Search Results (12)

A catastrophic Ms7.8 earthquake occurred in Tangshan in 1976 at a focal depth of approximately 12 km, resulting in severe casualties and substantial economic losses. Given its unique tectonic setting, the seismogenic structure and dynamic genesis of the Tangshan earthquake have long remained a key research topic in seismotectonic studies. To better characterize the tectonic framework, seismogenic mechanisms, and deep–shallow dynamical coupling within the Tangshan seismic zone, we employ multi-scale wavelet decomposition on high-resolution residual gravity anomalies to isolate crustal structure signals across different depth ranges. Integrating these structural signatures with the spatial distribution of seismicity yields a comprehensive framework for interpreting the regional tectonic evolution. The Tangshan seismic zone is positioned within the intricate structural architecture of the Tangshan rhombic fault block, a system embedded within the broader context of the North China Craton (NCC) destruction. Seismicity displays a distinct preferred orientation, with events concentrated along block-bounding faults and gravity anomaly gradient zones. With increasing wavelet decomposition levels, the gravity anomalies exhibit a systematic transition from spatially dispersed patterns associated with shallow structures to more concentrated features reflecting deeper geological domains. Shallow anomalies from the first to third decomposition orders, which are primarily controlled by Quaternary sedimentary layers, show a fragmented distribution that corresponds well with the development of local flower structures and the occurrence of diffuse shallow seismicity. The fourth- to seventh-order anomalies clearly delineate the rhombic block and its bounding peripheral faults, highlighting the structural intersections that hosted the Tangshan mainshock and its associated aftershock sequence. In contrast, the eighth- to tenth-order deep-seated anomalies corresponding to deeper structural levels exhibit pronounced coalescence, effectively imaging mantle upwelling and large-scale density heterogeneities within the lithospheric mantle. These concentrated gravity highs are closely coupled with mantle thermal activity, whose upward ascent induces thermal weakening of the lower crust and facilitates progressive stress transfer toward shallower crustal levels. Concurrently, frictional locking of shallow high-angle faults promotes intense stress accumulation within the rigid basement. The interplay between deep-seated dynamic concentration and shallow structural confinement ultimately triggers the catastrophic coseismic rupture responsible for the Tangshan earthquake. By delineating the structural transition from deep-seated aggregation centers to shallow dispersed fracture zones, this study establishes a robust framework for assessing seismogenic environments and regional seismic hazard potential across the progressively destroyed NCC. Full article

In this paper, we describe a method for computing calendar time forecasts in a local area for large earthquakes of a target magnitude M_T using a count of small earthquakes in the magnitude range M_S to M_T in the area. Using the idea that the Gutenberg–Richter (GR) relation is valid throughout the surrounding region, we define an ensemble of earthquakes in larger surrounding regions to be used in computing the forecast. What follows is simple data mining. “Local” is defined by the probability of a large earthquake occurring within a defined circle of arbitrary radius surrounding a point of interest. The main (and for that matter, the only) assumption for all these works is that the GR magnitude–frequency relation holds. The method has significant skill, as defined by the Receiver Operating Characteristic (ROC) test, which improves as the time since the last major earthquake increases. The probability is conditioned on the number of small earthquakes n(t), with M ≥ M_S = 3.49, that have occurred since the last large earthquake. The probability is computed directly as the Positive Predictive Value (PPV) associated with the ROC curve. The method is compared with the UCERF3 forecasts for the UCERF3-defined geographic boxes centered on Los Angeles and San Francisco and serves as an indicative benchmark. The method is then applied to a 125 km radius circular area around Los Angeles, California, following the 17 January 1994 magnitude M6.7 Northridge earthquake, and short-term forecasts (1-year and 5-year) are computed. We further apply the method to six additional geographic regions with validation by comparison with an estimate of the time-independent conditional Poisson probability. These regions are Athens, Greece; Chengdu, China; Jakarta, Indonesia; Lima, Peru; Santiago, Chile; and Tangshan, China. Full article

