流场控制体对喷水推进器性能预报影响的研究

为准确预报喷水推进器设计工况与非设计工况的水动力性能,采用CFD方法对喷水推进器性能预报所需流场控制体进行了研究.在验证计算方法和数值模型可信的基础上,通过对比不同流场控制体的计算结果,分析了流场控制体对喷水推进器性能预报的影响.首先,确定了设计工况下流场控制体的大小;然后,对非设计工况下流场控制体的选取进行了分析讨论.结果表明,非设计工况下流场控制体的大小对喷水推进器性能预报的影响比设计工况大,而且非设计工况下所需流场控制体要大于设计工况时的情况.     

结构灵敏度分析及计算方法概述

从结构优化、系统的理解和条件、结构模型发展和参数识别等方面概述了采用灵敏度分析(SA)的原因,又从设计变量、结构参数、结构响应和函数性态等四个不同角度上进行了SA的分类,并从基于计算策略和实验数据两个方面介绍了SA的计算方法。简要回顾了形状和尺寸SA、随机SA、应力/应变SA、位移SA和特征值/特征向量SA的最新进展和应用。对基于结构响应的SA综合考虑静态和动态响应,重点关注特征值和特征向量的导数求解等难点问题。     

汽车挡风玻璃除霜性能数值模拟

利用CFD方法建立汽车除霜性能动态模型,并量化了除霜器在挡风玻璃附近的气流速度场,对挡风玻璃除霜时间及效果进行了探讨,为汽车挡风玻璃除霜效果模拟工程提供了参考。     

多轴混合动力特种车辆空气动力学特性分析与改进设计

建立某多轴混合动力特种车辆整车外流场仿真模型,采用计算流体力学方法分析整车外流场特性.根据分析结果对驾驶室进气格栅、驾驶室与货箱之间的上部连接、驾驶室下部进风口三个部位进行优化设计.在优化设计过程中,特别关注提升各车桥分布式驱动电机的散热效果,并根据局部外流场特性确定车桥处的电机风扇朝向布置.结果表明,优化后的整车风阻...     

发动机水套方案优选

某涡轮增压发动机开发过程中,出现了缸垫黏结、机油积炭、缸孔轻微拉伤等过热问题。针对这些问题制订了5个发动机水套优化方案,然后通过制造工艺性、制造经济性、发动机可靠性、CAE计算结果多方面综合评估,优选出2个相对较好的方案。对优选出的方案进行样件试制、试验测试,确认优化效果。结合试验测试结果,确定出最终工程实施的技术方案。最终通过台架耐久性测试及试验后发动机拆解分析,确认过热问题得到解决。     

基于人机工程的客车驾驶员坐姿舒适性校核与评估

由目前正在参与的某型新能源电动客车的设计,对该电动客车的驾驶室进行人机工程的研究,利用CATIA软件建立某型新能源电动客车的驾驶室三维模型并对车辆驾驶室进行驾驶员坐姿舒适性校核,根据人机工程学对中国人体模型进行模型建立并对驾驶员坐姿舒适性进行评估。结果表明该客车的方向盘,座椅以及脚踏板等布置合理,实现了校核与评估一体化,为后期的总布置整体评估奠定了基础。     

Errors in dynamical fields inferred from oceanographic cruise data: Part I. The impact of observation errors and the sampling distribution

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. Here we present an error analysis of the first two sources. The third one is evaluated in Part II of this work (J. Mar. Sys. (2005), this issue). For observed variables and those linearly related to them, we use the Optimal Statistical Interpolation (OI) formulation. For variables which are not linearly related to observed variables (e.g., the vertical velocity), we carry out numerical experiments in a consistent way with OI statistics. Best results are obtained when some kind of scale selection or spatial filtering is applied in order to suppress small scales that cannot be properly resolved by the station distribution.The formulation is first applied to a high resolution (SeaSoar) sampling aimed to the recovery of mesoscale features in a region of large spatial variability (noise-to-signal fraction of the order of 0.002). Fractional errors (rms error divided by the standard deviation of the field) are estimated in about 2% for dynamic height and between 4% and 20% for geostrophic vorticity and vertical velocity. For observed variables, observation errors and sampling limitations are shown to contribute in similar amounts to total errors. For derived variables, sampling errors are by far the dominant contribution. For less dense samplings (e.g., equally spaced CTD stations), fractional errors are about 6% for dynamic height and between 15% and 30% for geostrophic vorticity and vertical velocity. For this sampling strategy, errors of all variables are mostly associated with sampling limitations.     

地裂时桥梁倒塌过程研究

利用LS-DYNA程序建立数值分析模型，再现土耳其Arifiye大桥在1999年地震中由于地裂引起倒塌的过程，并与真实的倒塌场景进行比较，验证了分析模型的正确性。有限元分析中，墩台和上部结构均采用平面应力单元，忽略弹性支座的影响；墩台与上部结构之间采用接触算法；结构动力分析采用显式有限元法进行。从对桥梁上部结构破坏过程中梁体位移的动力响应分析可知，梁体坠落过程中没有与相邻墩台发生明显的撞击。对地裂发生位置和上部结构形式对倒塌影响的研究表明，结构完整性能够明显阻止结构发生连续性倒塌破坏；在阻止地裂引起桥梁破坏方面，连续结构形式优于简支结构形式，可有效减轻地裂发生瞬间桥梁破坏造成的生命财产损失。     

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.