• Wind and Structures
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• v.38 no.1
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• pp.1-13
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• 2024

In order to effectively simulate nonstationary stochastic turbulent wind fields, four separation hybrid (SEP-H) models are proposed in the present study. Based on the assumption that the lateral turbulence component at one single-point is uncorrelated with the longitudinal and vertical turbulence components, the fluctuating wind is separated into 2nV-1D and nV1D nonstationary stochastic vector processes. The first process can be expressed as double proper orthogonal decomposition (DPOD) or proper orthogonal decomposition and spectral representation method (POD-SRM), and the second process can be expressed as POD or SRM. On this basis, four SEP-H models of nonstationary stochastic turbulent wind fields are developed. In addition, the orthogonal random variables in the SEP-H models are presented as random orthogonal functions of elementary random variables. Meanwhile, the number theoretical method (NTM) is conveniently adopted to select representative points set of the elementary random variables. The POD-FFT (Fast Fourier transform) technique is introduced in frequency to give full play to the computational efficiency of the SEP-H models. Finally, taking a long-span bridge as the engineering background, the SEP-H models are compared with the dimension-reduction DPOD (DR-DPOD) model to verify the effectiveness and superiority of the proposed models.

• Journal of the Society of Naval Architects of Korea
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• v.52 no.1
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• pp.88-95
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• 2015

For the frequency-domain spectral fatigue analysis, the probability density function of stress range needs to be estimated based on the stress spectrum only, which is a frequency domain representation of the response. The probability distribution of the stress range of the narrow-band spectrum is known to follow the Rayleigh distribution, however the PDF of wide-band spectrum is difficult to define with clarity due to the complicated fluctuation pattern of spectrum. In this paper, efforts have been made to figure out the links between the probability density function of stress range to the structural response of wide-band Gaussian random process. An artificial neural network scheme, known as one of the most powerful system identification methods, was used to identify the multivariate functional relationship between the idealized wide-band spectrums and resulting probability density functions. To achieve this, the spectrums were idealized as a superposition of two triangles with arbitrary location, height and width, targeting to comprise wide-band spectrum, and the probability density functions were represented by the linear combination of equally spaced Gaussian basis functions. To train the network under supervision, varieties of different wide-band spectrums were assumed and the converged probability density function of the stress range was derived using the rainflow counting method and all these data sets were fed into the three layer perceptron model. This nonlinear least square problem was solved using Levenberg-Marquardt algorithm with regularization term included. It was proven that the network trained using the given data set could reproduce the probability density function of arbitrary wide-band spectrum of two triangles with great success.

• The Korean Journal of Applied Statistics
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• v.33 no.1
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• pp.25-46
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• 2020

This paper presents ordinal probit semiparametric regression models using Bayesian Spectral Analysis Regression (BSAR) method. Ordinal probit regression is a way of modeling ordinal responses - usually more than two categories - by connecting the probability of falling into each category explained by a combination of available covariates using a probit (an inverse function of normal cumulative distribution function) link. The Bayesian probit model facilitates posterior sampling by bringing a latent variable following normal distribution, therefore, the responses are categorized by the cut-off points according to values of latent variables. In this paper, we extend the latent variable approach to a semiparametric model for the Bayesian ordinal probit regression with nonparametric functions using a spectral representation of Gaussian processes based BSAR method. The latent variable is decomposed into a parametric component and a nonparametric component with or without a shape constraint for modeling ordinal responses and predicting outcomes more flexibly. We illustrate the proposed methods with simulation studies in comparison with existing methods and real data analysis applied to a Korean National Health and Nutrition Examination Survey (KNHANES) 2016 for investigating nonparametric relationship between smoking behavior and coffee intake.

