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Time (color of the circles) and amplitudes (size of the circles) of the back-projection results for the M w 7.8 (a) and 7.5 (b) Turkey earthquakes. The seismic data recorded at Alaskan and Canadian stations were used in the back-projection. The red star indicates the epicenter determined by the USGS. The red, and yellow diamonds represent the aftershocks that occurred between the origin times of the M w 7.8 and 7.5 earthquakes, and in 15 h following the M w 7.5 earthquake (one day following the M w 7.8 earthquake) according to the EMSC.
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... horizontal grid points were setting at depth of 20 km with an interval of 2 km in horizontal plane. Figure 2 shows the time propagation of the back-projection results. We used the high frequency waveforms in the backprojection, Hence the results mainly represent rupture front propagations. ...
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... Many scholars have established the relationship between the duration of strong ground motion acceleration, velocity, and displacement, as well as the MMI (Trifunac and Brady, 1975;Atkinson and Sonley, 2000;Worden et al., 2012). For the soft data, the formula released by Si in 1999 is used as the GMPE (Si and Midorikawa, 1999); it has been verified in many earthquake cases, and the results have been proven to be reliable and applicable (Chen et al., 2022b;Zhao et al., 2022;Kang et al., 2023;An et al., 2023;Peng et al., 2023;Chen et al., 2023;Zhou et al., 2024;Jia et al., 2024). The ground motion value mainly used in this article is the PGV. ...
In this paper, we explored the combination of seismic station data and ground motion prediction equations (GMPE) to predict seismic intensity results by using Bayesian Maximum Entropy (BME) method. The results indicate that: 1) In earthquake analysis in Japan, soft data has predicted higher values of intensity in disaster areas. BME corrected this phenomenon, especially near the epicenter. Meanwhile, for earthquakes in the United States, BME corrected the erroneous prediction of rupture direction using soft data. 2) Compared with other spatial interpolation methods, the profile results of Japan earthquake and Turkey earthquake show that BME is more consistent with ShakeMap results than IDW and Kriging. Moreover, IDW has a low intensity anomaly zone. 3) The BME method overcomes the phenomenon that the strength evaluation results do not match the actual failure situation when the moment magnitude is small. It more accurately delineates the scope of the disaster area and enriches the post-earthquake processing of disaster area information and data. BME has a wide range of applicability, and it can still be effectively used for interpolation analysis when there is only soft data or few sites with data available.
... On February 6, 2023, two strong moment magnitude (M w ) 7.8 earthquakes occurred in Turkey, resulting in a large number of collapsed buildings and casualties [18,19]. Aftershocks continued during the post-disaster rescue period, greatly increasing the risk and difficulty of rescue [20]. These tragic events have once again raised the alarm on the seismic safety of engineering structures under the action of sequence-type earthquakes. ...
The seismic response analysis of subway underground structures only considers the impact of a single mainshock, ignoring the aftershocks, which may cause more serious secondary damage within a short time after strong earthquakes. To investigate the seismic performance of underground structures under sequential earthquakes and improve the understanding of aftershocks, we analyzed the dynamic response of subway station structures under mainshock-aftershock sequences. A typical two-story and three-span subway station was selected as the prototype, and a finite element model of a soil-underground structure interaction was established. Based on the basic concept of endurance time and design response spectrum of relevant seismic standards in China, an endurance time acceleration function was generated, and nine mainshock-aftershock sequences were constructed. Thereafter, the seismic responses of subway stations under the action of mainshock-aftershock sequences , such as lateral deformation characteristics and damage failure law, were discussed and analyzed. The results show that the endurance time method can be used as a new and efficient method to study the seismic performance of underground structures subjected to mainshock-aftershock sequences. The effects of aftershocks on the damage and lateral displacement of underground structures were preliminarily revealed. The structural deformation response of each layer varies greatly due to the different damage states of the mainshock. The maximum story drift θ of the structure increases with the increase of loading seismic intensity. From the perspective of seismic damage and relative deformation, the structural dynamic response, considering the effect of sequential earthquakes, is greater than that of the mainshock alone, which reflects the disadvantage of af-tershocks in seismic design. The results provide a reference for seismic analysis and damage assessment of structures under sequential earthquakes.
