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We present a novel Material Point Method (MPM) discretization of surface tension forces that arise from spatially varying surface energies. These variations typically arise from surface energy dependence on temperature and/or concentration. Furthermore, since the surface energy is an interfacial property depending on the types of materials on either side of an interface, spatial variation is required for modeling the contact angle at the triple junction between a liquid, solid and surrounding air. Our discretization is based on the surface energy itself, rather than on the associated traction condition most commonly used for discretization with particle methods. Our energy based approach automatically captures surface gradients without the explicit need to resolve them as in traction condition based approaches. We include an implicit discretization of thermomechanical material coupling with a novel particle-based enforcement of Robin boundary conditions associated with convective heating. Lastly, we design a particle resampling approach needed to achieve perfect conservation of linear and angular momentum with Affine-Particle-In-Cell (APIC) [Jiang et al. 2015]. We show that our approach enables implicit time stepping for complex behaviors like the Marangoni effect and hydrophobicity/hydrophilicity. We demonstrate the robustness and utility of our method by simulating materials that exhibit highly diverse degrees of surface tension and thermomechanical effects, such as water, wine and wax.

We present an updated Lagrangian discretization of surface tension forces for the simulation of liquids with moderate to extreme surface tension effects. The potential energy associated with surface tension is proportional to the surface area of the liquid. We design discrete forces as gradients of this energy with respect to the motion of the fluid over a time step. We show that this naturally allows for inversion of the Hessian of the potential energy required with the use of Newton's method to solve the systems of nonlinear equations associated with implicit time stepping. The rotational invariance of the surface tension energy makes it non-convex and we define a definiteness fix procedure as in [Teran et al. 2005]. We design a novel level-set-based boundary quadrature technique to discretize the surface area calculation in our energy based formulation. Our approach works most naturally with Particle-In-Cell [Harlow 1964] techniques and we demonstrate our approach with a weakly incompressible model for liquid discretized with the Material Point Method [Sulsky et al. 1994]. We show that our approach is essential for allowing efficient implicit numerical integration in the limit of high surface tension materials like liquid metals.

We present novel techniques for simulating and visualizing ductile fracture with the Material Point Method (MPM). We utilize traditional particle-based MPM [Stomakhin et al. 2013; Sulsky et al. 1994] as well as the Lagrangian energy formulation of [Jiang et al. 2015] that utilizes a tetrahedron mesh, rather than particle-based estimation of the deformation gradient and potential energy. We model failure and fracture via elastoplasticity with damage. Material is elastic until its deformation exceeds a Rankine or von Mises yield condition, at which point we use a softening model that shrinks the yield surface until a damage threshold is reached. Once damaged, the material Lamé coefficients are modified to represent failed material. We design visualization techniques for rendering the boundary of the material and its intersections with evolving crack surfaces. Our approach uses a simple and efficient element splitting strategy for tetrahedron meshes to represent crack surfaces that utilizes an extrapolation technique based on the MPM simulation. For traditional particle-based MPM we use an initial Delaunay tetrahedralization to connect randomly initialized MPM particles. Our visualization technique is a post-process and can be run after the MPM simulation for efficiency. We demonstrate our method with a number of challenging simulations of ductile failure with considerable and persistent self-contact.

We present a new hybrid Lagrangian Material Point Method for simulating elastic objects like hair, rubber, and soft tissues that utilizes a Lagrangian mesh for internal force computation and an Eulerian mesh for self collision as well as coupling with external materials. While recent Material Point Method (MPM) techniques allow for natural simulation of hyperelastic materials represented with Lagrangian meshes, they utilize an updated Lagrangian discretization where the Eulerian grid degrees of freedom are used to take variations of the potential energy. This often coarsens the degrees of freedom of the Lagrangian mesh and can lead to artifacts. We develop a hybrid approach that retains Lagrangian degrees of freedom while still allowing for natural coupling with other materials simulated with traditional MPM, e.g. sand, snow, etc. Furthermore, while recent MPM advances allow for resolution of frictional contact with codimensional simulation of hyperelasticity, they do not generalize to the case of volumetric materials. We show that our hybrid approach resolves these issues. We demonstrate the efficacy of our technique with examples that involve elastic soft tissues coupled with kinematic skeletons, extreme deformation, and coupling with multiple elastoplastic materials. Our approach also naturally allows for two-way rigid body coupling.

