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。     

公路客运市场退出影响因素实证分析

通过对广东省公路客运企业和政府主管部门的问卷调查,采用因子分析方法,从影响客运市场退出的相关主体及相关行为中筛选出关键变量．运用非参数检验过程,就各关键变量对退出的影响程度进行比较,最终得出驾驶员和承包经营人的相关行为对公路客运市场退出最具影响的结论,为政府部门进行行业管理和政策制定提供了实证依据．     

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。     

Sensitivity analysis of parameters for multi-stand roll forming using a new booting model

Multi-stand roll forming is a process that has very complicated deformation behaviour and shows significant nonlinearity.In this paper, the sensitivity analysis of parameters for multi-stand roll forming was performed via a new booting finite element method(FEM) model.Compared with the most of simulation, the new model is more consistent with production process and can account for the effects of roll rotating speed.Based on the model, the process of an open section channel formed with 10 passes was simulated and the sensitivity analysis was conducted with orthogonal experiment design combined FEM model.The multi-stand roll forming process can be efficiently analyzed by the new booting model.And sensitivity analysis shows the hardening exponent plays an important role in controlling the quality of the products.     

基于灵敏度分析的环肋圆柱壳结构优化

针对环肋圆柱壳结构强度和稳定性(包含肋骨侧向稳定性),引入新的灵敏度计算方法,开展了几何参数的灵敏度分析,获取了主要影响参数;给出了考虑肋骨侧向稳定性后的材料利用率计算公式后,在结构满足强度和稳定性要求的条件下,以重量最轻、材料利用率最高为优化目标建立了优化数学模型。采用多目标遗传算法对结构在考虑肋骨侧向稳定性后进行了优化。结果表明,这种灵敏度计算方法具有良好的可靠性,基于灵敏度分析的结构优化的方案具有显著的可行性、高效性。     

基于参数化船型的阻力优化研究

船型几何模型的参数化表达,是船型多学科设计优化的基础。其作用是为各学科分析和优化提供一个统一的几何模型,并根据各学科分析结果自动修改调整船体型线。文中尝试使用Friendship进行船体完全参数化建模,并使用该软件中的feature编程功能编程实现shipflow型值数据的提取;通过改变一系列重要的船型参数实现变换船型几何模型,以获得满足性能需求的船型。最后利用该软件的优化框架,采用切线搜索法 (Tangent Search, TSearch) 完成1300TEU集装箱船的兴波阻力优化,优化球首和前体船体曲面。结果表明,该参数化方法在改进船型水动力性能方面有很好的效果。