基于蒙特卡洛方法的海上搜寻区域确定模型

为了提高海上搜寻与救助的成功率,采用FVCOM模型进行遇难海域表面流场的数值预报,并与实测结果进行比较。采用经验公式法确定不同漂浮物种类风致漂移速度与风速的关系。引入蒙特卡洛方法,通过量化影响漂移的不确定性因素,确定漂浮物位置随时间变化的概率密度函数,并以统计区域作为搜寻区域,编制程序建立搜寻区域确定模型。模型实例验证效果较好,可为搜救工作的开展提供依据。     

结构自重及摩擦系数作变量对直立式防波堤可靠度的影响*

在直立式防波堤的抗滑、抗倾可靠度分析中,通常将结构与基床间的摩擦系数f,直立式防波堤在水中的重力G及其引起的稳定力矩MG均作为定值处理,而忽略三者的变动对可靠度的影响。以秦皇岛港燃料油基地的直立式防波堤为例,采用JC法、映射变换法及Monte Carlo模拟3种方法分别计算了摩擦系数f,自重G及其引起的稳定力矩MG作为定值和变量时直立式防波堤抗滑、抗倾的可靠性指标。结果表明：将摩擦系数f,自重G及其引起的稳定力矩MG均作为变量处理,得到的可靠性指标更精确、更符合实际情况;摩擦系数f的变动对直立式防波堤的可靠度影响较小,而自重G及其引起的稳定力矩MG二者的变动对直立式防波堤的可靠度影响较大。     

基于免疫进化算法的发动机悬置系统稳健优化

在分析各种优化方法优缺点的基础上,建立发动机悬置系统六自由度动力模型。以六自由度方向的解耦率为最大优化目标,以各悬置点三向刚度为设计变量,选用免疫进化算法对发动机的悬置刚度参数进行优化,最后用Monte Carlo法对悬置系统进行稳健性分析。结果表明,优化解不仅能保证六自由度方向的高解耦率,还能保证悬置系统的稳健性,提高了产品的质量。     

舰船空气净化材料吸附CO2的分子模拟研究

以往很少考虑舰船空气净化装置的CO2在空气中被吸附的能力及其吸附量随温度变化的情况。创新地将计算机分子模拟技术引进舰船设备研究领域,运用Materials Studio分子模拟软件建立了13X-APG分子筛的模型。采用分子模拟中比较常用的蒙特卡洛方法,对大量的分子构型进行重要性抽样,选择被接受的构型,产生平衡系统。借此验证分子筛和CO2的力场,并在此基础上模拟CO2在空气中被吸附的情况及其在20～40℃范围内吸附量的变化情况。模拟结果表明:13X-APG分子筛主要吸附CO2,并且随着温度的增加,CO2吸附量从20℃时的127.3 mg/g下降到了40℃时的108.5 mg/g。可见舰船空气净化装置可以使用分子筛来吸附CO2,但温度对其吸附量有一定的影响。     

基于土体刚度和蒙特卡洛法的基坑开挖对既有市政道路沉降影响分析

随着城市建设工程的持续增加,城市地下空间开发和市政设施建设产生的交叉也越来越多,许多基坑工程会在周边市政道路已经建成的条件下进行施工,基坑施工对既有市政道路产生一定的沉降影响,市政道路产生附加变形和附加应力降低了沥青路面的疲劳寿命。针对宁波市某基坑工程施工对近接市政道路的影响为工程背景,基于Plaxis数值模拟平台采用考虑小刚度的土体硬化本构模型,分析基坑的施工和简化的交通荷载对市政道路的受力变形的影响。在此基础上,采用蒙特卡洛法和数值模拟结果对道路结构层厚度进行随机选取,以沉降量为控制指标计算出疲劳寿命对该市政道路结构层给出了优化结果。     

