清华园隧道大直径泥水盾构始发控制掘进分析

清华园隧道某区间采用泥水盾构穿越粉质黏土及砂卵石地层,是全线典型质构法施工隧道。总结清华园隧道盾构始发的经验,对其掘进参数及反力架等工程构件布置进行研究,并采用有限元软件对反力架进行静强度分析计算。研究表明：(1)盾构机在粉质黏土及砂卵石地层中掘进时,反力架最大应力为270 MPa,最大静挠度为7.77 mm;(2)掘削量大小与泥水密度、黏度和切口水压等数值相关;(3)反力架上的应力分布在钢管支撑处最高,竖梁次之,横梁最小。     

空气悬架系统的干涉应力分析

由于国内特殊的路面条件,导致有些国外比较成熟的产品在国内却出现了很多故障。以几种国内客车常用的典型空气悬架系统的结构分析为例,分析了“干涉应力”产生的原因及可能产生的后果。指出:大部分空气悬架发生故障是由于悬架系统存在“干涉应力,”而悬架结构设计不合理是导致悬架系统产生“干涉应力”的主要原因。建议在设计悬架系统时,尽量避免导致系统产生“干涉应力”的结构出现。     

油束空间分布锥角对柴油可控预混压燃燃烧排放影响的试验研究

在柴油可控预混压燃燃烧模式下,进行了油束空间分布锥角及多脉冲参数对排放影响的研究。试验结果表明,在采用155°和125°油束空间分布锥角的两种油嘴时,通过改变多脉冲喷射定时均可控制预混燃烧放热幅度,但对NOx、HC和CO排放的影响不同;在3次和6次多脉冲喷射条件下,采用小分布锥角(125°)油嘴能够增加有效贯穿距离,提高气缸轴线方向的空气利用率,从而在大脉冲喷射定时条件下改善CO排放,并且可减少50%以上的HC排放。     

一种小型单轨游览车用抗侧滚装置

随着跨座式单轨游览车的广泛使用,部分小型跨座式单轨车体较轻,弹簧偏软,为保证乘客乘坐舒适,本文基于地铁使用抗侧滚装置,并结合牯牛降单轨游览列车悬挂结构设计一款小型单轨游览车用抗侧滚装置,计算验证其抗侧滚效果。     

一种新型小型单轨游览车牵引悬挂装置

随着跨座式单轨火车的发展,部分小型单轨高架游览车车厢较小,车厢重量较轻,采用的单节车厢设置一个转向架的结构,现有的单轨车牵引悬挂系统不适用于此类结构,故本文基于该状况,设计开发一种新型小型单轨游览车牵引悬挂装置。     

Regularization Method to the Parameter Identification of Interfacial Heat Transfer Coefficient and Properties during Casting Solidification

The accurate material physical properties, initial and boundary conditions are indispensable to the numerical simulation in the casting process, and they are related to the simulation accuracy directly. The inverse heat conduction method can be used to identify the mentioned above parameters based on the temperature measurement data. This paper presented a new inverse method according to Tikhonov regularization theory. A regularization functional was established and the regularization parameter was deduced, the Newton-Raphson iteration method was used to solve the equations. One detailed case was solved to identify the thermal conductivity and specific heat of sand mold and interfacial heat transfer coefficient (IHTC) at the meantime. This indicates that the regularization method is very efficient in decreasing the sensitivity to the temperature measurement data, overcoming the ill-posedness of the inverse heat conduction problem (IHCP) and improving the stability and accuracy of the results. As a general inverse method, it can be used to identify not only the material physical properties but also the initial and boundary conditions' parameters.     

货车转向架的双线性悬挂

介绍了俄罗斯和乌克兰铁路25 t轴重货车转向架采用的双线性悬挂,以及为防止不良响应所采取的措施.     

Transport energy consumption in mountainous roads. A comparative case study for internal combustion engines and electric vehicles in Andorra

This paper analyses transport energy consumption of conventional and electric vehicles in mountainous roads. A standard round trip in Andorra has been modelled in order to characterise vehicle dynamics in hilly regions. Two conventional diesel vehicles and their electric-equivalent models have been simulated and their performances have been compared. Six scenarios have been simulated to study the effects of factors such as orography, traffic congestion and driving style. The European fuel consumption and emissions test and Artemis urban driving cycles, representative of European driving cycles, have also been included in the comparative analysis. The results show that road grade has a major impact on fuel economy, although it affects consumption in different levels depending on the technology analysed. Electric vehicles are less affected by this factor as opposed to conventional vehicles, increasing the potential energy savings in a hypothetical electrification of the car fleet. However, electric vehicle range in mountainous terrains is lower compared to that estimated by manufacturers, a fact that could adversely affect a massive adoption of electric cars in the short term.     

Identifying tourists and analyzing spatial patterns of their destinations from location-based social media data

Reliable travel behavior data is a prerequisite for transportation planning process. In large tourism dependent cities, tourists are the most dynamic population group whose size and travel choices remain unknown to planners. Traditional travel surveys generally observe resident travel behavior and rarely target tourists. Ubiquitous uses of social media platforms in smartphones have created a tremendous opportunity to gather digital traces of tourists at a large scale. In this paper, we present a framework on how to use location-based data from social media to gather and analyze travel behavior of tourists. We have collected data of about 67,000 users from Twitter using its search interface for Florida. We first propose several filtering steps to create a reliable sample from the collected Twitter data. An ensemble classification technique is proposed to classify tourists and residents from user coordinates. The accuracy of the proposed classifier has been compared against the state-of-the-art classification methods. Finally, different clustering methods have been used to find the spatial patterns of destination choices of tourists. Promising results have been found from the output clusters as they reveal most popular tourist spots as well as some of the emerging tourist attractions in Florida. Performance of the proposed clustering techniques has been assessed using internal clustering validation indices. We have analyzed temporal patterns of tourist and resident activities to validate the classification of the users in two separate groups of tourists and residents. Proposed filtering, identification, and clustering techniques will be significantly useful for building individual-level tourist travel demand models from social media data.     

Capturing correlation with a mixed recursive logit model for activity-travel scheduling

Representing activity-travel scheduling decisions as path choices in a time–space network is an emerging approach in the literature. In this paper, we model choices of activity, location, timing and transport mode using such an approach and seek to estimate utility parameters of recursive logit models. Relaxing the independence from irrelevant alternatives (IIA) property of the logit model in this setting raises a number of challenges. First, overlap in the network may not fully characterize perceptual correlation between paths, due to their interpretation as activity schedules. Second, the large number of states that are needed to represent all possible locations, times and activity combinations imposes major computational challenges to estimate the model. We combine recent methodological developments to build on previous work by Blom Västberg et al. (2016) and allow to model complex and realistic correlation patterns in this type of network. We use sampled choices sets in order to estimate a mixed recursive logit model in reasonable time for large-scale, dense time-space networks. Importantly, the model retains the advantage of fast predictions without sampling choice sets. In addition to estimation results, we present an extensive empirical analysis which highlights the different substitution patterns when the IIA property is relaxed, and a cross-validation study which confirms improved out-of-sample fit.