漩涡发生器对燃油喷嘴的雾化性能影响的数值研究

为了探讨漩涡发生器(简称V.G)对燃油喷嘴雾化性能的影响,利用Gambit分别建立了原型喷嘴、加装2个漩涡发生器和加装4个漩涡发生器喷嘴的模型,并利用FLUENT软件进行了数值模拟,得到了三种模型的出口流场分布图。计算结果表明:在相同燃油压力下,加装漩涡发生器可以加快射流的混合速度,其中加装4个漩涡发生器的喷嘴的加速掺混能力最高,加装2个的其次,但仍比"原型"的情况有明显的改善;当燃油压力改变时,掺混能力会随着燃油压力的提高而提高。     

离心叶轮出口与无叶扩压器内部流动特性的DPIV实验研究

在叶轮转速n＝1500rpm对应的设计工况下,利用两维数字式粒子图像速度场仪(DPIV)对风机模型从叶轮出口至无叶扩压器区域内部流动状态进行整场测量,在"锁相"状态下获得沿扩压器宽度方向上三个径向面的瞬态速度场、涡量场的分布,并进一步对时均流场的流动特性进行全面讨论.测量结果表明:设计工况下,叶轮出口流动呈现典型的"射流-尾迹"流动结构,其对无叶扩压器内部流动状态具有深刻的影响.旋涡由叶轮叶片表面边界层的粘性切应力产生,并随流动被输运至下游无叶扩压器,然后随着流动的均匀化而逐渐消失.涡量的分布及变化反映了无叶扩压器内部流体相互掺混和能量传递、重新分布从而达到均匀化的过程.随着半径的增加,尽管无叶扩压器内流动在圆周方向亦逐渐趋于均匀化,但沿宽度方向的差距未得到改善,这将导致沿轴向α不变原则设计的叶片扩压器的二元叶片无法避免冲击损失.     

DO 28飞行试验数据一致性检验

 本文研究DO28试验机飞行试验数据一致性检验及其误差校正。建立了由非线性运动学方程及内容广泛的校正环节构成的一致性检验模型,解决了大地风场重构、测量信号时间延迟估计、ψ转换及测量控制信号的校正。为DO28参数估计提供了可靠、准确的飞行试验数据。     

GH4169高温合金惯性摩擦焊接头动态再结晶过程

当温度、应变、应变速率达到一定条件时 ,GH4 16 9镍基高温合金在惯性摩擦焊接过程中易发生动态再结晶。本文研究结果表明 ,由于GH4 16 9合金惯性摩擦焊接时间很短 ,动态再结晶进行得相当充分 ,而动态回复不足 ,在动态再结晶的过程中还可以看到有些结晶过程还处于形核阶段 ,这是惯性摩擦焊接头产生细晶乃至超细晶的根本原因     

进气温度畸变对某发动机稳定性影响的研究

本文采用有效的畸变传递模型，就进气温度畸变对某发动机稳定性和性能的影响进行了较深入的数值研究．详细地分析了温度畸变对发动机稳定性和性能的影响，探讨了温度畸变在发动机系统中的传递和分布情况。结果表明：对于发动机进口空间温度畸变，发动机稳定裕度损失更多地取决于畸变强度而非周向范围：向对于与时间相关的温度畸变，发动机进口温升率比周向范围的影响更为显著。     

A recursive multiple model approach to noise identification

Correct knowledge of noise statistics is essential for an estimator or controller to have reliable performance. In practice, however, the noise statistics are unknown or not known perfectly and thus need to be identified. Previous work on noise identification is limited to stationary noise and noise with slowly varying statistics only. An approach is presented here that is valid for nonstationary noise with rapidly or slowly varying statistics as well as stationary noise. This approach is based on the estimation with multiple hybrid system models. As one of the most cost-effective estimation schemes for hybrid system, the interacting multiple model (IMM) algorithm is used in this approach. The IMM algorithm has two desirable properties: it is recursive and has fixed computational requirements per cycle. The proposed approach is evaluated via a number of representative examples by both Monte Carlo simulations and a nonsimulation technique of performance prediction developed by the authors recently. The application of the proposed approach to failure detection is also illustrated     

湍流型动态畸变下涡喷发动机稳定性分析

对湍流型动态畸变进气流场进行了分析和描述，给出了随机涡在压气机进口所产生的总压脉动的通用分布曲线，并统计地分析和预测了该总压脉动引起的最可能最大失速裕度损失。数值分析表明在考虑压气机对非定常流响应方面，最为关心的压气机最大失速裕度损失值是脉动压力的均方根值、功率谱密度、压气机进口转子弦长和转速的函数。     

跨音速压气机动静叶排相干的三维非定常流动数值分析

采用时空二阶精度ＮＮＤ显式差分格式求解三维Ｅｕｌｅｒ方程，对跨音速压气机级中动静叶排相干形成的非定常流动进行了数值分析。除动静叶排流动的控制方程体系、数值方法外，着重讨论了动静叶排计算域、网格以及边界条件的处理。对某压气机第１级动静叶排相干的非定常流场的计算，给出了叶片表面的马赫数分布、压力波动幅值，以及叶片槽道中瞬态密度等值线等，并分析了结果的合理性。     

Multistage integration model for human egomotion perception

Human computational vision models that attempt to account for the dynamic perception of egomotion and relative depth typically assume a common three-stage process: first, compute the optical flow field based on the dynamically changing image; second, estimate the egomotion states based on the flow; and third, estimate the relative depth/shape based on the egomotion states and possibly on a model of the viewed surface. We propose a model more in line with recent work in human vision, employing multistage integration. Here the dynamic image is first processed to generate spatial and temporal image gradients that drive a mutually interconnected state estimator and depth/shape estimator. The state estimator uses the image gradient information in combination with a depth/shape estimate of the viewed surface and an assumed model of the viewer's dynamics to generate current state estimates; in tandem, the depth/shape estimator uses the image gradient information in combination with the viewer's state estimate and assumed shape model to generate current depth/shape estimates. In this paper, we describe the model and compare model predictions with empirical data.     

进气压力畸变对某三级风扇流场的影响

介绍了在某三级风扇上进行的固定式插板畸变试验，并详细分析了进气压力畸变对进、出口稳态压力和温度的影响。同时，采用频域和幅值域分析方法对脉动压力进行了分析，给出了脉动压力功率谱密度、幅值概率密度和自相关、互相关分析。