Joel P. Conte

Uncertainty and Sensitivity Analysis of Damage Identification Results Obtained Using Finite Element Model Updating

A full-scale seven-story reinforced concrete shear wall building structure was tested on the UCSD- NEES shake table in the period October 2005-January 2006. The shake table tests were designed so as to damage the building progressively through several historical seis- mic motions reproduced on the shake table. A sensitivity- based finite element (FE) model updating method was used to identify damage in the building. The estimation uncertainty in the damage identification results was ob- served to be significant, which motivated the authors to perform, through numerical simulation, an uncertainty analysis on a set of damage identification results. This study investigates systematically the performance of FE model updating for damage identification. The dam- aged structure is simulated numerically through a change in stiffness in selected regions of a FE model of the shear wall test structure. The uncertainty of the identified damage (location and extent) due to variability of five input factors is quantified through analysis-of-variance

Linear dynamic modeling of a uni‐axial servo‐hydraulic shaking table system

This paper focuses on the development of a linear analytical model (even though servo-hydraulic actuation systems are inherently non-linear, especially for large amplitude simulations — near the performance capacity of the system — linearized models proved experimentally to be quite effective overall in capturing the salient features of shaking table dynamics) of a uni-axial, servo-hydraulic, stroke controlled shaking table system by using jointly structural dynamics and linear control theory. This model incorporates the proportional, integral, derivative, feed-forward, and differential pressure gains of the control system. Furthermore, it accounts for the following physical characteristics of the system: time delay in the servovalve response, compressibility of the actuator fluid, oil leakage through the actuator seals and the dynamic properties of both the actuator reaction mass and test structure or payload. The proposed model, in the form of the total shaking table transfer function (i.e. between commanded and actual table motions), is developed to account for the specific characteristics of the Rice University shaking table. An in-depth sensitivity study is then performed to determine the effects of the table control parameters, payload characteristics, and servovalve time delay upon the total shaking table transfer function. The sensitivity results reveal: (a) a potential strong dynamic interaction between the oil column in the actuator and the payload, and (b) the very important effect of the servovalve time delay upon the total shaking table transfer function. Copyright

System Identification Study of a 7-Story Full-Scale Building Slice Tested on the UCSD-NEES Shake Table

A full-scale 7-story reinforced concrete building slice was tested on the unidirectional University of California-San Diego Net- work for Earthquake Engineering Simulation (UCSD-NEES) shake table during the period from October 2005 to January 2006. A rectangular wall acted as the main lateral force resisting system of the building slice. The shake table tests were designed to damage the building pro- gressively through four historical earthquake records. The objective of the seismic tests was to validate a new displacement-based design methodology for reinforced concrete shear wall building structures. At several levels of damage, ambient vibration tests and low-amplitude white noise base excitation tests were applied to the building, which responded as a quasi-linear system with dynamic parameters evolving as a function of structural damage. Six different state-of-the-art system identification algorithms, including three output-only and three input- output methods were used to estimate the modal parameters (natural frequencies, damping ratios, and mode shapes) at different damage levels based on the response of the building to ambient as well as white noise base excitations, measured using DC-coupled accelerometers. The modal parameters estimated at various damage levels using different system identification methods are compared to (1) validate/ cross-check the modal identification results and study the performance of each of these system identification methods, and to (2) investigate the sensitivity of the identified modal parameters to actual structural damage. For a given damage level, the modal parameters identified using different methods are found to be in good agreement, indicating that these estimated modal parameters are likely to be close to the actual modal parameters of the building specimen. DOI: 10.1061/(ASCE)ST.1943-541X.0000300.

Two-Dimensional Nonlinear Earthquake Response Analysis of a Bridge-Foundation-Ground System

This paper presents a two-dimensional advanced nonlinear FE model of an actual bridge, the Humboldt Bay Middle Channel (HBMC) Bridge, and its response to seismic input motions. This computational model is developed in the new structural analysis software framework OpenSees. The foundation soil is included to incorporate soil-foundation-structure interaction effects. Realistic nonlinear constitutive models for cyclic loading are used for the structural (concrete and reinforcing steel) and soil materials. The materials in the various soil layers are modeled using multi-yield-surface plasticity models incorporating liquefaction effects. Lysmer-type absorbing/transmitting boundaries are employed to avoid spurious wave reflections along the boundaries of the computational soil domain. Both procedures and results of earthquake response analysis are presented. The simulation results indicate that the earthquake response of the bridge is significantly affected by inelastic deformations of the supporting soil medium due to lateral spreading induced by soil liquefaction.

