a virtual model has been designed and modeled based on a proposed classroom in a school in the city of Tehran to simulate a virtual learning experience. In contrast, the classroom represents a realistic method of learning. Accordingly, each educational scenario, presented in reality and the virtual model, respectively, was conducted on a statistical sample of 20 students within the range of 20 to 25 years of age. Among the mentioned sample, the first group of 10 students was taught safety measures in a physical classroom. The second group of 10 students participated in a virtual classroom. Evaluation tests on safety measures against earthquakes were distributed after two weeks. Two self-reporting tests of Depression, Anxiety, Stress Scale (DASS) and Beck Anxiety Inventory (BAI) tests were assigned to the second group to evaluate the effect of foresight under two different scenarios. The results indicate that teaching through VR technology yields a higher performance level than the in-person education approach. Additionally, the ability to detect earthquakes ahead is an influential factor in controlling anxiety and determining the right decisions should the event occur.

Effect of Soil Type on Lateral Displacement of Reinforced Concrete Building

As has happened in various cases of earthquakes, the impact caused by each earthquake event varies, because the earthquake shaking that occurs on the ground is not only influenced by the distance and strength of the earthquake, but also by local soil conditions which are related to the amplification phenomenon. earthquake waves are influenced by the type and thickness of the soil/sediment layer above the bedrock. Reinforced concrete storey buildings are designed to withstand both vertical and horizontal loads. The taller the building, the greater the lateral load that will be received by the building structure. In the design of earthquake-resistant structures, the inelastic behavior of the structure is highly expected for the occurrence of earthquake energy dispersion during both moderate and strong earthquakes. In earthquake-prone countries such as Indonesia, it is required to comply with applicable national standards and the structure can still function and be safe from earthquakes affected by the earthquake. The purpose of this study was to determine how much influence the type of soil has on the lateral displacement of a 10-story reinforced concrete building using shear walls in accordance with earthquake building regulations (SNI 1726, 2019) and loading (SNI 1727, 2020). The results obtained that soft soil types have the largest displacement value with a value of 91,831 mm and hard rock soil types have the smallest displacement value with a value of 44,114 mm.

Machine learning-based predictive models for equivalent damping ratio of RC shear walls

Energy-based seismic design is being rapidly developed and suggests that the seismic demands are met by the energy dissipation capacity of the structural members. Equivalent damping ratio is a measure of energy dissipation in structural members that accounts for the post-elastic behavior of the member and provides insight regarding the dynamic response reduction during a seismic event. The present study implements a machine learning algorithm to estimate the equivalent damping ratio in reinforced concrete shear walls at displacements corresponding to a 1.0% lateral drift ratio. Five different machine learning models, namely, Robust Linear Regression, K-Nearest Neighbor Regression, Kernel Ridge Regression, Support Vector Regression, and Gaussian process regression were evaluated in order to choose the model with the highest accuracy. Among all models, Gaussian process regression, a machine learning method with successful implementation experiences in civil/structural engineering related problems, is selected to identify the equivalent damping ratio. The developed GPR-based algorithm uses a database of 161 rectangular shear walls subjected to quasi-static reversed cyclic loading with geometry and mechanical properties commonly found in building stocks of many earthquake-prone countries. The proposed algorithm estimates the equivalent damping ratio for each specimen by predicting the cyclic dissipated energy and lateral force values as two dependent variables. The model validation results show a mean coefficient of determination (R2) of about 0.89; a relative root mean square error of about 0.14 and a mean absolute percentage error of 10.44%, which is considered a substantially accurate prediction for such a complex problem. An open-source model and the entire database are provided which can be used by researchers and also design engineers. The proposed predictive model enables comparing the damping capacity of shear walls and the outcomes of this study are believed to contribute to the energy-based design or performance evaluation procedures in terms of predicting the energy capacity of shear walls.

