Jui-pin Wang

Seismic hazard analyses for Taipei city including deaggregation, design spectra, and time history with excel applications

Given the difficulty of earthquake forecast, Probabilistic Seismic Hazard Analysis (PSHA) has been a method to best estimate site-specific ground motion or response spectra in earthquake engineering and engineering seismology. In this paper, the first in-depth PSHA study for Taipei, the economic center of Taiwan with a six-million population, was carried out. Unlike the very recent PSHA study for Taiwan, this study includes the follow-up hazard deaggregation, response spectra, and the earthquake motion recommendations. Hazard deaggregation results show that moderate-size and near-source earthquakes are the most probable scenario for this city. Moreover, similar to the findings in a few recent studies, the earthquake risk for Taipei should be relatively high and considering this citys importance, the high risk should not be overlooked and a potential revision of the local technical reference would be needed. In addition to the case study, some innovative Excel applications to PSHA are introduced in this paper. Such spreadsheet applications are applicable to geosciences research as those developed for data reduction or quantitative analysis with Excels user-friendly nature and wide accessibility.

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.

RosenPoint: A Microsoft Excel-based program for the Rosenblueth point estimate method and an application in slope stability analysis

The Rosenblueth point estimate method is one of the probabilistic analyses in estimating failure probability of a system, such as a slope. The essence of the approach is to use two point estimates, mean value+/-standard deviation, to present a variable in safety evaluation. The simple and straightforward framework leads to its wide application, but as a system governed by n variables (n is large), mass computations (2^n repetitions in calculation) are required during the analysis. This prevents the possibility of hand computation using the approach, and a proper computing tool is needed under this situation. In this study, a Microsoft Excel-based program, RosenPoint, was developed for the Rosenblueth approach, and the program developments, descriptions and modifications are given in detail. The program is successfully demonstrated by computing the failure probability of an infinite slope under earthquake condition with a deterministic factor of safety (FOS) equal to 1.77. As the critical FOS is equal to 1.4, the slope that is considered stable by a conventional analysis is found associated with a substantial failure probability around 20%. Since the current version of RosenPoint is designed for estimating slope failure probability, the program needs modification as it is used for other tasks. Owing to the separated programming structure in RosenPoint, the subroutine governing FOS algorithms only needs to be replaced or recompiled as modification is needed. In addition, the capacity of the current RosenPoint is limited to 19 variables due to the dimension constraint of Excel spreadsheets (=2^2^0 rows). However, the capacity can be easily improved with sacrificing output completeness. This program modification is also described in this paper.

New pole-searching algorithm with applications to probabilistic circular slope stability assessment

Conventional deterministic analysis for evaluating slope stability, although computationally efficient, is gradually shadowed by probabilistic analysis in two aspects. First deterministic analysis does not account for inevitable soil variability, and secondly its assessment would be deficient especially under a critical condition. However, probabilistic analysis that is computationally expensive sometime deters itself from being used when efficient algorithms are absent. For optimizing the calculation during probabilistic slope analysis, this study introduces a new algorithm in searching for the center of a circular slip surface, referred to as the pole. Not only can this algorithm effectively locate the pole, but its accuracy is improved compared to that of the conventional method. This study further demonstrates the algorithm by performing a probabilistic analysis for a benchmark slope through Monte Carlo Simulation. Such a probabilistic analysis saves 10^6h from the use of the conventional pole-searching algorithm in an equivalent analysis. The results show that circular slope stability is indeed affected by soil variability, which should not be overlooked since it is inevitable owing to natural randomness.

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.

Two Bayesian Algorithms for the Estimation of Earthquake Parameters

The purpose of the Bayesian approach is to integrate multiple sources of information into one final best-estimate with a unique algorithm, and a few applications have been developed for a variety of studies. This technical note provides two Bayesian algorithms for earthquake studies: the development of earthquake source-to-site distance distributions and the smoothing of earthquake rates in a region. In addition to the derivations, this note also provides demonstrations on the basis of real earthquake data to provide a better explanation of the two Bayesian algorithms proposed.

Risk assessments on active faults in Taiwan

Engineering risk assessment is to estimate the structure’s failure probability multiplied by its failure consequences. On the other hand, the analysis was sometimes performed on a more general basis, utilizing a few indicators to quantify relative risk levels for decision-making. On the basis of such a framework, this paper introduces a novel risk assessment on 18 active faults in Taiwan, considering the fault’s location, earthquake size and return period from the literature. The result shows that the Chelungpu Fault in central Taiwan has the highest risk score among the 18 active faults, in contrast to the Hengchun Fault in southern Taiwan which has the lowest risk. Besides this, the 18 active faults in Taiwan were classified into four groups based on this risk assessment, and the classification could help the region’s sustainable development against earthquake hazard.

Estimating the standard deviation of soil properties with limited samples through the Bayesian approach

Characterizing the standard deviation of soil properties is important to a geotechnical probabilistic analysis, and the task is usually achieved with sufficient samples. However, sometimes soil samples or soil tests in a project could be limited (e.g., only one sample), making classical statistics approaches less applicable to the estimating. In this technical note, we introduce a new Bayesian algorithm to estimate the standard deviation of soil properties, using limited project-specific samples along with relevant prior information from the literature. In addition to the methodology, a few demonstrations are also given in the paper, to re-evaluate the standard deviation of soil properties with the new algorithm. Like many Bayesian algorithms, the new application could be useful for site characterizations when samples are limited.

Deterministic seismic hazard assessments for Taiwan considering non-controlling seismic sources

The region around Taiwan is known for active seismicity, and a few studies have reported a high seismic hazard in this region, including a deterministic seismic hazard analysis (DSHA) study. Essentially, DSHA is to estimate earthquake ground motions considering the worst-case earthquake size and location, but without considering the seismic hazards from non-controlling sources. Understandably, when many non-controlling sources are present, the original DSHA framework could be insufficient. Therefore, using the extreme probability theory, this study introduces a new DSHA framework taking non-controlling seismic sources into account during DSHA calculations. The new method was applied to a seismic hazard assessment for Taiwan, showing that near the conjunctions of seismic source zones, the increase in seismic hazard could be substantial after considering a total of 19 non-controlling sources. More importantly, like other seismic hazard assessments for Taiwan, this study conveys the same alarming message that a high level of seismic hazard should be present around the region.