... However, the vibration caused by metro operation had seriously affected the normal life of residents around the metro [1][2][3]. Meanwhile, earthquakes have occurred frequently in recent years [4][5][6], causing serious damage and collapse of building structures. To address the detrimental effects of metro vibration and seismic activity on structures, researchers have introduced a variety of 3D isolation bearings aimed at mitigating metro vibration [7][8][9] and enhancing the seismic resilience of buildings [10][11][12][13][14]. ...
... D⁺ (F + ) and D⁻ (F -) denote the maximum positive and negative horizontal displacements (horizontal force) of the 3DIB, respectively; ΔW represents the area of the hysteresis loop in the stress-strain curve (representing the energy loss), and W characterizes the elastic strain energy under the condition of maximum damping force and its corresponding deformation within a single cycle. (5) where: W is the elastic strain energy stored, σ is the stress, which can be defined as the maximum damping force observed in the hysteresis loop, and ε is the strain, which can be defined as the deformation corresponding to the maximum damping force in the hysteresis loop. The 3DIB effectively reduces both vertical and horizontal stiffness by combining LNR and SBs, providing energy dissipation in both vertical and horizontal directions. ...
... The epicenters of these events were located at a distance of about 100 km from each other and were themselves accompanied by numerous aftershocks (Dal Zilio and Ampuero, 2023;Erdik et al., 2023). These earthquakes, which claimed tens of thousands of human lives, caused a wide public outcry and, naturally, attracted close attention of the world scientific community Barbot et al., 2023;Chen et al., 2023;Delouis et al., 2023;Jiang et al., 2023;Karabacak et al., 2023;Kusky et al., 2023;Mai et al., 2023;Melgar et al., 2023;Rosakis et al., 2023;Zahradnik et al., 2023;and etc.). ...
... This is indicated by a significant (up to 24% for the first earthquake and up to 66% for the second) nonshear component in the tensors, published in the GCMT and NEIC catalogs (Global…, 2023;National…, 2023). A complex source, which includes several phases of rupture that differ in their mechanisms, was also revealed as a result of special studies (Barbot et al., 2023;Chen et al., 2023;Karabulut et al., 2023;Zahradnik et al., 2023; etc.) (see below). ...
... Further, the fault propagated bilaterally along the East Anatolian Fault, capturing its various segments. Judging from the values of the source duration and faulting length that we obtained, as well as the established strike of the fault plane (63°), we can conclude that they do not describe the entire rupture, but only its northeastern part, which belongs to the northeastern segments of the Eastern-Anatolian Fault and corresponding to the second segment in the model (National…, 2023), the ABCD segments in (Zahradnik et al., 2023), and the northeastern segments in (Barbot et al., 2023;Chen et al., 2023;Delouis et al., 2023;Mai et al., 2023). The estimated duration of the rupture for these segments is about 50 s, and its length is from 140 to 190 km, which agrees with our results. ...
... Although this issue may be resolved by later observational studies, the current ambiguity motivates us to examine a range of possible scenarios in Section 3. In any case, the back-projection results clearly confirm a pattern of rupture branching from the splay fault to the EAF, with a forward component to the NE and a backward component to the SW. Such a pattern has also been confirmed by other research groups employing teleseismic back-projection (Chen et al., 2023;Jia et al., 2023;Zhang et al., 2023;Xu et al., 2023a). ...
Multiple lines of evidence indicate that the 2023 Mw 7.8 Kahramanmaraş (Türkiye) earthquake started on a splay fault, then branched bilaterally onto the nearby East Anatolian Fault (EAF). This rupture pattern includes one feature previously deemed implausible, called backward rupture branching: rupture propagating from the splay fault onto the SW EAF segment through a sharp corner (with an acute angle between the two faults). To understand this feature, we perform 2.5-D dynamic rupture simulations considering a large set of possible scenarios. We find that both subshear and supershear ruptures on the splay fault can trigger bilateral ruptures on the EAF, which themselves can be either subshear, supershear, or a mixture of the two. In most cases, rupture on the SW segment of the EAF starts after rupture onset on its NE segment: the SW rupture is triggered by the NE rupture. Only when the EAF has initial stresses very close to failure can its SW segment be directly triggered by the initial splay-fault rupture, earlier than the activation of the NE segment. These results advance our understanding of the mechanisms of multi-segment rupture and the complexity of rupture processes, paving the way for a more accurate assessment of earthquake hazards.
