Estimation of Soil–Structure Model Parameters for the Millikan Library Building Using a Sequential Bayesian Finite Element Model Updating Technique

We present a finite element model updating technique for soil–structure system identification of the Millikan Library building using the seismic data recorded during the 2002 Yorba Linda earthquake. A detailed finite element (FE) model of the Millikan Library building is developed in OpenSees and up...

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Veröffentlicht in:	Buildings (Basel) Jg. 13; H. 1; S. 28
Hauptverfasser:	Ebrahimian, Hamed, Taha, Abdelrahman, Ghahari, Farid, Asimaki, Domniki, Taciroglu, Ertugrul
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Basel MDPI AG 01.01.2023
Schlagworte:	Bayesian analysis Bayesian estimation Damping Earthquakes Finite element method finite element model updating joint system and input identification Kinematics Libraries Mathematical models Mechanical properties Millikan Library Model updating Modulus of elasticity Parameter identification Parameter uncertainty Probability distribution Seismic activity Seismic analysis Simulation Soil structure Soils soil–structure interaction Stiffness Structural models Subsystems System identification
ISSN:	2075-5309, 2075-5309
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Abstract	We present a finite element model updating technique for soil–structure system identification of the Millikan Library building using the seismic data recorded during the 2002 Yorba Linda earthquake. A detailed finite element (FE) model of the Millikan Library building is developed in OpenSees and updated using a sequential Bayesian estimation approach for joint parameter and input identification. A two-step system identification approach is devised. First, the fixed-base structural model is updated to estimate the structural model parameters (including effective elastic modulus of structural components, distributed floor mass, and Rayleigh damping parameters) and some uncertain components of the foundation-level motion. Then, the identified structural model is used for soil–structure model updating wherein the Rayleigh damping parameters, the stiffness and viscosity of the soil subsystem (modeled using a substructure approach), and the foundation input motions (FIMs) are estimated. The identified model parameters are compared with state-of-practice recommendations. While a specific application is made for the Millikan Library, the present work offers a framework for integrating large-scale FE models with measurement data for model inversion. By utilizing this framework for different civil structures and earthquake records, key structural model parameters can be estimated from the real-world recorded data, which can subsequently be used for assessing and improving, as necessary, state-of-the-art seismic analysis and structural modeling techniques. This paper presents an effort towards using real-world measurements for large-scale FE model updating in the soil and structure, uniform soil time domain for joint parameter and input estimation, and thus paves the way for future applications in system identification, health monitoring, and diagnosis of civil structures.
AbstractList	We present a finite element model updating technique for soil–structure system identification of the Millikan Library building using the seismic data recorded during the 2002 Yorba Linda earthquake. A detailed finite element (FE) model of the Millikan Library building is developed in OpenSees and updated using a sequential Bayesian estimation approach for joint parameter and input identification. A two-step system identification approach is devised. First, the fixed-base structural model is updated to estimate the structural model parameters (including effective elastic modulus of structural components, distributed floor mass, and Rayleigh damping parameters) and some uncertain components of the foundation-level motion. Then, the identified structural model is used for soil–structure model updating wherein the Rayleigh damping parameters, the stiffness and viscosity of the soil subsystem (modeled using a substructure approach), and the foundation input motions (FIMs) are estimated. The identified model parameters are compared with state-of-practice recommendations. While a specific application is made for the Millikan Library, the present work offers a framework for integrating large-scale FE models with measurement data for model inversion. By utilizing this framework for different civil structures and earthquake records, key structural model parameters can be estimated from the real-world recorded data, which can subsequently be used for assessing and improving, as necessary, state-of-the-art seismic analysis and structural modeling techniques. This paper presents an effort towards using real-world measurements for large-scale FE model updating in the soil and structure, uniform soil time domain for joint parameter and input estimation, and thus paves the way for future applications in system identification, health monitoring, and diagnosis of civil structures.
Author	Asimaki, Domniki Ghahari, Farid Taha, Abdelrahman Taciroglu, Ertugrul Ebrahimian, Hamed
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Cites_doi	10.1002/eqe.4290160102 10.1002/stc.3078 10.1785/BSSA0650010013 10.1061/(ASCE)0733-9399(2003)129:12(1380) 10.1002/eqe.4290180403 10.1002/stc.1803 10.1080/00207720903042970 10.1785/0120080333 10.1061/(ASCE)GT.1943-5606.0000430 10.1785/BSSA0680010219 10.1002/eqe.4290100510 10.1002/eqe.4290030203 10.1016/S0267-7261(88)80012-5 10.1016/j.soildyn.2017.10.017 10.1016/j.soildyn.2017.05.034 10.1002/eqe.2532 10.1061/(ASCE)0733-9445(2009)135:1(54) 10.1002/0470045345 10.1016/j.ymssp.2016.02.002 10.1007/978-3-319-52425-2_15 10.1016/S0267-7261(88)80005-8 10.1785/BSSA0770061961 10.1029/2000WR900350 10.1061/(ASCE)EM.1943-7889.0000851 10.1002/stc.424 10.1016/j.soildyn.2016.09.041 10.1061/(ASCE)EM.1943-7889.0001590 10.1115/1.3422711 10.1002/eqe.646 10.1002/stc.2128 10.1785/BSSA0580030891 10.1016/j.ijdrr.2021.102267 10.1193/011613EQS003M 10.1061/(ASCE)0733-9399(1998)124:4(455) 10.1109/MCSE.2011.66
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SubjectTerms	Bayesian analysis Bayesian estimation Damping Earthquakes Finite element method finite element model updating joint system and input identification Kinematics Libraries Mathematical models Mechanical properties Millikan Library Model updating Modulus of elasticity Parameter identification Parameter uncertainty Probability distribution Seismic activity Seismic analysis Simulation Soil structure Soils soil–structure interaction Stiffness Structural models Subsystems System identification
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Title	Estimation of Soil–Structure Model Parameters for the Millikan Library Building Using a Sequential Bayesian Finite Element Model Updating Technique
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