• Title/Summary/Keyword: Structural Uncertainty

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Structural health monitoring of Canton Tower using Bayesian framework

  • Kuok, Sin-Chi;Yuen, Ka-Veng
    • Smart Structures and Systems
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    • v.10 no.4_5
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    • pp.375-391
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    • 2012
  • This paper reports the structural health monitoring benchmark study results for the Canton Tower using Bayesian methods. In this study, output-only modal identification and finite element model updating are considered using a given set of structural acceleration measurements and the corresponding ambient conditions of 24 hours. In the first stage, the Bayesian spectral density approach is used for output-only modal identification with the acceleration time histories as the excitation to the tower is unknown. The modal parameters and the associated uncertainty can be estimated through Bayesian inference. Uncertainty quantification is important for determination of statistically significant change of the modal parameters and for weighting assignment in the subsequent stage of model updating. In the second stage, a Bayesian model updating approach is utilized to update the finite element model of the tower. The uncertain stiffness parameters can be obtained by minimizing an objective function that is a weighted sum of the square of the differences (residuals) between the identified modal parameters and the corresponding values of the model. The weightings distinguish the contribution of different residuals with different uncertain levels. They are obtained using the Bayesian spectral density approach in the first stage. Again, uncertainty of the stiffness parameters can be quantified with Bayesian inference. Finally, this Bayesian framework is applied to the 24-hour field measurements to investigate the variation of the modal and stiffness parameters under changing ambient conditions. Results show that the Bayesian framework successfully achieves the goal of the first task of this benchmark study.

Investigation of modal identification and modal identifiability of a cable-stayed bridge with Bayesian framework

  • Kuok, Sin-Chi;Yuen, Ka-Veng
    • Smart Structures and Systems
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    • v.17 no.3
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    • pp.445-470
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    • 2016
  • In this study, the Bayesian probabilistic framework is investigated for modal identification and modal identifiability based on the field measurements provided in the structural health monitoring benchmark problem of an instrumented cable-stayed bridge named Ting Kau Bridge (TKB). The comprehensive structural health monitoring system on the cable-stayed TKB has been operated for more than ten years and it is recognized as one of the best test-beds with readily available field measurements. The benchmark problem of the cable-stayed bridge is established to stimulate investigations on modal identifiability and the present paper addresses this benchmark problem from the Bayesian prospective. In contrast to deterministic approaches, an appealing feature of the Bayesian approach is that not only the optimal values of the modal parameters can be obtained but also the associated estimation uncertainty can be quantified in the form of probability distribution. The uncertainty quantification provides necessary information to evaluate the reliability of parametric identification results as well as modal identifiability. Herein, the Bayesian spectral density approach is conducted for output-only modal identification and the Bayesian model class selection approach is used to evaluate the significance of different modes in modal identification. Detailed analysis on the modal identification and modal identifiability based on the measurements of the bridge will be presented. Moreover, the advantages and potentials of Bayesian probabilistic framework on structural health monitoring will be discussed.

Concurrent topology optimization of composite macrostructure and microstructure under uncertain dynamic loads

  • Cai, Jinhu;Yang, Zhijie;Wang, Chunjie;Ding, Jianzhong
    • Structural Engineering and Mechanics
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    • v.81 no.3
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    • pp.267-280
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    • 2022
  • Multiscale structure has attracted significant interest due to its high stiffness/strength to weight ratios and multifunctional performance. However, most of the existing concurrent topology optimization works are carried out under deterministic load conditions. Hence, this paper proposes a robust concurrent topology optimization method based on the bidirectional evolutionary structural optimization (BESO) method for the design of structures composed of periodic microstructures subjected to uncertain dynamic loads. The robust objective function is defined as the weighted sum of the mean and standard deviation of the module of dynamic structural compliance with constraints are imposed to both macro- and microscale structure volume fractions. The polynomial chaos expansion (PCE) method is used to quantify and propagate load uncertainty to evaluate the objective function. The effective properties of microstructure is evaluated by the numerical homogenization method. To release the computation burden, the decoupled sensitivity analysis method is proposed for microscale design variables. The proposed method is a non-intrusive method, and it can be conveniently extended to many topology optimization problems with other distributions. Several numerical examples are used to validate the effectiveness of the proposed robust concurrent topology optimization method.

