大型汽车滚装船固定坡道结构分析及优化

针对某大型汽车滚装船在运营过程中一坡道发生较严重裂纹的问题,利用MSC.Patran软件对坡道结构进行细化有限元分析,计算歪斜工况下的屈服强度,分析应力分布情况并对应力不满足的结构进行改进,裂纹发生的位置与细化有限元分析结果一致,表明对汽车滚装船所有坡道结构做细化有限元分析十分必要。     

Sea state estimation based on vessel motion responses: Improved smoothness and robustness using Bézier surface and L1 optimization

Floating structures oscillate in waves, where these wave-induced motions may be critical for various marine operations. An important consideration is thereby given to the sea states at the planning and operating stages for an offshore project. The most important information extracted from a sea state is the directional wave spectrum, indicating wave direction, significant wave height, and wave spectrum peak period. Among several available methods of measuring and estimating the directional wave spectrum, the wave buoy analogy technique based on vessel motion responses is an in situ and almost real-time solution without extra costs of devices. If the forms of the wave spectra are not predefined in the estimation, the method is called a nonparametric approach. Its most remarkable advantage is the flexible form, but the smoothness should be regulated. After the discrete Fourier transform has been applied to the measured vessel motions, smoothing is necessary. However, this process results in disturbed vessel cross-spectra and a lowpass characteristic of the windowing function. This paper presents a nonparametric approach for directional wave spectrum estimation based on vessel motion responses. It introduces novel smoothness constraints using Bézier surface and includes a more robust estimate using L1 optimization. Both techniques are applied to the wave buoy analogy for the first time. Numerical simulations are conducted to verify the proposed algorithm.     

汽车前照灯闪烁问题分析及设计优化

汽车前照灯是整车照明的重要组成,随着时代的发展,汽车前照灯的设计也越来越简单化、多样化。本文针对某车型项目阶段出现的前照灯闪烁问题,从前照灯的控制逻辑展开,分析故障产生的原因,并研究优化方案。     

基于PSO算法的地铁智能调线调坡系统开发与研究

为解决人工调线调坡费时费力、效率低下，且无有效评价指标评判方案优劣的现状问题，从分析线路平纵断面设计变量入手，依据规范相关规定制定约束条件，创新性地建立带有侵限容忍值惩罚项和合规性惩罚项的目标函数，提出一套基于粒子群优化算法，适用于矩形、马蹄形、圆形等多种隧道断面类型的地铁调线调坡数学分析模型，并以此开发地铁智能调线调坡系统。以长沙地铁4号线某区间右线隧道为例，对比人工设计和智能系统的调线调坡结果。由对比结果可知，智能系统在线路参数选择的合理性和改善侵限情况等方面均明显优于人工调线调坡，且具有可靠性和高效性。     

Multi-criteria optimization of traffic signals: Mobility,safety, and environment

Two-dimensional multi-objective optimizations have been used for decades for the problems in traffic engineering although only few times so far in the optimization of signal timings. While the other engineering and science disciplines have utilized visualization of 3-dimensional Pareto fronts in the optimization studies, we have not seen many of those concepts applied to traffic signal optimization problems. To bridge the gap in the existing knowledge this study presents a methodology where 3-dimensional Pareto Fronts of signal timings, which are expressed through mobility, (surrogate) safety, and environmental factors, are optimized by use of an evolutionary algorithm. The study uses a segment of 5 signalized intersections in West Valley City, Utah, to test signal timings which provide a balance between mobility, safety and environment. In addition, a set of previous developed signal timing scenarios, including some of the Connected Vehicle technologies such as GLOSA, were conducted to evaluate the quality of the 3-dimensional Pareto front solutions. The results show success of 3-dimensinal Pareto fronts moving towards optimality. The resulting signal timing plans do not show large differences between themselves but all improve on the signal timings from the field, significantly. The commonly used optimization of standard single-objective functions shows robust solutions. The new set of Connected Vehicle technologies also shows promising benefits, especially in the area of reducing inter-vehicular friction. The resulting timing plans from two optimization sets (constrained and unconstrained) show that environmental and safe signal timings coincide but somewhat contradict mobility. Further research is needed to apply similar concepts on a variety of networks and traffic conditions before generalizing findings.     

