A design method of tensile triangles and low transformation temperature weld metal for reduction of stress concentration and residual stress of welded joints

Stress concentration and residual stress have a significant influence on fatigue life of welded joints. In order to reduce the stress concentration of welded joints, a mathematical design method of tensile triangles (MTT) based on bionics was applied to weld shape design. Accordingly, the stress concentration of various weld beads in the corner boxing welded joint and the fillet welded T-joint was dissected using our in-house FEM software JWRIAN. It was found that there existed a large stress concentration in the conventional welded joints, whereas those welded joints with elongated weld bead were accompanied by a lower stress concentration, especially for elongated weld bead with MTT design. Furthermore, among the weld shapes of the corner boxing fillet welded joint, the rectangle shape of weld bead had the minimum stress concentration factor (1.05). For the fillet welded T-joint with MTT design, the stress concentration of weld toe decreased dramatically with the increase of the index of designed shape, but there was a minor difference of stress concentration at weld root between the weld beads with MTT design. In addition, application of low transformation temperature (LTT) weld metal utilizing martensitic transformation to the fillet welded T-joints can produce compressive residual stress at weld toe.     

舰船加筋板局部强度评估中的总纵应力折减系数研究

舰船加强筋尺寸的合理确定一直是结构设计中的热点问题。本文综合考虑总纵弯曲应力和局部载荷的相互作用,研究加强筋的许用应力折减系数(C_s)的影响因素与合理取值方法。通过分析加强筋的力学模型、对比不同规范中的C_s取值,以及用非线性有限元软件Abaqus计算一系列加筋板模型,拟合C_s曲线并与规范对比,并验证剖面对称性和局部载荷作用方向对C_s取值的影响方式,丰富了舰船局部强度校核方法的技术背景,为板架设计、舰船三维局部校核程序开发提供借鉴。     

兰州地铁地温分布特性及其演化规律

以兰州地铁所在地区为研究对象,实测地铁隧道开挖前的地温(简称为初始地温),根据实测数据,提出地铁初始地温预测模型公式。采用非稳态传热的数值模型,分析运营条件下地铁隧道围岩温度的演化规律。结果表明:兰州地铁初始地温随环境气温和埋深的变化而变化;年变温层位于自地表至埋深12m处;年恒温层位于埋深12m及其以下,温度为15℃左右;年变温层中,1年内初始地温变化规律与环境气温变化规律相似,近似呈正弦曲线状分布,但存在相位滞后的现象;1年中初始地温的振幅随埋深的增大呈指数下降趋势。在隧道内空气与围岩之间热交换中,兰州地铁隧道围岩的温度及其梯度、热透厚度(未达到极限时)均与隧道内环境温度、热交换时间成正相关关系,但与距隧道内壁的距离成负相关关系。     

25t轴重荷载作用下隧底脱空区域受力特性分析

为了研究在役铁路隧道在通车之后隧底脱空病害的问题,采用有限元理论,建立隧道脱空区域在围岩压力与25 t轴重列车动载作用下的数值计算模型,主要研究80 cm与40 cm脱空宽度分别距隧道中心线0,80 cm与160 cm时脱空区域的受力特性。结果表明:在围岩压力下,脱空区域中线上壁和外侧顶角混凝土中产生拉应力及内侧顶角中产生压应力,其中压应力对脱空的宽度更为敏感;同时施加列车动载作用时,脱空区域上壁出现了竖向动应力与横向拉应力,得到了脱空区域力学指标的最大响应值及其出现的具体位置,宽度的增加对脱空区上壁横向拉应力更为显著,上壁横向拉应力增幅超过200%,竖向动应力增幅达50%。因此,隧底脱空区周围应力分布复杂,拉应力与压应力在脱空区域同时存在,应力突变严重,对脱空现象应及时组织处理。     

