Local joint flexibility of tubular X-joints stiffened with external ring or external plates

In the present paper, the Local Joint Flexibility (LJF) of the ring-stiffened X-joints and plate-stiffened X-joints under compressive load is investigated. In the first phase, a finite element (FE) model was generated and verified with the results of available experimental tests and equations. In the next phase, a set number of 234 FE models were created to evaluate the role of the external ring size (β_r and τ_r), the external plate size (β_p and τ_p), and the connection geometry (γ, τ, and β) on the LJF factor (f_LJF). In these FE models, the weld connecting the chord and brace members was generated. The results indicated that the f_LJF of a plate stiffened joint can be down to 76% of the f_LJF of the corresponding un-stiffened joint. Also, the effect of the ring size on the f_LJF was more than the effect of the plate size on the f_LJF, because of the stiffener position. Despite the notable effect of the ring and the plate on the f_LJF, there is not any study or formula on tubular connections stiffened with ring or plate. Therefore, the FE results were used to propose two parametric formulas for determining the f_LJF in X-joints with external ring or external plate under brace compressive load. Moreover, the derived formulas were checked based on the UK DoE acceptance criteria.     

Human-like autonomous car-following model with deep reinforcement learning

This study proposes a framework for human-like autonomous car-following planning based on deep reinforcement learning (deep RL). Historical driving data are fed into a simulation environment where an RL agent learns from trial and error interactions based on a reward function that signals how much the agent deviates from the empirical data. Through these interactions, an optimal policy, or car-following model that maps in a human-like way from speed, relative speed between a lead and following vehicle, and inter-vehicle spacing to acceleration of a following vehicle is finally obtained. The model can be continuously updated when more data are fed in. Two thousand car-following periods extracted from the 2015 Shanghai Naturalistic Driving Study were used to train the model and compare its performance with that of traditional and recent data-driven car-following models. As shown by this study’s results, a deep deterministic policy gradient car-following model that uses disparity between simulated and observed speed as the reward function and considers a reaction delay of 1 s, denoted as DDPGvRT, can reproduce human-like car-following behavior with higher accuracy than traditional and recent data-driven car-following models. Specifically, the DDPGvRT model has a spacing validation error of 18% and speed validation error of 5%, which are less than those of other models, including the intelligent driver model, models based on locally weighted regression, and conventional neural network-based models. Moreover, the DDPGvRT demonstrates good capability of generalization to various driving situations and can adapt to different drivers by continuously learning. This study demonstrates that reinforcement learning methodology can offer insight into driver behavior and can contribute to the development of human-like autonomous driving algorithms and traffic-flow models.     

船舶通信英语口语与听力课程标准

结合船舶驾驶员的岗位职责,依照现代职业教育理论和成果,设计了船舶通信英语口语与听力课程标准.对该课程的课程概述、培养目标、与前后课程的联系、教学内容与学时分配、学习资源、教师要求、学习场地与设施要求、考核方式与标准、学习情境设计进行了设计和描述,将船舶通信中典型工作任务转化为学习型任务.     

加强教风学风建设 不断提高人才培养质量

在改革不断深入、经济社会深度转型的当下,大学生群体呈现出新的特点和个性。在新的形势下,要加强高校教风学风建设,更好的发挥高校培养人才的作用,促使人才培养质量提升。本文以辽宁省交通高等专科学校为例,着重从文化建设、教师育人能力提升、学生职业梦想等角度入手,提出了加强教风学风建设的具体举措和途径。     

行人微观仿真中的运动模型与行为模型——STEPS与NOMAD模型对比

为了解各类行人仿真模型的性能差异和适用范围,以选取适当模型进行交通枢纽行人仿真,对两种典型行人仿真模型进行研究。依据模型对行人行为描述的复杂程度,将行人仿真模型分为运动模型、部分行为模型、行为模型3类,并分别介绍了各自的特点。选取典型的运动模型软件STEPS和行为模型软件NOMAD,详细探讨其采用的数学模型,并通过4个仿真实例对比分析这两种模型的特点。分析结果得出两种模型在宏观与微观层面的异同点以及存在的问题。     

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海上运输关键节点安全评价研究是保障我国海上运输通道安全的重要环节,为科学全面评价我国海上运输关键节点的安全状况,本文建立评价指标体系,引入投影寻踪方法构建安全评价模型,通过遗传算法求解,对关键节点的安全状况进行评价,并挖掘相关海峡的主要安全威胁。评价结果表明,涉及我国重要物资如石油、集装箱运输的霍尔木兹海峡、马六甲海峡、曼德海峡及苏伊士运河的安全水平相对较低,而且印尼地区的龙目海峡、巽他海峡及望加锡海峡的安全状况也相对较差。评价结果为我国制定保障海上运输安全措施及做出相关管理决策提供科学依据,对提高我国海上运输安全性与可靠性具有重要意义。     

美国水道港口疏浚物的处理管理与利用

为维护发达的水运系统,美国每年从水道港口水域中疏浚2.0亿m3左右的沉积物,由此引发的巨量疏浚物处置问题并不亚于我国。从疏浚物的处理现状出发,总结美国在疏浚物管理机制和处理技术等方面的主要进展,分析疏浚物的有益利用及其工程案例。调查表明,美国疏浚物管理体系权责清晰,美国陆军工程兵团(USACE)和环境保护署(USEPA)在疏浚物处置管理过程中扮演了重要角色,疏浚物多数以栖息地营造、湿地修复、海滩养护、农业和水产养殖等多种方式得到有益利用。我国目前正处在疏浚土有益利用的研究和探索阶段,美国疏浚物处置管理的成功经验值得借鉴。     

沙枕抛投在荆江航道整治中的应用

沙枕袋可以有效防止水流冲刷河床底部,是稳定河床及岸坡、防止冲刷的主要加固措施。结合长江中游荆江段航道整治工程施工,介绍了抛沙枕进行护底补坡的施工工艺流程、施工要点,重点介绍沙枕袋在长江水流影响下的抛投质量控制措施及实施效果。     

北盘江石板寨水库泥沙准二维数学模型研究

通过对北盘江石板寨河段实际情况的勘察,结合历史流量和输沙率资料,采用准二维泥沙数学模型对石板寨水库有堰和无堰两种设计方案进行了计算比较.最后给出了无堰方案更有利于确保电站及水库的安全运行的结论.