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Helu Yu,Bin Wang,Guoqing Zhangb,Yong-Le Li,Xingyu Chen 한국풍공학회 2020 Wind and Structures, An International Journal (WAS Vol.31 No.5
Long-span bridges with high flexibility and low structural damping are very susceptible to the vortex-induced vibration (VIV), which causes extremely negative impacts on the ride comfort of vehicles running on the bridges. To assess the ride comfort of vehicles running on the long-span bridges subjected to VIV, a coupled wind-vehicle-bridge system applicable to the VIV case is firstly developed in this paper. In this system, the equations of motion of the vehicles and the bridge subjected to VIV are established and coupled through the vehicle-bridge interaction. Based on the dynamic responses of the vehicles obtained by solving the coupled system, the ride comfort of the vehicles can be evaluated using the method given in ISO 2631-1. At last, the proposed framework is applied to several case studies, where a long-span suspension bridge and two types of vehicles are taken into account. The effects of vehicle speed, vehicle type, road roughness and vehicle number on the ride comfort are investigated.
Kernel density estimation based on progressive type-II censoring
Helu Amal,Samawi Hani,Rochani Haresh,Yin Jingjing,Vogel Robert 한국통계학회 2020 Journal of the Korean Statistical Society Vol.49 No.2
Progressive censoring is essential for researchers in industry as a mean to remove subjects before the final termination point in order to save time and reduce cost. Recently, kernel density estimation has been intensively investigated due to its asymptotic properties and applications. In this paper, we investigate the asymptotic properties of the kernel density estimators based on progressive type-II censoring and their application to hazard function estimation. A bias-adjusted kernel density estimator is also proposed. Our simulation indicates that the kernel density estimates under progressive type-II censoring is competitive compared with kernel density estimates under simple random sampling, depending on the censoring schemes. An example regarding failure times of aircraft windshields is used to illustrate the proposed methods.
Samawi, Hani M.,Helu, Amal,Rochani, Haresh D.,Yin, Jingjing,Linder, Daniel The Korean Statistical Society 2016 Communications for statistical applications and me Vol.23 No.5
The stress-strength models have been intensively investigated in the literature in regards of estimating the reliability ${\theta}$ = P(X > Y) using parametric and nonparametric approaches under different sampling schemes when X and Y are independent random variables. In this paper, we consider the problem of estimating ${\theta}$ when (X, Y) are dependent random variables with a bivariate underlying distribution. The empirical and kernel estimates of ${\theta}$ = P(X > Y), based on bivariate ranked set sampling (BVRSS) are considered, when (X, Y) are paired dependent continuous random variables. The estimators obtained are compared to their counterpart, bivariate simple random sampling (BVSRS), via the bias and mean square error (MSE). We demonstrate that the suggested estimators based on BVRSS are more efficient than those based on BVSRS. A simulation study is conducted to gain insight into the performance of the proposed estimators. A real data example is provided to illustrate the process.