公路路面施工机械的优化配置方法

建立了公路路面基层施工机械优化配置的数学模型，并以一实际公路路面工程为例，经计算表明该模型是正确且有效的，适用于公路路面施工工程的机械设备选型与配置，以及校核公路路面施工机械设备是否达到优化配置。     

中意车前围改型设计及模型制作

介绍了中意车前围改型的全部过程，对概念设计、全尺寸模型的制作、涂装评审等方面作了全面的阐述，以两个1：1模型为例介绍了三维造型中经常遇到的难点问题和解决方法。     

具有迟滞模拟记忆功能的奥迪盘式制动器可变线性模型

本文以奥迪１００盘式制动器为研究对象，建立了一种可模拟制动压力－力矩响应迟清点特性的可变线性模型，首先，介绍在ＪＦ－１３２型汽车制动器试验台上进行防抱制动器模拟试验的方法，其次，在获得大量试验数据的基础上，运用曲线拟合和优化技术，建立制动压力－力矩关系的线性模型，心滞模型为线笥模型，最后，在相同制动压力输入的前提下，把模型的理论计算民试验结果进行对比分析了模型的有效性和精确性。     

盘式制动器制动尖叫计算模型的建立

借助于有限元和模态综合技术，建立了盘式制动器制动尖叫的摩擦耦合模型。通过复特征分析，得到了对应于每阶段动模态的阻尼与频率，模态阻尼值揭示了哪 些模态不稳定并有可能产生尖叫；最后运用耦合模型研究了摩擦系数和子结构模态对制动尖叫的影响。     

轮胎垂直振动动力学模型

本文提出一种自适应轮膜模型参数的简易测定方法，给出轮胎垂直振动动力学方程及相应的求解方法，并进行计算分析与试验测定。将分析结果与通常的点接触式模型相比较，对点接触式模型及本文所建立的自适应模型做了综合评价，结果表明，本模型的计算结果是令人满意的。     

采用模型设计和模型试验方法研制大型泵

本文对采用模型设计和模型试验方法研制大型离心泵的计算理论，结构设计和材料选用等问题进行了探讨，确认了只有在正确运用相似计算公式的前提下才能保证相似设计可靠性的观点，验证了叶轮进口截面几何形状对离心泵汽蚀性能和效率值的影响，并提出了国内现有的能较好满足船艇货油泵运转条件的材料组合建议方案。     

均匀设计在尾压浪板设计中的应用

本文利用均匀设计法设计了一个尾压浪板系列,从中优化出一个方案,解决排水型船加装尾压浪板在巡航速度附近减阻的问题,减阻效率达裸体阻力４％以上,对尾压浪板在排水型船上减阻的机理进行了初步分析,得到了船后体压力 尾压浪板对主船体阻主要原因这一结论。     

Unsteady finite-depth effects during resistance tests on a ship model in a towing tank

This paper covers an extension of the study of Doctors et al. (J Ship Res 52(4):263–273, 2008) on oscillations in wave resistance during the constant-velocity phase of a towing-tank resistance test on a ship model to the case of relatively shallow water. We demonstrate here that the unsteady effects are very prominent and that it is essentially impossible to achieve a steady-state resistance curve in a towing tank of typical proportions for a water-depth-to-model-length ratio of 0.25. This statement is particularly true in the speed region near a depth Froude number of unity. However, on the positive side, we show here that an application of unsteady linearized wave-resistance theory provides an excellent prediction of the measured total resistance, when one accounts for the form factor in the usual manner. Finally, a simple application of the results to the planning and analysis of towing-tank tests is presented.     

Ant Colony Routing algorithm for freeway networks

Dynamic traffic routing refers to the process of (re)directing vehicles at junctions in a traffic network according to the evolving traffic conditions. The traffic management center can determine desired routes for drivers in order to optimize the performance of the traffic network by dynamic traffic routing. However, a traffic network may have thousands of links and nodes, resulting in a large-scale and computationally complex non-linear, non-convex optimization problem. To solve this problem, Ant Colony Optimization (ACO) is chosen as the optimization method in this paper because of its powerful optimization heuristic for combinatorial optimization problems. ACO is implemented online to determine the control signal – i.e., the splitting rates at each node. However, using standard ACO for traffic routing is characterized by four main disadvantages: 1. traffic flows for different origins and destinations cannot be distinguished; 2. all ants may converge to one route, causing congestion; 3. constraints cannot be taken into account; and 4. neither can dynamic link costs. These problems are addressed by adopting a novel ACO algorithm with stench pheromone and with colored ants, called Ant Colony Routing (ACR). Using the stench pheromone, the ACR algorithm can distribute the vehicles over the traffic network with less or no traffic congestion, as well as reduce the number of vehicles near some sensitive zones, such as hospitals and schools. With colored ants, the traffic flows for multiple origins and destinations can be represented. The proposed approach is also implemented in a simulation-based case study in the Walcheren area, the Netherlands, illustrating the effectiveness of the approach.     

Using repeated cross-sectional travel surveys to enhance forecasting robustness: Accounting for changing mode preferences

Transportation system capacity and performance, urban form and socio-demographics define the influences and constraints conditioning the preferences of urban residents for different transport modes. Changes in characteristics of urban areas are likely to lead to changes in preferences for alternative modes of transport over time; as a consequence, statistical models to forecast mode choice need to be sensitive to both purposeful changes to urban systems as well as exogenous shocks. We make use of the 1996, 2001 and 2006 household surveys conducted in the Greater Toronto and Hamilton Area to study mode preference evolution and model forecasting performance. These repeated cross-sectional household surveys provide an opportunity to investigate aggregate structural changes in commuting mode preferences over time, in a manner sensitive to changes in the urban area. We focus on commuting mode choices because these trips are prime determinants of peak period congestion and peak spreading. We then address how to combine the three cross-sections econometrically in a robust way that allows for use of a single mode choice model across the entire period. Using independent data from 2012, we are able to compare the individual year and combined models in terms of forecasting performance to demonstrate the combined model’s more robust forecasting performance into the future.