Variance Analysis of Strong Motion Attenuation Relationships - 1N01

Project Title—ID Number Variance Analysis of Strong Motion Attenuation Relationships - 1N01
Start/End Dates 10/1/05 – 9/30/06
Funding Source PEER-Caltrans
Project Leader (boldface) and Other Team Members Robb Moss (CalPoly/F)
F=faculty; GS=graduate student; US=undergraduate student; PD=post-doc; I=industrial collaborator; O=other

Project goals and objectives

Quantify measurement uncertainty of input parameters and perform variance analysis using Bayesian regression.

Role of this project in supporting PEER's mission (vision)

This work is to provide an improved assessment of the uncertainty in ground motion estimations for use in seismic hazard analysis and performance based earthquake engineering.

Methodology employed

  1. (1) Evaluate and quantify measurement uncertainty of Mw and Vs.
    • - Identify original independent sources of magnitude estimates. Review methodology for uncertainty assignments.
    • - Develop measurement error models for Mw and Vs using NGA data and source material. Assess the theoretical probability distributions that best fit the uncertainty.
    • - Estimate the respective measurement errors associated with the different Vs tools.
  2. Complete and validate Bayesian regression code.
  3. Perform variance analysis by incorporating measurement uncertainty and using Bayesian regression. Improve characterization of attenuation model uncertainty. Evaluate sensitivity of attenuation model coefficients to Mw and Vs measurement uncertainty.

Brief Description of previous year's achievements, with emphasis on accomplishments during last year (Year 8)

Work will be done in Year 9. Funding is due to arrive soon for summer research season.

Expected milestones & deliverables

  1. Quantify measurement uncertainty of input parameters Mw and Vs.
  2. Assess the impact of measurement uncertainty on attenuation model coefficients and model error for one or more NGA models using the NGA database and Bayesian regression.

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