Glaciers calving ice into the ocean is predicted to significantly contribute to sea-level rise and will thus influence future climate. Although numerous factors that induce glacier calving have been identified and studied, it is still extremely challenging to develop a unified and continuum computational framework that simulates ice fracture and glacier calving taking into account all important ingredients such as the interaction between ice and water, including buoyancy and melting, on complex and large scale geometry. This prevents scientists to precisely predict calving rates at the outlet of glaciers. Here, we propose to address this issue through numerical simulations of glacier calving based on the Material Point Method and finite strain elastoplasticity. A non-associative Cam-Clay model was developed to simulate the ice while the water is modeled as a nearly in-compressible fluid. First, simplified 2D simulations were performed to analyse the size of calved icebergs which were in good agreement with analytical solutions. The model reproduces not only the vertical glacier fracture observed in real calving events but also iceberg formation and tsunami-wave generation. Finally, 3D simulations of glacier calving were performed, taking into account opened crevasses on the top of the glacier. Although at a preliminary stage, and lacking experimental validation, we show the promise of our approach for modeling glacier calving, and more generally glacier and sea-ice dynamics.

We present a novel method for simulation of thin shells with frictional contact using a combination of the Material Point Method (MPM) and subdivision finite elements. The shell kinematics are assumed to follow a continuum shell model which is decomposed into a Kirchhoff-Love motion that rotates the mid-surface normals followed by shearing and compression/extension of the material along the mid-surface normal. We use this decomposition to design an elastoplastic constitutive model to resolve frictional contact by decoupling resistance to contact and shearing from the bending resistance components of stress. We show that by resolving frictional contact with a continuum approach, our hybrid Lagrangian/Eulerian approach is capable of simulating challenging shell contact scenarios with hundreds of thousands to millions of degrees of freedom. Without the need for collision detection or resolution, our method runs in a few minutes per frame in these high resolution examples. Furthermore we show that our technique naturally couples with other traditional MPM methods for simulating granular and related materials.

The typical elastic surface or curve simulation method takes a Lagrangian approach and consists of three components: time integration, collision detection and collision response. The Lagrangian view is beneficial because it naturally allows for tracking of the codimensional manifold, however collision must then be detected and resolved separately. Eulerian methods are promising alternatives because collision processing is automatic and while this is effective for volumetric objects, advection of a codimensional manifold is too inaccurate in practice. We propose a novel hybrid Lagrangian/Eulerian approach that preserves the best aspects of both views. Similar to the Drucker-Prager and Mohr-Coulomb models for granular materials, we define our collision response with a novel elastoplastic constitutive model. To achieve this, we design an anisotropic hyperelastic constitutive model that separately characterizes the response to manifold strain as well as shearing and compression in the directions orthogonal to the manifold. We discretize the model with the Material Point Method and a novel codimensional Lagrangian/Eulerian update of the deformation gradient. Collision intensive scenarios with millions of degrees of freedom require only a few minutes per frame and examples with up to one million degrees of freedom run in less than thirty seconds per frame.

We present a multi-species model for the simulation of gravity driven landslides and debris flows with porous sand and water interactions. We use continuum mixture theory to describe individual phases where each species individually obeys conservation of mass and momentum and they are coupled through a momentum exchange term. Water is modeled as a weakly compressible fluid and sand is modeled with an elastoplastic law whose cohesion varies with water saturation. We use a two-grid Material Point Method to discretize the governing equations. The momentum exchange term in the mixture theory is relatively stiff and we use semi-implicit time stepping to avoid associated small time steps. Our semi-implicit treatment is explicit in plasticity and preserves symmetry of force linearizations. We develop a novel regularization of the elastic part of the sand constitutive model that better mimics plasticity during the implicit solve to prevent numerical cohesion artifacts that would otherwise have occurred. Lastly, we develop an improved return mapping for sand plasticity that prevents volume gain artifacts in the traditional Drucker-Prager model.

