Maria Q. Feng

Equivalent Modal Damping of Short-Span Bridges Subjected to Strong Motion

In this paper four different methods are investigated for estimating the equivalent modal damping ratios of a short-span bridge under strong ground motion by considering the energy dissipation at the boundary. The Painter Street Overcrossing (PSO) is investigated because of seismic data availability. Computed responses using the response-spectrum method with the equivalent damping ratios estimates are compared with the recorded responses. The results show that the four methods provide reasonable estimation of equivalent modal damping ratios and that neglecting off-diagonal elements in the damping matrix is the most efficient and practical method. The equivalent damping ratio of the PSO was nearly 25% under an earthquake with peak ground acceleration of 0.55g, which is much higher than the conventional assumption of 5%.

Nondestructive corrosion detection in concrete through integrated heat induction and IR thermography

Steel corrosion in concrete is a main cause of deterioration and early failure of concrete structures. A novel integration of electromagnetic heat induction and infrared (IR) thermography is proposed for nondestructive detection of steel corrosion in concrete, by taking advantage of the difference in thermal characteristics of corroded and non-corroded steel. This paper focuses on experimental investigation of the concept. An inductive heater is developed to remotely heat the steel rebar from concrete surface, which is integrated with an IR camera. Bare rebar and concrete samples with different cover depths are prepared. Each concrete sample is embedded with a single steel rebar in the middle, resulting an identical cover depth from the front and the back surfaces, which enables heat induction from one surface and IR thermogrphay from the other simultaneously. The impressed current method is adopted to induce accelerated corrosion on the rebar. IR video images are recorded during both heating and cooling periods. The test results demonstrate a clear difference in thermal characteristics between corroded and non-corroded samples. The corroded samples show higher rates of heating and cooling as well as a higher peak IR intensity than those of the non-corroded samples. This study demonstrates a potential for nondestructive detection of rebar corrosion in concrete.

Utilization of strong motion data for damage assessment of reinforced concrete bridges

This study investigates the performance of a vibration-based technique for damage assessment of reinforced concrete bridges from non-stationary and incomplete acceleration response measurements during high amplitude earthquakes. The proposed damage assessment technique is targeted to be used in the aftermath of a major earthquake event to rapidly and remotely assess the functionality status of the bridge and identify potential hazards to the public safety. As the first step of the procedure, time-frequency representation of the response of the bridge is achieved by applying stochastic subspace system identification technique to successive and overlapping windows of the response measurements. The timefrequency representation is then used to identify the longest ending segment of the response with relatively stable modal properties. Post-earthquake experimental modal properties of the bridge are subsequently extracted from the identified stable portion of the response. These properties are used to estimate the amount of degradation in stiffness of the structural elements through an optimization-based finite element model updating technique. The Genetic Algorithm optimization technique is used to update the stiffness properties of the structural elements by minimizing the error between analytical and experimental modal properties of the bridge. The proposed damage assessment procedure is applied to experimental data from a large-scale shake table test during which a quarter-scale model of a reinforced concrete bridge was subjected to a series of earthquake and low-amplitude white noise base excitations. The meaningful agreement between the stiffness correction factors identified from both types of motions at the same damage state of the bridge demonstrates that the proposed procedure can effectively be applied for post-earthquake damage assessment of the bridges from nonlinear responses during high amplitude earthquakes.

Damage assessment of the bridge structures using a hybrid optimization strategy

Vibration based damage assessment of structures can be formulated as an optimization problem with the objective of minimizing the error between the measured and simulated responses of the structure by updating analytical model parameters. In this study, genetic algorithm (GA) and pattern search technique are combined in a hybrid optimization framework for finite element (FE) model updating using two objective functions defined in time and modal domains. The proposed model updating techniques have been applied to experimental data recorded during a shake table test on a quarter-scale model of a two span reinforced concrete bridge. The bridge was subjected to a series of seismic base excitations with increasing intensities introducing progressive real damage to the structure. Bridge responses to intermediate low amplitude white noise excitations are used for the purpose of modal identification and damage assessment. The FE model parameters are updated at different stages of the experiment. This study shows that damage throughout the structure can be accurately and consistently detected, located and quantified using the proposed model updating techniques.

Identification and health monitoring of an instrumented building using earthquake response data

This paper describes the identification of finite dimensional, linear, time-invariant models of a 4-story building in the state space representation using multiple data sets of earthquake response. The building, instrumented with 31 accelerometers, is located on the University of California, Irvine campus. Multiple data sets, recorded during the 2005 Yucaipa, 2005 San Clemente, 2008 Chino Hills, and 2009 Inglewood earthquakes, are used for identification and validation. Considering the response of the building as the output and the ground motion as the input, the state space models that represent the underlying dynamics of the building in the discrete-time domain corresponding to each data set are identified. The four state space models identified demonstrate that the response of the building is amplitude dependent with the response frequency, and damping, being dependent on the magnitude of ground excitation. The practical application of this finding is that the consistency of this building response to future earthquakes can be quickly assessed, within the range of ground excitations considered (0.005g - 0.074g), for consistency with prior response - this assessment of consistent response is discussed and demonstrated with reference to the four earthquake events considered in this study. Inclusion of data sets relating to future earthquakes will enable the findings to be extended to a wider range of ground excitation magnitudes.

Long-Term Monitoring and Analysis of a Curved Concrete Box-Girder Bridge

Curved bridges are important components of a highway transportation network for connecting local roads and highways, but very few data have been collected in terms of their field performance. This paper presents two-years monitoring and system identification results of a curved concrete box-girder bridge, the West St. On-Ramp, under ambient traffic excitations. The authors permanently installed accelerometers on the bridge from the beginning of the bridge life. From the ambient vibration data sets collected over the two years, the element stiffness correction factors for the columns, the girder, and boundary springs were identified using the back-propagation neural network. The results showed that the element stiffness values were nearly 10% different from the initial design values. It was also observed that the traffic conditions heavily influence the dynamic characteristics of this curved bridge. Furthermore, a probability distribution model of the element stiffness was established for long-term monitoring and analysis of the bridge stiffness change.

Modal parameter identification of civil engineering structures under operational conditions

This paper deals with the realization of finite dimensional, linear, time-invariant models of structural systems in the state space description from the response (output) of the system. The theory and and underlying principles of two stochastic system identification algorithms are first described. The applications of the algorithms to two civil engineering structures follow the theory. Ambient vibration data collected from a building and a bridge, both are permanently instrumented by accelerometer networks, are used to derive the models. The vibration characteristics, i.e., the frequencies, damping ratios, and associated mode shapes, of the structures are then retrieved from the models. The stochastic system identification algorithms prove to be very effective in identifying the vibration characteristics of the structures.