Required test durations for converged short-term wave and impact extreme value statistics — Part 1: Ferry dataset

For the design of maritime structures in waves, the extreme values of responses such as motions and wave impact loads are required. Waves and wave-induced responses are stochastic, so such responses should always be related to a probability. This information is not easy to obtain for strongly non-linear responses such as wave impact forces. Usually class rules or direct assessment via experiments or numerical simulations are applied to obtain extreme values for design. This brings up questions related to the convergence of extreme values: how long do we need to test in order to obtain converged statistics for the target duration? Or, vice versa: given testing data, what is the uncertainty of the associated statistics? Often the test or simulation duration is cut up in ‘seeds’ or ‘realisations’, with an exposure duration of one or three hours based on the typical duration of a steady environmental condition at sea, or the time that a ship sails a single course. The required number of seeds for converged results depends on the type of structure and response, the exposure duration, and the desired probability level. The present study provides guidelines for the convergence of most probable maximum (MPM) wave crest heights and MPM green water wave impact forces on a ferry. Long duration experiments were done to gain insight into the required number of seeds, and the effect of fitting. The present paper presents part 1 of this study; part 2 [1] presents similar results for wave-in-deck loads on a stationary deck box.     

基于站点群体聚集性客流的公交串车调度优化

为提升城市公交准点率、减少延误，解决车辆串车问题，研究基于站点群体聚集性客流的公交调度优化方法。以乘客出行意愿、乘车属性、到站规律等标识公交客流变化特征，以车辆载客限制、站点延误、到达率、下车率等描述串车形成场景。考虑准时性、客流需求、调控策略等约束，采用实时混合控制策略，实现车头时距偏差与乘客总行程时间最小的多目标优化。提出的公交串车调度方法，考虑到乘客到达率的不确定性，并通过调控公交车辆站点驻站时间以及路段平均行驶速度，可满足站点时段性群体聚集公交客流出行需求，防范潜在的公交串车。在模型求解上，考虑到双目标优化视角的差异性，运用超车规则对串车场景下的出站车辆重新排序，设计基于NSGA-II的求解算法，以拥挤距离标定序度关系，以精英策略获取新种群，改进交叉算子，并基于TOPSIS法对获取的Pareto解集择优。最后，以实际公交线路为例进行案例分析，结果表明：基于站点群体聚集性客流的公交串车优化调度模型，系统考虑了乘客乘车属性与车辆载客限制，能够输出最优的车辆滞站与车速调整方案，并且能运算得出车辆离站时间、车头时距偏差、准点率、乘客等待时间以及乘客行程时间等多项运营指标。优化前后对比表...