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Method for Earthquake Motion-Damage Relationships with Application to Reinforced Concrete Frames
The research presented in this report provides a general method for developing relationships between earthquake ground motion and damage. The motion-damage relationships were presented as fragility curves and damage probability matrices. The major components of the methodology consist of: (1) characterization of the potential ground motions, (2) characterization of the nonlinear response of the structure when subjected to extreme dynamic loads, (3) application of the methodology to reinforced concrete frames, (4) sensitivity studies for different structural attributes, and (5) development of a Bayesian technique to update the motion-damage relationships.
Method for Earthquake Motion-Damage Relationships with Application to Reinforced Concrete Frames
The research presented in this report provides a general method for developing relationships between earthquake ground motion and damage. The motion-damage relationships were presented as fragility curves and damage probability matrices. The major components of the methodology consist of: (1) characterization of the potential ground motions, (2) characterization of the nonlinear response of the structure when subjected to extreme dynamic loads, (3) application of the methodology to reinforced concrete frames, (4) sensitivity studies for different structural attributes, and (5) development of a Bayesian technique to update the motion-damage relationships.
Method for Earthquake Motion-Damage Relationships with Application to Reinforced Concrete Frames
A. Singhal (author) / A. S. Kiremidjian (author)
1997
256 pages
Report
No indication
English
Structural Analyses , Reinforced concrete , Earthquake engineering , Ground motion , Dynamic response , Earthquake damage , Damage assessment , Structural failure , Seismic effects , Concrete structures , Structural components , Frames , Fragility , Soil-structure interactions , Monte Carlo method , Gaussian processes , Bayes theorem , Autoregressive processes , Probability , Sensitivity analysis , Mathematical models
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