Turbulence Spectra and Dissipation Rates in a Wind Tunnel Model of the Atmospheric Convective Boundary Layer

In this paper, the current drag of a barge-shaped floating liquefied natural gas (FLNG) vessel was studied. Three model tests were performed — a wind tunnel model test, a submerged double-body tow test and a surface tow test. Computational fluid dynamics (CFD) simulations were carried out to gain further insights into the test results. During testing, the tow speed was kept low to avoid surface waves. When the current heading was around the beam current direction, the transverse drag coefficient measured from the wind tunnel test was significantly lower than those of the submerged tow and surface tow tests. The submerged tow and the surface tow provided similar drag coefficients. Results presented in this paper indicated that the difference between the wind tunnel test and the tow tests was caused by the wind tunnel boundary layer effect on the incoming wind profile and formation of a recirculation zone on the upstream side of the model, with a possible additional contribution from the wind tunnel floor constraint on the flow in the wake. Such effects are not accounted for with the simple corrections based on flow velocity reduction in the wind tunnel boundary layer. When conducting future wind tunnel model tests for barge-shaped FLNG hulls, one should consider the potential under-measurement of the transverse drag. In this paper, details of the FLNG model, test setup, test quality assurance (QA), measurement and CFD simulation results are presented, as well as discussions and recommendations for model testing.

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A Method for Estimating the Turbulent Kinetic Energy Dissipation Rate from a Vertically Pointing Doppler Lidar, and Independent Evaluation from Balloon-Borne In Situ Measurements

Journal of Atmospheric and Oceanic Technology ◽

10.1175/2010jtecha1455.1 ◽

2010 ◽

Vol 27 (10) ◽

pp. 1652-1664 ◽

Cited By ~ 108

Author(s):

Ewan J. O’Connor ◽

Anthony J. Illingworth ◽

Ian M. Brooks ◽

Christopher D. Westbrook ◽

Robin J. Hogan ◽

...

Keyword(s):

Boundary Layer ◽

Convective Boundary Layer ◽

Sonic Anemometer ◽

Horizontal Wind ◽

Inertial Subrange ◽

Doppler Velocity ◽

Doppler Lidar ◽

Convective Boundary ◽

Dissipation Rates

Abstract A method of estimating dissipation rates from a vertically pointing Doppler lidar with high temporal and spatial resolution has been evaluated by comparison with independent measurements derived from a balloon-borne sonic anemometer. This method utilizes the variance of the mean Doppler velocity from a number of sequential samples and requires an estimate of the horizontal wind speed. The noise contribution to the variance can be estimated from the observed signal-to-noise ratio and removed where appropriate. The relative size of the noise variance to the observed variance provides a measure of the confidence in the retrieval. Comparison with in situ dissipation rates derived from the balloon-borne sonic anemometer reveal that this particular Doppler lidar is capable of retrieving dissipation rates over a range of at least three orders of magnitude. This method is most suitable for retrieval of dissipation rates within the convective well-mixed boundary layer where the scales of motion that the Doppler lidar probes remain well within the inertial subrange. Caution must be applied when estimating dissipation rates in more quiescent conditions. For the particular Doppler lidar described here, the selection of suitably short integration times will permit this method to be applicable in such situations but at the expense of accuracy in the Doppler velocity estimates. The two case studies presented here suggest that, with profiles every 4 s, reliable estimates of ε can be derived to within at least an order of magnitude throughout almost all of the lowest 2 km and, in the convective boundary layer, to within 50%. Increasing the integration time for individual profiles to 30 s can improve the accuracy substantially but potentially confines retrievals to within the convective boundary layer. Therefore, optimization of certain instrument parameters may be required for specific implementations.

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