含碎石化层的沥青加铺路面结构分析

利用ABAQUS有限元软件建立了含碎石化层的沥青加铺路面结构模型,研究土基、旧路基层与碎石化层模量以及碎石化层和加铺层厚度对含碎石化层沥青加铺层路面结构的力学响应的影响,确定碎石化模量的控制范围.结果表明,荷载作用中心点及附近一定区域,沥青加铺层层底受拉;沥青加铺层层底拉应力对土基模量、旧路基层模量、碎石化层厚度不敏感,但当碎石化层模量较小(接近300MPa)或加铺层厚(大于20cm)时层底拉应力均较大,在重载作用下更大.因此碎石化道路必须验算沥青层层底拉应力指标.为使沥青层层底拉应力峰值不至于过大甚至超过容许拉应力,使得受拉区域控制在一定范围以内,同时为降低加铺层竖向剪应力及土基顶面压应变,并达到防治反射裂缝的效果,碎石化层的模量宜控制在500～1000MPa.     

Analysis of cross effect on inherent deformation during the line heating process – Part 1 – Single crossed heating lines

This paper describes the effect of previous heating on inherent deformation by a subsequent heating line, more specifically, the case of two heating lines intersecting (crossing) each other. The paper has been divided into two parts. In the first part, the case of single crossed heating lines is studied in detail. The second part of the paper, discusses the case of more than one crossed heating lines. The novelty of the work lies in revealing the cross effect and how, factors such as, for example, the heating condition and the plate geometry, influence the resulting inherent deformation of crossed heating. In addition, relationships to easily get these influences are provided. The results are suitable for a wide range of heating conditions and plate thickness.     

Privacy-preserving MaaS fleet management

On-demand traffic fleet optimization requires operating Mobility as a Service (MaaS) companies such as Uber, Lyft to locally match the offer of available vehicles with their expected number of requests referred to as demand (as well as to take into account other constraints such as driver’s schedules and preferences). In the present article, we show that this problem can be encoded into a Constrained Integer Quadratic Program (CIQP) with block independent constraints that can then be relaxed in the form of a convex optimization program. We leverage this particular structure to yield a scalable distributed optimization algorithm corresponding to computing a gradient ascent in a dual space. This new framework does not require the drivers to share their availabilities with the operating company (as opposed to standard practice in today’s mobility as a service companies). The resulting parallel algorithm can run on a distributed smartphone based platform.     

横梁端部节点优化

通过有限元计算,对比几种常见的横梁端部连接方式,综合考虑结构整体强度、钢材使用量、舱室空间利用率、施工便利性等方面的影响因素,确定较优的连接过渡方式和过渡结构的参数尺寸,为船舶设计横梁端部节点形式的确定提供参考。     

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.     

Commuting and wellbeing: a critical overview of the literature with implications for policy and future research

ABSTRACT

This review provides a critical overview of what has been learnt about commuting’s impact on subjective wellbeing (SWB). It is structured around a conceptual model which assumes commuting can affect SWB over three time horizons: (i) during the journey; (ii) immediately after the journey; and (iii) over the longer term. Our assessment of the evidence shows that mood is lower during the commute than other daily activities and stress can be induced by congestion, crowding and unpredictability. People who walk or cycle to work are generally more satisfied with their commute than those who travel by car and especially those who use public transport. Satisfaction decreases with duration of commute, regardless of mode used, and increases when travelling with company. After the journey, evidence shows that the commute experience “spills over” into how people feel and perform at work and home. However, a consistent link between commuting and life satisfaction overall has not been established. The evidence suggests that commuters are generally successful in trading off the drawbacks of longer and more arduous commute journeys against the benefits they bring in relation to overall life satisfaction, but further research is required to understand the decision making involved. The evidence review points to six areas that warrant policy action and research: (i) enhancing the commute experience; (ii) increasing commute satisfaction; (iii) reducing the impacts of long duration commutes; (iv) meeting commuter preferences; (v) recognising flexibility and constraints in commuting routines and (vi) accounting for SWB impacts of commuting in policy making and appraisal.