铁路预应力路堤加固技术数值研究

研究目的:铁路预应力路堤在国内外尚属一种新型路基加固法,其受力变形特性暂未得到系统化研究,相关加固设计理论仍处于探索性阶段。因此,有必要通过数值手段了解预应力路堤的工作状态,以掌握其加固性能。鉴于此,借助ABAQUS软件平台构建预应力路堤仿真系统,分析差异化预应力加固参数对路堤变形和承载能力的影响以及预应力加固构件的受力特征。研究结论:(1)路堤本体段坡面较优加固位置为距本体顶面以下0.3倍本体高度处;(2)坡率1∶1的预应力路堤在第1、2排侧压板分别施加50 k Pa、100 k Pa预压荷载时,其变形与承载力均可达传统路堤(坡率1∶1.5)水平,并可通过提升加固标准进一步强化路堤承载性能;(3)当对第1、2、3排侧压板分别施加50 k Pa、100 k Pa、100 k Pa预压荷载时,路堤内部附加围压S11>13.5 k Pa区域大致呈"x"形分布并形成横贯路堤的"预压加固区";(4)侧压板锚固区受力集中且复杂,应注意保障锚固区板体强度;(5)力筋在路堤加载前后的应力变化量与坡面侧向变形特征相关;(6)本研究成果可为铁路预应力路堤的加固设计提供技术指导。     

公路地基真空排水预压法探讨

真空排水预压法与堆载预压法相比具有加载快、无需堆载材料、不会失稳等优势,适用于加固软土特别是含水量较高的超软土地基。真空-堆载联合预压法的应用也越来越多。经过国内外十几年的探索,真空排水预压法日趋成熟,已经成为大面积应用的加固软土地基的行之有效的方法之一。     

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.     

流线型钢箱梁涡激振动机理与气动控制措施

以某主跨390 m的独塔流线型钢箱梁斜拉桥为工程依托，采用风洞试验与计算流体动力学（Computational Fluid Dynamics，CFD）相结合的方法对流线型钢箱梁涡激振动机理与气动控制措施进行研究。首先，采用几何缩尺比为1∶30的主梁节段模型进行主梁涡振性能与气动控制措施优化研究；其次，采用CFD方法对主梁涡振响应进行流固耦合计算，将Newmark-β算法嵌入ANSYS Fluent用户自定义函数（User Defined Functions，UDFs）实现主梁结构振动响应求解，同时结合动网格技术实现主梁断面流固耦合分析；并根据判断条件来检索箱梁壁面上的网格单元，以获得主梁断面振动过程中的表面压力，然后结合主梁结构振动响应、表面压力以及流场特征等对主梁涡激振动机理进行分析。结果表明：该桥主梁原设计方案存在涡激共振现象，将梁底检修车轨道内移120 cm可有效抑制主梁涡振响应；主梁涡激振动响应的数值模拟结果与风洞试验结果吻合较好；检修车轨道内移120 cm后主要改变了箱梁下表面平均压力系数分布特性，且箱梁表面各测点脉动压力卓越频率不一致，有效减小了主梁涡激振动响应；流线型箱梁靠近迎风侧的“被动区域”对结构涡振响应贡献较小，背风侧“驱动区域”发生周期性旋涡脱落是影响流线型箱梁涡振的主要因素。     

桥梁单板受力的原因及解决措施

随着交通量的迅猛增长,桥梁单板受力情况越来越频繁,通过对单板受力现象产生原因进行分析,提出解决措施,以供同行参考和借鉴。     

高职院校公共《计算机基础》课程实践教学研究

对高职院校公共《计算机基础》实践教学效果及其存在的问题进行剖析,针对这些问题所采取的应对措施进行了探索和研究。提出加强实践教学改革的方案和具体方法,使高职院校的计算机基础教育能更好地与市场接轨。     

浅埋顶管沉井周边土体的三维破坏形状及沉降研究

为研究顶管沉井及周边土体在顶进力作用下的形变范围与大小，以加固旋喷桩作为沉井周围加固体建立ABAQUS软件计算模型，并将模拟结果与工程实例、PLAXIS 3D软件所得结果进行对比分析。同时，采用广州地区花岗岩残积土进行室内沉井模型试验，并通过试验结果对数值模拟结论进行验证，得出结论如下： 1）在开挖基坑前达到设计强度的旋喷桩能有效减小基坑周边土体塌陷变形、坑底隆起。2）在施加工作顶推力下，前侧主动区首先出现贯通裂缝，竖向位移斜率增大出现明显拐点；继续增大顶推力，土体位移会急剧增大导致地表沉降严重。3）对于后背土体，在顶推力作用下，地表破裂线的切线角度从0°逐渐增大至45°+φ/2，导致破裂范围也不断扩大；达到45°+φ/2处后，继续施加顶推力会导致短轴方向破坏范围扩大的速度较长轴方向的速度更快；三维空间中被动区破坏土体在地表处产生形状为椭圆的破坏面，椭圆长轴方向为顶推轴线方向，被动破坏体呈现为牛角状椭圆楔体。     

Key technologies of ship remote control system in inland waterways under ship-shore cooperation conditions北大核心CSCD

［Objective ］ To meet the requirements of remotely controlling ship in curved, narrow and crowded inland waterways, this paper proposes an approach that consists of CNN-based algorithms and knowledge based models under ship-shore cooperation conditions. ［Method］On the basis of analyzing the characteristics of ship-shore cooperation, the proposed approach realizes autonomous perception of the environment with visual simulation at the core and navigation decision-making control based on deep reinforcement learning, and finally constructs an artificial intelligence system composed of image deep learning processing, navigation situation cognition, route steady-state control and other functions. Remote control and short-time autonomous navigation of operating ships are realized under inland waterway conditions, and remote control of container ships and ferries is carried out. ［Results］The proposed approach is capable of replacing manual work by remote orders or independent decision-making, as well as realizing independent obstacle avoidance, with a consistent deviation of less than 20 meters. ［Conclusions］The developed prototype system carries out the remote control operation demonstration of the above ship types in such waterways as the Changhu Canal Shenzhou line and the Yangtze River, proving that a complete set of algorithms with a CNN and reinforcement learning at the core can independently extract key navigation information, construct obstacle avoidance and control awareness, and lay the foundation for inland river intelligent navigation systems. © 2022 Journal of Clinical Hepatology. All rights reserved.     

钩形外锁闭装置锁闭框组优化的探讨

钩形外锁闭装置在实践中逐步暴露出一些诸如转换不畅、卡阻,磨耗严重,适应尖轨窜动性不良等问题.为此研究探讨对既有的外锁闭装置锁闭框组（包括锁闭框、锁闭铁、耐磨板等）进行优化,提高道岔转换的可靠性.     

船舶海水管系的腐蚀问题及防止措施

船舶海水管系的腐蚀问题是影响使用和维修费用的重要因素。文章针对目前海水管系腐蚀情况,主要分析了船舶管系腐蚀特点和机理,并推断了的影响腐蚀的主要因素,同时提出了几种防腐措施,可供参考。