• Journal of the Earthquake Engineering Society of Korea
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• v.19 no.4
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• pp.161-171
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• 2015

A series of tests was conducted for full-scale single-pylon asymmetric cable-stayed bridges using a system of multiple shaking tables. The 2-span bridge length was 28 m, and the pylon height was 10.2 m. 4 different base conditions were considered: the fixed condition, RB (rubber bearings), LRB (lead rubber bearings), and HDRB (high damping rubber bearings). Based on investigation of the seismic response, the accelerations and displacements in the axial direction of the isolated bridge were increased compared to non-isolated case. However, the strain of the pylon was decreased, because the major mode of the structure was changed to translation for the axial direction due to the dynamic mass. The response of the cable bridge could differ from the desired response according to the locations and characteristics of the seismic isolator. Therefore, caution is required in the design and prediction in regard to the location and behavior of the seismic isolator.

• Earthquakes and Structures
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• v.7 no.3
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• pp.333-347
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• 2014

Multi-scale model can take both computational efficiency and accuracy into consideration when it is used to conduct elasto-plastic seismic response analysis for complex steel bridges. This paper proposed a method based on pushover analysis of member sharing the same section pattern to verify the accuracy of multi-scale model. A deck-through type steel arch bridge with a span length of 200m was employed for seismic response analysis using multi-scale model and fiber model respectively, the validity and necessity of elasto-plastic seismic analysis for steel bridge by multi-scale model was then verified. The results show that the convergence of load-displacement curves obtained from pushover analysis for members having the same section pattern can be used as a proof of the accuracy of multi-scale model. It is noted that the computational precision of multi-scale model can be guaranteed when length of shell element segment is 1.40 times longer than the width of section where was in compression status. Fiber model can only be used for the predictions of the global deformations and the approximate positions of plastic areas on steel structures. However, it cannot give exact prediction on the distribution of plastic areas and the degree of the plasticity.

• Wind and Structures
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• v.17 no.3
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• pp.275-298
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• 2013

This paper presents a number of approximated analytical formulations for the flutter analysis of long-span bridges using the so-called uncoupled flutter derivatives. The formulae have been developed from the simplified framework of a bimodal coupled flutter problem. As a result, the proposed method represents an extension of Selberg's empirical formula to generic bridge sections, which may be prone to one of the aeroelastic instability such as coupled-mode or single-mode (either dominated by torsion or heaving mode) flutter. Two approximated expressions for the flutter derivatives are required so that only the experimental flutter derivatives of ($H_1^*$, $A_2^*$) are measured to calculate the onset flutter. Based on asymptotic expansions of the flutter derivatives, a further simplified formula was derived to predict the critical wind speed of the cross section, which is prone to the coupled-mode flutter at large reduced wind speeds. The numerical results produced by the proposed formulas have been compared with results obtained by complex eigenvalue analysis and available approximated methods show that they seem to give satisfactory results for a wide range of study cases. Thus, these formulas can be used in the assessment of bridge flutter performance at the preliminary design stage.

• Wind and Structures
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• v.32 no.4
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• pp.293-308
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• 2021

For the past three decades a significant amount of research has been conducted on bridge flutter. Wind tunnel tests for a 2000 m class twin-box suspension bridge have revealed that a twin-box deck carrying 4 m tall 50% open area ratio wind screens at the deck edges achieved higher critical wind speeds for onset of flutter than a similar deck without wind screens. A result at odds with the well-known behavior for the mono-box deck. The wind tunnel tests also revealed that the critical flutter wind speed increased if the bridge deck assumed a nose-up twist relative to horizontal when exposed to high wind speeds - a phenomenon termed the "nose-up" effect. Static wind tunnel tests of this twin-box cross section revealed a positive moment coefficient at 0° angle of attack as well as a positive moment slope, ensuring that the elastically supported deck would always meet the mean wind flow at ever increasing mean angles of attack for increasing wind speeds. The aerodynamic action of the wind screens on the twin-box bridge girder is believed to create the observed nose-up aerodynamic moment at 0° angle of attack. The present paper reviews the findings of the wind tunnel tests with a view to gain physical insight into the "nose-up" effect and to establish a theoretical model based on numerical simulations allowing flutter predictions for the twin-box bridge girder.

