离心风机整机三维数值仿真方法及分析

离心风机的性能特征与其内部流场结构是密切关联的,某些简化模型下对风机内某个部件或某个流道做的数值仿真并不能准确反映蜗壳与叶轮之间的相互作用.为了解其性能变化的根本原因,达到优化风机性能改善系统特性,需要对整机进行详细的流场结构分析.在软件Numeca的Fine/ Turbo模块上,采用壁面函数法,对某离心风机在设计转速下不同工况点进行了数值仿真,与已有的试验数据对比,吻合较好,并准确反映了蜗壳与叶轮之间的相互作用,为风机的设计和性能优化提供了可信的理论依据.     

高速列车集电部气动噪声数值模拟

针对铁路提速后高速列车集电部气动噪声过大的问题,在集电部引入导流罩,应用FLUENT对不合导流罩及含导流罩集电部的外流场和气动噪声分别进行数值模拟和分析．流场计算采用稳态雷诺平均纳维斯托克斯（Reynolds Averaged Navier—Stokes,RANS）方法,声学模型选择边界层噪声模型．计算结果表明导流罩的设计至关重要,合理的设计能使得导流罩较好地引导气流,起到降低集电部气动噪声的作用．     

TLT离心风机的产品模型分析及数学模型建立

本文介绍了TLT离心风机的产品模型分析，及数学模型建立的基本方法。通过对TLT离心风机的产品特点进行分析，建立由各部件组成的层次模型，以及各部件相应的数学几何模型，并产生相应的几何和工程的约束控制关系。     

动车组司机室空调蒸发器气动噪声数值仿真

为研究动车组司机室空调蒸发器的噪声响应,建立某型司机室分体式空调蒸发器的计算流体动力学模型,采用FLUENT中的大涡模拟（large eddy simulation, LES）计算瞬态气动流场。对瞬态流场数据进行傅里叶变换,得到空气流场的频域数据。基于流场频域数据,采用Virtual.Lab的边界元法计算蒸发器的气动噪声,采用声压法计算蒸发器的辐射声功率,并与测试结果进行对比分析。结果表明：蒸发器出口位置气动噪声最高,最大声压级高于56 dB;最大声功率级出现在125~400 Hz的低频段;声功率级随着频率的增加逐渐降低,但在5 000 Hz的高频辐射中声功率级仍然超过55 dB,这表明空调蒸发器气动噪声属于宽频噪声;计算结果与测试结果吻合良好,验证声压法计算空调蒸发器气动声功率可行。     

基于混合数值算法的锯齿形喷管气动噪声仿真

为了预测航空发动机喷流噪声远场声压级,满足未来的航空器噪声适航要求,采用计算流体力学(CFD)和计算航空声学(CAA)混合数值算法,对安装Chevron型锯齿的喷管进行气动噪声仿真计算.使用大涡模拟(LES)计算喷管的瞬态喷流流场.在流场计算的基础上使用Ligthill声类比进行声源提取,结合有限元/无限元方法对喷流噪...     

Helmholtz共振腔气动噪声数值仿真

为探究出一套完整、准确的气动噪声仿真方法,用FLUENT和Actran仿真Helmholtz共振腔旁接管道系统模型.针对流场仿真,采用六面体网格建模,分析选择合适的网格密度,明确网格及边界条件的影响,以获得准确的声源信息;运用Lighthill声类比方法对声场进行仿真,采用数值计算、传声损失仿真和气动噪声仿真计算等3种方法提取管道内部场点声压级频谱曲线,分析曲线峰值频率特征,包括共振频率分析和声模态分析等.采用CFD软件与声学仿真软件相结合的方法,可以有效进行流场和声场的仿真.     

