Structural health monitoring (SHM) has gained in popularity in recent years since it can assess the performance and condition of instrumented structures in real time and provide valuable information to the asset's manager and owner. Operational modal analysis plays an important role in SHM and it involves the determination of natural frequencies, damping ratios and mode shapes of a constructed structure based on measured dynamic data. This paper presents the operational modal analysis and seismic response characterization of the Tsing Ma Suspension Bridge of 2,160 m long subjected to different earthquake events. Three kinds of events, i.e., short-distance, middle-distance and long-distance earthquakes are taken into account. A fast Bayesian modal identification method is used to carry out the operational modal analysis. The modal properties of the bridge are identified and compared by use of the field monitoring data acquired before and after the earthquake for each type of the events. Research emphasis is given on identifying the predominant modes of the seismic responses in the deck during short-distance, middle-distance and long-distance earthquakes, respectively, and characterizing the response pattern of various structural portions (deck, towers, main cables, etc.) under different types of earthquakes. Since the bridge is over 2,000 m long, the seismic wave would arrive at the tower/anchorage basements of the two side spans at different time instants. The behaviors of structural dynamic responses on the Tsing Yi side span and on the Ma Wan side span under each type of the earthquake events are compared. The results obtained from this study would be beneficial to the seismic design of future long-span bridges to be built around Hong Kong (e.g., the Hong Kong-Zhuhai-Macau Bridge).
The accuracy of the 30% and SRSS rules, commonly used to estimate the combined response of structures, and some related issues, are studied. For complex systems and earthquake loading, the principal components give the maximum seismic response. Both rules underestimate the axial load by about 10% and the COV of the underestimation is about 20%. Both rules overestimate the base shear by about 10%. The uncertainty in the estimation is much larger for axial load than for base shear, and, for axial load, it is much larger for inelastic than for elastic behavior. The effect of individual components may be highly correlated, not only for normal components, but also for totally uncorrelated components. The rules are not always inaccurate for large values of correlation coefficients of the individual effects, and small values of such coefficients are not always related to an accurate estimation of the response. Only for perfectly uncorrelated harmonic excitations and elastic analysis of SDOF systems, the individual effects of the components are uncorrelated and the rules accurately estimate the combined response. In the general case, the level of underestimation or overestimation depends on the degree of correlation of the components, the type of structural system, the response parameter, the location of the structural member and the level of structural deformation. The codes should be more specific regarding the application of these rules. If the percentage rule is used for MDOF systems and earthquake loading, at least a value of 45% should be used for the combination factor.
Finite element analysis is one of the important methods to study the structural performance. Due to the simplification, discretization and error of structural parameters, numerical model errors always exist. Besides, structural characteristics may also change because of material aging, structural damage, etc., making the initial finite element model cannot simulate the operational response of the structure accurately. Based on Bayesian methods, the initial model can be updated to obtain a more accurate numerical model. This paper presents the work on the field test, modal identification and model updating of a Chinese reinforced concrete pagoda. Based on the ambient vibration test, the acceleration response of the structure under operational environment was collected. The first six translational modes of the structure were identified by the enhanced frequency domain decomposition method. The initial finite element model of the pagoda was established, and the elastic modulus of columns, beams and slabs were selected as model parameters to be updated. Assuming the error between the measured mode and the calculated one follows a Gaussian distribution, the posterior probability density function (PDF) of the parameter to be updated is obtained and the uncertainty is quantitatively evaluated based on the Bayesian statistical theory and the Metropolis-Hastings algorithm, and then the optimal values of model parameters can be obtained. The results show that the difference between the calculated frequency of the finite element model and the measured one is reduced, and the modal correlation of the mode shape is improved. The updated numerical model can be used to evaluate the safety of the structure as a benchmark model for structural health monitoring (SHM).
Finite element model updating is very effective procedure to determine the uncertainty parameters in structural model and minimize the differences between experimentally and numerically identified dynamic characteristics. This procedure can be practiced with manual and automatic model updating procedures. The manual model updating involves manual changes of geometry and analyses parameters by trial and error, guided by engineering judgement. Besides, the automated updating is performed by constructing a series of loops based on optimization procedures. This paper addresses the ambient vibration based finite element model updating of long span reinforced concrete highway bridges using manual model updating procedure. Birecik Highway Bridge located on the $81^{st}km$ of Şanliurfa-Gaziantep state highway over Firat River in Turkey is selected as a case study. The structural carrier system of the bridge consists of two main parts: Arch and Beam Compartments. In this part of the paper, the arch compartment is investigated. Three dimensional finite element model of the arch compartment of the bridge is constructed using SAP2000 software to determine the dynamic characteristics, numerically. Operational Modal Analysis method is used to extract dynamic characteristics using Enhanced Frequency Domain Decomposition method. Numerically and experimentally identified dynamic characteristics are compared with each other and finite element model of the arch compartment of the bridge is updated manually by changing some uncertain parameters such as section properties, damages, boundary conditions and material properties to reduce the difference between the results. It is demonstrated that the ambient vibration measurements are enough to identify the most significant modes of long span highway bridges. Maximum differences between the natural frequencies are reduced averagely from %49.1 to %0.6 by model updating. Also, a good harmony is found between mode shapes after finite element model updating.
