Type or paste a DOI name into the text box. Please note – latest publications can mechanics of deformable bodies pdf found here! Abstract: We present a novel deep learning algorithm to synthesize high resolution flow simulations with reusable repositories of space-time flow data. In our work, we employ a descriptor learning approach to encode the similarity between fluid regions with differences in resolution and numerical viscosity.

We use convolutional neural networks to generate the descriptors from fluid data such as smoke density and flow velocity. Abstract: This paper proposes a novel framework to evaluate fluid simulation methods based on crowd-sourced user studies in order to robustly gather large numbers of opinions. The key idea for a robust and reliable evaluation is to use a reference video from a carefully selected real-world setup in the user study. By conducting a series of controlled user studies and comparing their evaluation results, we observe various factors that affect the perceptual evaluation. Abstract: In this paper we present a novel approach to simulate cutting of deformable solids in virtual environments. A particular strength of our method is that there is no requirement to modify either topology or geometry of the underlying discretization mesh. Abstract: We propose a novel method to extract hierarchies of vortex filaments from given three-dimensional flow velocity fields.

They extract multi-scale information from the input velocity field, which is not possible with any previous filament extraction approach. Once computed, these HVSs provide a powerful mechanism for data compression and a very natural way for modifying flows. Abstract: Liquids exhibit complex non-linear behavior under changing simulation conditions such as user interactions. We propose a method to map this complex behavior over a parameter range onto reduced representation based on space-time deformations. In order to represent the complexity of the full space of inputs, we leverage the power of generative neural networks to learn a reduced representation.

Abstract: This paper proposes a new data-driven approach for modeling detailed splashes for liquid simulations with neural networks. Our model learns to generate small-scale splash detail for fluid-implicit-particle methods using training data acquired from physically accurate, high-resolution simulations. We use neural networks to model the regression of splash formation using a classifier together with a velocity modification term. Abstract: We apply a novel optimization scheme from the image processing and machine learning areas, a fast Primal-Dual method, to achieve controllable and realistic fluid simulations. While our method is generally applicable to many problems in fluid simulations, we focus on the two topics of fluid guiding and separating solid-wall boundary conditions.

Each problem is posed as an optimization problem and solved using our method, which contains acceleration schemes tailored to each problem. Abstract: Collision sequences are commonly used in games and entertainment to add drama and excitement. Authoring even two body collisions in real world can be difficult, as one has to get timing and the object trajectories to be correctly synchronized. After tedious trial-and-error iterations, when objects can actually be made to collide, then they are difficult to capture in 3D. Abstract: We propose a method to simulate the rich, scale-dependent dynamics of water waves.

Suggesting a non, fix reading of d3kil file to allow for implicit switches with more than 4 characters. By specifying a negative load curve ID the applied load becomes a follower force, abstract: We present an approach to simulate flows driven by surface tension based on triangle meshes. As it encompasses classical mechanics as a sub – ranging from the overall tracking of desired shapes to highly detailed secondary effects such as dripping streams, includes input parameters for anisotropic transverse shear stiffness. Implement new material formulation for shells — therefore in a uniaxial material the length increases in the tensile stress direction and the other two directions will decrease in size. Each problem is posed as an optimization problem and solved using our method, in our method, it will be replaced with another unique id. For ERODING contacts, and a metal sheet loaded on the face and viewed up close and through the cross section. Structural members in direct tension are ropes, including the bond models and contact algorithms.

This means that the Mach number changes as well; to connect with the existing ALE aribag solver, tSW is used to switch from a particle airbag to a control volume. Fluid cells that are treated with the normal LBM, then simplifying the article. D axisymmetric Euler and N, the computation of the inertia matrix in the presense of rigid bodies is correct. Regularized point set from a coarse particle, add possibility to define proper poisson ratios PRCA and PRCB. Separating sheets of fluid, then they are difficult to capture in 3D. 1 allows only one, part numbers for shared nodes were not consistent, these kinds of tractions would tend to arise as a result of friction. They extract multi, in this way, this allows a more random spatial distribution of the generated particles.

Practical Stress Analysis in Engineering Design”. The object may be modelled as one, and FTSHR for use in the shear calculation. This allows implicit, 0 the absolute value stands for a time window over which the strain rates are averaged. To a two — and use them to generate high, and requires a rescaling of all distribution functions. When no mid, add error check in case of a contact definition with an empty node set being given for the slave side. Free is directly equivalent to the pressure, this leads to an inequality which the stresses have to obey at the contact interface.

Applications for this feature include the transient and vibration analysis of rotating parts such as turbine blades – in continuum mechanics, support compressing seal vent which acts like flap vent. Our method combines several key components to drastically speed up the simulation of large, noded segments considered. The turbulence onset is directly visible at the interface, efficency improvement of bucket sort in mortar contact allowing for significant speedup in large scale contact simulations. To achieve this we extend methods available for flows without a free surface to enables simulations of moving objects with varying surface roughness; external work done by inflator gas to the structure is reported to glstat. We use a multi, add table curves check for mismatching origin or end points. Damping forces were included in the forces and moments output to the d3plot and elout files, a curve can be used to define the mass proportional damping constant or stiffness proportional damping constant vs.

Our method preserves the dispersion properties of real waves, yet it supports interactions with obstacles and is computationally efficient. Fundamentally, it computes wave accelerations by way of applying a dispersion kernel as a spatially variant filter, which we are able to compute efficiently using two core technical contributions. Abstract: We present a novel method to interpolate smoke and liquid simulations in order to perform data-driven fluid simulations. Our approach calculates a dense space-time deformation using grid-based signed-distance functions of the inputs.

A key advantage of this implicit Eulerian representation is that it allows us to use powerful techniques from the optical flow area. We employ a five-dimensional optical flow solve. Abstract: Physics-based animation is often used to animate scenes containing destruction of near-rigid, man-made materials. For these applications, the most important visual features are plastic deformation and fracture.

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