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Welcome


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Welcome to the Computer Animation Group at RWTH Aachen University!

The research of the Computer Animation Group focuses on the physically-based simulation of rigid bodies, deformable solids and fluids in interactive virtual reality applications and computer animation, and on related topics such as GPGPU and real-time visualization. The main application areas include virtual prototyping, medical simulation, computer games and special effects in movies.

News

Best Paper Award

Our paper "Volume Maps: An Implicit Boundary Representation for SPH" got the best paper award at the ACM SIGGRAPH Motion, Interaction and Games.

Nov. 15, 2019

Best Paper Award

Our paper "A Micropolar Material Model for Turbulent SPH Fluids" got the best paper award at the ACM SIGGRAPH / EUROGRAPHICS Symposium on Computer Animation.

Aug. 15, 2017

SPlisHSPlasH now available on Github!

SPlisHSPlasH is an open-source library for the physically-based simulation of fluids. The simulation in this library is based on the Smoothed Particle Hydrodynamics (SPH) method which is a popular meshless Lagrangian approach to simulate complex fluid effects. Check it out here!

Nov. 17, 2016

CompactNSearch now available on Github!

We published an open source implementation of our fixed radius neighborhood search for point clouds. The algorithm is written in C++, parallelized and features reordering of the points according to a space-filling Z curve. The implementation is particularly useful for particle based fluid simulations following the Smoothed Particle Hydrodynamics (SPH) approach. Check it out here!

Nov. 17, 2016

Recent Publications

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Implicit Frictional Boundary Handling for SPH

IEEE Transactions on Visualization and Computer Graphics

In this paper, we present a novel method for the robust handling of static and dynamic rigid boundaries in Smoothed Particle Hydrodynamics (SPH) simulations. We build upon the ideas of the density maps approach which has been introduced recently by Koschier and Bender. They precompute the density contributions of solid boundaries and store them on a spatial grid which can be efficiently queried during runtime. This alleviates the problems of commonly used boundary particles, like bumpy surfaces and inaccurate pressure forces near boundaries. Our method is based on a similar concept but we precompute the volume contribution of the boundary geometry. This maintains all benefits of density maps but offers a variety of advantages which are demonstrated in several experiments. Firstly, in contrast to the density maps method we can compute derivatives in the standard SPH manner by differentiating the kernel function. This results in smooth pressure forces, even for lower map resolutions, such that precomputation times and memory requirements are reduced by more than two orders of magnitude compared to density maps. Furthermore, this directly fits into the SPH concept so that volume maps can be seamlessly combined with existing SPH methods. Finally, the kernel function is not baked into the map such that the same volume map can be used with different kernels. This is especially useful when we want to incorporate common surface tension or viscosity methods that use different kernels than the fluid simulation.

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Accurately Solving Physical Systems with Graph Learning

arXiv

Iterative solvers are widely used to accurately simulate physical systems. These solvers require initial guesses to generate a sequence of improving approximate solutions. In this contribution, we introduce a novel method to accelerate iterative solvers for physical systems with graph networks (GNs) by predicting the initial guesses to reduce the number of iterations. Unlike existing methods that aim to learn physical systems in an end-to-end manner, our approach guarantees long-term stability and therefore leads to more accurate solutions. Furthermore, our method improves the run time performance of traditional iterative solvers. To explore our method we make use of position-based dynamics (PBD) as a common solver for physical systems and evaluate it by simulating the dynamics of elastic rods. Our approach is able to generalize across different initial conditions, discretizations, and realistic material properties. Finally, we demonstrate that our method also performs well when taking discontinuous effects into account such as collisions between individual rods.

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Implicit Density Projection for Volume Conserving Liquids

IEEE Transactions on Visualization and Computer Graphics

We propose a novel implicit density projection approach for hybrid Eulerian/Lagrangian methods like FLIP and APIC to enforce volume conservation of incompressible liquids. Our approach is able to robustly recover from highly degenerate configurations and incorporates volume-conserving boundary handling. A problem of the standard divergence-free pressure solver is that it only has a differential view on density changes. Numerical volume errors, which occur due to large time steps and the limited accuracy of pressure projections, are invisible to the solver and cannot be corrected. Moreover, these errors accumulate over time and can lead to drastic volume changes, especially in long-running simulations or interactive scenarios. Therefore, we introduce a novel method that enforces constant density throughout the fluid. The density itself is tracked via the particles of the hybrid Eulerian/Lagrangian simulation algorithm. To achieve constant density, we use the continuous mass conservation law to derive a pressure Poisson equation which also takes density deviations into account. It can be discretized with standard approaches and easily implemented into existing code by extending the regular pressure solver. Our method enables us to relax the strict time step and solver accuracy requirements of a regular solver, leading to significantly higher performance. Moreover, our approach is able to push fluid particles out of solid obstacles without losing volume and generates more uniform particle distributions, which makes frequent particle resampling unnecessary. We compare the proposed method to standard FLIP and APIC and to previous volume correction approaches in several simulations and demonstrate significant improvements in terms of incompressibility, visual realism and computational performance.

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