• Earthquakes and Structures
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• v.14 no.6
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• pp.615-626
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• 2018

The seismic vulnerability of Turkey is relatively high due to its active fault systems with potential to create destructive earthquakes. Thus, reducing the loss of life and property, the number of the earthquake-prone buildings and their retrofit requirements are considerably significant key issues under the scenario earthquakes. The street survey based rapid assessment (SSRA) method can be considered as a powerful tool to determine the seismic vulnerability of building stock of an earthquake-prone city/state. In this study, the seismic vulnerability of the building stock of the Kirikkale province in Turkey is aimed to be estimated adopting the street survey based rapid assessment method (SSRA). For this purpose, central 2074 existing reinforced concrete (R/C) buildings were structurally surveyed with rapid visual site screening and disadvantages such as, the existence of short-column, soft-story, heavy overhangs, pounding effect and local soil conditions were determined for obtaining the structural performance score of each. The results obtained from the study demonstrate that 11-25% of the surveyed buildings in the study region needs to be investigated through more advanced assessment methods. Besides, higher correlation between increasing story number and unsafe/safe building ratio is obtained for the buildings with soft-story parameter than that for those with heavy overhangs and short-column parameters. The conformity of the results of the current study with the previous documented cases of rapid assessment efforts in the recent earthquakes in Turkey shows that the SSRA method for the Kirikkale province performed well, and thus this methodology can be reliably used for similar settlement areas.

• Magazine of the Korea Institute for Structural Maintenance and Inspection
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• v.17 no.4
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• pp.53-60
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• 2013

• Structural Engineering and Mechanics
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• v.78 no.3
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• pp.351-368
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• 2021

This paper, by applying a reliability-based framework, develops seismic vulnerability macrozonation maps for Tehran, the capital and one of the most earthquake-vulnerable city of Iran. Seismic performance assessment of 3-, 4- and 5-story steel moment resisting frames (SMRFs), designed according to ASCE/SEI 41-17 and Iranian Code of Practice for Seismic Resistant Design of Buildings (2800 Standard), is investigated in terms of overall maximum inter-story drift ratio (MIDR) and unit repair cost ratio which is hereafter known as "damage ratio". To this end, Tehran city is first meshed into a network of 66 points to numerically locate low- to mid-rise SMRFs. Active faults around Tehran are next modeled explicitly. Two different combination of faults, based on available seismological data, are then developed to explore the impact of choosing a proper seismic scenario. In addition, soil effect is exclusively addressed. After building analytical models, reliability methods in combination with structure-specific probabilistic models are applied to predict demand and damage ratio of structures in a cost-effective paradigm. Due to capability of proposed methodology incorporating both aleatory and epistemic uncertainties explicitly, this framework which is centered on the regional demand and damage ratio estimation via structure-specific characteristics can efficiently pave the way for decision makers to find the most vulnerable area in a regional scale. This technical basis can also be adapted to any other structures which the demand and/or damage ratio prediction models are developed.

• Magazine of the Korea Concrete Institute
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• v.6 no.5
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• pp.183-192
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• 1994

Seismic safety of RC structure can be evaluated by numerical analysis considering randomness of earthquake motion and hysteretic behavior of reinforced concrete, which is more rational than determirustic analysis. In the safety assessment of aseismatic structures by the deterministic theory, it is not easy to consider th effects of random variables but the reliability theory and random vibration theory are useful to assess seismic safety with considering random effects. This study aims at the evaluation of sesmic damage and risk of the RC frame structure by stochastic response analysis of hysteretic system and then the calculation stages of the prob ability of failure are presented.

• Earthquakes and Structures
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• v.13 no.3
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• pp.323-335
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• 2017

A simplified framework for the probabilistic estimation of economic losses induced by the structural vulnerability in single-story and single-bay precast industrial buildings is presented. The simplifications introduced in the framework are oriented to the definition of an expeditious procedure adoptable by government agencies and insurance companies for preliminary risk assessment. The economic losses are evaluated considering seismic hazard, structural response, damage resulting from the structural vulnerability and only structural-vulnerability-induced e]conomic losses, i.e., structural repair or reconstruction costs (stock and flow costs) and content losses induced by structural collapse. The uncertainties associated with each step are accounted for via Monte Carlo simulations. The estimation results in a probabilistic description of the seismic risk of portal-like industrial buildings, expressed in terms of economic losses for each occurrence (i.e., seismic event) that owners (i.e., insured) and stakeholders can use to make risk management decisions. The outcome may also be useful for the definition of the insurance premiums and the evaluation of the risks and costs for the owner corresponding to the insurance industrial costs. A prototype of a precast concrete industrial building located in Mirandola, Italy, hit by the 2012 Emilia earthquake, is used as an example of the application of the procedure.

• Smart Structures and Systems
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• v.16 no.5
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• pp.873-889
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• 2015

In civil engineering, probabilistic seismic risk assessment is used to predict the economic damage to a lifeline system of possible future earthquakes. The results are used to plan mitigation measures and to strengthen the structures where necessary. Instead, after an earthquake public authorities need mathematical models that compute: the damage caused by the earthquake to the individual vulnerable components and links, and the global behavior of the lifeline system. In this study, a framework that was developed and used for prediction purpose is modified to assess the consequences of an earthquake in quasi real-time after such earthquake happened. This is possible because nowadays entire seismic regions are instrumented with tight networks of strong motion stations, which provide and broadcast accurate intensity measure maps of the event to the public within minutes. The framework uses the broadcasted map and calculates the damage to the lifeline system and its component in quasi real-time. The results give the authorities the most likely status of the system. This helps emergency personnel to deal with the damage and to prioritize visual inspections and repairs. A highway transportation network is used as a test bed but any lifeline system can be analyzed.

