{"id":525,"date":"2022-10-07T15:41:35","date_gmt":"2022-10-07T06:41:35","guid":{"rendered":"https:\/\/lfc.media-creations.org\/?page_id=525"},"modified":"2022-12-07T15:04:49","modified_gmt":"2022-12-07T06:04:49","slug":"doc-page1-en","status":"publish","type":"page","link":"https:\/\/c-mng.cwh.hokudai.ac.jp\/lfc-me.eng\/Root\/research-project-en\/r-page-en\/doc-page1-en.html","title":{"rendered":"Color PIV"},"content":{"rendered":"\n
Particle Image Velocimetry (PIV) has advanced to three-dimensional three-component velocity vector field measurements in the last two decades. Among several types of 3D PIVs, use of color volumetric illumination allows a single-camera 3D measurement. Our laboratory developed two different kinds of Color PIV. One is Color PIV applicable to wind tunnel experiments, i.e. aerodynamic studies. This method relies on color decontamination [1] for smoke images that have particle-per-pixel value higher than unity. We applied this technique to engineering researches including 3D wake flow diagnosis for a delta wing and turbulent boundary layer subject to high heat transfer. The other technique is Color PTV (Particle Tracking Velocimetry) good for liquid flow measurements. Use of structured volumetric illumination [2] [3] and animation control [4] for the color-coding greatly improved the measurement performance. The technique was applied for rotating turbines, thermal convection, container\u2019s mixing, and flow structures around moving objects. Some of them includes machine-learning for colored opto-geometric calibration [5] to highly improve the measurement accuracy.<\/p>\n\n\n\n