第二代完整稳性瘫船失效模式直接评估方法研究

国际海事组织(IMO)在第二代完整稳性规则的制定中,针对每一种失效模式提出了3层薄弱性衡准.目前,瘫船稳性失效模式薄弱性衡准已经完成了第1、2层次的内容,第3层次直接评估方案还未形成.本文基于IMO船舶设计与构造分委会第一次会议(SDC1)提出的第2层薄弱性衡准草案中关于瘫船稳性的相关内容,采用单自由度横摇运动数学模型,编制数值计算程序,模拟船舶在极端恶劣条件下风浪联合作用的横摇运动,计算给定暴露时间船舶倾覆概率.将计算结果与CEHIPAR2792标准模型试验结果进行对比,验证并分析数值方法的可行性,为确定该失效模式的直接评估方法提供参考.     

基于蒙特卡洛法的实船功率性能试验不确定度分析

针对实船功率性能测量与分析涉及因素多,难以通过传统GUM法对修正得到的理想状态功率与航速结果进行不确定度评价的问题,提出基于蒙特卡洛法的实船功率性能不确定度分析方法,分析实船功率性能试验中的主要不确定度源,依据ISO15016数据处理方法建立测量模型,以大连海事大学教学实习船"育鲲"轮为对象分析实船功率性能试验与不确定...     

远航船舶的备件配置方法研究

根据船舶远航时的特点,提出以可用度为中心的备件配置方法,配置模型和Monte Carlo仿真方法可综合考虑远航船舶装备的可靠性及维修性影响,相比于传统经验方法,能较好反映实际需求。     

Critical assessment of five methods to correct for endogeneity in discrete-choice models

Endogeneity often arises in discrete-choice models, precluding the consistent estimation of the model parameters, but it is habitually neglected in practical applications. The purpose of this article is to contribute in closing that gap by assessing five methods to address endogeneity in this context: the use of Proxys (PR); the two steps Control-Function (CF) method; the simultaneous estimation of the CF method via Maximum-Likelihood (ML); the Multiple Indicator Solution (MIS); and the integration of Latent-Variables (LV). The assessment is first made qualitatively, in terms of the formulation, normalization and data needs of each method. Then, the evaluation is made quantitatively, by means of a Monte Carlo experiment to study the finite sample properties under a unified data generation process, and to analyze the impact of common flaws. The methods studied differ notably in the range of problems that they can address; their underlying assumptions; the difficulty of gathering proper auxiliary variables needed to apply them; and their practicality, both in terms of the need for coding and their computational burden. The analysis developed in this article shows that PR is formally inappropriate for many cases, but it is easy to apply, and often corrects in the right direction. CF is also easy to apply with canned software, but requires instrumental variables which may be hard to collect in various contexts. Since CF is estimated in two stages, it may also compromise efficiency and difficult the estimation of standard errors. ML guarantees efficiency and direct estimation of the standard errors, but at the cost of larger computational burden required for the estimation of a multifold integral, with potential difficulties in identification, and retaining the difficulty of gathering proper instrumental variables. The MIS method appears relatively easy to apply and requiring indicators that may be easier to obtain in various cases. Finally, the LV approach appears as the more versatile method, but at a high cost in computational burden, problems of identification and limitations in the capability of writing proper structural equations for the latent variable.     

Time control point strategy coupled with transfer coordination in bus schedule design

A schedule consisting of an appropriate arrival time at each time control point can ensure reliable transport services. This paper develops a novel time control point strategy coupled with transfer coordination for solving a multi‐objective schedule design problem to improve schedule adherence and reduce intermodal transfer disutility. The problem is formulated using a robust mixed‐integer nonlinear programming model. The mixed‐integer nonlinear programming model is equivalently transformed into a robust mixed‐integer linear programming model, which is then approximated by a deterministic mixed‐integer linear programming model through Monte Carlo simulation. Thus, the optimal scheduled arrival time at each time control point can be precisely obtained using cplex . Numerical experiments based on three bus lines and the mass rapid transit system in Singapore are presented, and the results show that the schedule determined using the developed model is able to provide not only reliable bus service but also a smooth transfer experience for passengers. Copyright © 2016 John Wiley & Sons, Ltd.