• Wind and Structures
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• v.12 no.3
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• pp.239-257
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• 2009

This paper develops and discusses a method by which it is possible to evaluate the Equivalent Static Force (ESF) of wind in the case of long-span bridges. Attention is focused on the alongwind direction. The study herein carried out deals with the classical problems of determining the maximum effects due to the alongwind action and the corresponding ESFs. The mean value of the maximum alongwind displacement of the deck is firstly obtained both by the spectral analysis and the Gust Response Factor (GRF) technique. Successively, in order to derive the other wind-induced effects acting on the deck, the Gust Effect Factor (GEF) technique is extended to long-span bridges. By adopting the GRF technique, it is possible to define the ESF that applied on the structure produces the maximum alongwind displacement. Nevertheless the application of the ESF so obtained does not furnish the correct maximum values of other wind-induced effects acting on the deck such as bending moments or shears. Based on this observation, a new technique is proposed which allows to define an ESF able to simultaneously reproduce the maximum alongwind effects of the bridge deck. The proposed technique is based on the GEF and the POD techniques and represents a valid instrument of research for the understanding of the wind excitation mechanism.

• Wind and Structures
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• v.31 no.3
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• pp.217-227
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• 2020

Based on translation models, both Gaussian and non-Gaussian wind fields are generated using spectral representation method for investigating the influence of non-Gaussian characteristics and directivity effect of wind load on fatigue damage of wind turbine. Using the blade aerodynamic model and multi-body dynamics, dynamic responses are calculated. Using linear damage accumulation theory and linear crack propagation theory, crack initiation life and crack propagation life are discussed with consideration of the joint probability density distribution of the wind direction and mean wind speed in detail. The result shows that non-Gaussian characteristics of wind load have less influence on fatigue life of wind turbine in the area with smaller annual mean wind speeds. Whereas, the influence becomes significant with the increase of the annual mean wind speed. When the annual mean wind speeds are 7 m/s and 9 m/s at hub height of 90 m, the crack initiation lives under softening non-Gaussian wind decrease by 10% compared with Gaussian wind fields or at higher hub height. The study indicates that the consideration of the influence of softening non-Gaussian characteristics of wind inflows can significantly decrease the fatigue life, and, if neglected, it can result in non-conservative fatigue life estimates for the areas with higher annual mean wind speeds.

• Wind and Structures
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• v.38 no.2
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• pp.119-128
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• 2024

The aerodynamic damping is an essential factor that can considerably affect the dynamic response of the cable-stayed bridge induced by crosswind load. However, developing an accurate and efficient aerodynamic damping model is crucial for evaluating the crosswind load-induced response on cable-stayed bridges. Therefore, this study proposes a new method for identifying aerodynamic damping of the bridge structures under crosswind load using an extended Kalman filter (EKF) and the particle filter (PF) algorithm. The EKF algorithm is introduced to capture the aerodynamic damping ratio. PF technique is used to select the optimal spectral representation of the noise. The effectiveness and accuracy of the proposed solution were investigated through full-scale vibration measurement data of the crosswind-induced on the bridge's girder. The results show that the proposed solution can generate an efficient and robust estimation. The errors between the target and extracted values are around 0.01mm and 0.003^o, respectively, for the vertical and torsional motion. The relationship between the amplitude and the aerodynamic damping ratio is linear for small reduced wind velocity and nonlinear with the increasing value of the reduced wind velocity. Finally, the results show the influence of the level of noise.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.4 s.310
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• pp.9-18
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• 2006

In the digital camera system, CMOS image sensor (CIS) is widely used because its size and weight become smaller and power consumption becomes lower. However, there are common problems that colors of the recorded image do not match those of the photographed object and that spectral sensitivity of the CIS used in different cameras varies largely in each case. Therefore, color correction is needed because the spectral sensitivity of the CIS in each color is neither the same color component for most standard colors nor the appropriate color representation for any output devices. In the conventional method, a color correction is empirically obtained by a large number of iterative experiments, but the result is not so satisfied. In this paper, a new method to obtain the efficient color correction matrix for digital camera using CIS is proposed. We obtain camera transfer matrix under the certain white-balance point, and color correction matrix that makes the transfer characteristic of digital camera close to the transfer characteristic of ideal camera is obtained. The experimental results show that the transfer characteristic of digital camera by the proposed method is close to that of the ideal camera. In addition, the image quality of pictures of digital camera using the proposed method is dramatically improved.

