Interactive Thin Elastic Materials

Despite great strides in past years are being made to generate motions of elastic 1 materials such as cloth and biological skin in virtual world, unfortunately, the computational cost of realistic high-resolution simulations currently precludes their use in interactive applications. Thin elastic materials such as cloth and biological skin often exhibit complex nonlinear elastic behaviors. However, modeling elastic nonlinearity can be computationally expensive and numerically unstable, imposing significant challenges for their use in interactive applications. This paper presents a novel simulation framework for simulating realistic material behaviours with interactive frame rate. Central to the framework is the use of a constraint-based multi-resolution solver for efficient and robust modelling of the material nonlinearity. We extend a strain limiting method to work on deformation gradients of triangulated surface models in three dimensional space with a novel data structure. The simulation framework utilises an iterative nonlinear Gauss-Seidel procedure and a multilevel hierarchy structure to achieve computational speed ups. As material non-linearity are generated by enforcing strain limiting constraints at a multilevel hierarchy, our simulation system can rapidly accelerate the convergence of the large constraint system with simultaneous enforcement of boundary conditions. The simplicity and efficiency of the framework makes simulations of highly realistic thin elastic materials substantially fast and is applicable of simulations for interactive applications

A consistent bending model for cloth simulation with corotational subdivision finite elements

Modelling bending energy in a consistent way is decisive for the realistic simulation of cloth. With existing approaches characteristic behaviour like folding and buckling cannot be reproduced in a physically convincing way. We present a new method based on a corotational formulation of subdivision finite elements. Due to the non-local nature of the employed subdivision basis functions a C1-continuous displacement field can be defined. It is thus possible to use the governing equations of thin shell analysis leading to a physically accurate bending behaviour. Using a corotated strain tensor allows the large displacement analysis of cloth while retaining a linear system of equations. Hence, known convergence properties and computational efficiency are preserved

A Finite Element Method for Interactive Physically Based Shape Modelling with Quadratic Tetrahedra

We present an alternative approach to standard geometric shape editing using physically-based simulation. With our technique, the user can deform complex objects in real-time. The enabling technology of this approach is a fast and accurate finite element implementation of an elasto-plastic material model, specifically designed for interactive shape manipulation. Using quadratic shape functions, we avoid the inherent drawback of volume locking exhibited by methods based on linear finite elements. The physical simulation uses a tetrahedral mesh, which is constructed from a coarser approximation of the detailed surface. Having computed a deformed state of the tetrahedral mesh, the deformation is transferred back to the high detail surface. This can be accomplished in an accurate and efficient way using the quadratic shape functions. In order to guarantee stability and real-time frame rates during the simulation, we cast the elasto-plastic problem into a linear formulation. For this purpose, we present a corotational formulation for quadratic finite elements. We demonstrate the versatility of our approach in interactive manipulation sessions and show that our animation system can be coupled with further physics-based animations like, e.g. fluids and cloth, in a bi-directional way

Handler and Canine: Exploring the Career Path of a K-9 Officer

The K-9 Unit is a special unit within police departments where an officer may have a canine as their partner. They are designed to assist law enforcement in their duties making it easier to keep cities and towns safe. Within this unit, it is required that both handler and canine undergo intensive training. This paper reviews the steps a person may take to join a K-9 Unit and how to excel with their canine partner on the force. After discussing the history of using canines to serve and protect, this paper explores the difficulties of being a K-9 Handler such as the belief that it is cruel and inhumane to utilize animals within such a field. The paper dives into this controversy and concludes that canines love to perform their work alongside their handlers, and work hard to do so

Modeling and estimation of internal friction in cloth

Force-deformation measurements of cloth exhibit significant hysteresis, and many researchers have identified internal friction as the source of this effect. However, it has not been incorporated into computer animation models of cloth. In this paper, we propose a model of internal friction based on an augmented reparameterization of Dahl's model, and we show that this model provides a good match to several important features of cloth hysteresis even with a minimal set of parameters. We also propose novel parameter estimation procedures that are based on simple and inexpensive setups and need only sparse data, as opposed to the complex hardware and dense data acquisition of previous methods. Finally, we provide an algorithm for the efficient simulation of internal friction, and we demonstrate it on simulation examples that show disparate behavior with and without internal friction

Neural Metamaterial Networks for Nonlinear Material Design

Nonlinear metamaterials with tailored mechanical properties have applications in engineering, medicine, robotics, and beyond. While modeling their macromechanical behavior is challenging in itself, finding structure parameters that lead to ideal approximation of high-level performance goals is a challenging task. In this work, we propose Neural Metamaterial Networks (NMN) -- smooth neural representations that encode the nonlinear mechanics of entire metamaterial families. Given structure parameters as input, NMN return continuously differentiable strain energy density functions, thus guaranteeing conservative forces by construction. Though trained on simulation data, NMN do not inherit the discontinuities resulting from topological changes in finite element meshes. They instead provide a smooth map from parameter to performance space that is fully differentiable and thus well-suited for gradient-based optimization. On this basis, we formulate inverse material design as a nonlinear programming problem that leverages neural networks for both objective functions and constraints. We use this approach to automatically design materials with desired strain-stress curves, prescribed directional stiffness and Poisson ratio profiles. We furthermore conduct ablation studies on network nonlinearities and show the advantages of our approach compared to native-scale optimization