• Smart Structures and Systems
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• v.9 no.3
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• pp.207-230
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• 2012

Full-scale shake table seismic experiments and low-amplitude vibration tests on a masonry building are carried out to assess its seismic performance as well as study the effectiveness of a new multifunctional textile material for retrofitting masonry structures against earthquakes. The un-reinforced and the retrofitted with glass fiber reinforced polymer (GFRP) strips masonry building was subjected to a series of earthquake excitations of increasing magnitude in order to progressively induce various small, moderate and severe levels of damage to the masonry walls. The performance of the original and retrofitted building states is evaluated. Changes in the dynamic characteristics (lowest four modal frequencies and damping ratios) of the building are used to assess and quantify the damage states of the masonry walls. For this, the dynamic modal characteristics of the structure states after each earthquake event were estimated by performing low-amplitude impulse hammer and sine-sweep forced vibration tests. Comparisons between the modal results calculated using traditional accelerometers and those using Fiber Bragg Grating (FBG) sensors embedded in the reinforcing textile were carried on to investigate the reliability and accuracy of FBG sensors in tracking the dynamic behaviour of the building. The retrofitting actions restored the stiffness characteristics of the reinforced masonry structure to the levels of the original undamaged un-reinforced structure. The results show that despite a similar dynamic behavior identified, corresponding to reduction of the modal frequencies, the un-reinforced masonry building was severely damaged, while the reinforced masonry building was able to withstand, without visual damage, the induced strong seismic excitations. The applied GFRP reinforcement architecture for one storey buildings was experimentally proven reliable for the most severe earthquake accelerations. It was easily placed in a short time and it is a cost effective solution (covering only 20% of the external wall surfaces) when compared to the cost for full wall coverage by GFRPs.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1998.04a
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• pp.309-316
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• 1998

In this paper, a newly derived formulation of a crack detection model is presented and its feasibility to detect cracks in structures is verified experimentally. To meet this objective, the followig approach is utilized. Firstly, the crack detection scheme which consists of the damage localization model and the crack detection model is formulated. Secondly, the feasibility and practicality of the complete procedure of the crack detection model is evaluated by locating and sizing cracks in clamped-clamped beams for which a f3w modal parameters were measured for sixteen uncracked and cracked states. Major results observed from the crack detection exercises include that far most damage cases, the predicted crack locations falls within very close to the inflicted locations of cracks in the test beam and the size of crack values estimated at the predicted locations are very close to the inflicted magnitudes.

• Structural Engineering and Mechanics
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• v.88 no.1
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• pp.13-23
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• 2023

Seismic risk assessment studies are one of the most crucial instruments for mitigating casualties and economic losses. This work utilizes fragility curves to evaluate the seismic risk of single-story precast buildings, which are generally favored in Marmara's organized industrial zones. First, the precast building stock in the region has been categorized into nine sub-classes. Then, seven locations in the Marmara region with a high concentration of industrial activities are considered. Probabilistic seismic hazard assessments were conducted for both the soil-dependent and soil-independent scenarios. Subsequently, damage analysis was performed based on the structural capacity and mean fragility curves. Considering four different consequence models, 630 sub-class-specific loss curves for buildings were obtained. In the current study, it has been determined that the consequence model has a significant impact on the loss curves, hence, average loss curves were computed for each case investigated. In light of the acquired results, it was found that the loss ratio values obtained at different locations within the same region show significant variation. In addition, it was observed that the structural damage states change from serviceable to repairable or repairable to unrepairable. Within the scope of the study, 126 average loss functions were presented that could be easily used by non-experts in earthquake engineering, regardless of structural analysis. These functions, which offer loss ratios for varying hazard levels, are valuable outputs that allow preliminary risk assessment in the region and yield sensible outcomes for insurance activities.

