Wind dispersal of natural and biomimetic maple samaras

TL;DR

This study compares natural and 3D-printed artificial maple samaras in wind dispersal, demonstrating that artificial versions can mimic natural seed behavior and informing bioinspired sensor deployment strategies.

Contribution

The paper introduces 3D-printed artificial samaras that replicate natural seed dispersal behavior, enabling bioinspired engineering applications and advancing understanding of wind dispersal mechanisms.

Findings

Artificial samaras match natural seed behavior in lab tests.

Natural samaras exhibit higher windage and longer dispersal distances.

Bioinspired designs can optimize sensor deployment over broad areas.

Abstract

Maple trees (genus $\textit{Acer}$) accomplish the task of distributing objects to a wide area by producing seeds which are carried by the wind as they slowly descend to the ground, known as samaras. With the goal of supporting engineering applications, such as gathering environmental data over a broad area, we developed 3D-printed artificial samaras. Here, we compare the behavior of both natural and artificial samaras in both still-air laboratory experiments and wind dispersal experiments in the field. We show that the artificial samaras are able to replicate (within 1 standard deviation) the behavior of natural samaras in a lab setting. We further introduce the notion of windage to compare dispersal behavior, and show that the natural samara has the highest mean windage, corresponding to the longest flights during both high wind and low wind experimental trials. This research provides a bioinspired design for the dispersed deployment of sensors and provides a better understanding of wind-dispersal of both natural and artificial samaras.