• Title/Summary/Keyword: Hot Wire Anemometer

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Reynolds Number Effects on the Near-Wake of an Oscillating Naca 4412 Airfoil, Part 1 : Mean Velocity Field (진동하는 NACA 4412 에어포일 근접후류에서의 레이놀즈수 효과 1: 평균속도장)

  • Jang,Jo-Won
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.31 no.7
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    • pp.15-25
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    • 2003
  • An experimental. study is carried out to investigate the near-wake characteristics of an airfoil oscillating in pitch. An NACA 4412 airfoil is sinusoidally pitched about the quarter chord point between the angle of attack -6$^{\circ}$ and +6$^{\circ}$. A hot-wire anemometer is used to measure the phase-averaged mean velocities in the near-wake region of an oscillating airfoil. The freestream velocities of present work are 3.4, 12.4, 26.2 m/s, and the corresponding Reynolds numbers are 5.3${\times}10^4$, 1.9${\times}10^5$, 4.l${\times}10^5$, and the reduced frequency is 0.1. Streamwise velocity profiles are presented to show the Reynolds number effects on the near-wake region behind an airfoil oscillating in pitch. All the cases in these measurements show that the velocity defects by the change of the Reynolds number are very large at the lowest Reynolds number $R_N$=5.3${\times}10^4$: and are small at the other Reynolds numbers ($R_N$=1.9${\times}10^5$ and 4.l${\times}10^5$) in the near-wake region. A significant difference of phase-averaged mean velocity between 5.3${\times}10^4$, and 1.9${\times}10^5$ is observed. The present study shows that a critical value of Reynolds number in the near-wake of an oscillating airfoil exists in the range between 5.3${\times}10^4$, and 1.9${\times}10^5$.

Visualization of Flow in a Transonic Centrifugal Compressor

  • Hayami Hiroshi
    • 한국가시화정보학회:학술대회논문집
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    • 2002.11a
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    • pp.1-6
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    • 2002
  • How is the flow in a rotating impeller. About 35 years have passed since one experimentalist rotating with the impeller. of a huge centrifugal blower made the flow measurements using a hot-wire anemometer (Fowler 1968). Optical measurement methods have great advantages over the intrusive methods especially for the flow measurement in a rotating impeller. One is the optical flow visualization (FV) technique (Senoo, et al., 1968) and the other is the application of laser velocimetry (LV) (Hah and Krain, 1990). Particle image velocimetries (PIVs) combine major features of both FV and LV, and are very attractive due to the feasibility of simultaneous and multi-points measurements (Hayami and Aramaki, 1999). A high-pressure-ratio transonic centrifugal compressor with a low-solidity cascade diffuser was tested in a closed loop with HFC134a gas at 18,000rpm (Hayami, 2000). Two kinds of measurement techniques by image processing were applied to visualize a flow in the compressor. One is a velocity field measurement at the inducer of the impeller using a PIV and the other is a pressure field measurement on the side wall of the cascade diffuser using a pressure sensitive paint (PSP) measurement technique. The PIV was successfully applied for visualization of an unsteady behavior of a shock wave based on the instantaneous velocity field measurement (Hayami, et al., 2002b) as well as a phase-averaged velocity vector field with a shock wave over one blade pitch (Hayami, et al., 2002a. b). A violent change in pressure was successfully visualized using a PSP measurement during a surge condition even though there are still some problems to be overcome (Hayami, et al., 2002c). Both PIV and PSP results are discussed in comparison with those of laser-2-focus (L2F) velocimetry and those of semiconductor pressure sensors. Experimental fluid dynamics (EFDs) are still growing up more and more both in hardware and in software. On the other hand, computational fluid dynamics (CFDs) are very attractive to understand the details of flow. A secondary flow on the side wall of the cascade diffuser was visualized based either steady or unsteady CFD calculations (Bonaiuti, et al.,2002). EFD and CFD methods will be combined to a hybrid method being complementary to each other. Measurement techniques by image processing as well as CFD calculations give a huge amount of data. Then, data mining technique will become more important to understand the flow mechanism both for EFD and CFD.

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