管道泄漏噪声的数值仿真分析

在管道运输的研究中,针对实时监控问题,目前管道泄漏噪声的获得主要是采用实验的方法,易受模型尺寸、测量精度等因素限制.以广义莱特希尔(Lighthill)理论为基础,利用商业软件fluent对输流管道泄漏的流场进行数值仿真.据实际情况设置边界条件,分析了流速的变化.接着运用基于LES大涡仿真法和FW-H方程相匹配的技术,对管道泄漏噪声进行了CAA数值仿真,通过快速傅立叶变换对泄漏点处及测量点处的压力进行了频谱分析,对比了不同点声压的特点.通过仿真实验,结果表明,为噪声研究提供了参考,对实际的管道泄漏声场分析和监测有较大的参考价值.     

TLT离心风机CAD系统的升级优化

介绍了计算机辅助设计软件AutoCAD的二次开发技术，然后以上海鼓风机厂TLT离心机CAD系统的升级优化为例，详细阐述了如何把利用AutoCAD二次开发技术进行开发设计的有关CAD设计的第三方专业软件由ADS开发版本升级到ObjectARX开发版本，以期提高CAD设计第三方专业软件的运行速度，最终达到系统升级的目的。     

一种新型气动蠕动机器人的机理研究

本文提出了一种新型气动蠕动机器人，分析了它的驱动机理和动态特性，这种蠕动机器人有一个基于气动驱动器的新颖驱动机构和四个吸附足，它结构简单，制造成本低，易于小型化，仿真表明本文的控制策略可行，响应快速，控制可靠，因而这种新型机器人在很多领域有着广泛的应用潜力。     

洗扫车用吸尘盘气动噪声的优化

吸尘盘作为洗扫车的关键组成部件,降低吸尘盘的气动噪声可极大提升产品性能.基于FLUENT软件和FW-H声比拟模型,对吸尘盘的气动噪声强度进行了计算,设计了一种带有肩部结构和倾斜壁面的新型吸尘盘结构,重点研究了肩部夹角和上壁面倾角对吸尘盘气动噪声产生的综合影响,基于MATLAB软件,采用多项式拟合方法分别建立了两参数与吸尘盘全压以及总声压级之间的函数关系,并结合多目标优化遗传算法对目标函数进行了优化分析.数值结果表明：肩部夹角对气动噪声的影响较为显著,在0°~20°范围内,夹角每增加1°,噪声可以降低0.4dB;合理地增大肩部夹角,可以在降低能量损失的同时有效降低吸尘盘的气动噪声,最大降幅为6.2dB.     

汽车发动机冷却风扇仿真方法对比

对比多参考坐标系(Multiple Reference Frame,MRF)模型和滑移网格模型(Sliding Mesh Model,SMM)在分析中的差异,分别应用FLUENT中的三维N-S方程和RNG湍流模型,对发动机冷却风扇的静止和旋转区域进行数值模拟,得到流道内空气的质量流量及风扇叶片表面的压力和速度矢量分布.SMM的结果更接近真实结果;根据SMM得出的结果说明MRF模型在工程领域的应用.     

大型车辆发动机冷却风扇流场的数值仿真方法

给出了发动机冷却风扇的数值仿真的建模方法和求解技术。以大型车辆发动机冷却风扇为研究对象,采用分区域划分网格的方法,运用滑移网格技术,对大型车辆冷却风扇三维流场进行了数值模拟和气动性能、气动噪声的研究。流场稳态模拟采用了基于雷诺平均的RNGκ-ε湍流模型,流场瞬态模拟采用了大涡模拟方法。给出了风扇流场的压力分析和速度分析,讨论了对风扇流量和气动噪声的影响因素。     

基于数值计算的高速列车气动阻力风洞试验缩比模型选取方法

为给高速列车气动阻力风洞试验模型选取提供更多的参考依据,通过计算流体力学(Computational Fluid Dynamics,CFD)方法,研究不同比例的高速列车缩比模型对气动阻力风洞试验结果的影响.首先,计算得到开口式风洞测试段的静压系数分布曲线,为高速列车气动阻力测量试验模型的长度选择以及摆放位置提供依据;其次,通过数值计算得到全尺寸模型列车在明线运行时,以及不同比例的模型列车在风洞中运行工况下的气动阻力信息,并从阻塞效应和雷诺数的变化,以及风洞试验段内静压分布的影响这3个方面对列车模型的气动阻力结果进行分析,得到在所研究风洞中较合理的列车缩比模型比例选取范围.这种以CFD为基础进行数值仿真,选取风洞试验中列车模型比例及试验测试位置的方法,为在地面交通工具风洞中进行高速列车模型气动阻力试验的缩比模型选取提供一定依据.     

