scholarly journals Conditional probability of distributed surface rupturing during normal-faulting earthquakes

Solid Earth ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 1197-1209
Author(s):  
Maria Francesca Ferrario ◽  
Franz Livio
Keyword(s):  
Conditional Probability ◽  
Normal Faults ◽  
Engineering Practice ◽  
Normal Faulting ◽  
Logic Tree ◽  
Case Histories ◽  
Full Spectrum ◽  
Empirical Relations ◽  
Fault Displacement ◽  
Tree Approach

Abstract. Coseismic surface faulting is a significant source of hazard for critical plants and distributive infrastructure; it may occur either on the principal fault or as distributed rupture on nearby faults. Hazard assessment for distributed faulting is based on empirical relations which, in the case of normal faults, were derived almost 15 years ago using a dataset of US earthquakes. We collected additional case histories worldwide, for a total of 21 earthquakes, and calculated the conditional probability of distributed faulting as a function of distance from the principal fault. We found no clear dependency on the magnitude nor the time of occurrence of the earthquakes, but our data consistently show a higher probability of rupture when compared with the scaling relations currently adopted in engineering practice. We derive updated empirical regressions and show that the results are strongly conditioned by the averaging of earthquakes effectively generating distributed faulting at a given distance and those which did not generate faulting; thus, we introduce a more conservative scenario that can be included in a logic tree approach to consider the full spectrum of potential ruptures. Our results can be applied in the framework of probabilistic assessment of fault displacement hazard.

scholarly journals Distributed faulting following normal earthquakes: reassessment and updating of scaling relations

2020 ◽  
Author(s):  
Maria Francesca Ferrario ◽  
Franz Livio
Keyword(s):  
Normal Faults ◽  
Scaling Relations ◽  
Engineering Practice ◽  
Probabilistic Assessment ◽  
Logic Tree ◽  
Case Histories ◽  
Full Spectrum ◽  
Empirical Relations ◽  
Fault Displacement ◽  
Tree Approach

Abstract. Coseismic surface faulting is a significant source of hazard for critical plants and distributive infrastructures; it may occur either on the primary fault, or as distributed rupture on nearby faults. Hazard assessment for distributed faulting is based on empirical relations which, in the case of normal faults, were derived almost 15 years ago on a dataset of US earthquakes. We collect additional case histories worldwide, for a total of 21 earthquakes, and we calculate the conditional probability of distributed faulting as a function of distance from the primary fault. We found no clear dependency on the magnitude nor the time of occurrence of the earthquakes, but our data consistently show a higher probability of rupture when compared to the scaling relations currently adopted in engineering practice. We derive updated empirical regressions and show that results are strongly conditioned by the averaging of earthquakes effectively generating distributed faulting at a given distance and those which did not generate faulting; thus, we introduce a more conservative scenario, which can be included in a logic tree approach to consider the full spectrum of potential ruptures. Our results can be applied in the framework of probabilistic assessment of fault displacement hazard.

scholarly journals Seismicity, focal mechanism, and stress tensor analysis of the Simav region, western Turkey

2020 ◽  
Vol 12 (1) ◽  
pp. 479-490
Author(s):  
Ahu Kömeç Mutlu
Keyword(s):  
Moment Tensor ◽  
Aftershock Sequence ◽  
Movement Direction ◽  
Normal Faults ◽  
Normal Faulting ◽  
Stress Inversion ◽  
Western Turkey ◽  
Stress Orientations ◽  
Extension Direction ◽  
Inversion Analysis

AbstractThis study focuses on the seismicity and stress inversion analysis of the Simav region in western Turkey. The latest moderate-size earthquake was recorded on May 19, 2011 (Mw 5.9), with a dense aftershock sequence of more than 5,000 earthquakes in 6 months. Between 2004 and 2018, data from earthquake events with magnitudes greater than 0.7 were compiled from 86 seismic stations. The source mechanism of 54 earthquakes with moment magnitudes greater than 3.5 was derived by using a moment tensor inversion. Normal faults with oblique-slip motions are dominant being compatible with the NE-SW extension direction of western Turkey. The regional stress field is assessed from focal mechanisms. Vertically oriented maximum compressional stress (σ1) is consistent with the extensional regime in the region. The σ1 and σ3 stress axes suggest the WNW-ESE compression and the NNE-SSW dilatation. The principal stress orientations support the movement direction of the NE-SW extension consistent with the mainly observed normal faulting motions.

