基于自然驾驶数据的高速公路跟驰模型参数标定

为了研究中国驾驶人在高速公路上的跟驰行为特征,从上海自然驾驶研究试验数据库中提取48位驾驶人在高速公路上的跟驰事件并进行特征分析。利用自动化筛选准则及人工验证方式提取1 548个有效事件,选取后车车速与车头间距为性能指标,其均方根百分比误差之和为目标函数,利用遗传算法对Gazis-Herman-Rothery模型、GIPPS模型、智能驾驶人模型、全速度差模型和Wiedemann模型进行参数标定及效果验证。基于误差、碰撞及后退等异常情况出现次数等比较其表现性。研究结果表明：不同模型对中国驾驶人的适应性不同,智能驾驶人模型具有最小的误差和误差标准差,更加适合仿真中国驾驶人在高速公路上的跟驰行为。研究结果对于开发适合于中国驾驶人与道路环境特征的跟驰模型具有重要价值。     

Bi-fidelity Kriging model for reliability analysis of the ultimate strength of stiffened panels

A method based on a Bi-fidelity Kriging model is proposed for structural reliability analysis. It is based on adding low-fidelity data samples to the model to predict high-fidelity values, thus saving computational effort. Distance Correlation develops the correlation between the low and high-fidelity functions, initially proposed to assess the correlation between two variables. The bi-fidelity Kriging response surface model's efficiency as a surrogate model will be assessed for structural reliability problems that demand high computational costs, such as nonlinear finite element analysis structural models. The efficiency assessment is performed by comparing the accuracy of the failure probability predictions based on the Subset Simulation and First-order reliability method using the Bi-fidelity Kriging model as a surrogate for the performance function. The idea is illustrated by considering a representative component of marine structures analyzed by finite element analysis to create bi-fidelity scenarios to assess structural reliability with many variables. The results show that the proposed multi-fidelity method can provide an accurate failure probability estimation with less computational cost.     

Uncertainty analysis of extreme mooring loads associated with environmental contours and peak tension distributions

This paper aims to assess the uncertainty on the extreme mooring loads of floating system considering short-term variability. Two environmental contour approaches based on the inverse First and Second Order Reliability Methods are employed to identify critical sea states that may give rise to extreme loads. The uncertainty related to the construction of environmental contours is addressed including significant differences due to marginal distribution fitting, parameter estimation methods and joint models. Three measured datasets are analysed using a known conditional joint distribution and proposed mixed copula model. 3-h time domain numerical simulation for each sea state is conducted and the characteristic extreme responses of mooring lines subjected to design loads are assessed. The uncertainties due to various statistical models including the average conditional exceedance rate method as well as global maxima, peak-over-threshold method combined with Gumbel distribution, Generalized Extreme Value distribution, Generalized Pareto distribution and 3-parameter Weibull distribution are investigated and quantified. It is observed that marginal distributions, joint models and parameters estimation methods have apparent effect on design loads estimation, and the extreme tensions of the semi-submersible platform shows significant difference using various probabilistic models. The results indicate that those epistemic uncertainties should be account for in the reliability analysis or safety factor calibration for mooring systems.