Nonlinear Earthquake Response Modeling of a Large-Scale Two-Span Concrete Bridge

Johnson, Nathan; Saiidi, Mehdi S.; Sanders, David H.

doi:10.1061/(asce)be.1943-5592.0000009

Cited by 23 publications

(15 citation statements)

References 3 publications

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“…An amount of 280 kip (1,245 kN) of additional mass is also provided on the slab to consider scaling effects. More detailed information about this structure and the related experimental study are available in Johnson et al (2006). Figure 1 shows a rendering of the bridge structure.…”

Section: Experimental Case Studymentioning

confidence: 99%

“…Different levels of shaking amplitude, covering the range of PGA =0.075 × g ∼ 2.11 × g, were conducted on the structure. Intermediate, white‐noise excitations were also applied for system identification purposes (Johnson et al, 2006). Although the specimen underwent these excitations at different times, a combined 390‐seconds time‐history for each record was used in this article.…”

Section: Experimental Case Studymentioning

confidence: 99%

“…Extensive instrumentation consisting of 298 channels (25 for slab displacements, 3 for footing slip, 68 for column curvatures, 15 for column shear, 14 for slab accelerations, 1 for support frame acceleration, 104 for longitudinal reinforcement strain, 56 for transverse reinforcement strain, and 12 for shake table response) were used to record the data at the frequency rate of 100 Hz (Johnson et al, 2006). From a practical point of view, real structures outside of the lab environment do not generally enjoy such a comprehensive level of instrumentation.…”

Section: Experimental Case Studymentioning

confidence: 99%

“… Top view (a) and elevation view (b) of the NEES@Reno bridge, together with selected sensor locations for this study. S1–S5 denote the location of accelerometers on the bridge deck (adapted from Johnson et al, 2006). …”

Section: Experimental Case Studymentioning

confidence: 99%

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Finite Element Model Updating Using Evolutionary Strategy for Damage Detection

Jafarkhani

Masri

2010

Computer-Aided Civil and Infrastructure Engineering

128

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Structural health monitoring through the use of finite element model updating techniques for dispersed civil infrastructures usually deals with minimizing a complex, nonlinear, nonconvex, high-dimensional cost function with several local minima. Hence, stochastic optimization algorithms with promising performance in solving global optimization problems have received considerable attention for finite element model updating purposes in recent years. In this study, the performance of an evolutionary strategy in the finite element model updating approach was investigated for damage detection in a quarter-scale two-span reinforced concrete bridge system which was tested experimentally at the University of Nevada, Reno. The damage sequence in the structure was induced by a range of progressively increasing excitations in the transverse direction of the specimen. Intermediate nondestructive white noise excitations and response measurements were used for system identification and damage detection purposes. It is shown that, when evaluated together with the strain gauge measurements and visual inspection results, the applied finite element model updating algorithm of this article could accurately detect, localize, and quantify the damage in the tested bridge columns throughout the different phases of the experiment.

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Section: Experimental Case Studymentioning

confidence: 99%

Section: Experimental Case Studymentioning

confidence: 99%

Section: Experimental Case Studymentioning

confidence: 99%

Section: Experimental Case Studymentioning

confidence: 99%

See 2 more Smart Citations

Finite Element Model Updating Using Evolutionary Strategy for Damage Detection

Jafarkhani

Masri

2010

Computer-Aided Civil and Infrastructure Engineering

128

View full text Add to dashboard Cite

show abstract

“…Deng and Morcous [29], Chacon and Mirambell [28], Frissen et al [21], Zhou et al [13], Johnson et al [8], Kaviani et al [12] and Ho et al (GT STRUDL Technical Papers) [42], used ANSYS [43], ABAQUS [44], TNO DIANA [45], Strand7 [46], Drain 3DX [47], Opensees [48], ADINA [49] and GT STRUDL [42], respectively, so as to numerically assess RC bridges through the use of different FE models. Commercial software that are referenced in [42][43][44][45][46][47][48][49] have the ability of using 3D FE models that incorporate damage material models.…”

Section: Introductionmentioning

confidence: 99%