Robust seismic retrofit design framework for asymmetric soft-first story structures considering uncertainties

  • Assefa Jonathan Dereje;Jinkoo Kim
    • Structural Engineering and Mechanics
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    • v.86 no.2
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    • pp.249-260
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    • 2023
  • The uncertainties involved in structural performances are of importance when the optimum number and property of seismic retrofit devices are determined. This paper proposes a seismic retrofit design framework for asymmetric soft-first-story buildings, considering uncertainties in the soil condition and seismic retrofit device. The effect of the uncertain parameters on the structural performance is used to find a robust and optimal seismic retrofit solution. The framework finds a robust and optimal seismic retrofit solution by finding the optimal locations and mechanical properties of the seismic retrofit device for different realizations of the uncertain parameters. The structural performance for each realization is computed to evaluate the effect of the uncertainty parameters on the seismic performance. The framework utilizes parallel processing to decrease the computationally intensive nonlinear dynamic analysis time. The framework returns a robust design solution that satisfies the given limit state for every realization of the uncertain parameters. The proposed framework is applied to the seismic retrofit design of a five-story asymmetric soft-first-story case study structure retrofitted with a viscoelastic damper. Robust optimal parameters for retrofitting a structure to satisfy the limit state for the different realizations of the uncertain parameter are found using the proposed framework. According to the performance evaluation results of the retrofitted structure, the developed framework is proved effective in the seismic retrofit of the asymmetric structure with inherent uncertainties.

Performance Evaluation of NDE Methods in Condition Assessment of Structural Elements (구조물 진단에 있어 비파괴 시험법의 성능평가)

  • Shim, Hyung Seop;Kang, Bo Soon
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.11 no.3
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    • pp.167-175
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    • 2007
  • The relations between data from test methods and conditions in structural elements are considered. NDE(Nondestructive Evaluation) methods are joint application of a test and a basis for interpretation of data obtained in the test. Correct assessments of conditions of elements depend on the inaccuracy and variability in the test data and on the uncertainty of correlations between attributes(what is measured) and conditions(what is sought in the inspection). A full description of the performance of NDE methods considers the relation of test data to condition of elements. The quality of the test data itself is important, but equally important is the interpretation that occurs after the test. To make the decision of the performance of NDE methods, this paper presents mathematical basis to measure the reliability of NDE methods.

Inspection of Structural Elements Using NDE (비파괴 시험을 이용한 RC 구조물 상태진단)

  • Shim, Hyung-Seop
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.13 no.5 s.57
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    • pp.101-108
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    • 2009
  • Mathematical basis of interpretation of data from nondestructive evaluation (NDE) methods in condition assessment of structures is presented. In structural inspection with NDE methods, NDE data are not directly used for the condition assessment. Instead, NDE data must be interpreted as condition of inspected element. Correct assessments of conditions depend on many factors such as the inaccuracy and the variability in NDE measurements and the uncertainty in correlation between attributes (what is measured) and conditions (what is sought in the inspection). A full description of the performance of NDE methods considers the relation of test data to conditions of elements. The quality of the test itself is important, but equally important is the interpretation that occurs after the test. The effects of variability in test data and uncertainty in correlations of attributes and conditions are presented in three examples of field testing methods.

New fuzzy method in choosing Ground Motion Prediction Equation (GMPE) in probabilistic seismic hazard analysis

  • Mahmoudi, Mostafa;Shayanfar, MohsenAli;Barkhordari, Mohammad Ali;Jahani, Ehsan
    • Earthquakes and Structures
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    • v.10 no.2
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    • pp.389-408
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    • 2016
  • Recently, seismic hazard analysis has become a very significant issue. New systems and available data have been also developed that could help scientists to explain the earthquakes phenomena and its physics. Scientists have begun to accept the role of uncertainty in earthquake issues and seismic hazard analysis. However, handling the existing uncertainty is still an important problem and lack of data causes difficulties in precisely quantifying uncertainty. Ground Motion Prediction Equation (GMPE) values are usually obtained in a statistical method: regression analysis. Each of these GMPEs uses the preliminary data of the selected earthquake. In this paper, a new fuzzy method was proposed to select suitable GMPE at every intensity (earthquake magnitude) and distance (site distance to fault) according to preliminary data aggregation in their area using ${\alpha}$ cut. The results showed that the use of this method as a GMPE could make a significant difference in probabilistic seismic hazard analysis (PSHA) results instead of selecting one equation or using logic tree. Also, a practical example of this new method was described in Iran as one of the world's earthquake-prone areas.