Existing structural health monitoring of LNG (liquefied natural gas) liquid storage tanks is strictly constrained by explosion-proof safety and engineering conditions, making it impractical to achieve full-domain coverage through dense sensor deployment. How to achieve effective coverage of structural seismic weak parts under limited measuring point conditions is the core issue for monitoring scheme optimization. This paper takes a practical large full-containment LNG storage tank project as the research object and proposes a targeted sensor deployment method based on finite element seismic response analysis: identifying structural seismic weak parts through refined finite element modeling and seismic response analysis, thereby achieving coverage of critical regions and improved monitoring efficiency under limited sensor constraints. The research approach is as follows: a finite element model of the LNG storage tank is established using ADINA software and verified through modal analysis combined with on-site ambient vibration testing, ensuring the accuracy and engineering applicability of numerical simulation. Typical seismic records including El Centro, Tangshan, and TAFT are selected, and seismic response analysis of the tank is carried out, clarifying the displacement response laws under different seismic waves and identifying the junctions of dome roof and tank wall, buttress columns and tank wall, and the upper and local areas of the tank wall as structural seismic weak parts. Based on the characteristics of these parts and on-site explosion-proof conditions, a four-measuring-point targeted monitoring sensor deployment scheme is formulated and applied in engineering. This research constructs a structural health monitoring method for LNG storage tanks featuring “structural model verification–weak part identification–monitoring scheme customization,” providing a new approach for tank monitoring under explosion-proof safety constraints and partially addressing the limitations of traditional empirical deployment methods. This study establishes a technical path covering the full cycle of routine operation, seismic response, and post-earthquake assessment, providing methodological support for the structural health monitoring of LNG storage tanks, and its core concepts can also serve as a reference for the structural health monitoring of similar large-scale thin-walled storage tanks. Full article

Three-dimensional gravity inversion technology involves inferring the underground density structure based on observed gravity anomaly data. In addition to gravity inversion based on physics-driven methods, deep learning, as a purely data-driven technique, is increasingly gaining attention in geophysical inversion problems. However, purely data-driven methods rely on the implicit relationships within the data during the inversion process, which results in a lack of clear physical significance. This study proposes a three-dimensional gravity inversion method that integrates physical equations with deep learning. Based on the U-Net architecture, the gravity forward equation is incorporated as a physical constraint term, and a composite loss function—comprising three-dimensional mean squared error, a depth-weighting function, and three-dimensional intersection-over-union loss—is constructed to enhance inversion accuracy. Numerical experiments indicate that this method outperforms traditional algorithms in terms of density recovery accuracy and boundary clarity. When applied to gravity anomaly data from the Tangshan earthquake region in China, this method successfully inverted the three-dimensional subsurface density structure, revealing a high-density anomaly beneath the seismic source area, which provides important evidence for understanding the regional earthquake generation mechanism. Full article

Earthquakes, as one of the most destructive natural disasters, often cause significant casualties and severe economic losses. Accurate prediction of earthquake fatalities is of great importance for pre-disaster prevention and mitigation planning, as well as post-disaster emergency response deployment. To address the challenges of small sample sizes, high dimensionality, and strong nonlinearity in earthquake fatality prediction, this paper proposes an integrated modeling approach (PCA-IWOA-XGBoost) combining Principal Component Analysis (PCA), the Improved Whale Optimization Algorithm (IWOA), and Extreme Gradient Boosting (XGBoost). The method first employs PCA to reduce the dimensionality of the influencing factor data, eliminating redundant information and improving modeling efficiency. Subsequently, the IWOA is used to intelligently optimize key hyperparameters of the XGBoost model, enhancing the prediction accuracy and stability. Using 42 major earthquake events in China from 1970 to 2025 as a case study, covering regions including the west (e.g., Tonghai in Yunnan, Wenchuan, Jiuzhaigou), central (e.g., Lushan in Sichuan, Ya’an), east (e.g., Tangshan, Yingkou), north (e.g., Baotou in Inner Mongolia, Helinger), northwest (e.g., Jiashi in Xinjiang, Wushi, Yongdeng in Gansu), and southwest (e.g., Lancang in Yunnan, Lijiang, Ludian), the empirical results showed that the PCA-IWOA-XGBoost model achieved an average test set accuracy of 97.0%, a coefficient of determination (R²) of 0.996, a root mean square error (RMSE) and mean absolute error (MAE) reduced to 4.410 and 3.430, respectively, and a residual prediction deviation (RPD) of 21.090. These results significantly outperformed the baseline XGBoost, PCA-XGBoost, and IWOA-XGBoost models, providing improved technical support for earthquake disaster risk assessment and emergency response. Full article

