Dispersion Kernels for Water Wave Simulation
José Ángel Canabal, doctorando en el área de dinámica de fluidos, presentará uno de sus trabajos en el área.
They propose a method to simulate the rich, scale-dependent dynamics of water waves. Their method preserves the dispersion properties of real waves, yet it supports interactions with obstacles and is computationally efficient. Fundamentally, it computes wave accelerations by way of applying a dispersion kernel as a spatially variant filter, which we are able to compute efficiently using two core technical contributions. First, they design novel, accurate, and compact pyramid kernels which compensate for low-frequency truncation errors. Second, they design a shadowed convolution operation that efficiently accounts for obstacle interactions by modulating the application of the dispersion kernel. They demonstrate a wide range of behaviours, which include capillary waves, gravity waves, and interactions with static and dynamic obstacles, all from within a single simulation.