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Surrogate Based Optimization of Aerodynamic Noise for Streamlined Shape of High Speed Trains

机译:基于替代的高速列车流线型气动噪声优化

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Aerodynamic noise increases with the sixth power of the running speed. As the speed increases, aerodynamic noise becomes predominant and begins to be the main noise source at a certain high speed. As a result, aerodynamic noise has to be focused on when designing new high-speed trains. In order to perform the aerodynamic noise optimization, the equivalent continuous sound pressure level (SPL) has been used in the present paper, which could take all of the far field observation probes into consideration. The Non-Linear Acoustics Solver (NLAS) approach has been utilized for acoustic calculation. With the use of Kriging surrogate model, a multi-objective optimization of the streamlined shape of high-speed trains has been performed, which takes the noise level in the far field and the drag of the whole train as the objectives. To efficiently construct the Kriging model, the cross validation approach has been adopted. Optimization results reveal that both the equivalent continuous sound pressure level and the drag of the whole train are reduced in a certain extent.
机译:空气动力学噪声随运行速度的六次方增加。随着速度的增加,空气动力噪声成为主要噪声,并开始以一定的高速成为主要噪声源。结果,在设计新的高速列车时必须关注空气动力噪声。为了进行空气动力学噪声优化,本文使用了等效连续声压级(SPL),可以考虑所有远场观测探头。非线性声学求解器(NLAS)方法已用于声学计算。使用克里格代理模型,对高速列车的流线型进行了多目标优化,以远场的噪声水平和整列列车的阻力为目标。为了有效地构建克里格模型,已经采用了交叉验证方法。优化结果表明,整个列车的等效连续声压级和阻力都在一定程度上降低了。

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