Errors in dynamical fields inferred from oceanographic cruise data: Part II. The impact of the lack of synopticity

Diagnostic studies of ocean dynamics based on the analysis of oceanographic cruise data are usually quite sensitive to observation errors, to the station distribution and to the synopticity of the sampling. The first two sources have been evaluated in the Part I of this work. Here we evaluate synopticity errors for different sampling strategies applied to simulated unstable baroclinic waves. As suggested in previous studies, downstream and upstream cross-front samplings produce larger errors than along-front samplings. In our particular case study, the along-front sampling results in fractional errors (rms error divided by the standard deviation of the field) of about 15% for dynamic height and more than 50% for relative vorticity and vertical velocity. These values are significantly higher than those obtained in Part I for typical observation errors and sampling limitations (about 6% for dynamic height and between 15 and 30% for geostrophic vorticity and vertical velocity).We also propose and test two methods aimed at reducing the impact of the lack of synopticity. The first one corrects the observations using the quasi-geostrophic tendency equation. The second method combines the relocation of stations (based on a system velocity) and the correction of observations (through the estimation of a growth rate). For the fields simulated in this work, the second method gives better results than the first, being able to eliminate practically all synopticity errors in the case of the along-front sampling. In practice, the error reduction is likely to be less effective, since actual fields cannot be expected to have a system velocity as homogeneous as for the single-mode waves simulated in this work.     

Improving the efficiency of repeated dynamic network loading through marginal simulation

Currently, the applicability of macroscopic Dynamic Network Loading (DNL) models for large-scale problems such as network-wide traffic management, reliability and vulnerability studies, network design, traffic flow optimization and dynamic origin–destination (OD) estimation is computationally problematic. The main reason is that these applications require a large number of DNL runs to be performed. Marginal DNL simulation, introduced in this paper, exploits the fact that the successive simulations often exhibit a large overlap. Through marginal simulation, repeated DNL simulations can be performed much faster by approximating each simulation as a variation to a base scenario. Thus, repetition of identical calculations is largely avoided. The marginal DNL algorithm that is presented, the Marginal Computation (MaC) algorithm, is based on first order kinematic wave theory. Hence, it realistically captures congestion dynamics. MaC can simulate both demand and supply variations, making it useful for a wide range of DNL applications. Case studies on different types of networks are presented to illustrate its performance.     

Density/Flow reconstruction via heterogeneous sources and Optimal Sensor Placement in road networks

This paper addresses the two problems of flow and density reconstruction in Road Transportation Networks with heterogeneous information sources and cost effective sensor placement. Following a standard modeling approach, the network is partitioned in cells, whose vehicle densities change dynamically in time according to first order conservation laws. The first problem is to estimate flow and the density of vehicles using as sources of information standard fixed sensors, precise but expensive, and Floating Car Data, less precise due to low penetration rates, but already available on most of main roads. A data fusion algorithm is proposed to merge the two sources of information to estimate the network state. The second problem is to place sensors by trading off between cost and performance. A relaxation of the problem, based on the concept of Virtual Variances, is proposed and solved using convex optimization tools. The efficiency of the designed strategies is shown on a regular grid and in the real world scenario of Rocade Sud in Grenoble, France, a ring road 10.5 km long.     

汽车空调风道系统CFD研究与优化

基于对某种风道的CFD分析。对后风道和中心导风管进行了优化设计，改善了风量分配同时增加了总风量。分析结果显示改进能够满足要求。     

桥头跳车引起的路面受力计算分析

桥头路面沉将导致路、桥过渡段纵坡几何不平顺,由此引起桥头跳车现象。桥头跳车现象将导致路面受力显著的变化。通过建立简化的车辆运动双轴动力模型,得出在桥头跳车过程中车辆的动力振动方程,进而考虑桥头跳车现象中车辆运动的各种边界条件,给出该方程的解析解。结合工程实例计算,对高等级公路跳车过程中后轮对路面作用力进行分析,由此揭示车辆驶向和驶离桥面时车轮对路面作用力的变化情况,可供桥头路基路面沉降分析及相应的设计规范或规定的制定参考。     

飞机牵引车全液压制动系统动态性能分析

分析了全液压制动系统的动态性能,并建立了全液压制动系统的数学模型.基于数学模型,应用Matlab/Simulink仿真程序,对全液压制动系统的动态特性进行仿真.并将仿真结果与气压制动系统和气顶液制动系统进行了分析对比,证明全液压制动系统具有良好的制动性能.     

汽车空调除霜风道结构优化研究

建立了3种汽车空调除霜风道模型，用以研究除霜风道内空气流动情况。利用商业软件Fluent，对速度场进行数值分析、计算流量。通过比较，得到效果较好的除霜风道结构。     

桥梁冲击系数反应谱的理论分析

基于结构力学及随机过程理论，分析桥梁所承受的车辆冲击力与车辆、桥梁的动力特性及桥面平整度之间的关系，提出了确定冲击系数的一种新方法，用示例将以此计算的冲击系数与我国现行的桥涵设计规范及加拿大安大略省设计规范所取的冲击系数进行对比和分析。     

基于CFD的船舶水动力计算收敛性分析

为基于计算流体动力学（Computational Fluid Dynamics,CFD）的单体船型水动力性能计算参数提供参考依据,开展相关的收敛性分析。采用CFD数值计算,分析网格尺度、湍流模型和时间步长对于船舶水动力计算的收敛性影响,提出基于CFD的船舶水动力计算优化参数模型,并以水池模型试验验证所提方案的准确性。采用船长2.83%的非结构化网格进行流体计算域网格划分,采用Realizable k-ε湍流模型,计算时间步长取波浪遭遇周期Te的1/200,可更加合理地模拟船舶在规则波中的运动响应,为基于CFD的船舶阻力与耐波性计算提供确定依据。     

Estimation of the hydrodynamic coefficients of the complex-shaped autonomous underwater vehicle TUNA-SAND

Hydrodynamic coefficients strongly affect the dynamic performance of autonomous underwater vehicles (AUVs). Thus it is important to have the true values of the coefficients in order to simulate the AUV’s dynamic performance accurately. Although these coefficients can be predicted by many methods, most are only applicable for AUVs with streamlined shapes. Computational fluid dynamics (CFD) can be applied to estimate the hydrodynamic coefficients of AUVs with complex shapes. In this study, CFD was applied to estimate the hydrodynamic coefficients of the AUV TUNA-SAND (which stands for terrain-based underwater navigable AUV for seafloor and natural resources development), which has a complex block-like structure. First, the validity of the CFD simulation was verified by comparison with experimental results. Second, the relationships between hydrodynamic loads and motions for all six degrees of freedom were analyzed using the simulated results. Third, the importance of each hydrodynamic coefficient was investigated based on these relationships. There are 16 key damping coefficients that relate to viscosity and 12 key inertial coefficients that relate to the potential flow around TUNA-SAND. Finally, the values of all the key coefficients were obtained and verified by comparing the solutions of the simulated dynamics with the experimental results.