Animals rely on odors to survive, navigating chaotic plumes for critical tasks like finding food, mates, and habitat. Humans have yet to understand and reproduce this skill for vital applications like search and rescue, explosive detection, and gas leak source identification. Recent research on olfactory navigation shows the importance of multimodal sensing, that is, simultaneous processing of the chemical signals from the odor as well as the mechanical signals from the flow. However, little data exists on the co-evolution of concentration and flow signals throughout airborne odor plumes, in large part due to the experimental challenges of obtaining time-resolved data for simultaneous velocity and concentration fields in a gaseous environment. Few examples exist of experiments in these low-Re, low-Sc regimes. The current work employs synchronous PLIF and stereo PIV for time-resolved measurements of the flow and odor fields for several configurations of naturalistic airborne plumes. Resulting datasets offer simultaneous velocity and concentration measurements over a 30 x 30 cm field of view at a temporal resolution of 20 Hz. A recirculating wind tunnel generates the flow at speeds up to 30 cm/s, with various regular and fractal turbulence grids to induce chaotic behavior and a variety of source configurations. The experiments result in rich datasets of naturalistic odor plumes that also yield insights into gaseous plume dispersion in low-Re, low-Sc conditions.
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