• Earthquakes and Structures
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• v.22 no.5
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• pp.503-515
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• 2022

This paper presents the development of seismic fragility curves for a precast reinforced concrete bridge instrumented with a structural health monitoring (SHM) system. The bridge is located near an active seismic fault in the Dominican Republic (DR) and provides the only access to several local communities in the aftermath of a potential damaging earthquake; moreover, the sample bridge was designed with outdated building codes and uses structural detailing not adequate for structures in seismic regions. The bridge was instrumented with an SHM system to extract information about its state of structural integrity and estimate its seismic performance. The data obtained from the SHM system is integrated with structural models to develop a set of fragility curves to be used as a quantitative measure of the expected damage; the fragility curves provide an estimate of the probability that the structure will exceed different damage limit states as a function of an earthquake intensity measure. To obtain the fragility curves a digital twin of the bridge is developed combining a computational finite element model and the information extracted from the SHM system. The digital twin is used as a response prediction tool that minimizes modeling uncertainty, significantly improving the predicting capability of the model and the accuracy of the fragility curves. The digital twin was used to perform a nonlinear incremental dynamic analysis (IDA) with selected ground motions that are consistent with the seismic fault and site characteristics. The fragility curves show that for the maximum expected acceleration (with a 2% probability of exceedance in 50 years) the structure has a 62% probability of undergoing extensive damage. This is the first study presenting fragility curves for civil infrastructure in the DR and the proposed methodology can be extended to other structures to support disaster mitigation and post-disaster decision-making strategies.

• Computers and Concrete
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• v.8 no.3
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• pp.311-325
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• 2011

Nowadays, many engineers believe that hybrid structures with reinforced concrete central core walls and perimeter steel frames offer an economical method to develop the strength and stiffness required for seismic design. As a result, a variety of such structures have recently been applied in actual construction. However, the performance-based seismic design of such structures has not been investigated systematically. In the performance-based seismic design, quantifying the seismic damage of complete structures by damage indices is one of the fundamental issues. Four damage states and the final softening index at each state for high-rise hybrid structures are suggested firstly in this paper. Based on nonlinear dynamic analysis, the relation of the maximum inter-story drift, the main structural characteristics, and the final softening index is obtained. At the same time, the relation between the maximum inter-story drift and the maximum roof displacement over the height is also acquired. A double-variable index accounting for maximum deformation and cumulative energy is put forward based on the pushover analysis. Finally, a case study is conducted on a high-rise hybrid structure model tested on shaking table before to verify the suggested quantities of damage indices.

• Nuclear Engineering and Technology
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• v.53 no.7
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• pp.2396-2406
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• 2021

The Pacific Earthquake Engineering Research (PEER) Center has been developing a performance-based earthquake engineering (PBEE) methodology, which is based on explicit determination of performance, e.g., monetary losses, in a probabilistic manner where uncertainties in earthquake ground motion, structural response, damage estimation, and losses are explicitly considered. To carry out the PEER PBEE procedure for a component of the nuclear power plant (NPP) such as the cable tray system, hazard curve and spectra were defined for two hazard levels of the ground motions, namely, operation basis earthquake, and safe shutdown earthquake. Accordingly, two sets of spectral compatible ground motions were selected for dynamic analysis of the cable tray system. In general, the PBEE analysis of the cable tray in NPP was introduced where the resulting floor motions from the time history analysis (THA) of the NPP structure should be used as the input motion to the cable tray. However, for simplicity, a finite element model of the cable tray was developed for THA under the effect of the selected ground motions. Based on the structural analysis results, fragility curves were generated in terms of specific engineering demand parameters. Loss analysis was performed considering monetary losses corresponding to the predefined damage states. Then, overall losses were evaluated for different damage groups using the PEER PBEE methodology.

• Structural Engineering and Mechanics
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• v.76 no.3
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• pp.355-365
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• 2020

In this study, considering the hydroelastic response represented by the springing and whipping phenomena, we propose a method of estimating the fatigue damage in the longitudinal connections of ships. First, we screened the design sea states using a load transfer function based on the frequency domain. We then conducted a time domain fluid-structure interaction (FSI) analysis using WISH-FLEX, an in-house code based on the weakly nonlinear approach. To obtain an effective and robust analytical result of the hydroelastic response, we also conducted an experimental model test with a 1/50-scale backbone-based model of a ship, and compared the experimental results with those obtained from the FSI analysis. Then, by combining the results obtained from the hydroelastic response with those obtained from the numerical fatigue analysis, we developed a fatigue damage estimation method. Finally, to demonstrate the effectiveness of the developed method, we evaluated the fatigue strength for the longitudinal connections of the real ship and compared it with the results obtained from the model tests.