• Structural Engineering and Mechanics
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• v.69 no.2
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• pp.155-162
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• 2019

It is very common to find an empirical formulation in an earthquake design code to calculate fundamental vibration period of a structural system. Fundamental vibration period or frequency is a key parameter to provide adequate information pertinent to dynamic characteristics and performance assessment of a structure. This parameter enables to assess seismic demand of a structure. It is possible to find an empirical formulation related to reinforced concrete structures, masonry towers and slender masonry structures. Calculated natural vibration frequencies suggested by empirical formulation in the literatures has not suits in a high accuracy to the case of rest of the historical masonry bridges due to different construction techniques and wide variety of material properties. For the listed reasons, estimation of fundamental frequency gets harder. This paper aims to present an empirical formulation through Mean Square Error study to find ambient vibration frequency of historical masonry bridges by using a non-linear regression model. For this purpose, a series of data collected from literature especially focused on the finite element models of historical masonry bridges modelled in a full scale to get first global natural frequency, unit weight and elasticity modulus of used dominant material based on homogenization approach, length, height and width of the masonry bridge and main span length were considered to predict natural vibration frequency. An empirical formulation is proposed with 81% accuracy. Also, this study draw attention that this accuracy decreases to 35%, if the modulus of elasticity and unit weight are ignored.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.5
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• pp.317-323
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• 2022

In this paper, a deep neural network(DNN) model for predicting the vibration characteristics of the composite rotor blade with c-spar cross section was developed. Herein, the present DNN model is defined by using the natural frequencies obtained through the in-house code based on the nonlinear co-rotational(CR) shell element. For the present DNN model, the accuracy of the model was evaluated via the data with a random distribution of thickness and a tendency to decrease in thickness along the blade span.

• Wind and Structures
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• v.36 no.6
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• pp.423-434
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• 2023

Aerodynamic force coefficients are generally obtained from traditional wind tunnel tests or computational fluid dynamics (CFD). Unfortunately, the techniques mentioned above can sometimes be cumbersome because of the cost involved, such as the computational cost and the use of heavy equipment, to name only two examples. This study proposed to build a deep neural network model to predict the aerodynamic force coefficients based on data collected from CFD simulations to overcome these drawbacks. Therefore, a series of CFD simulations were conducted using different geometric parameters to obtain the aerodynamic force coefficients, validated with wind tunnel tests. The results obtained from CFD simulations were used to create a dataset to train a multilayer perceptron artificial neural network (ANN) model. The models were obtained using three optimization algorithms: scaled conjugate gradient (SCG), Bayesian regularization (BR), and Levenberg-Marquardt algorithms (LM). Furthermore, the performance of each neural network was verified using two performance metrics, including the mean square error and the R-squared coefficient of determination. Finally, the ANN model proved to be highly accurate in predicting the force coefficients of similar bridge sections, thus circumventing the computational burden associated with CFD simulation and the cost of traditional wind tunnel tests.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2020.06a
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• pp.159-160
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• 2020

Flat plate structures are designed in the form of long span due to the development of construction materials and the improvement of construction technology. However, a high-rise structure of a flat plate of 50 less floors is constructed without detailed review of the inequality shortening, long-term deflection of the slab, and cracks. Therefore, it is possible to examine the case of defects in the structure due to deformation and damage of non-structures such as crack and leak, deflection of the door frame, and deformation of equipment ducts. In this study, it is a high-rise structure, and the inequality shortening and long-term deflection of the slab of the flat plate structure were evaluated through finite element analysis, and it was confirmed that prior precision analysis and correction during construction is necessary.

• Wind and Structures
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• v.38 no.1
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• pp.75-91
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• 2024

Reliable wind signal reconstruction can be beneficial to the operational safety of long-span bridges. Non-Gaussian characteristics of wind signals make the reconstruction process challenging. In this paper, non-Gaussian wind signals are converted into a combined prediction of two kinds of features, actual wind speeds and wind angles of attack. First, two decomposition techniques, empirical mode decomposition (EMD) and variational mode decomposition (VMD), are introduced to decompose wind signals into intrinsic mode functions (IMFs) to reduce the randomness of wind signals. Their principles and applicability are also discussed. Then, four artificial intelligence (AI) algorithms are utilized for wind signal reconstruction by combining the particle swarm optimization (PSO) algorithm with back propagation neural network (BPNN), support vector regression (SVR), long short-term memory (LSTM) and bidirectional long short-term memory (Bi-LSTM), respectively. Measured wind signals from a bridge site in a deep-cutting gorge are taken as experimental subjects. The results showed that the reconstruction error of high-frequency components of EMD is too large. On the contrary, VMD fully extracts the multiscale rules of the signal, reduces the component complexity. The combination of VMD-PSO-Bi-LSTM is demonstrated to be the most effective among all hybrid models.

• Journal of the Earthquake Engineering Society of Korea
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• v.1 no.2
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• pp.1-15
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• 1997

This paper presents substructural identification methods for the assessment of local damages in complex and large structural systems. For this purpose, an auto-regressive and moving average with stochastic input (ARMAX) model is derived for a substructure to process the measurement data impaired by noises. Using the substructural methods, the number of unknown parameters for each identification can be significantly reduced, hence the convergence and accuracy of estimation can be improved. Secondly, the damage index is defined as the ratio of the current stiffness to the baseline value at each element for the damage assessment. The indirect estimation method was performed using the estimated results from the identification of the system matrices from the substructural identification. To demonstrate the proposed techniques, several simulation and experimental example analyses are carried out for structural models of a 2-span truss structure, a 3-span continuous beam model and 3-story building model. The results indicate that the present substructural identification method and damage estimation methods are effective and efficient for local damage estimation of complex structures.