Role of the crown in tree resistance against high winds.

Rather than using wooden sticks to simulate the breakage of trees in high winds as in most research, we employ fresh samples from camphor and Formosa gum with branches and leaves to certify the crucial role of the tree crown. By using a blowdown wind tunnel with a maximum wind speed of 50 m/s, we purposely reduce the number of leaves and show that the drag force will drop by as much as two thirds when half pruned. Based on real observations, we model the leaf by an open and full cone in the presence of light and strong winds, and calculate how their corresponding cross-sectional area A and drag force F vary with wind speed v. Different slopes before and after the formation of a full cone are predicted and confirmed when these two quantities are plotted in full-log scale. Compared to the empirical value, our simple model gave α=2/5 and 2/3 for A∝v^{-α} and ß=4/5 and 2/3 for F∝v^{ß} at low and high winds. Discrepancies can be accounted for by including further details, such as the reorientation of open cones and the movement of branches.

Crumpling an elastoplastic thin sphere.

The phenomenon of crumpling is common in nature and our daily life. However, most of its properties, such as the power-law relation for pressure versus density and the ratio of bending and stretching energies, as well as the interesting statistical properties, were obtained by using flat sheets. This is in contrast to the fact that the majority of crumpled objects in the real world are three-dimensional. Notable examples are car wreckage, crushed aluminum cans, and blood cells that move through tissues constantly. In this work, we did a thorough examination of the properties of a crumpled spherical shell, hemisphere, cube, and cylinder via experiments and molecular-dynamics simulations. Physical arguments are provided to understand the discrepancies with those for flat sheets. The root of this disparity is found to lie less in the nonzero curvature, sharp edges and corner, and open boundary than in the dimensionality of the sample.