Do changes in neighborhood characteristics lead to changes in travel behavior? A structural equations modeling approach

Suburban sprawl has been widely criticized for its contribution to auto dependence. Numerous studies have found that residents in suburban neighborhoods drive more and walk less than their counterparts in traditional environments. However, most studies confirm only an association between the built environment and travel behavior, and have yet to establish the predominant underlying causal link: whether neighborhood design independently influences travel behavior or whether preferences for travel options affect residential choice. That is, residential self-selection may be at work. A few studies have recently addressed the influence of self-selection. However, our understanding of the causality issue is still immature. To address this issue, this study took into account individuals’ self-selection by employing a quasi-longitudinal design and by controlling for residential preferences and travel attitudes. In particular, using data collected from 547 movers currently living in four traditional neighborhoods and four suburban neighborhoods in Northern California, we developed a structural equations model to investigate the relationships among changes in the built environment, changes in auto ownership, and changes in travel behavior. The results provide some encouragement that land-use policies designed to put residents closer to destinations and provide them with alternative transportation options will actually lead to less driving and more walking.

Modeling residential sorting effects to understand the impact of the built environment on commute mode choice

This paper presents an examination of the significance of residential sorting or self selection effects in understanding the impacts of the built environment on travel choices. Land use and transportation system attributes are often treated as exogenous variables in models of travel behavior. Such models ignore the potential self selection processes that may be at play wherein households and individuals choose to locate in areas or built environments that are consistent with their lifestyle and transportation preferences, attitudes, and values. In this paper, a simultaneous model of residential location choice and commute mode choice that accounts for both observed and unobserved taste variations that may contribute to residential self selection is estimated on a survey sample extracted from the 2000 San Francisco Bay Area household travel survey. Model results show that both observed and unobserved residential self selection effects do exist; however, even after accounting for these effects, it is found that built environment attributes can indeed significantly impact commute mode choice behavior. The paper concludes with a discussion of the implications of the model findings for policy planning.

基于区位重要度的县乡公路网交通生成预测方法研究

通过分析县乡公路网建设与社会经济发展的相互关系,结合县乡公路网的特点,从经济发展度、连通度和导向度三个方面定义交通小区的重要度,建立基于区位重要度的县乡公路网交通生成模型。永定县县乡公路网规划实例使得该方法的合理性和有效性得到了验证。     

Detection of captopril based on its enhanced resonance light scattering signals of fluorosurfactant-capped gold nanoparticles

In this study, based on its enhancement effect on resonance light scattering (RLS) of fluorosurfactant (FSN)-capped gold nanoparticles (GNPs), we reported a simple approach for the rapid sensing of captopril. Under optimum conditions, the lowest detectable concentration of captopril through this approach (S/N=3) was 0.01μg/mL. The calibration curve was linear over the range of 0.08-4.0μg/mL for the detection of captopril. The recoveries of captopril were found to fall in the range between 99% and 100%. We have validated the applicability of our method through the analyses of captopril in pharmaceutical formulations. Good agreements were obtained for the determination of captopril between the present approach and official method.     

Integration of experiment and hydrostatic fluid-structure finite element analysis into dynamic characteristic prediction of a hydraulically damped rubber mount

Hydraulically damped rubber mount (HDM) can effectively attenuate vibrations transmitted between an automotive powertrain and body/chassis and reduce interior noise in the car compartment. Predicting the dynamic characteristics of a HDM faces challenges due to fluid-structure interactions between the rubber spring and fluid in the chambers, nonlinear material properties of the rubber parts and turbulent flow in the chambers and fluid track linking chambers. In this paper, an experimental analysis and hydrostatic finite element (FE) modeling technique are integrated in a numerical simulation approach to modeling the dynamic characteristics of a HDM with a lumped-parameter HDM model. The dynamic characteristics of a typical HDM with a fixed decoupler are predicted and compared with experimental results, which verify the effectiveness of the proposed approach. Moreover, a parametric effect analysis is performed to demonstrate parameter influence on dynamic characteristic, which provides a concise design guideline for the parameter adjustments necessary for a HDM to meet the vibration isolation requirements of a powertrain mount system.     