An efficient solution to improve the spectral noise suppression rules

Typical spectral noise suppression rules employ a multiplicative gain function in the frequency domain. In this paper, we propose a modified gain function to improve the speech enhancement. The general principle is based on a theoretical development of the classical gain function in order to derive an efficient estimator for the noise reduction system. The idea combines the performances of spectral subtraction method and statistical model estimator. The obtained combination involves two parameters. These parameters control the rate of noise reduction and speech distortion. Performances of the idea were evaluated using a number of tests in various environments through speech distortion measurement. Experimental evaluations show that the modified gain function yields better results as compared to the conventional gain functions.     

Automated reconstruction of 3D input data for noise simulation

Noise is one of the main problems in urban areas. To monitor and manage noise problems, governmental organisations at all levels are obliged to regularly carry out noise studies. The simulation of noise is an important part of these studies. Currently, different organisations collect their own 3D input data as required in noise simulation in a semi-automated way, even if areas overlap. This is not efficient, but also differences in input data may lead to differences in the results of noise simulation which has a negative impact on the reliability of noise studies. To address this problem, this paper presents a methodology to automatically generate 3D input data as required in noise simulations (i.e. buildings, terrain, land coverage, bridges and noise barriers) from current 2D topographic data and point clouds. The generated data can directly be used in existing noise simulation software. A test with the generated data shows that the results of noise simulation obtained from our generated data are comparable to results obtained in a current noise study from practice. Automatically generated input data for noise simulation, as achieved in this paper, can be considered as a major step in noise studies. It does not only significantly improve the efficiency of noise studies, thus reducing their costs, but also assures consistency between different studies and therefore it improves the reliability and reproducibility. In addition, the availability of countrywide, standardised input data can help to advance noise simulation methods since the calculation method can be adopted to improved ways of 3D data acquisition and reconstruction.     

Authenticating corrupted photo images based on noise parameter estimation

Photo image authentication is an interesting and demanding field in the computer vision and image processing community. This research is motivated by its wide range of applications, which include smart card authentication systems, biometric passport systems, etc. In this paper, we propose a method of authenticating corrupted photo images based on noise parameter estimation. The proposed method first generates corrupted images by adjusting the noise parameters in the initial training phase. This set of corrupted images and the noise parameters can be represented by a linear combination of the prototypes of the corrupted images and the noise parameters. In the testing phase, the noise parameters of the corrupted photo image can be estimated with a corrupted image and an original image. Finally, we can make a synthesized photo image from the original photo image using the estimated noise parameters and verify it with the corrupted photo image. The experimental results show that the proposed method can estimate the noise parameters accurately and improve the performance of photo image authentication.     

Spreading love through fan page liking: A perspective on small scale entrepreneurs

Growing popularity of Facebook has made it a value-adding marketing channel for the small and medium sized businesses. As a marketing medium characterized by low cost and minimum risk it attracts small scale entrepreneurs to utilize this new platform i.e. brand fan page of Facebook as a business communication tool for reaching out to customers. Considering the significance of Facebook as social media marketing platform for businesses and the lack of understanding of this area, the present study investigates whether there exists a significant relationship between brands “liked” on the Facebook fan pages and brand love, word of mouth, and purchase intention from potential buyer perspective. The research was conducted taking five popular small scale entrepreneur backed firms on the basis of the number of likes on their fan pages. Respondents of the survey were followers of fan pages of sampled firms. Structural Equation Modeling (SEM) was applied using primary data collected from 311 respondents. The study reveals a positive relationship between “liked” brands on Facebook fan-page and brand love. Further, the study finds that liking the fan pages is essentially converted into WOM, and it results into purchase proposition.