The real-time input of ground motions can effectively assess earthquake disasters in building structures. In this study, we proposed a nearby real-time simulation method that can be applied to assess regional earthquake disasters using structural monitoring recordings based on an urban earthquake simulation system. Real-time accelerations recorded during the 5.1 magnitude Tangshan earthquake were used to update and modify the computing models. El Centro waves were calibrated to 400 cm/s² for structural seismic resilience analyses. The results indicated that approximately 70% of the structural functions were lost during the rare earthquake. Regional numerical models of 216 buildings were constructed and timeously updated using a geographic information system and measured data. The inputting ground motions recorded in the 5.1 magnitude Tangshan earthquake and typical El Centro waves were selected to analyze the structural seismic response, in which the damage indexes were computed, and the damage predictions of the regional 216 buildings were also simulated in different levels of earthquakes by being combined with the simplified principles of structural damage estimation. Finally, the evaluation results were visualized in three dimensions using ParaView software. The simulated results of earthquake disasters at an urban scale will promote the prediction abilities of local earthquake administration agencies and have considerable potential to provide essential information for emergency responses and regional disaster mitigation. Full article

North China is one of the high-risk areas for destructive and strong earthquakes in mainland China and has experienced numerous strong historical earthquakes. An earthquake of magnitude M_W 5.5 struck Pingyuan County, Dezhou city, in Shandong Province, China, on 6 August 2023. This earthquake was the strongest in the eastern North China Craton since the 1976 Tangshan earthquake. Since the earthquake did not produce surface ruptures, the seismogenic structure for fault responsible for the Pingyuan M_W 5.5 earthquake is still unclear. To reveal the subsurface geological structure near the earthquake epicenter, this study used high-resolution two-dimensional (2D) seismic reflection profiles and constructed a three-dimensional (3D) geometric model of the Tuqiao Fault by interpreting the faults in the seismic reflection profiles. This study further combined focal mechanism solutions, aftershock clusters, and other seismological data to discuss the seismogenic fault of the Pingyuan M_W 5.5 earthquake. The results show that the Tuqiao Fault is not the seismogenic fault of the M_W 5.5 earthquake. The actual seismogenic structure may be related to the NE-oriented high-angle strike-slip blind fault developed in the basement. We further propose three possible fault models for the strong seismogenic structure in North China to discuss the potential seismotectonics in this region. Full article

This paper focuses on the seismic response of symmetrical underground subway stations to seismic waves with varying frequencies and peak ground accelerations (PGAs), essential in light of growing urban underground transit systems. A 1/40 scale station model was subjected to seismic simulations using waves from the Wenchuan and Tangshan earthquakes and an artificial wave spanning 0.1 g to 0.5 g PGAs. Shaking table tests revealed that seismic impacts divide at PGA = 0.3 g; high-frequency waves affect structures more below this threshold, while low-frequency waves have more impact above it. The columns on the third basement level responded more to seismic activity, particularly at their base. The study recommends prioritizing the seismic design of these columns during station construction, especially in earthquake-prone zones. Understanding the dynamic effects of different frequencies and amplitudes is crucial for selecting and reinforcing materials and structural designs to enhance seismic resistance. Full article

Establishing a database of building exposures is an important basic work in earthquake insurance research. How to efficiently, accurately, and scientifically construct the risk exposure database of buildings has become a hot topic these days. Based on multi-source data, a system for extracting seismic information from urban buildings was constructed in the Tangshan urban area, and a perfect earthquake insurance risk database was established in this study. In the extraction system, the U-net identification method, spatial overlay and kernel density estimation method, Kriging interpolation method, statistical analysis, and multi-temporal land cover data analysis were used, respectively, to extract the information of footprint areas, use function, story number, structure type, and construction age of the urban buildings. The extraction results are stratified and randomly sampled, and the confusion matrix is introduced to verify the extraction effect. The results show that the building covers an area of about 50 million square meters in the urban area of Tangshan City. With the training and validation of the U-net model, the global accuracy of the building footprint areas recognition model is 71%. By comparing the results of manually determined real data with the extraction results of this study for a sample of 660 buildings, it was found that the overall accuracy rates of the extraction results of building function, story number, structure type, and construction age were 88.62%, 86.65%, 86.49%, and 85.58%, respectively, and kappa coefficients were all over 0.8. These indicate that the information on buildings extracted by the method of this study is accurate and reliable. This study can provide data and methods for the establishment of the exposure database of earthquake insurance and provide strong data support for pre-earthquake disaster prevention, post-earthquake emergency rescue, and disaster loss assessment. Full article

