Damage Assessment of Seismically Excited Buildings Through Incomplete Measurements

Lin, Chi‐Chang; Lin, Ging‐Long; Hsieh, Kun-Shu

doi:10.1115/1.4027326

Cited by 3 publications

(5 citation statements)

References 20 publications

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“…The FEM of the full-scale three-story frame is simplified as a 3-DOFs shear frame, and the mass of each story for this lumped-mass system is 6000 kg. [70] In FEM, the initial stiffness of each story is 1.2 Â 10 6 N/m. This assumption is based on the trial and error method and inspiration from those values obtained by Xu et al [74] The mass matrix (M) and initial stiffness matrix (K Initial ) is assembled as follows:…”

Section: Comparison Of Computational Time On the Numerical Examplesmentioning

confidence: 99%

“…The uniform weights and total height of the building are 18 tons and 9 m, respectively. [70,72] To induce damage, flanges of two columns were cut, as shown in Figure 5. [71] According to Lin et al, the stiffness reduction factor for the first story is 13%, which means SRF 1 = 0.13.…”

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confidence: 99%

“…[73] The first three natural frequencies for the damaged state are 1.03, 3.16, and 5.09 Hz. [70] Experimental mode shapes are also plotted in Figure 6. The optimization parameters for FEM updating are Search_Agents = 30, and Maxi-mum_ Iterations = 100, and these parameters for damage detection are Search_Agents = 50, and Maximum_ Iterations = 350.…”

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confidence: 99%

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Efficiency of the slime mold algorithm for damage detection of large‐scale structures

Ghannadi

Kourehli

2022

Structural Design Tall Build

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Summary Optimization‐based methods are increasingly being implemented for structural damage detection problems through the minimization of the objective functions based on vibration data. The adopted optimization algorithm and objective function play an important role in the accurate detection and quantification of damages. Meanwhile, the challenge of long computational time is another aspect of structural damage identification problems, especially upon addressing large‐scale structures. In this paper, recently developed optimization techniques called slime mold algorithm (SMA) and marine predators algorithm (MPA) are applied to damage assessment of large‐scale structures for the first time. The performance of these algorithms is compared with those obtained using other well‐known optimization techniques such as ant lion optimizer (ALO), whale optimization algorithm (WOA), and grasshopper optimization algorithm (GOA). Furthermore, the sensitivity of three objective functions based on modal assurance criterion (MAC), modified total modal assurance criterion (MTMAC), and natural frequency vector assurance criterion (NFVAC) are examined. Two numerical studies, including the 53‐bar planar truss and the Guangzhou New TV tower, and a full‐scale three‐story frame as an experimental investigation are conducted to present a statistical comparison. The overall results show that the combination of SMA and objective function based on MTMAC provides an accurate tool for damage identification. However, improved SMA (ISMA) has been introduced to enhance the capability of standard SMA for damage detection, and especially finite element model updating in the experimental example. Five benchmark functions are also used to evaluate the global optimization capacity of ISMA and SMA. The results show that the ISMA has many benefits in terms of tackling global optimization problems. MPA‐MTMAC can provide promising results compared with ALO‐MTMAC, WOA‐MTMAC, and GOA‐MTMAC. However, excessive computation time is a big drawback for MPA. The overall results confirm the perfection of the objective function based on MTMAC compared with two others based on MAC and NFVAC.

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Section: Comparison Of Computational Time On the Numerical Examplesmentioning

confidence: 99%

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confidence: 99%

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Efficiency of the slime mold algorithm for damage detection of large‐scale structures

Ghannadi

Kourehli

2022

Structural Design Tall Build

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“…In real applications, only an incomplete set of recorded time histories are available. This may impair the applicability of the SHM methods and should be considered in practice (Franco et al, 2006; Li et al, 2014; Lus et al, 2003; Lin et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

A novel rapid screening method for health monitoring of building structures from earthquake records

Lin

Wang

Lin

et al. 2019

Advances in Structural Engineering

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This study presents a rapid screening method for health monitoring of building structures based on earthquake records. Compared with conventional damage detection techniques, the rapid screening system with few sensors is more attractive and cost-effective in assessing the global behaviors of a building structure. Only two tri-axial accelerometers are required for a building. One is mounted at the ground level, and another one is mounted at the top floor. First, the relative displacement of top floor to ground is calculated by on-line integration. Then, the diagram of absolute acceleration versus relative displacement of top floor is used to determine the pseudo stiffness of the whole building by linear regression. The decrease of pseudo stiffness denotes the occurrence and degree of damage in the building. A novel real-time damage technique is also proposed to detect nonlinear behavior of a building. A five-story shear-type building under earthquake excitations was illustrated for sensitivity analysis of pseudo stiffness considering different damage cases. Shaking-table-test data of a three-story benchmark building were used to verify the accuracy of the proposed damage assessment technique. In addition, the proposed method was also applied to evaluate a new eight-story residential building equipped with accelerometers in Taipei, Taiwan. Finally, the acceleration response records of a real building, which experienced moderate damages caused by the main shock of 1999 Taiwan Chi-Chi earthquake ( ML = 7.3), were considered to examine the applicability of the proposed method to generate a real-time damage indicator for a building with nonlinear behavior. All of the results show that the proposed method is reliable and effective for rapid diagnosis of building health.

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“…SEREP expansion was used by Zhao and Zhang [12] with the residual force vector used to identify the damage location. Theorizing that the first mode shape dictates behavior of a structure from an earthquake, Lin et al [13] updated a structural model after an earthquake using limited sensors by optimization of the measurements compared to the first mode shape response, and used the updated model to determine the damage to the structure. However, the estimation of unmeasured parameters using measured parameters can lead to error in the analysis, making these methods undesirable for damage quantification.…”

Section: Introductionmentioning

confidence: 99%

Remaining stiffness estimation of buildings using incomplete measurements

Eskew

Jang

2016

Struct. Control Health Monit.

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After hazardous events, it is important to be able to quickly identify the remaining stiffness of affected structures for condition evaluation. Model updating can be used to update structural models to reflect current conditions based upon experimental measurements. Direct model updating is a simple and quick method of damage detection, but does not guarantee physical relevance. Least-squares optimization can be used to accurately identify damage with physical relevance, but needs more measurements then updating parameters in order to produce an accurate solution. However, after an extreme event sensors on the structure may be damaged, creating a scenario with limited measurements which can render optimization techniques incapable of assessing the remaining stiffness. To address this issue, this paper proposes a two-phase method to localize and then quantify the remaining stiffness of the structure. Direct model updating with limited measurements is used to localize potential damage to a subset of parameters, and a least-squares optimization using the localized parameters is used to quantify the remaining stiffness in the structure. Numerical simulations using a simplified model based upon the phase I IASCE-ASCE structural health monitoring benchmark problem with missing first floor sensors have been employed to demonstrate, and experiments using a five-story steel frame structure are conducted to validate the methodology.

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Damage Assessment of Seismically Excited Buildings Through Incomplete Measurements

Cited by 3 publications

References 20 publications

Efficiency of the slime mold algorithm for damage detection of large‐scale structures

Efficiency of the slime mold algorithm for damage detection of large‐scale structures

A novel rapid screening method for health monitoring of building structures from earthquake records

Remaining stiffness estimation of buildings using incomplete measurements

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