车辆天窗气动噪声的数值分析与实验研究

本文从汽车天窗气动噪声的机理入手,利用与实车几何尺寸为1:5的简化模型进行了空腔绕流的数值计算,分析了其流场结构及气动噪声产生的原因.在低速静音风洞中进行了不同流速下的流场和声场实验研究,研究了天窗不同位置的速度剪切层变化,以及不同流速下的声压级变化,发现了除了特征频率下的风振噪声,还存在较大频率范围的气动噪声,其随着...     

Buffeting in transonic flow prediction using time‐dependent turbulence model

In transonic flow conditions, the shock wave/turbulent boundary layer interaction and flow separations on wing upper surface induce flow instabilities, ‘buffet’, and then the buffeting (structure vibrations). This phenomenon can greatly influence the aerodynamic performance. These flow excitations are self‐sustained and lead to a surface effort due to pressure fluctuations. They can produce enough energy to excite the structure. The objective of the present work is to predict this unsteady phenomenon correctly by using unsteady Navier–Stokes‐averaged equations with a time‐dependent turbulence model based on the suitable (k–ε) turbulent eddy viscosity model. The model used is based on the turbulent viscosity concept where the turbulent viscosity coefficient (Cμ) is related to local deformation and rotation rates. To validate this model, flow over a flat plate at Mach number of 0.6 is first computed, then the flow around a NACA0012 airfoil. The comparison with the analytical and experimental results shows a good agreement. The ONERA OAT15A transonic airfoil was chosen to describe buffeting phenomena. Numerical simulations are done by using a Navier–Stokes SUPG (streamline upwind Petrov–Galerkin) finite‐element solver. Computational results show the ability of the present model to predict physical phenomena of the flow oscillations. The unsteady shock wave/boundary layer interaction is described. Copyright © 2005 John Wiley & Sons, Ltd.     

基于首超破坏机制的大跨斜拉桥抖振动力可靠性分析

分别采用泊松分布和马尔可夫过程，给出了在一次强风作用下以及在设计基准期内桥梁结构某一特定截面或节点的抖振动力可靠性分析方法。然后，考虑斜拉桥的结构特点及其承受风荷栽的具体情况，确定了以斜拉桥的主梁系统为研究对象的结构体系抖振动力可靠性分析模型。在此基础上，采用串联失效模式，建立了斜拉桥主梁系统抖振动力可靠性分析过程。本文采用有限元法分析结构的空气静力响应。为了快速、准确地计算结构的抖振响应，考虑气弹力与抖振力的联合作用以及多模态耦合效应，采用有限元法和虚拟激励法相结合分析结构的抖振响应。最后，以某大跨斜拉桥为工程背景，对其主梁系统进行了基于刚度要求的抖振动力可靠性分析。     

安装固定气动翼板的大跨桥梁抖振分析

建立了安装固定气动翼板的大跨桥梁多模态耦合抖振分析框架，推演了作用在整个桥梁-气动翼板系统上的抖振力和自激力的显式表达式，考虑了多模态耦合效应．基于有限元法，作用在主梁-气动翼板系统上的抖振力转化为节点力，进一步得到作用在整个桥梁上的抖振力并导出了其功率谱密度矩阵；作用在主梁．气动翼板系统上的气弹自激力转化为节点力，并将其表达为气弹刚度矩阵和气弹阻尼矩阵．通过组集得到系统的运动方程，然后运用虚拟激励法在频域计算系统的抖振响应．以某大跨斜拉桥为例进行研究，结果表明：在主梁下方安装-对固定气动翼板后，主梁的扭转角位移、角加速度以及侧向加速度响应能够得到有效控制。     

大跨悬索桥抖振内力响应分析

基于虚拟激励法和有限元法,在频域建立了一种新的桥梁抖振内力响应分析的随机振动方法。该方法与传统随机振动方法相比具有如下两个特点:(1)单元抖振内力响应同时考虑了保留模态多模态耦合产生的动力效应和保留模态外高频模态产生的拟静力效应;(2)单元抖振内力响应同时考虑了单元杆端位移产生的单元杆端力和单元上分布荷载产生的单元固端力。以香港青马悬索桥为例,分析了保留模态多模态耦合产生的动力效应、高频模态拟静力效应、单元上分布荷载产生的单元固端力及主缆上的抖振荷载等因素对主梁抖振内力响应的贡献。结果表明:保留模态多模态耦合产生的动力效应对主梁抖振内力响应占据主导地位,高频模态拟静力效应、单元上分布荷载产生的单元固端力等因素对主梁抖振内力响应均有一定的影响,主缆上的抖振荷载对主梁侧向抖振内力响应有较大贡献。     