The 4 December 2015 Mw 7.1 Normal-Faulting Antarctic Plate Earthquake and Its Seismotectonic Implications

2020 ◽  
Vol 110 (3) ◽  
pp. 1090-1100
Author(s):  
Ronia Andrews ◽  
Kusala Rajendran ◽  
N. Purnachandra Rao
Keyword(s):  
Body Wave ◽  
Focal Depth ◽  
Normal Fault ◽  
Normal Faults ◽  
Oceanic Plate ◽  
Normal Faulting ◽  
Transform Faults ◽  
Wave Inversion ◽  
Spreading Ridges ◽  
Southeast Indian Ridge

ABSTRACT Oceanic plate seismicity is generally dominated by normal and strike-slip faulting associated with active spreading ridges and transform faults. Fossil structural fabrics inherited from spreading ridges also host earthquakes. The Indian Oceanic plate, considered quite active seismically, has hosted earthquakes both on its active and fossil fault systems. The 4 December 2015 Mw 7.1 normal-faulting earthquake, located ∼700  km south of the southeast Indian ridge in the southern Indian Ocean, is a rarity due to its location away from the ridge, lack of association with any mapped faults and its focal depth close to the 800°C isotherm. We present results of teleseismic body-wave inversion that suggest that the earthquake occurred on a north-northwest–south-southeast-striking normal fault at a depth of 34 km. The rupture propagated at 2.7  km/s with compact slip over an area of 48×48  km2 around the hypocenter. Our analysis of the background tectonics suggests that our chosen fault plane is in the same direction as the mapped normal faults on the eastern flanks of the Kerguelen plateau. We propose that these buried normal faults, possibly the relics of the ancient rifting might have been reactivated, leading to the 2015 midplate earthquake.

Fault displacement gradients on normal faults and associated deformation

AAPG Bulletin ◽  
2014 ◽  
Vol 98 (6) ◽  
pp. 1161-1184 ◽  
Author(s):  
Alan P. Morris ◽  
Ronald N. McGinnis ◽  
David A. Ferrill
Keyword(s):  
Normal Faults ◽  
Fault Displacement

Logic-tree Approach for Probabilistic Tsunami Hazard Analysis and its Applications to the Japanese Coasts

2007 ◽  
Vol 164 (2-3) ◽  
pp. 577-592 ◽  
Author(s):  
Tadashi Annaka ◽  
Kenji Satake ◽  
Tsutomu Sakakiyama ◽  
Ken Yanagisawa ◽  
Nobuo Shuto
Keyword(s):  
Hazard Analysis ◽  
Tsunami Hazard ◽  
Logic Tree ◽  
Probabilistic Tsunami Hazard Analysis ◽  
Tree Approach

scholarly journals Probabilistic seismic hazard analysis using the logic tree approach – Patna district (India)

2019 ◽  
Vol 19 (10) ◽  
pp. 2097-2115 ◽  
Author(s):  
Panjamani Anbazhagan ◽  
Ketan Bajaj ◽  
Karanpreet Matharu ◽  
Sayed S. R. Moustafa ◽  
Nassir S. N. Al-Arifi
Keyword(s):  
Epistemic Uncertainty ◽  
Hazard Analysis ◽  
Response Spectra ◽  
Maximum Magnitude ◽  
Logic Tree ◽  
Ground Acceleration ◽  
Incremental Method ◽  
Seismicity Parameters ◽  
Hazard Response ◽  
Tree Approach

