Socio-demographic and built environment influences on the odds of being overweight or obese: The Atlanta experience

This paper explores the association of socio-demographic and built environment characteristics on the odds of being overweight and obese using data from the Atlanta SMARTRAQ travel survey. A new methodological framework based on a multinomial logit (MNL) model and an enhanced odds ratio plot is presented. The use of an MNL model overcomes limitations of many prior studies that employ a sequence of binary logit models to examine multiple weight categories. The use of an enhanced odds ratio plot provides important information into the relative importance of socio-demographic and built environment characteristics. Several new findings for the Atlanta area result from this study. Socio-demographic variables, including age and educational attainment, exhibit a non-linear relationship with the odds of being overweight or obese. Gender, age, ethnicity, and educational attainment are strongly associated with the odds of being overweight or obese, while income and number of students between 5 and 16 years old in the household have smaller effects. Built environment characteristics such as increased net residential densities and enhanced street connectivity are associated with reductions in the odds of being overweight and/or obese. Relative to socio-demographic variables, however, such built environment characteristics have a much smaller impact on describing the odds of being overweight or obese.     

Assessing the CO2 impact of current and future rail track in the UK

This paper investigates the CO₂ impact of current and future UK rail track and estimates the material, process and transport emissions associated with construction, maintenance and end-of-life activities for designs at high and low traffic loads. Analysis shows that for current track configurations, track with concrete sleepers has the lowest CO₂ impact, followed by steel, hardwood and softwood. Several potential future rail track designs have been analysed including embedded rail and double and quadruple-headed rail. All future track designs have a lower impact than current designs, but this improvement is more marked at high traffic loads. Up to a 40% reduction in CO₂ impact could be achieved if the UK rail network was to move from conventional track design to a double-headed embedded rail design. Key levers for reducing the CO₂ impact of track are identified as service life extension, traffic load reduction and the selection of low impact track designs.     

跨铁路站场斜拉桥静动载试验研究

徐州市和平路跨铁路站场立交桥为独塔双索面预应力混凝土斜拉桥,介绍该桥的静动力试验成果,并结合静动力有限元理论分析,将计算结果与试验结果比对,对该桥现状进行评定。     

考虑稳健性的汽车结构耐撞性优化设计

本文中基于C-NCAP中40%重叠度的偏置碰撞工况对某轿车进行结构耐撞性优化。为提高输出响应的预测精度,使用基于粒子群算法优化的支持向量回归模型来拟合设计变量与输出响应之间的关系,并利用非支配排序多目标遗传算法Ⅱ获得该优化问题的Pareto前沿。在确定性优化的基础上,并考虑产品性能在不确定因素影响下的波动,对其进行稳健性优化设计。最后,对优化结果进行有限元仿真验证。结果表明:优化后,结构质量减轻,耐撞性能明显提升,同时保障了稳定的产品性能。     

Comprehensive lateral driver model for critical maneuvering conditions

A new comprehensive driver model is presented for critical maneuvering conditions with more accurate dynamic control performance. In order to achieve a safe maneuvering mode, a new path planning scheme to maintain stability of the vehicle was designed. A new steering strategy, considering the errors of vehicle position and yaw angle between the real track and the planned path, was established to obtain the steering angle. Therefore, the vehicle can be adjusted to accurately follow the desired path with the driver model, and the stability of the vehicle and the smoothness of the steering angle input were comprehensively considered. Simulation results were used to validate the control performance in comparison with the optimal preview driver model proposed by Macadam.     

Parameter identification for a LuGre model based on steady-state tire conditions

The purpose of this study was to effectively identify parameters for a LuGre friction model based on experimental measures. In earlier work related to this study (Yang et al., 2009), which was based on the characters of polygonal wear (Sueoka and Ryu, 1997), we showed a frictional vibration model for a mass on a moving belt. This model reflected lateral vibrations caused by velocity and toe-in angle. An important aspect of the present study is the improved friction model. A previous friction model, which divided the process into four parts, expressed the sable excited vibration well but failed to reflect the hysteresis loop change when vehicles accelerated or decelerated continuously. A LuGre friction model can solve this problem, but several model parameters must be obtained experimentally. We measured contact width and length of tires as vertical pressure changed; this provided a theoretical basis for apparent stiffness of a unit of tire tread. Based on tire data from Bakker E’s article in a SAE paper from 1987, we identified the Stribeck exponent and Stribeck velocity in LuGre. Then, the results were implemented in a vibration system that verified the rationality of the data.     

Competition and disruption in a dynamic urban supply chain

Rapid changes and complexities in business environments have stressed the importance of interactions between partners and competitors, leading supply chains to become the most important element of contemporary business environments. There is a concomitant need for foresight in describing supply chain performance in all operating environments, including those involving punctuated disruptions. Furthermore, the urban metropolis is now widely recognized to be an environment which is especially vulnerable to supply chain disruptions and for which integrated supply chain decisions can produce very substantial net benefits. Accordingly, this paper presents a dynamic supply chain network model formulated as a differential variational inequality; the model is fashioned to allow consideration of supply chain disruption threats to producers, freight carriers, and retail enterprises. The DVI is solved using a fixed-point algorithm, and a simple numerical example, introduced to illustrate how the impacts of supply chain disruptions may be quantified, is presented.     

Approximate network loading and dual-time-scale dynamic user equilibrium

In this paper we present a dual-time-scale formulation of dynamic user equilibrium (DUE) with demand evolution. Our formulation belongs to the problem class that Pang and Stewart (2008) refer to as differential variational inequalities. It combines the within-day time scale for which route and departure time choices fluctuate in continuous time with the day-to-day time scale for which demand evolves in discrete time steps. Our formulation is consistent with the often told story that drivers adjust their travel demands at the end of every day based on their congestion experience during one or more previous days. We show that analysis of the within-day assignment model is tremendously simplified by expressing dynamic user equilibrium as a differential variational inequality. We also show there is a class of day-to-day demand growth models that allow the dual-time-scale formulation to be decomposed by time-stepping to yield a sequence of continuous time, single-day, dynamic user equilibrium problems. To solve the single-day DUE problems arising during time-stepping, it is necessary to repeatedly solve a dynamic network loading problem. We observe that the network loading phase of DUE computation generally constitutes a differential algebraic equation (DAE) system, and we show that the DAE system for network loading based on the link delay model (LDM) of Friesz et al. (1993) may be approximated by a system of ordinary differential equations (ODEs). That system of ODEs, as we demonstrate, may be efficiently solved using traditional numerical methods for such problems. To compute an actual dynamic user equilibrium, we introduce a continuous time fixed-point algorithm and prove its convergence for effective path delay operators that allow a limited type of nonmonotone path delay. We show that our DUE algorithm is compatible with network loading based on the LDM and the cell transmission model (CTM) due to Daganzo (1995). We provide a numerical example based on the much studied Sioux Falls network.