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A Mw7.8 earthquake struck Turkey on 6 February 2023, causing severe casualties and economic losses. This paper investigates the characteristics of strong ground motion and seismogenic fault of the earthquake. We collected and processed the strong ground motion records of 379 stations using Matlab, SeismoSignal, and Surfer software: Matlab (Version R2016a), SeismoSignal (Version 5.1.0), and Surfer (Version 23.0.15), and obtained the peak ground acceleration (PGA) contour map. We analyzed the near-fault effect, the fault locking segment effect, and the trampoline effect of the earthquake based on the spatial distribution of PGA, the fault geometry, and slip distribution. We found that the earthquake generated a very strong ground motion concentration effect in the near-fault area, with the maximum PGA exceeding 2000 cm/s2. However, the presence of fault locking segments influenced the spatial distribution of ground motion, resulting in four significant PGA high-value concentration areas at a local dislocation, a turning point, and the end of the East Anatolian Fault. We also revealed for the first time the typical manifestation of the trampoline effect in this earthquake, which was characterized by a large vertical acceleration with a positive direction significantly larger than the negative direction. This paper provides an important reference for understanding the seismogenic mechanism, damage mode, characteristics, and strong earthquake law of the Turkey earthquake.
... In 2015, an earthquake with an M w of 7.8 struck Gorkha, Nepal, resulting in over 30,000 people dead or injured, eight million people displaced, 500,000 houses destroyed, and another 250,000 houses damaged [5]. In 2023, a 7.8 M w earthquake happened in Turkey and Syria, where there were around 55,000 fatalities, 130,000 injuries, and 50,000 destroyed or badly damaged structures as a result of the tragedy, which affected approximately 18 million people [6,7]. Given the above shocking and alarming facts, it would be useful to be able to rapidly identify buildings with severe and light damage after an earthquake to implement proper rescue and reconstruction, facilitating the sustainable development of cities. ...
... Accuracy, precision, and recall are three common fundamental metrics. These metrics are formally defined by true positive (TP), false negative (FN), false positive (FP), and true negative (TN), as illustrated in Figure 2. Accuracy, an overall metric that evaluates the performance of all categories, is defined by the proportion of correctly predicted samples, i.e., TP and TN, to the total number, as presented in Equation (6). The classification performance of a specific category can be evaluated by precision and recall. ...
... TP Accuracy, an overall metric that evaluates the performance of all categories, is defined by the proportion of correctly predicted samples, i.e., TP and TN, to the total number, as presented in Equation (6). The classification performance of a specific category can be evaluated by precision and recall. ...
The rapid assessment of post-earthquake building damage for rescue and reconstruction is a crucial strategy to reduce the enormous number of human casualties and economic losses caused by earthquakes. Conventional machine learning (ML) approaches for this problem usually employ one-hot encoding to cope with categorical features, and their overall procedure is neither sufficient nor comprehensive. Therefore, this study proposed a three-stage approach, which can directly handle categorical features and enhance the entire methodology of ML applications. In stage I, an integrated data preprocessing framework involving subjective–objective feature selection was proposed and performed on a dataset of buildings after the 2015 Gorkha earthquake. In stage II, four machine learning models, KNN, XGBoost, CatBoost, and LightGBM, were trained and tested on the dataset. The best model was judged by comprehensive metrics, including the proposed risk coefficient. In stage III, the feature importance, the relationships between the features and the model’s output, and the feature interaction effects were investigated by Shapley additive explanations. The results indicate that the LightGBM model has the best overall performance with the highest accuracy of 0.897, the lowest risk coefficient of 0.042, and the shortest training time of 12.68 s due to its relevant algorithms for directly tackling categorical features. As for its interpretability, the most important features are determined, and information on these features’ impacts and interactions is obtained to improve the reliability of and promote practical engineering applications for the ML models. The proposed three-stage approach can provide a reference for the overall ML implementation process on raw datasets for similar problems.
