Real fields: Computer Graphics, Simulation
Simulation of dense smoke, clouds, avalanches relies on 3D fluid mechanics, which numerical solving (CFD) is extremely costly. These animated elements are more and more important in Computer Graphics applications (special effects and games), but CG requires very high resolution. In the scope of Computer Graphics, new algorithms allow for faster and stable simulation at the price of accuracy. Still, the 3D simulation is way to costly for interactive animation, and even storing the high-res 3D data is an issue. Moreover, CG does not aim at blind simulation: the graphist user wants some control on the look of the result. To cope with all these constraints, a new approach consists in separating the problem into a classical coarse 3D fluid simulation (supposedly known), and a mechanism able to add high-res details to it (which is our focus of interest here). Our teams already studied several such approaches in the past, mostly in 2D. In particular, texture advection (the texture pattern is an animated Perlin noise), either all over the scene (texture coordinates are advected with the flow), or using a sum of local deformed sprites advected with the flow. The purpose of this project is to revisit this approach and to adapt to 3D, in the case of dense opaque core inside transparent environment (such as dense smoke). Our team also works on real-time rendering of clouds, which lack animation, andof large detailed volumes, which could be used to visualize animated 3D fluid sprites.
Details are represented as a collection of 3D “sprites”, which
can deform thanks to a small 3D grid which nodes are advected along
the coarse flow. Each sprite is associated with a piece of 3D
texture, which is not an image but a function
to be evaluated on the fly during rendering. Sprites can be seen as
thick particles, which must cover evenly all the places where the
smoke, the clouds or the avalanche appears (nothing in transparent
air, and if possible nothing in internal or hidden areas, which is
one of the strengthes of the approach). Thus, sprites much appear and
disappear so as to keep their distribution even, and to replace
sprites which are too distorted (according to a metric to be
defined). These two aspects are key issues to elaborate.
Moreover, efficient coarse fluid simulators as well as our real-time volume rendering engine run entirely on GPU. Thus, it is interesting to also have the 3D texture advection algorithm also running on GPU, especially knowing it is potentially very data-parallel (list of independent nodes, lists of independent sprites, etc). Nowadays, it is easy to write such multithread-able algorithm in generic high level GPU language such CUDA (very close to C) and to benefit from the incredible computational power of modern graphics card. Thus, we would like to obtain an algorithm with properties compatible with good parallelism (the not obvious part is the resampling of sprite distribution). If possible, the final version (or before!) could be directly written in CUDA and run on GPU, which would ease the final visualization.
Notions of parallelism (multithreading) or GPU programming would be a plus, but these can be learn easily during the practice.
cf links along the text.