Prioritizing road extension projects with interdependent benefits under time constraint

Since transportation projects are costly and resources are limited, prioritizing or sequencing the projects is imperative. This study was inspired by a client who asked: “I have tens of approved road extension projects, but my financial resources are limited. I cannot construct all the projects simultaneously, so can you help me prioritize my projects?” To address this question, the benefits and costs of all the possible scenarios must be known. However, the impacts (or benefit) of road extension projects are highly interdependent, and in sizable cases cannot be specified thoroughly. We demonstrate that the problem is analogous to the Traveling Salesman Problem (TSP). Dynamic change in travel demand during construction is another aspect of the complexity of the problem. The literature is yet to provide efficient methods for large cases. To this end, we developed a heuristic methodology in which the variation of travel demand during the construction period is considered. We introduce a geometrical objective function for which a solution-finding policy based on “gradient maximization” is developed. To address the projects’ interdependency, a special neural network (NN) model was devised. We developed a search engine hybridized of Ant Colony and Genetic Algorithm to seek a solution to the TSP-like problem on the NN based on gradient maximization. The algorithm was calibrated and applied to real data from the city of Winnipeg, Canada, as well as two cases based on Sioux-Falls. The results were reliable and identification of the optimum solution was achievable within acceptable computational time.     

A multiobjective land development optimization model: the case of New Castle County,Delaware

This paper develops a multiobjective optimization model to consider transportation impacts of the future development of land. The output of the model is the best location and type of land use that has minimal negative transportation effects and uses the maximum available public transportation infrastructure. It provides tools for both planners and transportation engineers and enables them to consider different scenarios of possible policies and land development. Since multiple objectives and their nonlinear structures are considered, the model is solved using mixed integer nonlinear programming. The final results are shown in both tabular and graphical format. The effectiveness of the model is applied to the northern part of New Castle County, Delaware. The results show that the model successfully finds the best locations for both residential and commercial land uses in order to meet several criteria discussed in the paper.     

A modified reinforcement learning algorithm for solving coordinated signalized networks

This study proposes Reinforcement Learning (RL) based algorithm for finding optimum signal timings in Coordinated Signalized Networks (CSN) for fixed set of link flows. For this purpose, MOdified REinforcement Learning algorithm with TRANSYT-7F (MORELTRANS) model is proposed by way of combining RL algorithm and TRANSYT-7F. The modified RL differs from other RL algorithms since it takes advantage of the best solution obtained from the previous learning episode by generating a sub-environment at each learning episode as the same size of original environment. On the other hand, TRANSYT-7F traffic model is used in order to determine network performance index, namely disutility index. Numerical application is conducted on medium sized coordinated signalized road network. Results indicated that the MORELTRANS produced slightly better results than the GA in signal timing optimization in terms of objective function value while it outperformed than the HC. In order to show the capability of the proposed model for heavy demand condition, two cases in which link flows are increased by 20% and 50% with respect to the base case are considered. It is found that the MORELTRANS is able to reach good solutions for signal timing optimization even if demand became increased.     

郑万高铁隧道大型机械化施工支护优化

为解决郑万高铁大断面隧道建造过程中初期支护、二次衬砌、超前支护等支护结构安全储备较大、支护不经济的问题,以郑万高铁湖北段大断面隧道工程为依托,基于通用设计图A开展支护结构应力应变现场测试,对测试数据进行分析,并据此提出支护参数优化方案。采用现场实测和荷载-结构有限元方法对优化方案进行检算,最终确定优化设计图B,并进行现场应用。结果表明： 支护结构整体处于安全状态,优化方案合理可行。该支护优化方案不仅可以有效保证大断面隧道的安全性和稳定性,而且能降低成本,提高材料利用率,减少现场作业人员的劳动量。     

隧道衬砌可靠指标的优化求解方法

为解决JC法计算隧道衬砌可靠指标过程中极限状态选用方法的缺陷,通过随机有限元方法和Monte-Carlo法对时速350 km高速铁路双线隧道Ⅲa、Ⅳb型衬砌进行抽样计算,得到2种衬砌各截面偏心距平均值和变异系数; 通过对素混凝土和钢筋混凝土衬砌极限状态功能函数及其适用条件的分析,引入几何优化法,以约束函数表示功能函数的约束条件,建立可靠指标的优化求解模型; 选用寻优性能良好的Global Search函数,对2种衬砌各截面可靠指标进行优化求解,并与JC法进行对比,证明优化方法的优势。