Robust Methods for the Physically-Based Animation of Large Deformations in Computer Graphics

计算机图形学中基于物理的大变形动画的鲁棒方法

基本信息

项目摘要

The goal of this research project is the development of robust and efficient methods for the physically-based animation of large deformations in computer graphics applications. This project has been funded by the German Research Foundation (DFG) for 18 months. In this time period our research group first investigated the stability problems in finite element simulations caused by degenerate and inverted elements. We were able to solve these problems using a method based on an analytic polar decomposition. Further, in the first project phase we developed a novel, very efficient simulation method based on a corotated elasticity model, which is more than a hundred times faster than previous methods using the same model. This enabled us to perform animations with multiple hundred thousand elements in real-time. In computer graphics time integration is mostly performed using the implicit Euler method due to its good stability. However, this method suffers from numerical damping which leads to a loss of important details and realism. Therefore, our group developed a stable implicit time integration method of higher order, which provides more accurate results and which reduces the numerical damping significantly. In the continuation of this project we plan to investigate the application of new material models to robustly simulate large deformations. More precisely, we want to investigate micropolar models, which were already successfully used in computer graphics to simulate elastic rods and fluids. These models define additional rotational degrees of freedom which enable a better representation of the bending and torsion of a deformable body. The improved representation has the advantage that less elements are required in elastic rods simulations. Moreover, it was shown that the numerical damping could be significantly reduced in simulations of turbulent fluids using a micropolar model. In the next phase of this research project we plan to use micropolar material models for the animation of two- and three-dimensional deformable bodies. To the best of our knowledge this has not been done before in computer graphics. In this way we want to benefit from the advantages of micropolar models, especially when simulating large deformations with rotations. First, we plan to develop a simulation method for volumetric bodies. Then we want to extend this method to simulate two-dimensional shells. To perform the time integration, the method, which we developed in the first phase, should be extended to solve the additional equations required for the micropolar models. Further, we plan to investigate the animation of plastic deformations considering the rotational degrees of freedom. Finally, we want to use the additional degrees of freedom to realize a detailed visualization with high-resolution surface meshes.
本研究项目的目标是为计算机图形学应用中的大变形的基于物理的动画开发鲁棒性和有效性的方法。该项目由德国研究基金会(DFG)资助18个月。在这段时间里,我们的研究小组首先研究了有限元模拟中由退化和反演单元引起的稳定性问题。我们能够解决这些问题,使用基于解析极分解的方法。此外,在项目的第一阶段,我们开发了一种基于共旋弹性模型的新型、非常有效的模拟方法,该方法比使用相同模型的先前方法快一百多倍。这使我们能够实时执行数十万个元素的动画。在计算机图形学中,时间积分大多采用隐式欧拉法,因为它具有良好的稳定性。然而,这种方法遭受数值阻尼,导致重要的细节和现实的损失。因此,我们的小组开发了一个稳定的隐式时间积分方法的高阶,它提供了更准确的结果,并减少了数值阻尼显着。在这个项目的延续中,我们计划研究新材料模型的应用,以鲁棒地模拟大变形。更确切地说,我们想研究微极模型,它已经成功地用于计算机图形学来模拟弹性杆和流体。这些模型定义了额外的旋转自由度,使得能够更好地表示可变形体的弯曲和扭转。改进后的表示法具有在弹性杆模拟中需要较少单元的优点。此外,它表明,数值阻尼可以显着减少在模拟湍流流体中使用微极模型。在这个研究项目的下一阶段,我们计划使用微极材料模型的二维和三维可变形物体的动画。据我们所知,这在计算机图形学中以前还没有做过。通过这种方式,我们希望受益于微极模型的优势,特别是在模拟带有旋转的大变形时。首先,我们计划开发一种体积体的模拟方法。然后,我们想扩展这种方法来模拟二维壳。为了进行时间积分,我们在第一阶段开发的方法应该扩展到求解微极模型所需的附加方程。此外,我们计划研究考虑旋转自由度的塑性变形的动画。最后,我们希望使用额外的自由度来实现具有高分辨率表面网格的详细可视化。

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

Professor Dr. Jan Stephen Bender其他文献

Professor Dr. Jan Stephen Bender的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