Sensor Network for Structural Health Monitoring of a Highway Bridge

A bridge monitoring TestBed is developed as a research environment for sensor networks and related decision-support technologies. A continuous monitoring system, capable of handling a large number of sensor data channels and three video signals, is deployed on a four-span, 90-m long, reinforced concrete highway bridge. Of interest is the integration of the image and sensor data acquisition into a single computer, thereby providing accurate time synchronization between the response and corresponding traffic loads. Currently, video and acceleration records corresponding to traffic induced vibration are being recorded. All systems operate online via a high-speed wireless Internet network, allowing real-time data transmission. Elements of the above health monitoring framework are presented herein. Integration of these elements into an automated functional system is emphasized. The recorded data are currently being employed for structural system identification via a model-free technique. Effort is also underway to correlate the moving traffic loads with the recorded accelerations. Finally, the TestBed is available as a resource for verification of new sensor technologies, data acquisition/ transmission algorithms, data mining strategies, and for decision-support applications.

Damage Identification of a Composite Beam Using Finite Element Model Updating

The damage identification study presented in this paper leveraged a full-scale sub-component experiment conducted in the Charles Lee Powell Structural Research Laboratories at the University of California, San Diego. As payload project attached to a quasi-static test of a full-scale composite beam, a high-quality set of low-amplitude vibration response data was acquired from the beam at various damage levels. The Eigensystem Realization Algorithm was applied to identify the modal parameters (natural frequencies, damping ratios, displacement and macro-strain mode shapes) of the composite beam based on its impulse responses recorded in its undamaged and various damaged states using accelerometers and long-gage fiber Bragg grating strain sensors. These identified modal parameters are then used to identify the damage in the beam through a finite element model updating procedure. The identified damage is consistent with the observed damage in the composite beam.

Nonstationary ARMA modeling of seismic motions

Abstract Discrete time-varying autoregressive — moving average (ARMA) models are used to describe realistic earthquake ground motion time histories. Both amplitude and frequency nonstationarities are incorporated in the model. An iterative Kalman filtering scheme is introduced to identify the time-varying parameters of an ARMA model from an actual earthquake record. Several model verification tests are performed on the identified model. Applications of these identification and verification procedures are given and show that the proposed models and identification algorithms are able to capture accurately the nonstationary features of real earthquake accelerograms, especially the time-variation of the frequency content. The well-known Kanai-Tajimi earthquake model is covariance equivalent with a subset of the low order ARMA(2,1) model. Using the results and methodology of this study, the parameters of a time-varying Kanai-Tajimi earthquake model can be estimated from a target earthquake record or they can be directly associated with characteristic earthquake features such as predominant frequency and frequency bandwidth.

Modal Identification Study of Vincent Thomas Bridge Using Simulated Wind-Induced Ambient Vibration Data

In this paper, wind-induced vibration response of Vincent Thomas Bridge, a suspension bridge located in San Pedro near Los Angeles, California, is simulated using a detailed three-dimensional finite element model of the bridge and a state-of-the-art stochastic wind excitation model. Based on the simulated wind-induced vibration data, the modal parameters (natural frequencies, damping ratios, and mode shapes) of the bridge are identified using the data-driven stochastic subspace identification method. The identified modal parameters are verified by the computed eigenproperties of the bridge model. Finally, effects of measurement noise on the system identification results are studied by adding zero-mean Gaussian white noise processes to the simulated response data. Statistical properties of the identified modal parameters are investigated under increasing level of measurement noise. The framework presented in this paper will allow to investigate the effects of various realistic damage scenarios in long-span cable-supported (suspension and cable-stayed) bridges on changes in modal identification results. Such studies are required in order to develop robust and reliable vibration-based structural health monitoring methods for this type of bridges, which is a long-term research objective of the authors.

Finite-Element Model Updating for Assessment of Progressive Damage in a 3-Story Infilled RC Frame

AbstractThis paper presents a study on the identification of progressive damage, using an equivalent linear finite-element model updating strategy, in a masonry infilled RC frame that was tested on a shake table. A two-thirds-scale, 3-story, 2-bay, infilled RC frame was tested on the UCSD–NEES shake table to investigate the seismic performance of this type of construction. The shake table tests induced damage in the structure progressively through scaled historical earthquake records of increasing intensity. Between the earthquake tests and at various levels of damage, low-amplitude white-noise base excitations were applied to the infilled RC frame. In this study, the effective modal parameters of the damaged structure have been identified from the white-noise test data with the assumption that it responded in a quasi-linear manner. Modal identification has been performed using a deterministic-stochastic subspace identification method based on the measured input–output data. A sensitivity-based finite-ele...

Long-gage fiber optic Bragg grating strain sensors to monitor civil structures

Fiber optic Bragg gratings packaged in long gage configurations are being used to measure static and dynamic macro-strains in structures and structural models to monitor structural health and detect and identify macro-damage incurred from a seismic event. These long gage sensors are being used to experimentally verify analytical models of small-scale structural models in their pre- and post-damage states using system identification techniques. This fiber optic deformation measurement system could play a significant role in monitoring/recording with a higher level of completeness the actual seismic response of structures and in non-destructive seismic damage assessment techniques based on dynamic signature analysis. This new sensor technology will enable field measurements of the response of real structures to real earthquakes with the same or higher level of detail/resolution as currently in structural testing under controlled laboratory conditions.