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A Predictive Modeling Approach to Estimating Seismic Retrofit Costs.

Juan F Fung1, Siamak Sattar2, David T Butry2

  • 1National Institute of Standards and Technology, 100 Bureau Dr., Mailstop 8603, Gaithersburg, MD 20899.

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This study introduces a method to estimate seismic retrofit costs using historical data and generalized linear models (GLMs). It provides quick, reliable cost predictions for large building portfolios, including uncertainty measures.

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Area of Science:

  • Civil Engineering
  • Structural Engineering
  • Risk Management

Background:

  • Accurate seismic retrofit cost estimation is crucial for managing risks associated with aging infrastructure.
  • Existing methods can be time-consuming or lack the scalability needed for large building portfolios.

Purpose of the Study:

  • To develop a cost-effective methodology for estimating seismic retrofit expenses.
  • To utilize historical data for predictive modeling of retrofit costs.
  • To quantify the uncertainty associated with these cost estimations.

Main Methods:

  • A generalized linear model (GLM) was developed using historical seismic retrofit cost data (FEMA 156).
  • Building characteristics were used as predictors for retrofit costs.
  • Prediction error was analyzed to compare different modeling choices and cost distributions.

Main Results:

  • The GLM provides a practical approach for generating rapid seismic retrofit cost estimates.
  • The methodology offers a quantifiable measure of prediction uncertainty.
  • The choice of cost distribution significantly impacts the final cost estimates.

Conclusions:

  • The proposed methodology offers a valuable tool for decision-makers managing extensive building portfolios.
  • This approach balances accuracy with ease of application for preliminary seismic retrofit cost assessments.
  • Understanding the influence of distribution choice is key for refining cost predictions.