Welcome




The research of the Computer Animation Group focuses on physically-based simulation of rigid body systems, deformable solids, and fluids, collision handling, cutting, fracturing, and real-time simulation methods. The main application areas include virtual prototyping, simulation in engineering, medical simulation, computer games and special effects in movies.
News
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Implicit Density Projection now available on GitHub! The code for our paper "Implicit Density Projection for Volume Conserving Liquids" has been implemented in the open source project Mantaflow and is now available on GitHub. Check here for the most recent version. |
July 27, 2022 |
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Best Paper Award Our paper "Fast Corotated Elastic SPH Solids with Implicit Zero-Energy Mode Control" got the best paper award at the ACM SIGGRAPH / EUROGRAPHICS Symposium on Computer Animation 2021. |
Sept. 10, 2021 |
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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 |
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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 |
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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 |
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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
![]() Micropolar Elasticity in Physically-Based Animation Proceedings of the ACM on Computer Graphics and Interactive Techniques (SCA) We explore micropolar materials for the simulation of volumetric deformable solids. In graphics, micropolar models have only been used in the form of one-dimensional Cosserat rods, where a rotating frame is attached to each material point on the one-dimensional centerline. By carrying this idea over to volumetric solids, every material point is associated with a microrotation, an independent degree of freedom that can be coupled to the displacement through a material's strain energy density. The additional degrees of freedom give us more control over bending and torsion modes of a material. We propose a new orthotropic micropolar curvature energy that allows us to make materials stiff to bending in specific directions. For the simulation of dynamic micropolar deformables we propose a novel incremental potential formulation with a consistent FEM discretization that is well suited for the use in physically-based animation. This allows us to easily couple micropolar deformables with dynamic collisions through a contact model inspired from the Incremental Potential Contact (IPC) approach. For the spatial discretization with FEM we discuss the challenges related to the rotational degrees of freedom and propose a scheme based on the interpolation of angular velocities followed by quaternion time integration at the quadrature points. In our evaluation we validate the consistency and accuracy of our discretization approach and demonstrate several compelling use cases for micropolar materials. This includes explicit control over bending and torsion stiffness, deformation through prescription of a volumetric curvature field and robust interaction of micropolar deformables with dynamic collisions. ![]() |
![]() A comparison of linear consistent correction methods for first-order SPH derivatives Proceedings of the ACM on Computer Graphics and Interactive Techniques (SCA) A well-known issue with the widely used Smoothed Particle Hydrodynamics (SPH) method is the neighborhood deficiency. Near the surface, the SPH interpolant fails to accurately capture the underlying fields due to a lack of neighboring particles. These errors may introduce ghost forces or other visual artifacts into the simulation. In this work we investigate three different popular methods to correct the first-order spatial derivative SPH operators up to linear accuracy, namely the Kernel Gradient Correction (KGC), Moving Least Squares (MLS) and Reproducing Kernel Particle Method (RKPM). We provide a thorough, theoretical comparison in which we remark strong resemblance between the aforementioned methods. We support this by an analysis using synthetic test scenarios. Additionally, we apply the correction methods in simulations with boundary handling, viscosity, surface tension, vorticity and elastic solids to showcase the reduction or elimination of common numerical artifacts like ghost forces. Lastly, we show that incorporating the correction algorithms in a state-of-the-art SPH solver only incurs a negligible reduction in computational performance. ![]() |
![]() Consistent SPH Rigid-Fluid Coupling Vision, Modeling and Visualization A common way to handle boundaries in SPH fluid simulations is to sample the surface of the boundary geometry using particles. These boundary particles are assigned the same properties as the fluid particles and are considered in the pressure force computation to avoid a penetration of the boundary. However, the pressure solver requires a pressure value for each particle. These are typically not computed for the boundary particles due to the computational overhead. Therefore, several strategies have been investigated in previous works to obtain boundary pressure values. A popular, simple technique is pressure mirroring, which mirrors the values from the fluid particles. This method is efficient, but may cause visual artifacts. More complex approaches like pressure extrapolation aim to avoid these artifacts at the cost of computation time. We introduce a constraint-based derivation of Divergence-Free SPH (DFSPH) --- a common state-of-the-art pressure solver. This derivation gives us new insights on how to integrate boundary particles in the pressure solve without the need of explicitly computing boundary pressure values. This yields a more elegant formulation of the pressure solver that avoids the aforementioned problems. ![]() |