We analyze a set of precursory data measured before but compiled in retrospect of the M_S7.5 Haicheng earthquake in February 1975 and the M_S7.6–7.8 Tangshan earthquake in July 1976. We propose a robust and simple coarse-graining method that aggregates and counts how all the anomalies together (levelling, geomagnetism, soil resistivity, earth currents, gravity, earth stress, well water radon, well water level) develop as a function of time. We demonstrate strong evidence for the existence of an acceleration of the number of anomalies leading up to the major Haicheng and Tangshan earthquakes. In particular for the Tangshan earthquake, the frequency of occurrence of anomalies is found to be well described by the log-periodic power law singularity (LPPLS) model, previously proposed for the prediction of engineering failures and later adapted to the prediction of financial crashes. Using a mock real-time prediction experiment and simulation study, based on this methodology of monitoring accelerated rates of physical anomalies measured at the surface, we show the potential for an early warning system with a lead time of a few days. Full article

Rapid socioeconomic development in earthquake-prone areas can cause rapid changes in seismic loss risks. These changes make it difficult to ensure that risk reduction strategies are realistic, practical and effective over time. To overcome this difficulty, ongoing changes in risk should be captured timely, definitively, and accurately and then specific and well-timed adjustments of the relevant strategies should be made. However, methods for rapidly characterizing such seismic disaster risks over a large area have not been sufficiently developed. By focusing on building loss risks, this paper presents the development of an integrated method that combines remote sensing data and local knowledge to resolve this problem. This method includes two key interdependent steps. (1) To extract the heights and footprint areas of a large number of buildings accurately and quickly from single high-resolution optical remote sensing images; (2) To estimate the floor areas, identify structural types, develop damage probability matrixes, and determine economic parameters for calculating monetary losses due to seismic damage to the buildings by reviewing building-relevant local knowledge based on these two parameters (i.e., the building heights and footprint areas). This method is demonstrated in the Tangshan area of China. Based on the integrated method, the total floor area of the residential and public office buildings in central Tangshan in 2009 was 3.99% lower than the corresponding area number obtained by a conventional earthquake loss estimation project. Our field-based verification indicated that the mean relative error of the method for estimating the floor areas of the assessed buildings was 2.99%. A simulation of the impacts of the 1976 Ms 7.8 Tangshan earthquake using this method indicated that the total damaged floor area of the residential and public office buildings and the associated direct monetary loses in the study area could have been 8.00 and 28.73 times greater, respectively, than in 1976 if this earthquake had recurred in 2009, which is a strong warning to the local people regarding the increasing challenges they may face. Full article

Anomalies in animal behavior and meteorological phenomena before major earthquakes have been reported throughout history. Bio-mimetics or bionics aims at learning disaster anticipation from animals. Since modern science is reluctant to address this problem an effort has been made to track down the knowledge available to ancient natural philosophers. Starting with an archaeologically documented human sacrifice around 1700 B.C. during the Minoan civilization immediately before a large earthquake, which killed the participants, earthquake prediction knowledge throughout antiquity is evaluated. Major practical experience with this phenomenon has been gained from a Chinese earthquake prediction initiative nearly half a century ago. Some quakes, like that of Haicheng, were recognized in advance. However, the destructive Tangshan earthquake was not predicted, which was interpreted as an inherent failure of prediction based on animal phenomena. This is contradicted on the basis of reliable Chinese documentation provided by the responsible earthquake study commission. The Tangshan earthquake was preceded by more than 2,000 reported animal anomalies, some of which were of very dramatic nature. They are discussed here. Any physical phenomenon, which may cause animal unrest, must involve energy turnover before the main earthquake event. The final product, however, of any energy turnover is heat. Satellite based infrared measurements have indeed identified significant thermal anomalies before major earthquakes. One of these cases, occurring during the 2001 Bhuj earthquake in Gujarat, India, is analyzed together with parallel animal anomalies observed in the Gir national park. It is suggested that the time window is identical and that both phenomena have the same geophysical origin. It therefore remains to be demonstrated that energy can be released locally before major earthquake events. It is shown that by considering appropriate geophysical feedback processes, this is possible for large scale energy conversion phenomena within highly non-linear geophysical mechanisms. With satellite monitored infrared anomalies indicating possible epicenters and local animal and environmental observations immediately initiated, the learning experience towards an understanding of the phenomena involved could be accelerated. Full article