Probabilistic sensitivity of base-isolated buildings to uncertainties

  • Gazi, Hatice;Alhan, Cenk
    • Smart Structures and Systems
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    • v.22 no.4
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    • pp.441-457
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    • 2018
  • Characteristic parameter values of seismic isolators deviate from their nominal design values due to uncertainties and/or errors in their material properties and element dimensions, etc. Deviations may increase over service life due to environmental effects and service conditions. For accurate evaluation of the seismic safety level, all such effects, which would result in deviations in the structural response, need to be taken into account. In this study, the sensitivity of the probability of failure of the structures equipped with nonlinear base isolation systems to the uncertainties in various isolation system characteristic parameters is investigated in terms of various isolation system and superstructure response parameters in the context of a realistic three-dimensional base-isolated building model via Monte Carlo Simulations. The inherent record-to-record variability nature of the earthquake ground motions is also taken into account by carrying out analyses for a large number of ground motion records which are classified as those with and without forward-directivity effects. Two levels of nominal isolation periods each with three different levels of uncertainty are considered. Comparative plots of cumulative distribution functions and related statistical evaluation presented here portray the potential extent of the deviation of the structural response parameters resulting from the uncertainties and the uncertainty levels considered, which is expected to be useful for practicing engineers in evaluating isolator test results for their projects.

Multiple failure criteria-based fragility curves for structures equipped with SATMDs

  • Bakhshinezhad, Sina;Mohebbi, Mohtasham
    • Earthquakes and Structures
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    • v.17 no.5
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    • pp.463-475
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    • 2019
  • In this paper, a procedure to develop fragility curves of structures equipped with semi-active tuned mass dampers (SATMDs) considering multiple failure criteria has been presented while accounting for the uncertainties of the input excitation, structure and control device parameters. In this procedure, Latin hypercube sampling (LHS) method has been employed to generate 30 random SATMD-structure systems and nonlinear incremental dynamic analysis (IDA) has been conducted under 20 earthquakes to determine the structural responses, where failure probabilities in each intensity level have been evaluated using Monte Carlo simulation (MCS) method. For numerical analysis, an eight-story nonlinear shear building frame with bilinear hysteresis material behavior has been used. Fragility curves for the structure equipped with optimal SATMDs have been developed considering single and multiple failure criteria for different performance levels and compared with that of uncontrolled structure as well as structure controlled using passive tuned mass damper (TMD). Numerical analysis has shown the capability of SATMDs in significant enhancement of the seismic fragility of the nonlinear structure. Also, considering multiple failure criteria has led to increasing the fragility of the structure. Moreover, it is observed that the influence of the uncertainty of input excitation with respect to the other uncertainties is considerable.

Correlation between chloride-induced corrosion initiation and time to cover cracking in RC Structures

  • Hosseini, Seyed Abbas;Shabakhty, Naser;Mahini, Seyed Saeed
    • Structural Engineering and Mechanics
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    • v.56 no.2
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    • pp.257-273
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    • 2015
  • Numerical value of correlation between effective parameters in the strength of a structure is as important as its stochastic properties in determining the safety of the structure. In this article investigation is made about the variation of coefficient of correlation between effective parameters in corrosion initiation time of reinforcement and the time of concrete cover cracking in reinforced concrete (RC) structures. Presence of many parameters and also error in measurement of these parameters results in uncertainty in determination of corrosion initiation and the time to crack initiation. In this paper, assuming diffusion process as chloride ingress mechanism in RC structures and considering random properties of effective parameters in this model, correlation between input parameters and predicted time to corrosion is calculated using the Monte Carlo (MC) random sampling. Results show the linear correlation between corrosion initiation time and effective input parameters increases with increasing uncertainty in the input parameters. Diffusion coefficient, concrete cover, surface chloride concentration and threshold chloride concentration have the highest correlation coefficient respectively. Also the uncertainty in the concrete cover has the greatest impact on the coefficient of correlation of corrosion initiation time and the time of crack initiation due to the corrosion phenomenon.