Extreme value statistics of interval maximum amplitudes due to aftershocks and its application for early forecast

Author(s):  
Kaoru Sawazaki

<p>Waveforms from many aftershocks occurring immediately after a large earthquake tend to overlap in a seismogram, which makes it difficult to pick their P- and S-wave phases. Accordingly, to determine hypocenter and magnitude of the aftershocks becomes difficult and thereby causes deterioration of earthquake catalog. Using such deteriorated catalog may cause misevaluation of ongoing aftershock activity. Since aftershock activity is usually most intense in the early period after a large earthquake, requirement of early aftershock forecast and deterioration of the aftershock catalog are impatient.</p><p>Several methods for aftershock forecast, using deteriorated automatic earthquake catalog (Omi et al., 2016, 2019) or continuous seismic envelopes (Lippiello et al., 2016), have been proposed to overcome such a situation. In this study, I propose another method that evaluates excess probability of maximum amplitude (EPMA) due to aftershocks using a continuous seismogram. The proposed method is based on the extreme value statistics, which provides probability distribution of maximum amplitudes within constant time intervals. From the Gutenberg-Richter and the Omori-Utsu laws and a conventional ground motion prediction equation (GMPE), I derived this interval maximum amplitude (IMA) follows the Frechet distribution (or type Ⅱ extreme-value distribution). Using the Monte-Carlo based approach, I certified that this distribution is well applicable to IMAs and available for forecasting maximum amplitudes even if many seismograms are overlapped.</p><p>Applying the Frechet distribution to the first 3 hour-long seismograms of the 2008 Iwate-Miyagi Nairiku earthquake (M<sub>W</sub> 6.9), Japan, I computed the EPMAs for 4 days at 4 stations. The maximum amplitudes due to experienced aftershocks proceeded following mostly within the 10 % to 90 % EPMA curves. This performance may be acceptable for a practical use.</p><p>Differently from the catalog-based method, the proposed method is almost unaffected by overlap of seismograms even in early lapse times. Since it is based on a single station processing, even seismic “network” is not required, and can be easily deployed at locations of poor seismic network coverage. So far, this method is correctly applicable for typical mainshock-aftershock (Omori-Utsu-like) sequence only. However, potentially, it could be extended to multiple sequences including secondary aftershocks and remotely triggered earthquakes.</p>

Author(s):  
Kaoru Sawazaki

ABSTRACT To evaluate the exceedance probability of maximum amplitude (EPMA) due to aftershocks, I developed a forecasting scheme based on the extreme value statistics applied to a single continuous seismogram of early aftershocks. By combining the general laws of aftershock activity (Gutenberg–Richter and Omori–Utsu laws) and a ground-motion prediction equation (including source, path, and site factors), I verified that the interval maximum amplitude of a continuous seismogram of aftershocks follows the non-stationary Frechet distribution (NFD), which is one of the extreme value distributions. The parameters of NFD are written explicitly from the parameters commonly used in seismology. By optimizing the NFD parameters through the maximum-likelihood method and using the maximum-likelihood estimates and their covariance values, I derived the EPMA due to aftershocks based on the Bayesian approach. The performance of the EPMA was examined by Monte Carlo simulations and real seismograms. The numerically generated maximum amplitude was predicted well from the EPMA, which was evident even in the period of intense seismicity in which many waveforms overlap in a seismogram. This performance was also robust for real seismograms of aftershocks for the 2008 Iwate–Miyagi Nairiku, Japan, earthquake. The maximum amplitudes observed for four days were mostly within the 10% and 90% EPMA curves issued within 3 hr of the mainshock. The proposed method does not need to evaluate source, path, and site factors because these factors are included in the estimated NFD parameters. Given that the proposed method allows single-station processing, a seismic “network” is not required. Therefore, the proposed algorithm will be easily implementable in a seismic observation system installed at important facilities. Also, the NFD parameters estimated robustly in the early lapse times may provide important knowledge regarding early aftershocks.


2020 ◽  
Vol 70 (5) ◽  
pp. 1211-1230
Author(s):  
Abdus Saboor ◽  
Hassan S. Bakouch ◽  
Fernando A. Moala ◽  
Sheraz Hussain

AbstractIn this paper, a bivariate extension of exponentiated Fréchet distribution is introduced, namely a bivariate exponentiated Fréchet (BvEF) distribution whose marginals are univariate exponentiated Fréchet distribution. Several properties of the proposed distribution are discussed, such as the joint survival function, joint probability density function, marginal probability density function, conditional probability density function, moments, marginal and bivariate moment generating functions. Moreover, the proposed distribution is obtained by the Marshall-Olkin survival copula. Estimation of the parameters is investigated by the maximum likelihood with the observed information matrix. In addition to the maximum likelihood estimation method, we consider the Bayesian inference and least square estimation and compare these three methodologies for the BvEF. A simulation study is carried out to compare the performance of the estimators by the presented estimation methods. The proposed bivariate distribution with other related bivariate distributions are fitted to a real-life paired data set. It is shown that, the BvEF distribution has a superior performance among the compared distributions using several tests of goodness–of–fit.


2013 ◽  
Author(s):  
M. Laurenza ◽  
G. Consolini ◽  
M. Storini ◽  
A. Damiani

2016 ◽  
Vol 31 (1) ◽  
Author(s):  
Gadde Srinivasa Rao ◽  
Kanaparthi Rosaiah ◽  
Mothukuri Sridhar Babu ◽  
Devireddy Charanaudaya Sivakumar

AbstractIn this article, acceptance sampling plans are developed for the exponentiated Fréchet distribution based on percentiles when the life test is truncated at a pre-specified time. The minimum sample size necessary to ensure the specified life percentile is obtained under a given customer's risk and producer's risk simultaneously. The operating characteristic values of the sampling plans are presented. One example with real data set is also given as an illustration.


1999 ◽  
Vol 150 (6) ◽  
pp. 209-218 ◽  
Author(s):  
Felix Forster ◽  
Walter Baumgartner

The two maps of intense rainfall in the Hydrological Atlas of Switzerland (1992, 1997) are compared to data of an evaluation of extreme value statistics. The results are transferred to recommendations for practioners.


Metals ◽  
2021 ◽  
Vol 11 (12) ◽  
pp. 1915
Author(s):  
Jungsub Lee ◽  
Sang-Youn Park ◽  
Byoung-Ho Choi

In this study, the fatigue characteristics of aluminum alloys and mechanical components were investigated. To evaluate the effect of forging, fatigue specimens with the same chemical compositions were prepared from billets and forged mechanical components. To evaluate the cleanliness of the aluminum alloys, the cross-sectional area of specimens was observed, and the maximum inclusion sizes were obtained using extreme value statistics. Rotary bending fatigue tests were performed, and the fracture surfaces of the specimens were analyzed. The results show that the forging process not only elevated the fatigue strength but also reduced the scatter of the fatigue life of aluminum alloys. The fatigue characteristics of C-specimens were obtained to develop finite-element method (FEM) models. With the intrinsic fatigue properties and strain–life approach, the FEM analysis results agreed well with the test results.


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