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... 6.35 mm rod mounted to the leading edge of the plate, just after the convergent section of the tunnel. The experimental apparatus is shown in Figure 1. The experiment was conducted at nine velocities (V1- V9) for each of eight wall temperatures. Including the neutrally stable case, they were labelled N, S1–S7. The temperature difference between the wall and freestream, ∆Θ s varied between zero (N) and 130 ◦ C (S7). The corresponding Richardson number and Reynolds number ranges were 0 ≤ Ri δ ≤ 0 . 2 and 600 ≤ Re θ ≤ 2050. Particle Image Velocimetry (PIV) was used determine the velocity field in a plane containing the wall-normal and streamwise directions. A New Wave Tempest and Gemini dual head ND:YAG laser system was used as the laser source. Each laser delivers 100 mJ energy per pulse at a wavelength of 532 nm. The flow was imaged with a PCO.1600 Camera with an interframe time of 300 μ s . Seeding was generated using an MGD Max 3000 APS mineral oil based fog generator. It was injected into a large enclosure attached to the inlet of the tunnel allowing the particles to be well-mixed with the incoming air before entering the tunnel inlet. The PIV images were processed using the a modified WIDIM code detailed in Scarano and Riethmuller (2000). It is an adaptive multigrid scheme that uses iterative image defor- mation to enhance correlation and reduce peak-locking. The final window size was 32 × 32 pixels with 50% window over- lap. The regression filter was set to 2. The internal signal to noise filter was disabled because it was found to have negli- gible impact on statistical resuls while requiring a large pro- portion of vectors to be interpolated. In some higher stability cases, near-wall seeding was found to be insufficient due to the strong local density gradient and low levels of mixing. These regions were cropped from the images and results. The field of view of PIV measurements was approximately half the boundary layer height so the remaining mean velocity profile was measured using a Pitot tube. The static pressure was measured using a static pressure probe mounted in the freestream. An Omega PX653-0.05BD5V high accu- racy, pressure transducer was used. Using these profiles, the boundary layer thickness and freestream velocity could be estimated. Due to the low dynamic pressures involved and the variation in density across the layer, the Pitot tube profiles measured at higher wall temperatures were found to be unreliable. Therefore, the boundary layer thicknesses and freestream velocities found in the neutral case were used to non-dimensionalize the data for the stable cases, as well. As data was taken varying both temperature and velocity, two sets of statistics will be shown, keeping one of these variables constant. The case with constant velocity enables us to examine the statistics with the smallest Reynolds number variation. Other data sets show very similar trends and are not included. Tables 1 and 2 list the global properties of each of these flows. The mean velocity profiles, shown in Figure 2(a), show a strong reduction in wall shear as the increasing level of stability decreases turbulent mixing. The strongest stability cases are almost laminar in nature. These profiles are qualitatively very similar to those shown by Ayra (1974) and Ohya et al. (1996) . The damping of turbulence is clearly seen in Figures 2(b) and 2(c), and the data are in good qualitative agreement with the results obtained by Ohya et al. (1996) . As with previous studies, the profiles can be divided into two regimes: the weakly stable, with minor reductions in turbulence intensity and shear stress, and the strongly stable where the turbulent stresses are significantly damped. The strongly stable stable profiles are also observed have a fundamentally differ- ent shape, with the peak in turbulence intensity moving away from the wall. This phenomena was also observed in Ohya et al. (1996). Case T3V4, common to both figures, appears to represent a transitional state between these two regimes and we will refer to it as the critical case. One of the most interest- ing aspects of our results was the critical Richardson number. It was found to be Ri δ = 0 . 05, which is much lower than the critical values measured by Ohya et al. (1996) or predicted by Miles-Howard theory (Miles, 1961) or Arya (1972). To examine whether this discrepancy is a Reynolds number effect, Figure 3 plots Re θ against Ri δ for all the cases studied in our experiment. The data were divided into weakly and strongly stable categories based on the behavior of the turbulent intensity profiles. While the Reynolds number range near the critical value is small in extent, it can be seen that the value of 0.05 defines a clear threshold above which the flow becomes strongly stable. Although Ohya et al (1996) do not quote momentum thickness Reynolds numbers, they were estimated from mean velocity profiles to be in the range 2500 ≤ Re θ ≤ 5000 and thus it seems unlikely that the differences between these two critical Richardson numbers can be ascribed to Reynolds number differences. The source of the ...