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Ground-motion prediction equations (GMPEs) relate ground-motion intensity measures to variables describing earthquake source, path, and site effects. We select from many available GMPEs those models recommended for use in seismic hazard assessments in the Global Earthquake Model. We present a GMPE selection procedure that evaluates multi-dimensional ground motion trends (e.g., with respect to magnitude, distance and structural period), examines functional forms, and evaluates published quantitative tests of GMPE performance against independent data. Our recommendations include: four models, based principally on simulations, for stable continental regions (SCRs); three empirical models for interface and in-slab subduction zone (SZ) events; and three empirical models for active shallow crustal regions (ACRs). To approximately incorporate epistemic uncertainties, the selection process accounts for alternate representations of key GMPE attributes, such as the rate of distance attenuation, which are defensible from available data. Recommended models for each domain will change over time as additional GMPEs are developed.

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The losses incurred by industrial facilities following catastrophic events can be broadly broken down into property damage and business interruption due to the ensuing downtime. This article describes a generalized probabilistic methodology for estimating facility downtime under multi-hazard scenarios. Since the vulnerability of each components of an industrial facility varies with the types of hazard, it is beneficial to adopt a system-of-systems approach for analyzing such complex facilities under multiple interdependent hazards. In this approach, the complex layout of the facility is first broken down into its constituent components. The component vulnerabilities to different hazards are combined using Boolean logic, assuming their repair time as a common basis for defining damage states of the component. This combination results in multi-hazard fragility functions for each component of the system, which give the probability of damage under combined occurrence of multiple perils. The time to repair a component is expressed probabilistically using restoration functions. Using fault tree analysis, the components' fragility functions and restoration functions are propagated to calculate system-level downtime. We demonstrate the methodology on a case-study power plant to estimate downtime risk under combined earthquake and tsunami hazard.

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