{{ truncateString('Professor Dr. Jan Stephen Bender', 18)}}的其他基金

Physically-Based Animation of Cutting, Tearing and Fracturing in Computer Graphics
计算机图形学中基于物理的切割、撕裂和断裂动画
  • 批准号:
    411281008
  • 财政年份:
    2018
  • 资助金额:
    --
  • 项目类别:
    Research Grants
Entwicklung echtzeitfähiger geometrischer Verfahren für eine interaktive chirurgische Simulation
交互式手术模拟实时几何方法的开发
  • 批准号:
    221909711
  • 财政年份:
    2012
  • 资助金额:
    --
  • 项目类别:
    Research Grants
Physically-based animation of deformable solids using Eulerian approaches in computer graphics
使用计算机图形学中的欧拉方法对可变形固体进行基于物理的动画
  • 批准号:
    310833819
  • 财政年份:
  • 资助金额:
    --
  • 项目类别:
    Research Grants

相似国自然基金

Computational Methods for Analyzing Toponome Data
  • 批准号:
    60601030
  • 批准年份:
    2006
  • 资助金额:
    17.0 万元
  • 项目类别:
    青年科学基金项目

相似海外基金

Advanced Markov chain Monte Carlo methods for physically based lighting simulations
用于基于物理的照明模拟的高级马尔可夫链蒙特卡罗方法
  • 批准号:
    546767-2020
  • 财政年份:
    2022
  • 资助金额:
    --
  • 项目类别:
    Postgraduate Scholarships - Doctoral
Accurate, Efficient, and Robust Adaptive Solution Methods and Models for Predicting Multi-Scale Physically-Complex Flows
用于预测多尺度物理复杂流的准确、高效、鲁棒的自适应解决方法和模型
  • 批准号:
    RGPIN-2019-06758
  • 财政年份:
    2022
  • 资助金额:
    --
  • 项目类别:
    Discovery Grants Program - Individual
Advanced Markov chain Monte Carlo methods for physically based lighting simulations
用于基于物理的照明模拟的高级马尔可夫链蒙特卡罗方法
  • 批准号:
    546767-2020
  • 财政年份:
    2021
  • 资助金额:
    --
  • 项目类别:
    Postgraduate Scholarships - Doctoral
Accurate, Efficient, and Robust Adaptive Solution Methods and Models for Predicting Multi-Scale Physically-Complex Flows
用于预测多尺度物理复杂流的准确、高效、鲁棒的自适应解决方法和模型
  • 批准号:
    DGDND-2019-06758
  • 财政年份:
    2021
  • 资助金额:
    --
  • 项目类别:
    DND/NSERC Discovery Grant Supplement
Physically compatible finite element methods for an electrically-induced heating problem
用于电致加热问​​题的物理兼容有限元方法
  • 批准号:
    2597059
  • 财政年份:
    2021
  • 资助金额:
    --
  • 项目类别:
    Studentship
Accurate, Efficient, and Robust Adaptive Solution Methods and Models for Predicting Multi-Scale Physically-Complex Flows
用于预测多尺度物理复杂流的准确、高效、鲁棒的自适应解决方法和模型
  • 批准号:
    RGPIN-2019-06758
  • 财政年份:
    2021
  • 资助金额:
    --
  • 项目类别:
    Discovery Grants Program - Individual
Accurate, Efficient, and Robust Adaptive Solution Methods and Models for Predicting Multi-Scale Physically-Complex Flows
用于预测多尺度物理复杂流的准确、高效、鲁棒的自适应解决方法和模型
  • 批准号:
    RGPIN-2019-06758
  • 财政年份:
    2020
  • 资助金额:
    --
  • 项目类别:
    Discovery Grants Program - Individual
Accurate, Efficient, and Robust Adaptive Solution Methods and Models for Predicting Multi-Scale Physically-Complex Flows
用于预测多尺度物理复杂流的准确、高效、鲁棒的自适应解决方法和模型
  • 批准号:
    DGDND-2019-06758
  • 财政年份:
    2020
  • 资助金额:
    --
  • 项目类别:
    DND/NSERC Discovery Grant Supplement
Advanced Markov chain Monte Carlo methods for physically based lighting simulations
用于基于物理的照明模拟的高级马尔可夫链蒙特卡罗方法
  • 批准号:
    546767-2020
  • 财政年份:
    2020
  • 资助金额:
    --
  • 项目类别:
    Postgraduate Scholarships - Doctoral
Accurate, Efficient, and Robust Adaptive Solution Methods and Models for Predicting Multi-Scale Physically-Complex Flows
用于预测多尺度物理复杂流的准确、高效、鲁棒的自适应解决方法和模型
  • 批准号:
    DGDND-2019-06758
  • 财政年份:
    2019
  • 资助金额:
    --
  • 项目类别:
    DND/NSERC Discovery Grant Supplement
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了