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A new filter was developed to collect harmful algae colonies by adapting the cross-step filtration structures and mechanisms discovered recently in filter-feeding fish. Extending beyond previously published models that closely emulated the basic morphology of the fish, the new cross-step filter's major innovations are helical slots, radial symmetry, and rotation as an active anti-clogging mechanism. These innovations enable the transport of concentrated particles to the downstream end of the filter. This advance was made possible by recognizing that biologically imposed constraints such as bilateral symmetry do not apply to human-made filters. The use of helical slots was developed in a series of iterative tests that used watertracing dye and algae-sized microspheres. The major products of the iterative tests were refinements in the helical design and an understanding of how varying the major structural parameters qualitatively influenced fluid flow and filter performance. Following the iterative tests, the clogging behavior of select filters was quantified at high particle concentrations. Vortices in the helical filter were effective at reducing clogging in the center of the slots. By considering the design space that is free of the biological constraints on the system and exploring the effects of variations in major structural parameters, our work has identified promising new directions for cross-step filtration and provided key insights into the biological system.

In this work, several different bioinspired filter geometries are proposed, fabricated, and tested in a flow tank. A novel approach is explored that mimics how filter-feeding fish efficiently remove small food particles from water. These filters generally take the form of a cone with water entering the large end of the cone and exiting through mesh-covered slots in the side of the cone, which emulates the rib structure of these filter-feeding fish. The flow in and around the filters is characterized and their ability to collect algae-scale, neutrally-buoyant particles is evaluated. Filter performance is evaluated by using image processing to count the number of particles collected and studying how the particles are deposited on the filter. Results are presented in the form of particle collection efficiencies, which is a ratio of particles collected to the particles that would nominally enter the filter inlet, and images of the fluorescent particles deposited on the filter at different time intervals. The results show little sensitivity to the filters’ inlet geometries, which was the major difference between filters tested. Comparative results are also presented from a 2D CFD model of the filters generated in COMSOL. The different geometries may differentiate themselves more at larger Reynolds numbers, and it is believed that a fluid exit ratio, or ratio of inlet area to exit area, is the most critical filter parameter. Field testing has demonstrated collection of real algae (i) with this bioinspired filter, and (ii) from a robot platform, but using a more conventional plankton net. The larger vision is to develop these filters and mount them on a swarm of autonomous surface vehicles, i.e. a robot boat swarm, which is being developed in parallel.

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