Information theory measures for the engineering validation of ground-motion simulations

This short communication introduces a quantitative approach for the engineering validation of ground-motion simulations based on information theory concepts and statistical hypothesis testing. Specifically, we use the Kullback-Leibler divergence to measure the similarity of the probability distributions of recorded and simulated ground-motion intensity measures (IMs). We demonstrate the application of the proposed validation approach to ground-motion simulations computed by using a variety of methods, including Graves and Pitarka hybrid broadband, the deterministic composite source model, and a stochastic white noise finite-fault model. Ground-motion IMs, acting as proxies for the (nonlinear) seismic response of more complex engineered systems, are considered herein to validate the considered ground-motion simulation methods. The list of considered IMs includes both spectral-shape and duration-related proxies, shown to be the optimal IMs in several probabilistic seismic demand models of different structural types, within the framework of performance-based earthquake engineering. The proposed validation exercise (1) can highlight the similarities and differences between simulated and recorded ground motions for a given simulation method and/or (2) allow the ranking of the performance of alternative simulation methods. The similarities between records and simulations should provide confidence in using the simulation method for engineering applications, while the discrepancies should help in improving the tested method for the generation of synthetic records

Validation of hazard-compatible stochastic ground motion model modification techniques

An important consideration for the adoption of stochastic ground motion models in performance-based earthquake engineering applications is that the probability distribution of target intensity measures from the developed suites of time-histories is compatible with the prescribed hazard at the site and structure of interest. The authors have recently developed a computationally efficient framework to modify existing stochastic ground motion models to facilitate such a compatibility. For a given seismicity scenario, the framework identifies the modified stochastic ground motion model that can sufficiently match the prescribed hazard while maintaining similarity to regional physical ground motion model characteristics. This paper extends this effort through a validation study. Suites of recorded and stochastic ground motions, whose spectral acceleration statistics match the mean and variance of target spectra within a period range of interest, are utilized as input to perform response history analysis of inelastic single-degree-of-freedom case-study systems. The resultant engineering demand parameters distributions are then compared to assess the effect of the proposed modification

Modification of stochastic ground motion models for matching target intensity measures

Stochastic ground motion models produce synthetic time‐histories by modulating a white noise sequence through functions that address spectral and temporal properties of the excitation. The resultant ground motions can be then used in simulation‐based seismic risk assessment applications. This is established by relating the parameters of the aforementioned functions to earthquake and site characteristics through predictive relationships. An important concern related to the use of these models is the fact that through current approaches in selecting these predictive relationships, compatibility to the seismic hazard is not guaranteed. This work offers a computationally efficient framework for the modification of stochastic ground motion models to match target intensity measures (IMs) for a specific site and structure of interest. This is set as an optimization problem with a dual objective. The first objective minimizes the discrepancy between the target IMs and the predictions established through the stochastic ground motion model for a chosen earthquake scenario. The second objective constraints the deviation from the model characteristics suggested by existing predictive relationships, guaranteeing that the resultant ground motions not only match the target IMs but are also compatible with regional trends. A framework leveraging kriging surrogate modeling is formulated for performing the resultant multi‐objective optimization, and different computational aspects related to this optimization are discussed in detail. The illustrative implementation shows that the proposed framework can provide ground motions with high compatibility to target IMs with small only deviation from existing predictive relationships and discusses approaches for selecting a final compromise between these two competing objectives

Hazard-compatible modification of stochastic ground motion models

A computationally efficient framework is presented for modification of stochastic ground motion models to establish compatibility with the seismic hazard for specific seismicity scenarios and a given structure/site. The modification pertains to the probabilistic predictive models that relate the parameters of the ground motion model to seismicity/site characteristics. These predictive models are defined through a mean prediction and an associated variance, and both these properties are modified in the proposed framework. For a given seismicity scenario, defined for example by the moment magnitude and source-to-site distance, the conditional hazard is described through the mean and the dispersion of some structure-specific intensity measure(s). Therefore, for both the predictive models and the seismic hazard, a probabilistic description is considered, extending previous work of the authors that had examined description only through mean value characteristics. The proposed modification is defined as a bi-objective optimization. The first objective corresponds to comparison for a chosen seismicity scenario between the target hazard and the predictions established through the stochastic ground motion model. The second objective corresponds to comparison of the modified predictive relationships to the pre-existing ones that were developed considering regional data, and guarantees that the resultant ground motions will have features compatible with observed trends. The relative entropy is adopted to quantify both objectives, and a computational framework relying on kriging surrogate modeling is established for an efficient optimization. Computational discussions focus on the estimation of the various statistics of the stochastic ground motion model output needed for the entropy calculation

A method for determining the suitability of schools as evacuation shelters and aid distribution hubs following disasters: case study from Cagayan de Oro, Philippines

Despite the controversy regarding their use, school buildings are often assigned as emergency evacuation shelters, temporary accommodation and aid distribution hubs following disasters. This paper presents a methodology to compare the relative suitability of different school buildings for these purposes by using the analytical hierarchy process to weight criteria based on the combined opinions of relevant experts and combine these with descriptive scores from surveyed buildings. The aggregated weights show that approximately equal weighting should be given to the hard characteristics (hazard at location and physical vulnerability) and soft characteristics (accessibility, communications, living environment, access to supplies). As well as immediate safety, conditions for inhabitation are important so that displaced persons are not discouraged from evacuating to shelters and shelter life is not detrimental to health and well-being. The study allows an optimal selection of school buildings used as shelters before and after a disaster and highlights where most improvement could be made with relatively little time and resources for both individual buildings and the whole study area. This method was applied to Cagayan de Oro in the Philippines, an area exposed to floods, windstorms and earthquakes, but can be adapted for other local contexts and building types. Among the 38 school buildings surveyed, we identified key areas for improvement as being insufficient pedestrian access for evacuation at night and for those with mobility constraints, and a lack of alternate spaces for evacuee activities leading to interference with education

Simulated ground motions for seismic risk assessment of structures

The recent advances in computational efficiency and the scarcity/absence of recorded ground motions for specific seismicity scenarios have led to an increasing interest in the use of ground motion simulations for seismic hazard analysis, structural demand assessment through response-history analysis, and ultimately seismic risk assessment. Two categories of ground motion simulations, physics-based and stochastic site-based are considered in this study. Physics-based ground motion simulations are generated using algorithms that solve the fault rupture and wave propagation problems and can be used for simulating past and future scenarios. Before being used with confidence, they need to be validated against records from past earthquakes. The first part of the study focuses on the development of rating/testing methodologies based on statistical and information theory measures for the validation of ground motion simulations obtained through an online platform for past earthquake events. The testing methodology is applied in a case-study utilising spectral-shape and duration-related intensity measures (IMs) as proxies for the nonlinear peak and cyclic structural response. Stochastic site-based ground motion simulations model the time-history at a site by fitting a statistical process to ground motion records with known earthquake and site characteristics. To be used in practice, it is important that the output IMs from the developed time-histories are consistent with these prescribed at the site of interest, something that is not necessarily guaranteed by the current models. The second part of the study presents a computationally efficient framework that addresses the modification of stochastic ground motion models for given seismicity scenarios with a dual goal of matching target IMs for specific structures, while preserving desired trends in the physical characteristics of the resultant time-histories. The modification framework is extended to achieve a match to the full probability model of the target IMs. Finally, the proposed modification is validated by comparison to seismic demand of hazard-compatible recorded ground motions. This study shows that ground motion simulation is a promising tool that can be used for many engineering applications