Impact of structural information fidelity on reduced-order model development for regional risk assessment

Reduced-order models (ROMs) are widely used for seismic vulnerability estimation, both for approximating the response of specific structures as well as for modeling a portfolio of buildings within regional risk assessment applications. There are different ROM modeling approaches with different degrees of complexity, and the modeling choice, as well as the accuracy of the estimated response, naturally depends on the fidelity of the available information for developing the ROM. For regional risk assessment applications, the ROM implementation is commonly established using an automated workflow that leverages generic information about basic building characteristics to derive the mechanical parameters of the simulation models. This paper investigates the influence of information fidelity on the downstream risk analysis when utilizing ROMs in such a context, focusing specifically on moment-resisting frames (MRFs). Initially, a framework for establishing multi-degree-of-freedom (MDoF) ROMs with hysteretic nonlinear behavior is presented, establishing rulesets to derive nominal values of ROM parameters from commonly available building descriptions such as number of stories, story height, design specifications, or structural system type and its material(s) (e.g., reinforced concrete or steel). The rulesets place emphasis on explicitly modeling differences across stories instead of relying on simplified approximations that utilize equivalence to inelastic single-degree-of-freedom systems. The fidelity of the information for developing the ROM is quantified by assigning probability distributions over the aforementioned nominal values, with different degrees of uncertainty across the different parameters. Parametric and global sensitivity analyses are then performed to investigate the importance of this information fidelity. A computational workflow leveraging resampling principles is discussed to promote computational efficiency in these analyses. The results provide unique insights into the parameters of critical importance for establishing ROMs for different MDoF archetypes and offer guidance for the type of data that needs to be collected with higher fidelity (degree of confidence) when deploying ROMs in regional scale seismic risk assessment, in order to improve the prediction accuracy.