Numerical calculations of tectonic stress field of Chinese mainland and its neighboring regions and their applications to explanation of seismic activity

Mingruo, Jiao; Zhang, Guomin; Che, Shi; Liu, Jie

doi:10.1007/s11589-999-0018-1

Cited by 7 publications

(5 citation statements)

References 1 publication

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“…15a) is located in the eastern part of the island of Taiwan and the sea along its east coast. This is also consistent with the stress convergence point of the collision (Jiao et al 1999), which is believed to form the Central Mountains extended northeasterly in the central east part of the island of Taiwan (Cheng 2002;Zhuang et al 2005).…”

Section: Methodssupporting

confidence: 83%

“…15a and the maximum value of the stress is found around the center of Cluster 1 in Fig. 15a (Jiao et al 1999). The same situation also occurs in the island of Taiwan and the adjacent sea (the third area).…”

Section: Methodsmentioning

confidence: 54%

“…As the distribution of the clustered strong earthquakes is in accordance with the pattern of tectonics and tectonic stress in East and Southeast Asia (Jiao et al 1999), DECODE and OPTICS can be compared by analyzing the consistency between the tectonics and clusters detected by them. We first discuss the classification generated by DECODE.…”

Section: Methodsmentioning

confidence: 99%

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DECODE: a new method for discovering clusters of different densities in spatial data

Pei

Jasra

Hand

et al. 2008

Data Min Knowl Disc

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When clusters with different densities and noise lie in a spatial point set, the major obstacle to classifying these data is the determination of the thresholds for classification, which may form a series of bins for allocating each point to different clusters. Much of the previous work has adopted a model-based approach, but is either incapable of estimating the thresholds in an automatic way, or limited to only two point processes, i.e. noise and clusters with the same density. In this paper, we present a new density-based cluster method (DECODE), in which a spatial data set is presumed to consist of different point processes and clusters with different densities Responsible editor: Charu Aggarwal. belong to different point processes. DECODE is based upon a reversible jump Markov Chain Monte Carlo (MCMC) strategy and divided into three steps. The first step is to map each point in the data to its mth nearest distance, which is referred to as the distance between a point and its mth nearest neighbor. In the second step, classification thresholds are determined via a reversible jump MCMC strategy. In the third step, clusters are formed by spatially connecting the points whose mth nearest distances fall into a particular bin defined by the thresholds. Four experiments, including two simulated data sets and two seismic data sets, are used to evaluate the algorithm. Results on simulated data show that our approach is capable of discovering the clusters automatically. Results on seismic data suggest that the clustered earthquakes, identified by DECODE, either imply the epicenters of forthcoming strong earthquakes or indicate the areas with the most intensive seismicity, this is consistent with the tectonic states and estimated stress distribution in the associated areas. The comparison between DECODE and other state-of-the-art methods, such as DBSCAN, OPTICS and Wavelet Cluster, illustrates the contribution of our approach: although DECODE can be computationally expensive, it is capable of identifying the number of point processes and simultaneously estimating the classification thresholds with little prior knowledge.

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Section: Methodssupporting

confidence: 83%

Section: Methodsmentioning

confidence: 54%

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DECODE: a new method for discovering clusters of different densities in spatial data

Pei

Jasra

Hand

et al. 2008

Data Min Knowl Disc

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“…Chinese mainland and its neighboring region is divided into six subplates, medium parameters of which are listed in Table 1, boundary condition of which are listed in Table 2 (Jiao, et al, 1999). The whole area is divided into 489 60*N: elements, 275 nodal points (Figure 1).…”

Section: Medium Parameter and Boundary Conditionmentioning

confidence: 99%

Study on seismic numerical model on the Chinese mainland and its vicinity

et al. 1999

Self Cite

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This paper presents the stress incremental rate of each element by using finite element numerical simulation way. Combined with the practical continent boundary condition and medium parameters, this paper applies the stress increment rate to the more practical modified cell automaton model according to the cell automaton principle. The paper preliminarily gives the more practical seismic space-time repeated evolutive maps, and compares the imitative seismic energy release with the real seismic energy release. It is thought that this model has its advantage over the old one whether in the seismic imitative characteristics or in the comparison with the real situation and is more practical model. Key words: finite element cell automaton model stress distribution seismic activity '

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“…For example, Wang S Y and Xu Z H et al [6,7] made a study of relative magnitude of forces acting on China continent and its surrounding plates using focal mechamism solutions in China and its vicinity. Jiao M R et al [8] did research on tectonic stress field in China and its vicinity by recent data of boundary displacement rates. They had almost the same conclusion that the India-Eurasia collision has the most important influence on China continent, the impact from the Philippines sea plate is secondary and that from the Pacific plate is the third one.…”

Section: Introductionmentioning

confidence: 99%

Dynamics of the Present‐Day Crustal Movement in the China Mainland

Ye¹,

Wang²

2004

Chinese J of Geophysics

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We employ the finite element method to perform modeling for the crustal and lithospheric movement in the China mainland and its neighboring areas. In the modeling we use a viscous sheet (Newtonian and non‐Newtonian) to simulate the continental lithosphere. By solving the force balance equations, we obtain the velocity field of China continental crust with respect to Eurasia plate and compare them with the recent Global Positioning System (GPS) measurements. Our result shows that the primary driving force source accounting for the crustal movement in this region is from the collision between the India and Eurasia plates as well as the huge gravity potential energy of the Qinghai‐Xizang plateau. In comparison, the contribution from the former is larger than the latter. The result also indicates that the media of the China lithosphere has a strong heterogeneity of rheology, which results in its block‐division feature of the present‐day crustal velocity field.

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Numerical calculations of tectonic stress field of Chinese mainland and its neighboring regions and their applications to explanation of seismic activity

Cited by 7 publications

References 1 publication

DECODE: a new method for discovering clusters of different densities in spatial data

DECODE: a new method for discovering clusters of different densities in spatial data

Study on seismic numerical model on the Chinese mainland and its vicinity

Dynamics of the Present‐Day Crustal Movement in the China Mainland

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