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Tuned seismic vulnerability functions The problem: loss modeler can't model an important building feature. Insurers sometimes have more information about building conditions than commercial loss models can handle in a strongly defensible fashion. Modelers may lack adequate historical data to distinguish the effects of important building features. An example is the effect of foundation type on the performance of woodframe buildings. Houses with unbraced cripple walls perform significantly differently from buildings with slab-on-grade construction, braced cripple walls, post-and-pier foundations, etc. The solution: analytically derived seismic vulnerability functions and adjustment factors. We create empirically based analytical seismic vulnerability functions to reflect a specific building and adjustment factors to account for a particular condition in multiple buildings. Our vulnerability functions use either scalar or vector-based hazard measures. We use laboratory test data and a computer model that accounts for important sources of uncertainty, and create analytical seismic vulnerability relationships for buildings with and without various important features. We can create a probabilistic mix of buildings with and without a feature to represent average conditions. The modelers' vulnerability functions--developed using historical loss data or other means--also represent average conditions, and account for claim-adjustment practices, etc. We provide a ratio: analytical vulnerability with the feature to analytical vulnerability under average conditions. The modeler multiplies its empirical average-condition seismic vulnerability function by our analytical adjustment factor and produces a with-feature seismic vulnerability function. The new function both accounts for historical loss data and the theoretical effect of the important feature. Applications
Key Benefits
Available adjustment factors for woodframe construction
Available adjustment factors for steel-frame construction
Other structure types and conditions
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