Abstract. Peak ground acceleration (PGA) and study area (SA) distribution for the Patna district are presented considering both the classical and zoneless approaches through a logic tree framework to capture the epistemic uncertainty. Seismicity parameters are calculated by considering completed and mixed earthquake data. Maximum magnitude is calculated using three methods, namely the incremental method, Kijko method, and regional rupture characteristics approach. The best suitable ground motion prediction equations (GMPEs) are selected by carrying out an “efficacy test” using log likelihood. Uniform hazard response spectra have been compared with Indian standard BIS 1893. PGA varies from 0.38 to 0.30 g from the southern to northern periphery considering 2 % probability of exceedance in 50 years.

scholarly journals Probabilistic seismic hazard analysis using logic tree approach – Patna District (India)

2019 ◽  
Author(s):  
Panjamani Anbazhagan ◽  
Ketan Bajaj ◽  
Karanpreet Matharu ◽  
Sayed S. R. Moustafa ◽  
Nassir S. N. Al-Arifi
Keyword(s):  
Epistemic Uncertainty ◽  
Hazard Analysis ◽  
Response Spectra ◽  
Maximum Magnitude ◽  
Logic Tree ◽  
Incremental Method ◽  
Seismicity Parameters ◽  
Hazard Response ◽  
Frame Work ◽  
Tree Approach

Abstract. PGA and SA distribution for Patna district is presented considering both classical and zoneless approach through logic tree frame work to capture the epistemic uncertainty. Seismicity parameters are calculated by considering completed and mixed earthquake data. Maximum magnitude was calculated using three methods namely incremental method, Kijko method and regional rupture characteristics approach. Best suitable GMPE was selected by carrying out efficacy test using log likelihood. Uniform hazard response spectra have been compared with Indian standard BIS 1893. PGA varies from 0.38 g to 0.30 g from southern to northern periphery considering 2 % probability of exceedence in 50 years.

Safety evaluation of truss structures using nested discrete Bayesian networks

2020 ◽  
Vol 19 (6) ◽  
pp. 1924-1936 ◽  
Author(s):  
Sheng-En Fang ◽  
Jia-li Tan ◽  
Xiao-Hua Zhang
Keyword(s):  
Bayesian Network ◽  
Conditional Probability ◽  
Network Topology ◽  
Safety Evaluation ◽  
System Level ◽  
Truss Structures ◽  
Engineering Practice ◽  
Directed Edge ◽  
Civil Structures ◽  
Nested Network

Truss structures have been widely adopted for civil structures such as long-span buildings and bridges. An actual truss system is usually statically indeterminate having numerous members and high redundancy. It is practically difficult to evaluate the truss safety through traditional reliability-based approaches in view of complex failure modes and uncertainties. Moreover, monitoring data are generally insufficient in reality due to limited sensors under cost consideration. Therefore, a nested discrete Bayesian network has been developed for safety evaluation of truss structures. A concept of member risk coefficient is first proposed based on the mechanical relationship between load effects and member resistance. According to the coefficients of all members, member risk sequences are found as the basis for establishing the topology of a member-level Bayesian network. Each network node represents a truss member and a nodal variable having three states: elasticity, plasticity, and failure. Two relevant member nodes are connected by a directed edge whose causality strength is expressed by a conditional probability table. Meanwhile, a system-level network topology is established to reflect the effects of member states on the truss system. The system is assigned with a node having two states: safety and failure. The directed edge of each member node directly points to the system node. Then, the two networks are combined to form a nested network topology. By this means, direct topology learning is avoided in order to find rational and concise topologies satisfying the mechanical characteristics of civil structures. After that, the conditional probability tables for the nested network are obtained through parameter learning on complete numerical observation data. The data acquirement procedure takes into account uncertainties by defining the randomness of cross-sectional areas and external loads. With the conditional probability tables, the nested network is ready for use. When new evidence from limited monitored members is input into the nested network, the state probabilities of the other members, as well as the system, are simultaneously updated using exact inference algorithms. The inference ability using insufficient information well accords with the demand of engineering practice. Finally, the proposed method has been successfully verified against both numerical and experimental truss structures. It was found that the network estimations could be further confirmed with more evidence.

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