• Structural Engineering and Mechanics
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• v.63 no.1
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• pp.47-53
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• 2017

The fundamental goal of this study is to minimize the uncertainty of the median fragility curve and to assess the structural vulnerability under earthquake excitation. Bayesian Inference with Markov Chain Monte Carlo (MCMC) simulation has been presented for efficient collapse response assessment of the independent intake water tower. The intake tower is significantly used as a diversion type of the hydropower station for maintaining power plant, reservoir and spillway tunnel. Therefore, the seismic fragility assessment of the intake tower is a pivotal component for estimating total system risk of the reservoir. In this investigation, an asymmetrical independent slender reinforced concrete structure is considered. The Bayesian Inference method provides the flexibility to integrate the prior information of collapse response data with the numerical analysis results. The preliminary information of risk data can be obtained from various sources like experiments, existing studies, and simplified linear dynamic analysis or nonlinear static analysis. The conventional lognormal model is used for plotting the fragility curve using the data from time history simulation and nonlinear static pushover analysis respectively. The Bayesian Inference approach is applied for integrating the data from both analyses with the help of MCMC simulation. The method achieves meaningful improvement of uncertainty associated with the fragility curve, and provides significant statistical and computational efficiency.

• Earthquakes and Structures
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• v.11 no.3
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• pp.505-516
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• 2016

This paper evaluates the scaling of ground motions recorded from nine intermediate-depth earthquakes produced in the Vrancea seismic zone in Romania. The considered ground motion database consists of 363 horizontal recordings obtained on soil classes B and C (according to Eurocode 8). An analysis of the inter- and intra-event spectral accelerations is performed in order to gain information regarding the magnitude and distance scaling of the Vrancea ground motions. The analyses reveal a significant influence of the earthquake magnitude and focal depth on the distance scaling and different magnitude and distance scaling for the two soil classes. A linear magnitude and distance scaling is inferred from the results for the range of magnitudes $5.2{\leq}M_W{\leq}7.1$. The results obtained are checked through stochastic simulations and the influence of the stress drop and kappa values on the ground motion levels is assessed. In addition, five ground motion models which were tested in other studies using recordings from Vrancea earthquakes are analyzed in order to evaluate their corresponding host stress drop and kappa. The results show generally a direct connection between the host kappa values and the host stress drop values. Moreover, all the ground motion models depict magnitude dependent host kappa and stress drop levels.

• Smart Structures and Systems
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• v.26 no.2
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• pp.175-184
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• 2020

Conventional Monte Carlo simulation-based methods for seismic risk assessment of water networks often require excessive computational time costs due to the hydraulic analysis. In this study, an Artificial Neural Network-based surrogate model was proposed to efficiently evaluate the flow-based system reliability of water distribution networks. The surrogate model was constructed with appropriate training parameters through trial-and-error procedures. Furthermore, a deep neural network with hidden layers and neurons was composed for the high-dimensional network. For network training, the input of the neural network was defined as the damage states of the k-dimensional network facilities, and the output was defined as the network system performance. To generate training data, random sampling was performed between earthquake magnitudes of 5.0 and 7.5, and hydraulic analyses were conducted to evaluate network performance. For a hydraulic simulation, EPANET-based MATLAB code was developed, and a pressure-driven analysis approach was adopted to represent an unsteady-state network. To demonstrate the constructed surrogate model, the actual water distribution network of A-city, South Korea, was adopted, and the network map was reconstructed from the geographic information system data. The surrogate model was able to predict network performance within a 3% relative error at trained epicenters in drastically reduced time. In addition, the accuracy of the surrogate model was estimated to within 3% relative error (5% for network performance lower than 0.2) at different epicenters to verify the robustness of the epicenter location. Therefore, it is concluded that ANN-based surrogate model can be utilized as an alternative model for efficient seismic risk assessment to within 5% of relative error.

• Earthquakes and Structures
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• v.13 no.5
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• pp.497-507
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• 2017

Flooding induced scour has been long recognized as a major hazard to river-crossing bridges. Many studies in recent years have attempted to evaluate the effects of scour on the seismic performance of bridges, and probabilistic frameworks are usually adopted. However, direct and straightforward insight about how foundation scour affects bridges as a type of soil-foundation-structure system is usually understated. In this paper, we provide a comprehensive review of applied methods centering around seismic assessment of scoured bridges considering soil-foundation-structure interaction. When introducing these applied analysis and modeling methods, a simple bridge model is provided to demonstrate the use of these methods as a case study. Particularly, we propose the use of nonlinear modal pushover analysis as a rapid technique to model scoured bridge systems, and numerical validation and application of this procedure are given using the simple bridge model. All methods reviewed in this paper can serve as baseline components for performing probabilistic vulnerability or risk assessment for any river-crossing bridge system subject to flood-induced scour and earthquakes.