study, we investigate the slithering of snakes on flat surfaces.
Previous studies of slithering have rested on the assumption that
snakes slither by pushing laterally against rocks and branches. In this
combined experimental and theoretical study, we develop a model for
slithering locomotion by observing snake motion kinematics and
experimentally measuring the friction coefficients of snake skin. Our
predictions of body speed show good agreement with observations,
demonstrating that snake propulsion on flat ground, and possibly in
general, relies critically on the frictional anisotropy of their
scales. We also highlight the importance of the snake's dynamically
redistributing its weight during locomotion in order to improve speed
and efficiency. We conclude with an overview of our experimental
observations of other methods of propulsion by snakes, including
sidewinding and a unidirectional accordion-like mode.
of dense granular flow remains a difficult computational challenge.
Currently, modeling in practical and industrial situations would
typically be carried out by using the Discrete-Element Method (DEM),
individually simulating particles according to Newton's Laws. The
contact models in these simulations are stiff and require very small
timesteps to integrate accurately, meaning that even relatively small
problems require days or weeks to run on a parallel computer. These
brute-force approaches often provide little insight into the relevant
collective physics, and they are infeasible for applications in
real-time process control, or in optimization, where there is a need to
run many different configurations much more rapidly.
Based upon a number of recent theoretical advances, a general
multiscale simulation technique for dense granular flow will be
presented, that couples a macroscopic continuum theory to a discrete
microscopic mechanism for particle motion. The technique can be applied
to arbitrary slow, dense granular flows, and can reproduce similar flow
fields and microscopic packing structure estimates as in DEM. Since
forces and stress are coarse-grained, the simulation technique runs two
to three orders of magnitude faster than conventional DEM. A particular
strength is the ability to capture particle diffusion, allowing for the
optimization of granular mixing, by running an ensemble of different
A density functional theory of Ohta and Kawasaki gives rise to nonlocal perturbations of the well-studied Cahn-Hilliard and isoperimetric variational problems. In this talk, I will discuss these simple but rich variational problems in the context of diblock copolymers. Via a combination of rigorous analysis and numerical simulations, I will attempt to characterize minimizers without any preassigned bias for their geometry.
climate scientists studying tracer transport in the oceans are among many who rely on
trajectory predictions from ocean models. State-of-the-art models have been shown to
produce reliable velocity forecasts for 48-72 hours, yet the predictability horizon for
trajectories and related Lagrangian quantities remains significantly shorter. We
investigate the potential for decreasing Lagrangian prediction errors by applying a
constrained normal mode analysis (NMA) to blend drifter observations with model velocity
fields. The properties of an unconstrained NMA and the effects of parameter choices are
discussed. The constrained NMA technique is initially presented in a perfect model
simulation, where the “true” velocity field is known and the resulting error can be
directly assessed. Finally, we will show results from a recent experiment in the East
Asia Sea, where real observations were assimilated into operational ocean model hindcasts.