Comparing of CFD contours using image analysing method: a study on velocity distributions

Ahmet ERDOĞAN, Mahmut DAŞKIN
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引用次数: 1

Abstract

Contour plotting, a widely utilized graphical technique for visualizing CFD (Computational Fluid Dynamics) outcomes, is highly valuable. It provides an effective and practical approach to analysing distributions of magnitudes belonging to fluid domains such as; velocity, temperature, pressure, volume fraction, etc. Nevertheless, when analysing multiple contours, especially showing similar distribution, identifying the ideal contour can be difficult and open to speculation. In this research, the issue was addressed by employing the Image Analysis Method for the classification of velocity distribution contours. This led to determining which picture has the best distribution among a few of the contour’s pictures. Firstly, velocity distribution contours downstream of the diffuser located in Air Handling Unit (AHU) unit were obtained by using CFD. The contour pictures were then transferred to MATLAB environment. With pixel analysis in MATLAB, the pictures were able to be classified based on which parameters had an effect on the velocity distribution. Variable parameters are the length of the fan channel (x) and the ratio of cross-sectional areas of the AHU (A/Ao). The results showed that x=250 mm and A/Ao=0.5 improved velocity distributions by 6% and 20%, respectively.
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用图像分析方法比较CFD轮廓:速度分布的研究
等值线图是一种广泛应用于CFD(计算流体动力学)结果可视化的图形技术,具有很高的价值。它提供了一种有效和实用的方法来分析属于流体域的震级分布,例如;速度、温度、压力、体积分数等。然而,当分析多个轮廓线时,特别是显示相似的分布时,确定理想的轮廓线可能是困难的,并且容易引起猜测。本研究采用图像分析方法对速度分布轮廓线进行分类,解决了这一问题。这就决定了在几个轮廓图中哪一张图的分布最好。首先,利用CFD计算得到了空气处理机组扩压器下游的速度分布轮廓。然后将轮廓图转移到MATLAB环境中。在MATLAB中进行像素分析,根据对速度分布有影响的参数对图像进行分类。可变参数为风机通道长度(x)和AHU的截面积比(A/Ao)。结果表明,x=250 mm和A/Ao=0.5分别改善了6%和20%的速度分布。
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