In this paper, we introduce a novel material point method for heat transport, melting and solidifying materials. This brings a wider range of material behaviors into reach of the already versatile material point method. This is in contrast to best-of-breed fluid, solid or rigid body solvers that are difficult to adapt to a wide range of materials. Extending the material point method requires several contributions. We introduce a dilational/deviatoric splitting of the constitutive model and show that an implicit treatment of the Eulerian evolution of the dilational part can be used to simulate arbitrarily incompressible materials. Furthermore, we show that this treatment reduces to a parabolic equation for moderate compressibility and an elliptic, Chorin-style projection at the incompressible limit. Since projections are naturally done on marker and cell (MAC) grids, we devise a staggered grid MPM method. Lastly, to generate varying material parameters, we adapt a heat-equation solver to a material point framework.

Snow slab avalanches start with a failure in a weak snow layer buried below a cohesive snow slab. After failure, the very porous character of the weak layer leads to its volumetric collapse and thus closing of crack faces due to the weight of the overlaying slab. This complex process, generally referred to as anticrack, explains why avalanches that release on steep slopes can be triggered from flat terrain. On the basis of a new elastoplastic model for porous cohesive materials and the Material Point Method, we investigate the dynamics of mixed-mode anticracks, the subsequent detachment of the slab and the flow of the avalanche. In particular, we performed two and three dimensional slope scale simulations of both the release and flow of slab avalanches triggered either directly or remotely. We describe the fracture and flow dynamics on a realistic topography and focus on the volumetric plastic strain, stress invariants, propagation speed and flow velocity. Our simulations reproduce typical observations of en-echelon fractures and the propagation speed reached up to three times that measured in field experiments. In addition, slab fracture always started from the top in the Propagation Saw Test while it systematically initiated at the interface with the weak layer at the crown of slope-scale simulations in agreement with limited field observations. During the avalanche flow, snow granulation, erosion and deposition processes were naturally simulated and do not need additional implementations. Our unified model represents a significant step forward as it allows simulating the entire avalanche process, from failure initiation to crack propagation and to solid-fluid phase transitions, which is of paramount importance to forecast and mitigate snow avalanches., Cold Regions Science and Technology, 168, ISSN:0165-232X, ISSN:1872-7441

Snow is a challenging natural phenomenon to visually simulate. While the graphics community has previously considered accumulation and rendering of snow, animation of snow dynamics has not been fully addressed. Additionally, existing techniques for solids and fluids have difficulty producing convincing snow results. Specifically, wet or dense snow that has both solid- and fluid-like properties is difficult to handle. Consequently, this paper presents a novel snow simulation method utilizing a user-controllable elasto-plastic constitutive model integrated with a hybrid Eulerian/Lagrangian Material Point Method. The method is continuum based and its hybrid nature allows us to use a regular Cartesian grid to automate treatment of self-collision and fracture. It also naturally allows us to derive a grid-based semi-implicit integration scheme that has conditioning independent of the number of Lagrangian particles. We demonstrate the power of our method with a variety of snow phenomena including complex character interactions.

