Laboratory and numerical modeling of stably stratified wind flow over water surface

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Abstract

The objective of this chapter is to perform laboratory and direct numerical modeling of turbulent wind over water surface under stable stratification conditions. Laboratory and numerical experiments are performed under the same bulk Reynolds and Richardson numberswhich allowa direct comparison between themeasurements and calculations. The laboratory experiments are performed in a wind-wave flume on the basis of a thermostratified tank facility at IAP RAS. A sufficiently strong stable stratification (with the air-water temperature difference of up to 18 K) and a comparatively large bulk Richardson number (up to Ri ≈ 0.04) in the experiment are created by heating the incoming air flow while maintaining a relatively low wind speed (up to 3 m/s) and the corresponding bulk Reynolds number up to Re ≈ 60000. The air velocity field is retrieved by employing both contact (Pitot tube) and PIV methods, and the air temperature profile is measured simultaneously by a set of contact probes.The same bulk Ri and Re are prescribed in direct numerical simulation where turbulent Couette flowis considered as amodel of the nearwater constant stress atmospheric boundary layer. The mean velocity and temperature profiles obtained in our laboratory and numerical experiments agree well and also are well predicted by the Monin-Obukhov similarity theory. The results show that sufficiently strong stratification, although allowing a statistically stationary turbulent regime, leads to a drastic reduction of both turbulent momentum and heat fluxes. Under this regime, the flow turbulent Reynolds number (based on the Obukhov length scale and friction velocity) is found to be in agreement with known criteria characterizing stationary strongly stratified turbulence.

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Druzhinin, O. A., Sergeev, D. A., Troitskaya, Y. I., Tsai, W. T., & Vdovin, M. (2018). Laboratory and numerical modeling of stably stratified wind flow over water surface. In Nonlinear Waves and Pattern Dynamics (pp. 103–112). Springer International Publishing. https://doi.org/10.1007/978-3-319-78193-8_6

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