Analysis, Evaluation, and Improvement of Performance-Based Earthquake Engineering Damage and Loss Predictions

Performance-based earthquake engineering (PBEE) has in many ways revolutionized
the thinking about seismic engineering design and acceptable performance of buildings in earthquakes. It is now making its way into commercial engineering design and
risk analysis practice, as engineers aim to design better-performing buildings, and
holders of mortgage or insurance instruments try to better understand the risk they
face from damage to associated buildings. Some parts of the calculations (e.g. structural response) have been extensively assessed and validated. There are few similar
studies, however, that focus on the damage and loss predictions. The purpose of this
dissertation is to address this, by analyzing, evaluating, and improving the damage
and loss predictions. The specific PBEE methodology examined in this dissertation
is the FEMA P-58 Seismic Performance Assessment Procedure.

FEMA P-58 damage and loss predictions are analyzed, to determine how they
are impacted by other parts of the calculations. Firstly, variance-based sensitivity
analyses are conducted to investigate the interaction of loss predictions with different
inputs to the calculations, using two buildings at an example site in downtown Los
Angeles. This type of sensitivity analysis operates within a probabilistic framework,
and measures sensitivity across the whole input space. Of the six inputs considered
in the analyses, it is found that predictions of building repair cost (as a fraction of
replacement value) are most sensitive to shaking intensity and building age, while
building re-occupancy time predictions are most sensitive to shaking intensity and
building lateral system. Secondly, a methodology is developed to quantify the impact
of available structural response data from seismic instrumentation on the quality of
the damage and loss predictions. The methodology is applied to buildings that were instrumented during the 1994 Mw 6.7 Northridge earthquake. The density of instrumentation examined ranges from the case in which all floors are instrumented to that
in which no floors are instrumented and simplified procedures are used to produce
structural response predictions. It is found that the quality of the predictions generally improves as the density of seismic instrumentation increases, but it is not crucial
for the density to be very high to achieve reasonable accuracy in both damage and
loss predictions (although this may depend on the arrangement of instrumentation
within a building).

Loss predictions are evaluated using data observed in previous seismic events, to
understand the degree to which they reflect real-life consequences of earthquakes. A
methodology is developed for evaluating the ability of FEMA P-58 component-level
losses to predict damage observed for groups of buildings. The methodology explicitly
incorporates uncertainties in predictions, and utilizes a ground shaking benchmark to
determine whether the FEMA P-58 loss predictions provide more insight into damage
than variations in ground shaking between buildings. Two sample applications of
the methodology are provided, involving non-structural component damage data for
groups of buildings in the 2011 Mw 6.1 Christchurch earthquake, for which there is
negligible variation in shaking between buildings, and the Northridge earthquake, for
which there is notable variation in shaking between buildings. It is found that FEMA
P-58 non-structural component-level loss predictions perform better overall than the
ground shaking benchmark in both cases. A preliminary evaluation of building-level
losses is also conducted for a sample of buildings in the Christchurch earthquake.
Mean building repair cost predictions are compared with observed building damage,
and mean recovery time predictions are compared with closure times reported by
tenants. Both types of building-level loss predictions are found to generally align
with the observed data, despite limitations of the information used to produce the
predictions.

Finally, this dissertation includes a number of recommendations for improving
non-structural mechanical component fragility functions and associated loss predictions used in FEMA-58 calculations. The fitting technique currently used for the functions does not converge in some cases, and the methodology used to predict anchored mechanical component losses can lead to some unexpected results, such as
non-smooth variation of repair costs with anchorage capacity. An alternative statistical technique is proposed for fitting the fragility functions that mitigates the
non-convergence problems when fitting and makes predictions that better align with
damage observed in past events. A more intuitive methodology for predicting anchored mechanical component losses is suggested, which leads to loss predictions that
vary monotonically as a function of anchorage capacity and better correspond with
damage observed in past events.

The findings of this dissertation help to enhance understanding of, and improve,
the damage and loss predictions used in the FEMA P-58 seismic performance assessment procedure. They ultimately enable various stakeholders, such as building
owners, design professionals, lenders, and insurers, to make more informed decisions
about seismic risk.