• Smart Structures and Systems
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• v.22 no.5
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• pp.561-574
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• 2018

In this paper, for efficiently reducing the computational cost of the model updating during the optimization process of damage detection, the structural response is evaluated using properly trained surrogate model. Furthermore, in practice uncertainties in the FE model parameters and modelling errors are inevitable. Hence, an efficient approach based on Monte Carlo simulation is proposed to take into account the effect of uncertainties in developing a surrogate model. The probability of damage existence (PDE) is calculated based on the probability density function of the existence of undamaged and damaged states. The current work builds a framework for Probability Based Damage Detection (PBDD) of structures based on the best combination of metaheuristic optimization algorithm and surrogate models. To reach this goal, three popular metamodeling techniques including Cascade Feed Forward Neural Network (CFNN), Least Square Support Vector Machines (LS-SVMs) and Kriging are constructed, trained and tested in order to inspect features and faults of each algorithm. Furthermore, three wellknown optimization algorithms including Ideal Gas Molecular Movement (IGMM), Particle Swarm Optimization (PSO) and Bat Algorithm (BA) are utilized and the comparative results are presented accordingly. Furthermore, efficient schemes are implemented on these algorithms to improve their performance in handling problems with a large number of variables. By considering various indices for measuring the accuracy and computational time of PBDD process, the results indicate that combination of LS-SVM surrogate model by IGMM optimization algorithm have better performance in predicting the of damage compared with other methods.

• Wind and Structures
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• v.30 no.4
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• pp.379-392
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• 2020

The paper presents a Life-Cycle Cost-based optimization framework for wind-excited tall buildings equipped with Tuned Mass Dampers (TMDs). The objective is to minimize the Life-Cycle Cost that comprises initial costs of the structure, the control system and costs related to repair, maintenance and downtime over the building's lifetime. The integrated optimization of structural sections and mass ratio of the TMDs is carried out, leading to a set of Pareto optimal solutions. The main advantage of the proposed methodology is that, differently from the traditional optimal design approach, it allows to perform the unified design of both the structure and the control system in a Life Cycle Cost Analysis framework. The procedure quantifies wind-induced losses, related to structural and nonstructural damage, considering the stochastic nature of the loads (wind velocity and direction), the specificity of the structural modeling (e.g., non-shear-type vibration modes and torsional effects) and the presence of the TMDs. Both serviceability and ultimate limit states related to the structure and the TMDs' damage are adopted for the computation of repair costs. The application to a case study tall building allows to demonstrate the efficiency of the procedure for the integrated design of the structure and the control system.

• Smart Structures and Systems
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• v.31 no.4
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• pp.311-323
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• 2023

Ever since ancient times, earthquakes have been a major threat to the civil infrastructures and the safety of human beings. The majority of casualties in earthquake disasters are caused by the damaged civil infrastructures but not by the earthquake itself. Therefore, the efficient and accurate post-earthquake assessment of the conditions of structural damage has been an urgent need for human society. Traditional ways for post-earthquake structural assessment rely heavily on field investigation by experienced experts, yet, it is inevitably subjective and inefficient. Structural response data are also applied to assess the damage; however, it requires mounted sensor networks in advance and it is not intuitional. As many types of damaged states of structures are visible, computer vision-based post-earthquake structural assessment has attracted great attention among the engineers and scholars. With the development of image acquisition sensors, computing resources and deep learning algorithms, deep learning-based post-earthquake structural assessment has gradually shown potential in dealing with image acquisition and processing tasks. This paper comprehensively reviews the state-of-the-art studies of deep learning-based post-earthquake structural assessment in recent years. The conventional way of image processing and machine learning-based structural assessment are presented briefly. The workflow of the methodology for computer vision and deep learning-based post-earthquake structural assessment was introduced. Then, applications of assessment for multiple civil infrastructures are presented in detail. Finally, the challenges of current studies are summarized for reference in future works to improve the efficiency, robustness and accuracy in this field.