大跨度悬索桥施工状态气动弹性模型风洞试验研究

本文通过桥梁气动弹性模型风洞试验，给出了汕头海湾大桥施工状态的颤振、抖振特性．     

基于虚拟激励法的空间网格结构风致抖振响应分析

基于虚拟激励法理论,推导了空间网格结构的抖振响应计算公式,公式中自动包含了激励之间的非完全相关性、振型之间耦合项的贡献。根据虚拟激励法直接求解出位移均方根的特点,推导了适用于多振型参振的脉动风等效静力荷载及相应的荷载风振系数计算公式。在此基础上,利用Matlab编制了相应的计算程序,并进行了算例验证与分析。算例分析验证了本文理论及程序的正确性,也表明本文方法具有很高的计算效率。本文工作为进一步系统研究大跨网格结构的风振随机响应打下了良好的基础。     

大跨悬索桥三维非平稳耦合抖振分析

基于Priestley(1967)演变功率谱模型，并采用Lin和Yang(1983)的建议，建立了脉动风速的非平稳功率谱模型。依据此模型，采用三维有限元法，建立了大跨桥梁非平稳耦合抖振运动方程。然后，将虚拟激励法和精细时程积分法相结合，建立了求解桥梁三维非平稳耦合抖振运动方程的快速算法。以某大跨悬索桥为例，分析了该桥的非平稳耦合抖振响应，并与平稳耦合抖振响应进行了比较。计算结果表明：随着脉动风速平稳部分持时的增大，非平稳抖振分析结果逐渐收敛于平稳抖振分析结果；但若脉动风速的平稳部分持时较短，非平稳抖振分析结果将低于平稳抖振分析结果。     

Numerical analysis and passive control of a car side window buffeting noise based on Scale-Adaptive Simulation

Flow over an open side window in a car exhibits similar characteristics as the flow over an open cavity. Computational Fluid Dynamics (CFD) simulation over a cavity was done as a benchmark. The unsteady flow simulation was carried out using Scale Adaptive Simulation (SAS) turbulence model. The benchmark results, frequency and sound pressure levels of feedback and resonance modes, all well matched with the experimental data. Then, with the right rear window, for example, the mechanism of the side window buffeting was investigated. The simulation results show that side window buffeting noise is generated by large scale vortices and in low frequency. Furthermore, buffeting noise characteristics under several patterns of side windows opening were also numerically investigated. As a result, rear window buffeting noise is more severe than that of front window when one window open, and combination pattern of side windows open can reduce buffeting noise. To decrease the interior noise and improve car ride comfort, four suppression measures through adding a side window weather deflector at the A-pillars, constructing a cavity at the B-pillars, combination of the front and rear windows and installing a row of square cylinder deflector at the B-pillars were also studied, respectively. In conclusion, certain noise reduction can be achieved through four passive control methods.     

Using a Proper Orthogonal Decomposition representation of the aerodynamic forces for stochastic buffeting prediction

High-performance aircraft often suffer from the consequences of tail buffeting at moderate subsonic Mach numbers and medium to high angles of attack. The impact of the aircraft’s highly unsteady flow field on the tails can result in significant structural fatigue and degraded handling qualities. Various methods have been developed to predict tail buffeting. Stochastic response methods are among frequently used approaches. For such methods the size of the excitation data set can become an issue, especially when the auto- and cross-spectra of all available excitation signals on the configuration are considered. The present paper demonstrates how to modify stochastic tail buffeting prediction methods using Proper Orthogonal Decomposition (POD). The approach is based on the modal decomposition of the aerodynamic buffet excitation data set. It notably reduces the computational effort for structural response and loads prediction with limited losses in accuracy while using all power- and cross-spectra of the reduced dataset. The method was applied to the computational buffeting prediction for a generic configuration with double-delta wing and horizontal tail plane (HTP) over a wide range of angles of attack. It was shown that the POD-modes of the aerodynamic buffet excitation resembled the characteristics of configuration’s complex vortical flow field. The predicted structural response and loads converged well with increasing number of POD-modes. With the presented approach, the computational effort of stochastic tail buffeting prediction has been reduced by orders of magnitude compared to the case with the full aerodynamic buffet excitation data set.