Turbulence and Particles in Fluids

Multi-pulse PIV and IPI

The role of turbulence in droplet growth in clouds between 20 µm and 100 µm in diameter, known as the size-gap problem, is not yet resolved. In order to shed light on the coupling of cloud microphysics and turbulence, it is indispensable to globally record droplet dynamics. Interferometric Particle Imaging (IPI) is a non-intrusive method that allows to simultaneously and globally measure droplet size, 2D spatial distribution, phase (spherical liquid drops vs. non-spherical ice particles), as well as 2D velocity by combining it with Particle Image velocimetry (PIV) technique. To achieve this we use a four-pulse laser system to capture two PIV frames interlaced with IPI images recorded on two high-speed cameras.

The IPI technique is based on out-of focus imaging of spherical particles where a laser sheet illuminates the region of interest. The camera captures the interference patterns of the first order reflection and refraction. By the following formula, one can calculate the particle diameter from the imaged pattern via the recognized pattern wave number and the pattern diameter.

Interference particle imaging is an out-of-focus non-intrusive measurement technique to globally determine particle sizes, phase and distribution and measuring 2D velocities by multiple frame sequences. Interference of the first order refraction and reflection yield a stripe pattern in out-of focus planes that is recorded by the camera as shown in the image. In the case of multiple droplets traversing the laser sheet, the overlap of particle images is a function of aperture size and degree of defocussing. (bottom left) Syntactic IPI image with the simulated (white) and the re-calculated size (blue). Recognition is more accurate for larger particles (higher frequency). (bottom right) Interference pattern of some water droplets generated with a regular hand spray and recorded via our IPI setup. Due to imperfections in the lenses and dirt, the patterns are not perfectly round and overlapped with a circular pattern. The bottom one has a homogeneous stripe pattern and was successfully analyzed whereas the droplet in the top is too large to be analyzed with this setup causing aliasing. — Interference particle imaging is an out-of-focus non-intrusive measurement technique to globally determine particle sizes, phase and distribution and measuring 2D velocities by multiple frame sequences. Interference of the first order refraction and reflection yield a stripe pattern in out-of focus planes that is recorded by the camera as shown in the image. In the case of multiple droplets traversing the laser sheet, the overlap of particle images is a function of aperture size and degree of defocussing. **(bottom left)** Syntactic IPI image with the simulated (white) and the re-calculated size (blue). Recognition is more accurate for larger particles (higher frequency). **(bottom right)** Interference pattern of some water droplets generated with a regular hand spray and recorded via our IPI setup. Due to imperfections in the lenses and dirt, the patterns are not perfectly round and overlapped with a circular pattern. The bottom one has a homogeneous stripe pattern and was successfully analyzed whereas the droplet in the top is too large to be analyzed with this setup causing aliasing.

Interference particle imaging is an out-of-focus non-intrusive measurement technique to globally determine particle sizes, phase and distribution and measuring 2D velocities by multiple frame sequences. Interference of the first order refraction and reflection yield a stripe pattern in out-of focus planes that is recorded by the camera as shown in the image. In the case of multiple droplets traversing the laser sheet, the overlap of particle images is a function of aperture size and degree of defocussing. **(bottom left)** Syntactic IPI image with the simulated (white) and the re-calculated size (blue). Recognition is more accurate for larger particles (higher frequency). **(bottom right)** Interference pattern of some water droplets generated with a regular hand spray and recorded via our IPI setup. Due to imperfections in the lenses and dirt, the patterns are not perfectly round and overlapped with a circular pattern. The bottom one has a homogeneous stripe pattern and was successfully analyzed whereas the droplet in the top is too large to be analyzed with this setup causing aliasing.

The ultimate goal is to predict droplet collisions via momentum conservation and coalescence as a function of the interference pattern. In the first step, we have found optimal parameters for designing the IPI setup. Then, a set of synthetic IPI images is made to assess the accuracy of particle detection and sizing algorithms for different droplet size distributions and concentrations typically encountered in clouds. Finally, preliminary experiments are carried out in the lab and exemplary analyzed for droplet sizes.