In a numerical study, a shorter span extent than experiment is often used to save the computational resource. The predicted sound pressure level should be corrected before compared with the experimental results. This study concerns the extended aeroacoustic spanwise correction method for the noise prediction radiated from large-span objects. Four new types of spanwise correction models are derived based on the assumption of the spanwise coherence function taking the form of a rectangular function, a trigonometric function, a Laplacian function and a Gaussian function, respectively. The large eddy simulation (LES) combined with the acoustic analogy theory is used for the aerodynamic noise prediction. The predicted far-field sound levels are then corrected by the proposed spanwise correction methods for the large-span objects. Far-field acoustic measurements and near-field hot-wire measurements are also performed in an anechoic wind tunnel for validation purpose. The predicted aerodynamic and aeroacoustic results are found in good agreement with the experiments with the proposed spanwise correction method. The present models based on the Laplacian function and Gaussian function are unified models taking the advantage of that there is no need to compare the relative extent of the numerical length, experimental length, and coherence length. The results also indicate that although there is no significant difference between the various functions, corrections based on the Gaussian profile seem to perform better compared with other functions.

在数值研究中，通常使用比实验更短的跨度范围来节省计算资源。预测的声压级应在与实验结果比较之前进行校正。本研究涉及大跨度物体辐射噪声预测的扩展气动声学跨向校正方法。假设展向相干函数分别为矩形函数、三角函数、拉普拉斯函数和高斯函数，推导出了四种新的展向校正模型。大涡模拟（LES）结合声学类比理论用于气动噪声预测。预测的远场声级然后通过所提出的大跨度对象的跨度校正方法进行校正。出于验证目的，还在消声风洞中进行远场声学测量和近场热线测量。预测的空气动力学和气动声学结果与使用所提出的展向校正方法的实验非常吻合。现有的基于拉普拉斯函数和高斯函数的模型是统一模型，其优点是不需要比较数值长度、实验长度和相干长度的相对范围。结果还表明，虽然各种函数之间没有显着差异，但与其他函数相比，基于高斯轮廓的校正似乎表现更好。预测的空气动力学和气动声学结果与使用所提出的展向校正方法的实验非常吻合。现有的基于拉普拉斯函数和高斯函数的模型是统一模型，其优点是不需要比较数值长度、实验长度和相干长度的相对范围。结果还表明，虽然各种函数之间没有显着差异，但与其他函数相比，基于高斯轮廓的校正似乎表现更好。预测的空气动力学和气动声学结果与使用所提出的展向校正方法的实验非常吻合。现有的基于拉普拉斯函数和高斯函数的模型是统一模型，其优点是不需要比较数值长度、实验长度和相干长度的相对范围。结果还表明，虽然各种函数之间没有显着差异，但与其他函数相比，基于高斯轮廓的校正似乎表现更好。现有的基于拉普拉斯函数和高斯函数的模型是统一模型，其优点是不需要比较数值长度、实验长度和相干长度的相对范围。结果还表明，虽然各种函数之间没有显着差异，但与其他函数相比，基于高斯轮廓的校正似乎表现更好。现有的基于拉普拉斯函数和高斯函数的模型是统一模型，其优点是不需要比较数值长度、实验长度和相干长度的相对范围。结果还表明，虽然各种函数之间没有显着差异，但与其他函数相比，基于高斯轮廓的校正似乎表现更好。