倾斜蜗舌对多翼离心通风机内部非定常流动及噪声特性的影响

以不同倾斜蜗舌的多翼离心通风机为研究对象,采用数值模拟方法,对风机内部流动特性以及气动噪声进行了非定常计算,讨论了倾斜蜗舌结构对多翼离心通风机内流场和噪声的影响。结果表明:蜗舌附近的压力分布随着蜗舌半径的增大而减小;对蜗舌处压力脉动和三维涡量的分析表明,倾斜蜗舌结构和合理的蜗舌间隙比减低了蜗舌和蜗壳出口附近局部流动损失;在设计工况下,采用蜗舌倾斜角为14.7°的改进模型,其出口处可降低噪声2.5 dB。因此,采用倾斜蜗舌结构可以有效改善离心通风的流动状况,减低流动损失和降低噪声。

Editorial: Special Topic on Machine Learning for Wireless Networks

Success in applying deep learning in speech recognition had triggered a resurgence of interests in deep learning,starting around 2010.Since then,deep learning has been applied with remarkable results to many problems,such as image recognition,speech and image synthesis,natural language processing,finance and artificial intelligence such as game playing.The success owes much to the availability of large amount of data,improved computational capabilities,and advances in algorithms.