Duruo Huang

New Evidence and Perspective to the Poisson Process and Earthquake Temporal Distribution from 55,000 Events around Taiwan since 1900

AbstractEarthquake prediction is by all means controversial and challenging, given the fact that some recent catastrophic earthquakes went unpredicted. Not surprisingly, statistical approaches have been utilized to model earthquake randomness in time or space. One of the suggestions is that the earthquake’s temporal probability distribution should follow the Poisson model, which is suitable for rare events by definition. As a result, the customarily used hypothesis should be largely associated with the prior judgment that earthquakes are rare, but not as a result of abundant quantitative evidence or theoretical derivation. Therefore, this study aims to offer new empirical evidence to the hypothesis based on 110-year-long earthquake data around Taiwan. From the series of statistical tests, the first statistical inference is indeed in line with the model’s proposition: the level of fitting between observation and theory is better for earthquakes with a lower mean rate. To be more specific, it shows that the...

Deterministic seismic hazard map for Taiwan developed using an in-house Excel-based program

Seismic hazard analyses, either in a deterministic (DSHA) or probabilistic (PSHA) framework, are both commonly adopted for evaluating earthquake risk. Although different in methodology, both approaches involving tedious calculation are certainly a computer-aided analysis. For Taiwan, a few PSHA studies have been conducted, but not a single comprehensive DSHA study is yet available for this region. As a result, this study aims to develop a DSHA seismic hazard map for Taiwan through an Excel-based program. In use of the in-house program, the result shows that the deterministic seismic hazards for Taiwan are comparable to those estimated by the recent PSHA; in particular the 50th PGA (mean motion) in this DSHA was found in a good agreement with the PSHA at 10% exceedance probability in 50 years. In addition to developing the DSHA map for Taiwan, this paper provides the details of the in-house, Excel-based tool for Excel applications in geosciences studies.

Region‐Specific Spatial Cross‐Correlation Model for Stochastic Simulation of Regionalized Ground‐Motion Time Histories

Stochastic simulation of spatially distributed ground-motion time histor- ies is important for performance-based earthquake design of geographically distrib- uted systems. In this study, we develop a novel technique to stochastically simulate regionalized ground-motion time histories by taking account of the influence of regional site conditions. For this purpose, a transient acceleration time history is char- acterized by wavelet-packet parameters proposed by Yamamoto and Baker (2013). The wavelet-packet parameters can fully characterize ground-motion time histories in terms of energy content, time-frequency-domain characteristics and time-frequency nonstationarity. This study further investigates the spatial cross correlations of wavelet- packet parameters based on geostatistical analysis of 1500 regionalized ground-motion data from eight well-recorded earthquakes in California, Mexico, Japan, and Taiwan. The linear model of coregionalization (LMC) is used to develop a permissible spatial cross-correlation model for each parameter group. The geostatistical analysis of ground- motion data from different regions reveals significant dependence of the LMC structure on regional site conditions, which can be characterized by the correlation range of VS30 in each region. In general, the spatial correlation and cross correlation of wavelet- packet parameters are stronger if the site condition is more homogeneous. The pro- posed region-specific correlation model improves stochastic simulation of spatially correlated ground motions, as is demonstrated in illustrative examples in this article. The developed method has great potential to be used in computationally based seismic analysis and loss estimation in a regional scale.

On-site earthquake early warning with multiple regression analysis: Featuring two user-friendly applications for Excel

A variety of user-friendly spreadsheet templates have been developed for geoscience studies. However, the use of the built-in matrix functions within spreadsheet programs, such as Excel, is not particularly straightforward, lowering the value of spreadsheet programs for matrix-based computations, such as multiple regression analyses. Therefore, this study first developed two applications for Excel to perform multiple regression analyses in a much more user-friendly manner. Then using earthquake time histories from a reputable database, a series of regression analyses were performed. A new framework for on-site earthquake early warning based on multiple regression analyses is presented as an alternative to conventional models which were developed with single regression analyses.

Seismic hazard assessment on NPP sites in taiwan through an observation-oriented monte carlo simulation

This paper uses Monte Carlo Simulation to evaluate the seismic hazard in two nuclear power plants sites in Taiwan. This approach is different from the two commonly-used methods, featuring the direct use of observed earthquakes to develop magnitude and distance probability functions. Those earthquakes with larger sizes and closer to the site are considered capable of causing damage on engineered structures. The result shows that even though two NPP sites in Taiwan are only 30 km away from each other, NPP site 4 is situated with the seismic hazard four-time as large as NPP site 1. Given our limited understanding and the complicated, random earthquake process, none of a seismic hazard analysis is perfect without challenge. The accountability of seismic hazard analysis relates to analytical transparency, traceability, etc., not to analytical complexity and popularity.