基于CAD2AME的飞机液压系统流阻计算方法

飞机液压系统包含泵源系统、管路系统、附件和用户系统,飞机管路系统是飞机泵源和用户之间的纽带,液压管路流阻特性决定了用户系统入口的压力和流量,影响用户动静态响应性能,特别是对一些伺服作动系统。传统流阻特性计算方法主要针对稳态工况计算,难以实现动态响应计算,且对工作人员要求高、计算工作量大。随着全三维设计应用于飞机液压管路系统设计制造,为基于计算机的流阻特性仿真分析提供了可能。本文介绍和对比了三种计算方法,选取了较优的CAD2AME方法对某飞机局部液压管路系统流阻特性进行仿真分析,证明该方法可快速准确的对飞机液压管路进行分析。     

智慧高速公路设计案例分析

本文以某智慧高速的设计案例为依托,首先对国内外智慧高速发展和应用现状进行归纳总结,分析认为电动化、智能化的新型运载工具,信息化和功能专业化的基础设施,开放、共享、协同的管理与服务将是未来高速公路三大发展趋势。通过对高速公路使用者和管理者的需求针对性地精准分析,构建面向高速公路使用者和管理者的创新型应用服务。结合新技术的发展趋势,以服务需求为导向,建设"三网合一"智慧高速基础设施和智慧云控平台构成、数据流为驱动的、"开放、包容、创新"的智慧高速公路。基于案例分析的智慧高速规划设计全过程,对于国内智慧高速的整体设计和建设规划具有重要参考价值,探索开辟全新的高速公路智能化建设方向和思路。     

A Delphi analysis on green performance evaluation indices for ports in China

This study identified a set of applicable and practical green performance evaluation indices for Chinese ports using the Delphi technique. The research was conducted by targeting three representative Chinese ports in Eastern China: the Shanghai Port, Ningbo Port, and Qingdao Port. An effective expert panel was structured with direct stakeholders related to green performance, which was based on a sufficient consideration of the unique and the special decision-making system for Chinese ports. Twenty-one green performance indices in six dimensions (i.e. liquid pollution management, air pollution management, noise control, low carbon regulations and energy savings, marine biology preservation, and organization and management) were eventually identified through three rounds of iterations. The identified green performance indices for Chinese ports are highly consistent with the Chinese Government’s environmental policies. Compared with European ports, the green port performance indicators in China are not as comprehensive. The indicators that are strictly consistent with national macro policies and the factors that are more easily seen, heard, and felt were perceived to be more important. From an academic perspective, this study offers a new approach for system establishment and green practice criteria exploration and thus provides a significant basis for further green port studies.     

Incorporating the extended theory of planned behavior in a school travel mode choice model: a case study of Shaoxing,China

Travel to and from school can have social, economic, and environmental implications for students and their parents. Therefore, understanding school travel mode choice behavior is essential to find policy-oriented approaches to optimizing school travel mode share. Recent research suggests that psychological factors of parents play a significant role in school travel mode choice behavior and the Multiple Indicators and Multiple Causes (MIMIC) model has been used to test the effect of psychological constructs on mode choice behavior. However, little research has used a systematic framework of behavioral theory to organize these psychological factors and investigate their internal relationships. This paper proposes an extended theory of planned behavior (ETPB) to delve into the psychological factors caused by the effects of adults’ cognition and behavioral habits and explores the factors’ relationship paradigm. A theoretical framework of travel mode choice behavior for students in China is constructed. We established the MIMIC model that accommodates latent variables from ETPB. We found that not all the psychological latent variables have significant effects on school travel mode choice behavior, but habit can play an essential role. The results provide theoretical support for demand policies for school travel.     

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.     

����ϵ�����ڳǼʸ�������������е�Ӧ��

高速铁路为人们提供了一种高效的运输方式.本文借鉴弹性系数法的相关理论,首先运用广义费用函数测算样本中高铁开通前后两地区综合客运成本的变化,结合两地区高铁开通前后客运量的变化得到了运输成本弹性系数,用于衡量两地区对于高铁开通的迫切性程度,从而在另一个层面衡量高铁建设的可行性.然后根据运输经济学及新经济地理学的相关理论,从人口、距离、人均GDP差异、平均人均GDP和产业结构相似度5个维度对样本的运输成本弹性系数进行建模,运用神经网络的方法来拟合其对运输成本弹性系数的影响情况,并以此为依据来测算北京市和张家口市对即将开通的京张高铁的迫切性程度.     

Accessibility and transport infrastructure improvement assessment: The role of borders and multilateral resistance

The market potential indicator is a commonly used tool in transport planning for evaluating the potential economic effects derived from improvements in transport infrastructures. The general assumption is that exports from a given region will rise with increased accessibility, thus benefiting economic activities. However, the specification of the market potential model is typically very simple and ignores both the impact of competing rivals and the role of international borders, which leads to unrealistic results. Spatial interaction models on bilateral trade have already proved that international trade is affected by multilateral resistance, borders, adjacency, language or currency. Nevertheless, apart from some recent analyses that simply calibrate the distance decay parameter from trade datasets, these variables have hardly been integrated into research on market potential. This paper sets out to demonstrate that more realistic results are obtained by calibrating the distance-decay parameter and introducing the impact of competing rivals and border effects into the market potential formulation. The proposed model is then applied to the assessment of the accessibility impacts of new road transport infrastructure in the European Union between 2001 and 2012, which shows that the greatest improvements in accessibility were experienced by peripheral countries with high road infrastructure investment.     

Does crowding affect the path choice of metro passengers?

This paper investigates crowding effect on the path choice of metro passengers. We show people reroute not only to avoid the delay from crowding but also to evade crowding itself. More specifically, a logit model fits best when it uses the transit delay from crowding as well as the passenger load of a connection in addition to the conventional explanatory variables. Also, we demonstrate that crowding decreases the overall welfare of metro passengers. The model is tested on the real path choice data acquired by the recent algorithm by Hong et al. (2015) known to detect the real path choice from Smart Card data in more than 90% of the cases.     

Empirical analysis of short period traffic counts and their efficiency: the case of Indian traffic

Short period traffic counts (SPTCs) are conducted routinely to estimate the annual average daily traffic (AADT) at a particular site. This paper uses Indian traffic volume data to methodically and extensively study the effect of four aspects related to the design of SPTCs. These four aspects are: (i) for how long, (ii) on which days should SPTCs be carried out, (iii) how many times, and (iv) on which months should SPTCs be carried out? The analyses indicate that the best durations for conducting SPTCs are 3 days (starting with a Thursday) and 7 days, for total traffic and truck traffic, respectively. Further, these counts should be repeated twice a year keeping a separation of two months between the counts to obtain good estimates of AADT at minimal cost. An additional outcome of this study has been the determination of seasonal factor values for roads in developing economies, like India.     

引气剂对硬化混凝土力学性能与气泡特征参数的影响

对比研究了烷基苯磺酸盐类与皂甙类引气剂对混凝土力学性能和硬化后含气量、气泡间距系数、孔径分布、气泡平均直径等气泡特征参数的影响。结果表明:当新拌混凝土含气量小于6.5%时,随着含气量的增大,混凝土的抗折强度基本不受影响,抗压强度显著降低,混凝土的折压比提高,脆性显著降低,韧性大幅提高;与新拌混凝土的含气量相比,硬化后混凝土的含气量大幅降低;随着混凝土含气量的逐渐增加,硬化后混凝土的气泡间距系数减小,气泡平均直径降低,气泡总数提高。另外,烷基苯磺酸盐类引气剂比皂甙类引气剂的稳泡性能更好,可使硬化后的混凝土气泡结构更优。