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    Bayesian Model–Data Fusion for Mechanistic Postearthquake Damage Assessment of Building Structures 

    Source: Journal of Engineering Mechanics:;2016:;Volume ( 142 ):;issue: 009
    Author(s): Kalil Erazo; Eric M. Hernandez
    Publisher: American Society of Civil Engineers
    Abstract: This paper presents a probabilistic framework for estimating seismic-induced damage in partially instrumented buildings. The proposed framework uses acceleration measurements at a limited number of stories and Bayesian ...
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    Uncertainty Quantification of State Estimation in Nonlinear Structural Systems with Application to Seismic Response in Buildings 

    Source: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering:;2016:;Volume ( 002 ):;issue: 003
    Author(s): Kalil Erazo; Eric M. Hernandez
    Publisher: American Society of Civil Engineers
    Abstract: This paper presents the application of Bayesian filtering for the estimation and uncertainty quantification of interstory drifts and shears in partially instrumented buildings. We investigate the performance of four Bayesian ...
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    Uncertainty Quantification of State Estimation in Nonlinear Structural Systems with Application to Seismic Response in Buildings 

    Source: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering:;2016:;Volume ( 002 ):;issue: 003
    Author(s): Kalil Erazo; Eric M. Hernandez
    Publisher: American Society of Civil Engineers
    Abstract: This paper presents the application of Bayesian filtering for the estimation and uncertainty quantification of interstory drifts and shears in partially instrumented buildings. We investigate the performance of four Bayesian ...
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    Parameter Estimation of Stochastic Fractional Dynamic Systems Using Nonlinear Bayesian Filtering System Identification Methods 

    Source: Journal of Engineering Mechanics:;2024:;Volume ( 150 ):;issue: 002:;page 04023117-1
    Author(s): Kalil Erazo; Alberto Di Matteo; Pol Spanos
    Publisher: ASCE
    Abstract: This paper presents the application of nonlinear Bayesian filtering–based system identification (SI) methods when employed to estimate the parameters of stochastic fractional dynamic systems. The objective is to demonstrate ...
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    DSpace software copyright © 2002-2015  DuraSpace
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