... The occurrence of large-scale earthquake events is often associated with the vital damage to the built environment, along with their impacts on human life and the economy, for example, the 2023 Turkey earthquake (W. Chen et al., 2023) and the 2015 Nepal earthquake (H. Chen et al., 2017). ...
... The performance of this trained model is evaluated based on its performance on unseen damaged images, which are collected after the recent Turkey earthquake in February 2023 (W. Chen et al., 2023). Moreover, the comparison is made between the QCNN model performance with the results of various deep CNN architectures, such as AlexNet, Visual Geometric Group with 16 convolutional layers (VGG-16) and 19 convolutional layers (VGG-19), Residual Network with 50 deep layers (ResNet50), InceptionV2, InceptionV3, MobileNetV2, Xception, and DenseNet. ...
The traditional visual inspection technique for damage assessment of buildings immediately after an earthquake can be time-consuming, labor-intensive, and risky. Numerous studies have been carried out using deep learning techniques, particularly convolutional neural network (CNN), to evaluate the damage to building structures after an earthquake using buildings' damage images. Quantum computing, on the other hand, is a computing environment that can exploit superposition and entanglement, which are not available in classical computing environments, to achieve higher performance using parallelism between qubits. This paper presents a novel quantum CNN (QCNN) approach to detect damage to reinforced concrete (RC) buildings from images after the earthquake. The QCNN model is developed and trained using the RC building damaged images collected from past earthquakes. The performance of this model is evaluated based on the multiclass damage detection ability of the real-world RC building damaged images collected from the recent earthquake in Turkey in February 2023. Furthermore, the seismic damage detection accuracy obtained from the QCNN model is compared with various CNN architecture results.
... It also plays a critical role in improving the country's resilience to natural disasters like earthquakes by providing a vital link for rescue and disaster management operations [1][2][3]. Many recent earthquakes, like the Turkey earthquake of 2023, the Pakistan earthquake of 2019, the Pidie Jaya and Christchurch earthquakes of 2016, and the Nepal earthquake of 2015, have witnessed major cracking of roads, failure of bridges and other transportation infrastructure [4][5][6][7][8]. Several geotechnical reconnaissance findings confirm that liquefaction-induced lateral spreading and flow failures are the leading causes of damage to these structures during an earthquake [5,[9][10][11][12][13][14][15][16]. ...
... Kokusho [118], from their laboratory test data, and Mele et al. [119], from their in-situ test data, demonstrated that the progression of pore pressures and development of shear strains is uniquely correlated to the strain energy dissipated in the specimens. The amount of cumulative strain energy dissipated per unit volume of the test specimen (ΔW) at any point 'i' on its way to liquefaction during cyclic shearing that has a total of 'n' data points can be computed using equation (8), as given by Figueroa et al. [113]. ...
On 6 February 2023, the destructive earthquakes (EQs) occurred in Kahramanmaras Turkey with the maximum magnitude 7.8. In this paper, based on multi-source satellite observations, we investigated the pre-seismic anomalies of infrared radiation and ionosphere, and analyzed the coupling features of multi-parameter anomalies in temporal evolution and spatial distribution. Analysis results indicated that in the vicinity of the epicenter, the outgoing longwave radiation (OLR) anomalies observed from NOAA-18 satellite were very obvious in January 2023, and the ionospheric plasma anomalies observed from CSES and SWARM satellites were significantly detected on 30 January 2023, which were probably the precursor signals of the impending main shock. Combined with the analysis results of crustal deformation and atmospheric compositions for the Turkey EQs in published articles, we believed that crustal stress changes and rock ruptures in the boundaries between the Arabian and African plates and the Anatolian block were more likely to cause the pre-seismic anomalies in infrared radiation, atmosphere and ionosphere. The observed anomalies had a clear coupling relationship, and represented the stage changes of seismogenic process for the Turkey EQs. In addition, the satellite remote sensing technology is very helpful for us to monitor the multi-parameter variations in lithosphere, atmosphere and ionosphere, better verify the correlation of pre-seismic anomalies in Earth’s multi-sphere structures, and further promote the research on the multi-sphere anomaly coupling mechanism.
