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Characteristics of Very Large-Scale Motions in Rough-Bed Open-Channel Flows
Rough-bed open-channel flows (OCFs) are ubiquitous in rivers and canals. However, the scaling and energy contents of very-large-scale motions (VLSMs) in such flows remain unclear. In this study, the above characteristics of VLSMs are experimentally investigated with the measurement of particle imaging velocimetry (PIV). VLSM wavelengths obtained via premultiplied spectra analysis were consistent with previously reported values. Comparisons with these studies ruled out the role of relative submergence, and suggested that the channel aspect ratio is key to controlling the VLSM wavelengths in OCFs. VLSMs carry approximately 60% of the turbulence kinetic energy (TKE) and 38–50% of the Reynolds stress in rough-bed OCFs. The VLSM-related TKE fraction in the 0.1–0.5H range increased with increasing friction Reynolds number, while variation in the Reynolds shear stress did not exhibit any explicit trend.
Characteristics of Very Large-Scale Motions in Rough-Bed Open-Channel Flows
Rough-bed open-channel flows (OCFs) are ubiquitous in rivers and canals. However, the scaling and energy contents of very-large-scale motions (VLSMs) in such flows remain unclear. In this study, the above characteristics of VLSMs are experimentally investigated with the measurement of particle imaging velocimetry (PIV). VLSM wavelengths obtained via premultiplied spectra analysis were consistent with previously reported values. Comparisons with these studies ruled out the role of relative submergence, and suggested that the channel aspect ratio is key to controlling the VLSM wavelengths in OCFs. VLSMs carry approximately 60% of the turbulence kinetic energy (TKE) and 38–50% of the Reynolds stress in rough-bed OCFs. The VLSM-related TKE fraction in the 0.1–0.5H range increased with increasing friction Reynolds number, while variation in the Reynolds shear stress did not exhibit any explicit trend.
Characteristics of Very Large-Scale Motions in Rough-Bed Open-Channel Flows
Ying Shen (author) / Shengfa Yang (author) / Jie Liu (author)
2023
Article (Journal)
Electronic Resource
Unknown
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