深汕西高速公路浸水路段路基稳定性的评估

借助室内试验、可靠度分析和有限元技术,采用Duncan-Chang非线性本构关系,建立了土性参数随机场模型,对深汕西高速公路浸水路段路基的稳定性进行了评估。评估得出的结论与现场监测反馈的结果相一致,从而证实了采用非线性摄动随机有限元法评估浸水路段路基稳定性可靠度是可行的,可供今后类似的工程处理提供借鉴。     

基于蚁群优化算法与出租车GPS数据的公众出行路径优化

以出租车GPS采集的浮动车数据为依据,研究出租车驾驶员路径选择的认知及类蚂蚁的行为特征。根据城市道路功能等级与出租车的通行频率等信息素,建立出租车驾驶员路径选择信息素等级路网,并以此作为路网初始信息素,综合考虑路径通行时间、通行距离、路径信息素等级等多个因素,提出了基于蚁群优化算法的公众出行路径规划优化算法。以武汉市路网和浮动车为试验数据,将模型规划的道路与浮动车数据库中的轨迹进行了比较。结果表明:基于蚁群优化算法与出租车GPS数据的公众出行路径同出租车驾驶员选择的出行路径相似度很高,能为公众出行提供出租车驾驶员选择的行车路径。     

Superpave技术应用于醴茶高速公路沥青路面的可行性分析

在介绍Superpave技术和分析马歇尔设计方法存在问题的基础上,分析了Superpave技术应用醴茶高速公路沥青路面的可行性。应用Superpave理念对醴茶高速路面结构进行了优化,对比了优化方案的经济性,同时对Superpave的施工要点进行分析,以保证Superpave技术在施工中能够得到良好实现。     

Effects of split injection,oxygen enriched air and heavy EGR on soot emissions in a diesel engine

The effects of split injection, oxygen enriched air, and heavy exhaust gas recirculation (EGR) on soot emissions in a direct injection diesel engine were studied using the KIVA-3V code. When split injection is applied, the second injection of fuel into a cylinder results in two separate stoichiometric zones, which helps soot oxidation. As a result, soot emissions are decreased. When oxygen enriched air is applied together with split injection, a higher concentration of oxygen causes higher temperatures in the cylinder. The increase in temperature promotes the growth reaction of acetylene with soot. However, it does not improve acetylene formation during the second injection of fuel. As more acetylene is consumed in the growth reaction with soot, the concentration of acetylene in the cylinder is decreased, which leads to a decrease in soot formation and thus soot emissions. A combination of split injection, a high concentration of oxygen, and a high EGR ratio shows the best results in terms of diesel emissions. In this paper, the split injection scheme of 75.8.25, in which 75% of total fuel is injected in the first pulse, followed by 8°CA of dwell time, and 25% of fuel is injected in the second pulse, with an oxygen concentration of 23% in volume and an EGR ratio of 30% shows a 45% reduction in soot emissions, with the same NOx emissions as in single injection.     

Multi-response optimization of diesel engine performance parameters using thumba biodiesel-diesel blends by applying the Taguchi method and grey relational analysis

This paper presents an experimental study that involves an application of the Taguchi method and grey relational analysis to determine the optimum factor level to obtain optimum multiple-performance characteristics of a diesel engine run with different low-percentage thumba biodiesel-diesel blends. Four factors, namely, low-percentage thumba biodiesel-diesel blend, compression ratio, nozzle opening pressure and injection timing were each considered at three levels. An L₉ orthogonal array was used to collect data for various engine performance- and emission-related responses under different engine loads. The signal-to-noise (S/N) ratio and grey relational analysis were used for data analysis. The results of the study revealed that the combination of a blend consisting of 30% thumba biodiesel (B30), a compression ratio of 14, a nozzle opening pressure of 250 bar and an injection timing of 20° produces maximum multiple performance of a diesel engine with minimum multiple emissions from the engine.