Consistency of ground-motion predictions from the past four decades: peak ground velocity and displacement, Arias intensity and relative significant duration

Edwards

2016

Earth-Science Reviews

Self Cite

166

Seismic hazard analyses (SHA) are routinely carried out around the world to understand the hazard, and consequently the risk, posed by earthquake activity. Whether single scenario, deterministic analyses, or state-of-the art probabilistic approaches, considering all possible events, a founding pillar of SHA is the estimation of the ground-shaking field from potential future earthquakes. Early models accounted for simple observations, such that ground shaking from larger earthquakes is stronger and that ground motion tends to attenuate rapidly away from the earthquake source. The first ground motion prediction equations (GMPEs) were, therefore, developed with as few as two principal predictor variables: magnitude and distance. Despite the significant growth of computer power over the last few decades, and with it the possibility to compute kinematic or dynamic rupture models coupled with simulations of 3D wave propagation, the simple parametric GMPE has remained the tool of choice for hazard analysts. There are numerous reasons for this. First and foremost GMPEs are robust and reliable within the model space considered during their derivation, and many can be extrapolated to a degree beyond this space with some confidence. With ever expanding datasets and improved metadata the models are becoming more and more useful: a range of predictor variables are now used, describing the source, path and site effects in detail. GMPEs are also relatively easy to implement and computationally inexpensive. Despite this, probabilistic hazard calculations using GMPEs and accounting for uncertainties can still take several days to run. Full simulation-based approaches, therefore, clearly lie outside the computation budget afforded to most projects. As well as the ever expanding list of predictor variables, other recent developments have also significantly improved the predictive power of GMPEs. This has allowed them to maintain their advantage over more `physical' simulation techniques. Possibly the biggest aspect of this is not related to the median ground-shaking field, but rather its variability (and correlation in space and with oscillator period). This is a major advantage of empirical as opposed to simulation approaches, which typically struggle to replicate the covariance of input variables and, consequently, the variance of the ground motion. In this article we summarize some of the recent advances in ground motion prediction equations, including their application in SHA. We begin with a summary of the current state-of-the-art, then introduce the main additional predictor variables now used. Region- and event-type (tectonic or induced) specific predictions and adjustments are then discussed. Additional topics include advances in estimating ground-motion variability (epistemic and aleatory) and expanding GMPEs to predict other intensity measures or waveform features. The article concludes with a discussion on the path forward in earthquake ground motion prediction

Section: Epistemic Uncertaintymentioning

confidence: 97%

Section: Extensions To Ground-motion Modelsmentioning

confidence: 99%

Recent and future developments in earthquake ground motion estimation

Edwards

2016

Earth-Science Reviews

Self Cite

166

“…One also has to keep in mind that other considerations can influence the choice of the IM, such as its ability to be predicted via GMPEs (e.g. Douglas, 2012). It is assumed that the very slight differences in AUC values displayed in Table 5 are not significant; therefore, any couples of IMs presented in this table can be considered for use, as they are at least as efficient as any single IM (see Table 4).…”

Section: Linear Combinations Of Two Imsmentioning

confidence: 99%

Vector-valued fragility functions for seismic risk evaluation

Gehl

Seyedi

2012

Bull Earthquake Eng

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This article presents a method for the development of vector-valued fragility functions, which are a function of more than one intensity measure (IM, also known as ground-motion parameters) for use within seismic risk evaluation of buildings. As an example, a simple unreinforced masonry structure is modelled using state-of-the-art software and hundreds of nonlinear time-history analyses are conducted to compute the response of this structure to earthquake loading. Dozens of different IMs (e.g. peak ground acceleration and velocity, response spectral accelerations at various periods, Arias intensity and various duration and number of cycle measures) are considered to characterize the earthquake shaking. It is demonstrated through various statistical techniques (including Receiver Operating Characteristic analysis) that the use of more than one IM leads to a better prediction of the damage state of the building than just a single IM, which is the current practice. In addition, it is shown that the assumption of the lognormal distribution for the derivation of fragility functions leads to more robust functions than logistic, log-logistic or kernel regression. Finally, actual fragility surfaces using two pairs of IMs (one pair are uncorrelated while the other are correlated) are derived and compared to scalar-based fragility curves using only a single IM and a significant reduction in the uncertainty of the predicted damage level is observed. This type of fragility surface would be a key component of future risk evaluations that take account of recent developments in seismic hazard assessment, such as vector-valued probabilistic seismic hazard assessments.

“…Other IMs are less well served by robust GMPEs. Douglas (2012) identified 96 GMPEs for the prediction of PGV, 19 for PGD, 33 for AI and 15 for relative significant duration. There are even fewer published GMPEs for the remaining IMs (e.g.…”

Section: Ground-motion Models For Prediction Of Imsmentioning

confidence: 99%

Evaluation of seismic hazard for the assessment of historical elements at risk: description of input and selection of intensity measures

Seyedi

Ulrich

et al. 2014

Bull Earthquake Eng

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International audienceThe assessment of historical elements at risk from earthquake loading presents a number of differences from the seismic evaluation of modern structures, for design or retrofitting purposes, which is covered by existing building codes, and for the development of fragility curves, procedures for which have been extensively developed in the past decade. This article briefly discusses: the hazard framework for historical assets, including a consideration of the appropriate return period to be used for such elements at risk; the intensity measures that could be used to describe earthquake shaking for the analysis of historical assets; and available approaches for their assessment. We then discuss various unique aspects of historical assets that mean the characterisation of earthquake loading must be different from that for modern structures. For example, historical buildings are often composed of heterogeneous materials (e.g. old masonry) and they are sometimes located where strong local site effects occur due to: steep topography (e.g. hilltops), basin effects or foundations built on the remains of previous structures. Standard seismic hazard assessment undertaken for modern structures and the majority of sites is generally not appropriate. Within the PERPETUATE project performance-based assessments, using nonlinear static and dynamic analyses for the evaluation of structural response of historical assets, were undertaken. The steps outlined in this article are important for input to these assessments