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141.
为考虑岩石内微裂纹间相互作用对岩石损伤的影响,基于广义自洽理论研究岩石材料的损伤效应,建立了反映荷载作用下的岩石微裂纹发展变化损伤本构模型;采用概率统计理论,对岩石损伤模型中微裂纹密度演变过程进行探讨;以模式分层优化算法反分析确定模型参数,并结合工程实例对岩石微裂纹统计损伤模型及参数确定方法进行了验证。研究结果表明,基于广义自洽理论的岩石微裂纹统计损伤本构模型能够反应岩石内微裂纹间的相互影响的工程实际,模式分层优化算法确定的模型参数真实可信,在工程应用中具有一定适用价值。 相似文献
142.
起动机/发电机/电动机一体化技术的ISG的技术主要应用在轻度混合动力汽车上.主要介绍了ISG系统结构组成、工作原理,以及对国内外车用ISG系统发展现状的分析,并指出了ISG系统的关键技术及发展趋势.这种技术结构简单,成本较低,能够很好应用在传统的汽车上,具有很好的应用前景. 相似文献
143.
分析简单混联式混合动力客车动力系统的结构;基于混合动态系统理论制定能量管理策略,并且通过仿真将该方案与原车进行比较.仿真结果表明,采用该方案的车辆动力性有所改善,燃油经济性有显著提高. 相似文献
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Competition and disruption in a dynamic urban supply chain 总被引:1,自引:0,他引:1
Terry L. Friesz Ilsoo Lee Cheng-Chang Lin 《Transportation Research Part B: Methodological》2011,45(8):1212-1231
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. 相似文献
147.
Terry L. Friesz Taeil Kim Changhyun Kwon Matthew A. Rigdon 《Transportation Research Part B: Methodological》2011,45(1):176-207
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. 相似文献
148.
Xinkai WuHenry X. Liu 《Transportation Research Part B: Methodological》2011,45(10):1768-1786
In this paper a new traffic flow model for congested arterial networks, named shockwave profile model (SPM), is presented. Taking advantage of the fact that traffic states within a congested link can be simplified as free-flow, saturated, and jammed conditions, SPM simulates traffic dynamics by analytically deriving the trajectories of four major shockwaves: queuing, discharge, departure, and compression waves. Unlike conventional macroscopic models, in which space is often discretized into small cells for numerical solutions, SPM treats each homogeneous road segment with constant capacity as a section; and the queuing dynamics within each section are described by tracing the shockwave fronts. SPM is particularly suitable for simulating traffic flow on congested signalized arterials especially with queue spillover problems, where the steady-state periodic pattern of queue build-up and dissipation process may break down. Depending on when and where spillover occurs along a signalized arterial, a large number of queuing patterns may be possible. Therefore it becomes difficult to apply the conventional approach directly to track shockwave fronts. To overcome this difficulty, a novel approach is proposed as part of the SPM, in which queue spillover is treated as either extending a red phase or creating new smaller cycles, so that the analytical solutions for tracing the shockwave fronts can be easily applied. Since only the essential features of arterial traffic flow, i.e., queue build-up and dissipation, are considered, SPM significantly reduces the computational load and improves the numerical efficiency. We further validated SPM using real-world traffic signal data collected from a major arterial in the Twin Cities. The results clearly demonstrate the effectiveness and accuracy of the model. We expect that in the future this model can be applied in a number of real-time applications such as arterial performance prediction and signal optimization. 相似文献
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Xuegang Ban Peng Hao Zhanbo Sun 《Transportation Research Part C: Emerging Technologies》2011,19(6):1133-1156
We study how to estimate real time queue lengths at signalized intersections using intersection travel times collected from mobile traffic sensors. The estimation is based on the observation that critical pattern changes of intersection travel times or delays, such as the discontinuities (i.e., sudden and dramatic increases in travel times) and non-smoothness (i.e., changes of slopes of travel times), indicate signal timing or queue length changes. By detecting these critical points in intersection travel times or delays, the real time queue length can be re-constructed. We first introduce the concept of Queue Rear No-delay Arrival Time which is related to the non-smoothness of queuing delay patterns and queue length changes. We then show how measured intersection travel times from mobile sensors can be processed to generate sample vehicle queuing delays. Under the uniform arrival assumption, the queuing delays reduce linearly within a cycle. The delay pattern can be estimated by a linear fitting method using sample queuing delays. Queue Rear No-delay Arrival Time can then be obtained from the delay pattern, and be used to estimate the maximum and minimum queue lengths of a cycle, based on which the real-time queue length curve can also be constructed. The model and algorithm are tested in a field experiment and in simulation. 相似文献