# Improving FEMA P-58 non-structural component fragility functions and loss predictions

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## Abstract

Fragility functions are an important tool in earthquake engineering, used to compute the probabilities of different damage states as a function of seismic response. They can be developed for large systems like buildings and bridges, as well as for individual structural and non-structural components, such as those used in the FEMA P-58 Seismic Performance Assessment Procedure. There are currently a number of problems associated with some P-58 non-structural mechanical component fragility functions and related loss predictions, including non-convergence when fitting the fragility functions in some cases and non-monotonic loss predictions. In this study, we recommend improvements to these fragility functions and loss predictions. Firstly, we recommend using the maximum likelihood method to fit the fragility functions to the underlying empirical data. This mitigates the non-convergence problems when fitting and makes predictions that better align with damage observed in past events. To compute predicted losses for anchored mechanical components, it is necessary to additionally consider anchorage damage, which can be predicted using fragility functions based on building code provisions. We recommend refining the current FEMA P-58 method for predicting anchored mechanical component losses, such that component and anchorage damage are calculated directly according to their corresponding fragility functions. The proposed method yields more intuitive loss predictions that vary monotonically with anchorage capacity. It also leads to better predictions of losses relative to damage observed in previous events. If implemented, the recommendations made in this paper would enhance the FEMA P-58 Seismic Performance Assessment Procedure.

## Keywords

Non-structural components Fragility functions Loss predictions FEMA P-58## Notes

### Acknowledgements

We thank an anonymous reviewer for comments that improved the quality of this manuscript. We appreciate helpful feedback received from Dustin Cook, Curt Haselton, Katie Fitzgerald Wade, and Brendon Bradley. We thank Farzad Naeim for providing a copy of the SMIP Information System, and for feedback on typical equipment installation conditions.

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