Comprehensive understanding of the flood risk assessments via frequency analysis often demands multivariate designs under the different notations of return periods. Flood is a tri-variate random consequence, which often pointing the unreliability of univariate return period and demands for the joint dependency construction by accounting its multiple intercorrelated flood vectors i.e., flood peak, volume & durations. Selecting the most parsimonious probability functions for demonstrating univariate flood marginals distributions is often a mandatory pre-processing desire before the establishment of joint dependency. Especially under copulas methodology, which often allows the practitioner to model univariate marginals separately from their joint constructions. Parametric density approximations often hypothesized that the random samples must follow some specific or predefine probability density functions, which usually defines different estimates especially in the tail of distributions. Concentrations of the upper tail often seem interesting during flood modelling also, no evidence exhibited in favours of any fixed distributions, which often characterized through the trial and error procedure based on goodness-of-fit measures. On another side, model performance evaluations and selections of best-fitted distributions often demand precise investigations via comparing the relative sample reproducing capabilities otherwise, inconsistencies might reveal uncertainty. Also, the strength & weakness of different fitness statistics usually vary and having different extent during demonstrating gaps and dispensary among fitted distributions. In this literature, selections efforts of marginal distributions of flood variables are incorporated by employing an interactive set of parametric functions for event-based (or Block annual maxima) samples over the 50-years continuously-distributed streamflow characteristics for the Kelantan River basin at Gulliemard Bridge, Malaysia. Model fitness criteria are examined based on the degree of agreements between cumulative empirical and theoretical probabilities. Both the analytical as well as graphically visual inspections are undertaken to strengthen much decisive evidence in favour of best-fitted probability density.
Ramos, Salvador;Arredondo, Cesar;Reinoso, Eduardo;Leonardo-Suarez, Miguel;Torres, Marco A.
Earthquakes and Structures
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제20권1호
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pp.71-86
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2021
This paper focuses on the development and assessment of the expected damage for the rocking response of rigid anchored blocks, with irregular geometry and non-uniform mass distribution, considering the site conditions and the seismicity of Mexico City. The non-linear behavior of the restrainers is incorporated to evaluate the pure tension and tension-shear failure mechanisms. A probabilistic framework is performed covering a wide range of block sizes, slenderness ratios and eccentricities using physics-based ground motion simulation. In order to incorporate the uncertainties related to the propagation of far-field earthquakes with a significant contribution to the seismic hazard at study sites, it was simulated a set of scenarios using a stochastic summation methods of small-earthquakes records, considered as Empirical Green's Function (EGFs). As Engineering Demand Parameter (EDP), the absolute value of the maximum block rotation normalized by the body slenderness, as a function of the peak ground acceleration (PGA) is adopted. The results show that anchorages are more efficient for blocks with slenderness ratio between two and three, while slenderness above four provide a better stability when they are not restrained. Besides, there is a range of peak intensities where anchored blocks located in soft soils are less vulnerable with respect to those located in firm soils. The procedure used in here allows to take decisions about risk, reliability and resilience assessment of different types of contents, and it is easily adaptable to other seismic environments.
Under a severe environment of multiple hazards such as earthquakes and winds, the life-cycle performance of engineering structures may inevitably be deteriorated due to the fatigue effect caused by long-term exposure to wind loads, which would further increase the structural vulnerability to earthquakes. This paper presents a framework for evaluating the lifetime structural seismic performance under the effect of wind-induced fatigue considering different sources of uncertainties. The seismic behavior of a high-rise steel-concrete composite frame with buckling-restrained braces (FBRB) during its service life is systematically investigated using the proposed approach. Recorded field data for the wind hazard of Fuzhou, Fujian Province of China from Jan. 1, 1980 to Mar. 31, 2019 is collected, based on which the distribution of wind velocity is constructed by the Gumbel model after comparisons. The OpenSees platform is employed to establish the numerical model of the FBRB and conduct subsequent numerical computations. Allowed for the uncertainties caused by the wind generation and structural modeling, the final annual fatigue damage takes the average of 50 groups of simulations. The lifetime structural performance assessments, including static pushover analyses, nonlinear dynamic time history analyses and fragility analyses, are conducted on the time-dependent finite element (FE) models which are modified in lines with the material deterioration models. The results indicate that the structural performance tends to degrade over time under the effect of fatigue, while the influencing degree of fatigue varies with the duration time of fatigue process and seismic intensity. The impact of wind-induced fatigue on structural responses and fragilities are explicitly quantified and discussed in details.
