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Accurate risk analysis requires representative mathematical models of infrastructure. One of the main challenges in developing mathematical models of infrastructure is selecting the modeling resolution from multiple candidates for the required analyses, each candidate having different computational cost, accuracy, and possibly ability to provide information. The goal of selecting the model resolution is to allocate computational resources to the model that best delivers the desired information with the desired accuracy level. This paper proposes a mathematical formulation to select the appropriate resolution for the modeling of infrastructure. We formulate the model selection as an iterative process until a tradeoff is achieved among accuracy, simplicity, and computational efficiency.To select the appropriate level of resolution, we propose novel metrics that measure the level of agreement between estimates of the quantities of interest computed using different levels of resolution. Specifically, we propose global metrics of accuracy that inform if a model is sufficiently detailed or oversimplified. Likewise, we introduce local metrics of accuracy to inform which parts of the model (e.g., spatial portions of the infrastructure model) need refinements. We illustrate the proposed mathematical formulation by selecting the level of resolution of the water infrastructure of Seaside, Oregon, for the purpose of assessing its functionality after a seismic hazard.

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