Simulating the physical behaviors of deformable objects and fluids has been an important topic in computer graphics. While the Lagrangian Finite Element Method (FEM) is widely used for elasto-plastic solids, it usually requires additional computational components in the case of large deformation, mesh distortion, fracture, self-collision and coupling between materials. Often, special solvers and strategies need to be developed for a particular problem. Recently, the hybrid Eulerian/Lagrangian Material Point Method (MPM) was introduced to the graphics community. It uses a continuum description of the governing equations and utilizes user-controllable elasto-plastic constitutive models. The hybrid nature of MPM allows using a regular Cartesian grid to automate treatment of self-collision and fracture. Like other particle methods such as Smoothed Particle Hydrodynamics (SPH), topology change is easy due to the lack of explicit connectivity between Lagrangian particles. Furthermore, MPM allows a grid-based implicit integration scheme that has conditioning independent of the number of Lagrangian particles. MPM also provides a unified particle simulation framework similar to Position Based Dynamics (PBD) for easy coupling of different materials. The power of MPM has been demonstrated in a number of recent papers for simulating various materials including elastic objects, snow, lava, sand and viscoelastic fluids. It is also highly integrated into the production framework of Walt Disney Animation Studios and has been used in featured animations including Frozen, Big Hero 6 and Zootopia.

A tandem of particle-based computational methods is adapted to simulate injury and hemorrhage in the human body. In order to ensure anatomical fidelity, a three-dimensional model of a targeted portion of the human body is reconstructed from a dense sequence of CT scans of an anonymized patient. Skin, bone and muscular tissue are distinguished in the imaging data and assigned with their respective material properties. An injury geometry is then generated by simulating the mechanics of a ballistic projectile passing through the anatomical model with the material point method. From the injured vascular segments identified in the resulting geometry, smoothed particle hydrodynamics (SPH) is employed to simulate bleeding, based on inflow boundary conditions obtained from a network model of the systemic arterial tree. Computational blood particles interact with the stationary particles representing impermeable bone and skin and permeable muscular tissue through the Brinkman equations for porous media. The SPH results are rendered in post-processing for improved visual fidelity. The overall simulation strategy is demonstrated on an injury scenario in the lower leg.

We present a new technique for transferring momentum and velocity between particles and grid with Particle-In-Cell (PIC) calculations which we call Affine-Particle-In-Cell (APIC). APIC represents particle velocities as locally affine, rather than locally constant as in traditional PIC. We show that this representation allows APIC to conserve linear and angular momentum across transfers while also dramatically reducing numerical diffusion usually associated with PIC. Notably, conservation is achieved with lumped mass, as opposed to the more commonly used Fluid Implicit Particle (FLIP) transfers which require a 'full' mass matrix for exact conservation. Furthermore, unlike FLIP, APIC retains a filtering property of the original PIC and thus does not accumulate velocity modes on particles as FLIP does. In particular, we demonstrate that APIC does not experience velocity instabilities that are characteristic of FLIP in a number of Material Point Method (MPM) hyperelasticity calculations. Lastly, we demonstrate that when combined with the midpoint rule for implicit update of grid momentum that linear and angular momentum are exactly conserved., 26 pages, 9 figures

Practical time steps in today’s state-of-the-art simulators typically rely on Newton’s method to solve large systems of nonlinear equations. In practice, this works well for small time steps but is unreliable at large time steps at or near the frame rate, particularly for difficult or stiff simulations. We show that recasting backward Euler as a minimization problem allows Newton’s method to be stabilized by standard optimization techniques with some novel improvements of our own. The resulting solver is capable of solving even the toughest simulations at the $24\,\text{Hz}$ frame rate and beyond. We show how simple collisions can be incorporated directly into the solver through constrained minimization without sacrificing efficiency. We also present novel penalty collision formulations for self collisions and collisions against scripted bodies designed for the unique demands of this solver. Finally, we show that these techniques improve the behavior of Material Point Method (MPM) simulations by recasting it as an optimization problem.

We utilize the shape derivative of the classical Griffith's energy in a level set method for the simulation of dynamic ductile fracture. The level set is defined in the undeformed configuration of the object, and its evolution is designed to represent a transition from undamaged to failed material. No re-meshing is needed since the resulting topological changes are handled naturally by the level set method. We provide a new mechanism for the generation of fragments of material during the progression of the level set in the Griffith's energy minimization. Collisions between different material pieces are resolved with impulses derived from the material point method over a background Eulerian grid. This provides a stable means for colliding with embedded interfaces. Simulation of corotational elasticity is based on an implicit finite element discretization.