Natural hazards like earthquakes, high winds, and tsunami are a threat all the time for multi-story structures. The environmental forces cannot be clogged but the structures can be prevented from these natural hazards by using protective systems. The structural control can be achieved by using protective systems like the passive, active, semi-active, and hybrid protective systems; but the semi-active protective system has gained importance because of its adaptability to the active systems and reliability of the passive systems. Therefore, a semi-active protective system for the earthquake forces has been adopted in this work. Magneto-Rheological (MR) damper is used in the structure as a semi-active protective system; which is connected to the current driver and proposed controller. The Proportional Integral Derivative (PID) controller and reliable PID controller are two proposed controllers, which will actuate the MR damper and the desired force is generated to mitigate the vibration of the structural response subjected to the earthquake. PID controller and reliable PID controller are designed and tuned using Ziegler-Nichols tuning technique along with the MR damper simulated in Simulink toolbox and MATLAB to obtain the reduced vibration in a three-story benchmark structure. The earthquake is considered to be uncertain; where the proposed control algorithm works well during the presence of earthquake; this paper considers robustness to provide satisfactory resilience against this uncertainty. In this work, two different earthquakes are considered like El-Centro and Northridge earthquakes for simulation with different controllers. In this paper performances of the structure with and without two controllers are compared and results are discussed.
Ma, Juan;Yue, Peng;Du, Wenyi;Dai, Changping;Wriggers, Peter
Structural Engineering and Mechanics
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제83권3호
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pp.293-304
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2022
In this work, a novel reliability approach for combined high and low cycle fatigue (CCF) estimation is developed by combining active learning strategy with least squares support vector machines (LS-SVM) (named as ALS-SVM) surrogate model to address the multi-resources uncertainties, including working loads, material properties and model itself. Initially, a new active learner function combining LS-SVM approach with Monte Carlo simulation (MCS) is presented to improve computational efficiency with fewer calls to the performance function. To consider the uncertainty of surrogate model at candidate sample points, the learning function employs k-fold cross validation method and introduces the predicted variance to sequentially select sampling. Following that, low cycle fatigue (LCF) loads and high cycle fatigue (HCF) loads are firstly estimated based on the training samples extracted from finite element (FE) simulations, and their simulated responses together with the sample points of model parameters in Coffin-Manson formula are selected as the MC samples to establish ALS-SVM model. In this analysis, the MC samples are substituted to predict the CCF reliability of turbine blades by using the built ALS-SVM model. Through the comparison of the two approaches, it is indicated that the reliability model by linear cumulative damage rule provides a non-conservative result compared with that by the proposed one. In addition, the results demonstrate that ALS-SVM is an effective analysis method holding high computational efficiency with small training samples to gain accurate fatigue reliability.
Surface subsidence caused by mining subsidence has an impact on neighboring structures and utilities. In other words, subsurface voids created by mining or tunneling activities induce soil movement, exposing buildings to physical and/or functional destruction. Soil-structure is evaluated employing probability distribution laws to account for their uncertainty and complexity to estimate structural vulnerability. In this study, to investigate the displacement field and surface settlement profile caused by mining subsidence, on the basis of a Winklersoil model, analytical equations for the moment-rotation response ofsoil during mining induced ground movements are developed. To define the full static moment-rotation response, an equation for the uplift-yield state is constructed and integrated with equations for the uplift- and yield-only conditions. The constructed model's findings reveal that the inverse of the factor of safety (x) has a considerable influence on the moment-rotation curve. The maximal moment-rotation response of the footing is defined by X = 0:6. Despite the use of Winkler model, the computed moment-rotation response results derived from the literature were analyzed through the ELM-SVM hybrid of Extreme Learning Machine (ELM) and Support Vector Machine (SVM). Also, Monte Carlo simulations are used to apply continuous random parameters to assess the transmission of ground motions to structures. Following the findings of RMSE and R2, the results show that the choice of probabilistic laws of input parameters has a substantial impact on the outcome of analysis performed.
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