• Wind and Structures
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• v.20 no.2
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• pp.249-274
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• 2015

Long-span cable-stayed bridges exhibit some features which are more critical than typical long span bridges such as geometric and aerodynamic nonlinearities, higher probability of the presence of multiple vehicles on the bridge, and more significant influence of wind loads acting on the ultra high pylon and super long cables. A three-dimensional nonlinear fully-coupled analytical model is developed in this study to improve the dynamic performance prediction of long cable-stayed bridges under combined traffic and wind loads. The modified spectral representation method is introduced to simulate the fluctuating wind field of all the components of the whole bridge simultaneously with high accuracy and efficiency. Then, the aerostatic and aerodynamic wind forces acting on the whole bridge including the bridge deck, pylon, cables and even piers are all derived. The cellular automation method is applied to simulate the stochastic traffic flow which can reflect the real traffic properties on the long span bridge such as lane changing, acceleration, or deceleration. The dynamic interaction between vehicles and the bridge depends on both the geometrical and mechanical relationships between the wheels of vehicles and the contact points on the bridge deck. Nonlinear properties such as geometric nonlinearity and aerodynamic nonlinearity are fully considered. The equations of motion of the coupled wind-traffic-bridge system are derived and solved with a nonlinear separate iteration method which can considerably improve the calculation efficiency. A long cable-stayed bridge, Sutong Bridge across the Yangze River in China, is selected as a numerical example to demonstrate the dynamic interaction of the coupled system. The influences of the whole bridge wind field as well as the geometric and aerodynamic nonlinearities on the responses of the wind-traffic-bridge system are discussed.

• Smart Structures and Systems
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• v.21 no.5
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• pp.591-600
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• 2018

The probabilistic characterization of wind field characteristics is a significant task for fatigue reliability assessment of long-span railway bridges in wind-prone regions. In consideration of the effect of wind direction, the stochastic properties of wind field should be represented by a bivariate statistical model of wind speed and direction. This paper presents the construction of the bivariate model of wind speed and direction at the site of a railway arch bridge by use of the long-term structural health monitoring (SHM) data. The wind characteristics are derived by analyzing the real-time wind monitoring data, such as the mean wind speed and direction, turbulence intensity, turbulence integral scale, and power spectral density. A sequential quadratic programming (SQP) algorithm-based finite mixture modeling method is proposed to formulate the joint distribution model of wind speed and direction. For the probability density function (PDF) of wind speed, a double-parameter Weibull distribution function is utilized, and a von Mises distribution function is applied to represent the PDF of wind direction. The SQP algorithm with multi-start points is used to estimate the parameters in the bivariate model, namely Weibull-von Mises mixture model. One-year wind monitoring data are selected to validate the effectiveness of the proposed modeling method. The optimal model is jointly evaluated by the Bayesian information criterion (BIC) and coefficient of determination, $R^2$. The obtained results indicate that the proposed SQP algorithm-based finite mixture modeling method can effectively establish the bivariate model of wind speed and direction. The established bivariate model of wind speed and direction will facilitate the wind-induced fatigue reliability assessment of long-span bridges.

• Bulletin of the Society of Naval Architects of Korea
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• v.26 no.2
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• pp.25-31
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• 1989

Two-dimensional large-amplitude motions in regular harmonic wave are treated in time domain, by satisfying the exact body boundary condition and the linear free surface condition. For the present numerical calculation, the method of free-surface spectral representation with simple source distribution on the instantaneous body surface has been extended to include the effect of the incident wave. Calculations of the wave exciting force are performed for a submerged circular cylinder fixed or oscillating with large amplitude. Especially, nonlinear effects on the time-mean forces are studied in detail. It is shown that relative motion between the body and the fluid particle gives a significant effect on the lift and drift forces. Also, large-amplitude motion of a submerged circular cylinder and that of a floating Lewis-form cylinder are directly simulated in time domain. In the calculation results, some nonlinear effects are shown.