Some effects of limited wall-sensor availability on flow estimation with 3D-GANs

IF 2.2 3区 工程技术 Q2 MECHANICS Theoretical and Computational Fluid Dynamics Pub Date : 2024-09-09 DOI:10.1007/s00162-024-00718-w
Antonio Cuéllar, Andrea Ianiro, Stefano Discetti
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Abstract

In this work we assess the impact of the limited availability of wall-embedded sensors on the full 3D estimation of the flow field in a turbulent channel with \(Re_{\tau }=200\). The estimation technique is based on a 3D generative adversarial network (3D-GAN). We recently demonstrated that 3D-GANs are capable of estimating fields with good accuracy by employing fully-resolved wall quantities (pressure and streamwise/spanwise wall shear stress on a grid with DNS resolution). However, the practical implementation in an experimental setting is challenging due to the large number of sensors required. In this work, we aim to estimate the flow fields with substantially fewer sensors. The impact of the reduction of the number of sensors on the quality of the flow reconstruction is assessed in terms of accuracy degradation and spectral length-scales involved. It is found that the accuracy degradation is mainly due to the spatial undersampling of scales, rather than the reduction of the number of sensors per se. We explore the performance of the estimator in case only one wall quantity is available. When a large number of sensors is available, pressure measurements provide more accurate flow field estimations. Conversely, the elongated patterns of the streamwise wall shear stress make this quantity the most suitable when only few sensors are available. As a further step towards a real application, the effect of sensor noise is also quantified. It is shown that configurations with fewer sensors are less sensitive to measurement noise.

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墙壁传感器可用性有限对 3D-GAN 流量估算的一些影响
在这项工作中,我们评估了墙壁嵌入式传感器的有限可用性对具有 \(Re_{\tau }=200\) 湍流通道中流场的全三维估计的影响。估计技术基于三维生成式对抗网络(3D-GAN)。我们最近证明,三维生成式对抗网络能够通过采用完全解析的壁面量(具有 DNS 分辨率的网格上的压力和流向/跨向壁面切应力)来准确估计流场。然而,由于需要大量传感器,在实验环境中实际应用具有挑战性。在这项工作中,我们的目标是用更少的传感器来估算流场。我们从精度下降和涉及的频谱长度尺度两个方面评估了减少传感器数量对流场重建质量的影响。结果发现,精度下降的主要原因是空间尺度采样不足,而不是传感器数量减少本身。我们探讨了估计器在只有一个壁面量的情况下的性能。在有大量传感器的情况下,压力测量能提供更精确的流场估算。相反,流向壁面剪应力的细长模式使其在仅有少量传感器的情况下成为最合适的参数。在实际应用中,我们还对传感器噪声的影响进行了量化。结果表明,传感器数量较少的配置对测量噪声的敏感度较低。
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来源期刊
CiteScore
5.80
自引率
2.90%
发文量
38
审稿时长
>12 weeks
期刊介绍: Theoretical and Computational Fluid Dynamics provides a forum for the cross fertilization of ideas, tools and techniques across all disciplines in which fluid flow plays a role. The focus is on aspects of fluid dynamics where theory and computation are used to provide insights and data upon which solid physical understanding is revealed. We seek research papers, invited review articles, brief communications, letters and comments addressing flow phenomena of relevance to aeronautical, geophysical, environmental, material, mechanical and life sciences. Papers of a purely algorithmic, experimental or engineering application nature, and papers without significant new physical insights, are outside the scope of this journal. For computational work, authors are responsible for ensuring that any artifacts of discretization and/or implementation are sufficiently controlled such that the numerical results unambiguously support the conclusions drawn. Where appropriate, and to the extent possible, such papers should either include or reference supporting documentation in the form of verification and validation studies.
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