VULNERABILITY ZONING OF URBAN AREAS AGAINST EARTHQUAKE (CASE STUDY: URMIA CITY)

The danger of earthquake always overshadows human societies and causes irreparable damage to these societies; therefore, preparedness to deal with this crisis by identifying vulnerability points and removing them is effective in reducing the damages caused by earthquake. Due to the location of Iran on one of the two world’s earthquake belts and the existence of many faults, the occurrence of earthquakes on the plateau of Iran is a natural phenomenon. Iran is one of the ten earthquake-prone countries in the world. Consequently, the city of Urmia is no exception to this rule due to its location in the hillsides of the Zagros Mountains and witnesses a large number of earthquakes with different intensities every year. Therefore, to deal with the above problem, we need more detailed studies in the fields of construction and safety. In this study, in order to evaluate the severity of earthquake vulnerability, effective parameters were identified and weighted using fuzzy hierarchical analysis process. Vulnerability maps were prepared by index overlap method and fuzzy logic, for statistical blocks of Urmia city and were presented visually in spatial information system. The results showed that about 50% of the city is vulnerable to earthquakes; to be more precise, about 151574 square meters, i.e. 0.005% has a very high degree of vulnerability and 11538359 square meters, with a percentage of 0.40%, has a high degree of vulnerability to earthquakes.

Investigation of Dynamic Compaction and Vibro-compaction to Mitigate Liquefaction: A Case Study

Liquefaction is one of the phenomena that can be triggered by an earthquake. Earthquake causes an increase in pore-water pressure in soil, reducing soil’s effective stress to zero or near-zero. In this state, the soil loses its strength and behaves like a liquid. This is known as liquefaction. When soil loses its strength, so it also loses its bearing capacity, causing damage or failure to structures. The soil type that is most prone to liquefaction is loose saturated fine sand. Such soil can be found in many of coastal areas in Indonesia. Indonesia is also one of the most earthquake prone countries in the world, hence liquefaction is one of the natural hazards that Indonesia has to face. Earthquake cannot be prevented, and its occurrence cannot be accurately predicted. Fortunately, liquefaction can be prevented by doing soil improvement to increase the sand density. The two most commonly used ground improvement techniques to increase sand density is dynamic-compaction and vibro-compaction. A case study from Aceh province, where both ground improvement techniques were used, is presented in this paper to compare the performance of dynamic compaction and vibro-compaction.

Structural Performance of EB-FRP-Strengthened RC T-Beams Subjected to Combined Torsion and Shear Using ANN.

This research study applied Artificial Neural Networks (ANNs) to predict and evaluate the structural responses of externally bonded FRP (EB-FRP)-strengthened RC T-beams under combined torsion and shear. Previous studies proved that, compared to reinforced concrete (RC) rectangular beams, RC T-beams performance in shear is significantly higher in structural analysis and design. The structural response of RC beams experiences a critical change while torsion moments are applied in load conditions. Fiber Reinforced Polymer (FRP) is used to retrofit the structural elements due to changing structural design codes and loadings, especially in earthquake-prone countries. We applied Finite Element Method (FEM) software, ABAQUS, to provide a precise numerical database of a set of experimentally tested FRP-retrofitted RC T-beams in previous research works. ANN predicted structural analysis results and Mean Square Error (MSE) and Multiple Determination Coefficients proved the accuracy of this study. The MSE values that were less than 0.0009 and values greater than 0.9960 showed that the ANN precisely fits the data. The consistency between analyzed experimental and numerical results demonstrated the accurate implication of ANN, MSE, and in predicting the structural responses of EB-FRP- strengthened RC T-beams.

A Review On-Confined Masonry Construction

Masonry structures are popularly built in many parts of India so it is necessary to provide suitable guidelines and safety rules for proper construction of masonry buildings.Confined masonry (CM) structures is appearing as anaccepted building construction technique in many earthquake-prone countries including India. India falls under four earthquake zones namely, zone II, zone III, zone IV and zone V. CMconstruction type has been known to perform well in numerousmajorseismic events, even though it started as an informal construction. This paper is a review of various experimental studies done by various researchers in India and around the world who studied and analyzed on seismic performance of CM buildings. This paper also gives summarized construction guidelines of CM construction and also gives a comparison of CM and reinforced concrete (RC) frame construction. This study shows that CM building construction if standardized in India, under proper guidance of engineers and building codes can prove to be a better alternative to seismic resistant masonry construction.