PROBABILISTIC PRE DICTION OF RETROFIT COST F OR MASONRY STRUCTURES

A probabilistic model is deve loped that predicts the retrofit cost for masonry buildings. This model is key in the prioritization of vulner able structures for seismic retrofit. A database of real data for school buildings in Iran is compiled and the Bayesian regression modeling methodology is employed to establish the model. This modeling approa ch emphasizes the comprehensive characterization and modeling of epistemic uncertainties. As a result, the model is updated as new data become available. The explanatory functions of the model are selected in accordance with the mechanics of the problem. An important explanatory function is the amoun t of increase in lateral strength of buildings d ue to retrofit, which is accounted for in such a model for t he first time. The paper presents the data collecti on, model development, insights obtained from the model, annd concludes with a numerical example.

کلیدواژه ها:

Retrofit Cost ، Masonry Buildings ، Probabilistic Models ، Bayesian Regression ، Shotcrete