Talk at BIRS workshop on “Computational Contact Mechanics: Advances and Frontiers in Modeling Contact”
Research from Computer Graphics Group at University of Copenhagen
Vincent Visseq, Ulrik Bonde, Marek K. Misztal and Kenny Erleben
Computer simulation of physical phenomena involving contact mechanics is of great in- terest to many fields of research and industries. New applications, such as biomedical simulations, are appealing for the modelling of soft materials and sliding contact. Several different approaches have been developed over the last four decades to formulate con- tact constraints for numerical simulation methods. In the finite element method, mortar meshes, Lagrange multipliers and penalty approaches are widely used to handle con- tact constraints. We propose to develop a new simulation framework providing conform- ing contact manifolds for deformable multibody dynamics, based on the Moving Meshes framework.
Ulrik Bonde, Marek K. Misztal, Vincent Visseq and Kenny Erleben
Contact interactions in the modeling of biomechanical systems are often simplified as Dirichlet or Neumann boundary conditions. The aim of this work is to propose a generic framework for the simulation of biomechanical disjoint domains and large transformations.
Jedediyah Williams, Ying Lu, Sarah Niebe, Michael Andersen, Kenny Erleben, and Jeff C. Trinkle
We present the RPI-MATLAB-Simulator (RPIsim) as an open source tool for research and education in multibody dynamics. RPIsim is designed and organized to be extended. Its modular design allows users to edit or add new components without worrying about extra implementation details. RPIsim has two main goals: 1. Provide an intuitive and easily extendable platform for research and education in multibody dynamics; 2. Maintain an evolving code base of useful algorithms and analysis tools for multibody dynamics problems. Although research often focuses on a specific subset of problems, work too often begins with developing software in a broader scope simply to realize a test bed for research to begin. It is our hope that RPIsim alleviates some of this burden by decreasing development time, thusly increasing efficiency in research. Further, we aim to provide a practical teaching tool. Because it is a fully working simulator, and since it offers the instant gratification of visualized contact dynamics, RPIsim offers students the opportunity to experiment and explore dynamics in the powerful environment of MATLAB. With multiple built-in simulation methods, and support for a simulation data convention, RPIsim facilitates the fair comparison of methods, including those being developed with RPIsim.
Marek. K. Misztal, Kenny Erleben, Adam Bargteil, Jens Fursund, Brian Bunch Christensen, J. Andreas. Bærentzen and Robert Bridson
In this paper, we present a method for animating multiphase flow of immiscible fluids using unstructured moving meshes. Our underlying discretization is an unstructured tetrahedral mesh, the deformable simplicial complex (DSC), that moves with the flow in a Lagrangian manner. Mesh optimization operations improve element quality and avoid element inversion. In the context of multiphase flow, we guarantee that every element is occupied by a single fluid and, consequently, the interface between fluids is represented by a set of faces in the simplicial complex. This approach ensures that the underlying discretization matches the physics and avoids the additional book-keeping required in grid-based methods where multiple fluids may occupy the same cell. Our Lagrangian approach naturally leads us to adopt a finite element approach to simulation, in contrast to the finite volume approaches adopted by a majority of fluid simulation techniques that use tetrahedral meshes. We characterize fluid simulation as an optimization problem allowing for full coupling of the pressure and velocity fields and the incorporation of a second-order surface energy. We introduce a preconditioner based on the diagonal Schur complement and solve our optimization on the GPU. We provide the results of parameter studies as well as a performance analysis of our method, together with suggestions for performance optimization.
Author Morten Engell-Nørregård
This PhD thesis concerns itself with modelling and simulation of human motion. The research subjects in this thesis have at least two things in common.
First, they are concerned with Human Motion. Even though the models may be used for other things as well, the main focus is on modelling the human body.
Second, they are all concerned with simulation as a tool to synthesize motion and thus, get animations. This is an important point since it means we are not only creating tools for animators to make fun and interesting animations, but also models for simulation of realistic motion. As the project progressed, the focus has shifted from purely graphics oriented to something which may be at least as interesting for the biomechanics community:
The main scientific contributions of this work are:
• An efficient method for solving interactive constrained inverse kinematics problems, using an optimization based approach. The method is usable for motion planning of complex articulated mechanisms, with a large degree of interdependency between different parts such as a human body.
• A general and fast joint constraint model. The joint constraint model is well suited for modelling joints with highly non-convex limits and multiple degrees of freedom. Even though this constraint model may have many other uses we believe it is very well suited for the modelling of human joints which exhibit both non-convexity and multiple degrees of freedom.
• A general and versatile model for activating soft bodies. The model may be used as an animation tool but would be equally well suited for simulation of human muscles since it adheres to basic physical principles. Further, it can be used with any softbody simulation method such as finite elements or mass spring systems.
• A control method for deformable bodies based on the space time optimization. The method may be used to control the contraction of muscles in a muscle simulation.
Thesis (pdf) Download