When a slab of snow cracks and slides down a slope, the exact size and shape of the resulting avalanche is hard to predict. The sliding slab is denser than the snow underneath it, giving the system a mix of solid and liquid properties.
Chenfanfu Jiang, assistant professor in the Department of Computer and Information Science, is an expert on the dynamics involved in porous materials. But unlike most research in applied mathematics and physics-based simulations, Jiang’s work has been seen by millions of people around the world. Before coming to Penn, he developed computer graphics for the entertainment industry; his computational models of snow, sand, and water have appeared in the Disney films Frozen, Zootoptia and Moana.
The math that power these realistic digital depictions are now set to have a real-world impact. Jiang recently published a study in Nature Communications that leverages these simulations as a way of capturing and predicting the complexity of a slab of snow’s behavior as cracks propagate through it.
Along with colleagues from the Swiss Federal Institute of Technology and the University of California, Los Angeles, Jiang developed a numerical model that accurately conforms to real-life observations of so-called snow slab avalanches.
“As a computer graphics researcher, my work has always been focusing on efficient, robust and accurate computational models for natural phenomena. In computer graphics, the area is generally called ‘physics-based animation,’ Jiang says.”
Historically, physics-based animation has not been particularly accurate when it comes to the real-life laws of physics. It has simply been too computationally difficult to make fully accurate simulations, and given the choice, the entertainment industry prioritizes visual realism over physical correctness.
By advancing a technique known as “material point method,” Jiang is hoping to get the best of both worlds.
“By absorbing ideas and developing new algorithms combining applied mathematics, high-performance computing, numerical analysis and photorealistic visualization, I’m hoping to bridge the gap between physics-based animation and more traditional computational engineering,” Jiang says.
Having the tools of computer graphics applied to real situations could potentially save lives; snow slab avalanches are particularly dangerous as they often triggered by hikers and skiers.
The Swiss Federal Institute of Technology’s Sarah Perrin described the complexities of the behavior that Jiang and his colleagues aimed to model in their recent paper:
A snow slab avalanche is usually triggered when there is an extra load — such as a crossing skier — on the snow, or when the snowpack is destabilized in some other way, for instance by an explosion. This causes a crack to appear in the bottom layer of snow, which can spread rapidly. At this point, the snow is behaving in accordance with the principles of solid mechanics. As the crack spreads, the weak layer’s porous structure causes it to collapse under the weight of the surface slab. Because of its mass and the slope, the slab is then released and begins to slide across the weaker layer. The collisions, frictions and fractures that the solid snow experiences as the top layer slides downward and breaks apart lead to a collective behavior characteristic of a fluid.
The researchers were able to simulate the collapse of the porous bottom layer for the first time at a large scale using a continuum approach. In addition, the model integrates only the relatively few key parameters that dictate how the snow will behave at the various stages of the process; these include the dynamics of the fracture, friction, and the level of compaction based on the type of snow.
Beyond snow, Jiang’s work has applications in understanding water-induced landslides, sediment transport, and terradynamics, or the mechanics behind ground-based locomotion. The latter is particular relevant for legged robots who need to move over shifting terrain, like sand, dirt or gravel.
“Research like this shows that computer graphics and traditional computational engineering can learn from each other and mutually benefit,” Jiang says.