Physical Simulation of Deformable Models Based on Geometric Mapping

基于几何映射的变形模型物理模拟

• 批准号: 0727098
• 负责人: Xiaohu Guo
• 金额: --
• 依托单位: University of Texas at Dallas
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-09-15 至 2011-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0727098&HistoricalAwards=false
• 关键词: Physical; Simulation; Deformable; Models; Based; Physical; Simulation; Deformable; Models; Based

Interactive physically based modeling, simulation, and analysis of digitized real-world models are extremely challenging tasks. Physically based simulation approaches, such as finite element methods based on continuum mechanics, are computationally intensive, which makes them impractical for simulating and visualizing large-scale complex data in real-time. The introduction of geometric mapping in this research provides Euclidean parametric domain and regular structure inherent to complex geometric shapes, and provides efficient tools (such as GPU-based computation) to speed up the simulation process. This research tackles the speed bottleneck of physical simulation and visualization of deformable models by exploring the relationship between conformal and harmonic geometric mapping with physically based simulation, and develops efficient algorithms that allow users to perform real-time physical simulation, collision detection, material modeling, and visualization of large-scale, complicated geometric data. In particular, efficient and robust algorithms are investigated to enable dynamic space & time adaptive physical deformation of thin-shells and volumetric objects, by exploiting novel numerical methods to solve PDEs/ ODEs on graphics hardware, based on surface and volumetric mappings. The PI investigates novel GPU-based hierarchical collision detection algorithms for deformable models, using multiresolution geometry images to represent the bounding deformation trees as dynamic textures in the graphics hardware, to efficiently detect both inter-objects collision and self-collision of deformable models during simulations. This research project also develops powerful GPU-based multiresolution modeling and parallel visualization methods to efficiently represent and render heterogeneous material properties of the simulated deformable models. This investigation has broad impacts on an array of applications spanning physical science, mechanical engineering, medicine, K-12 education, training, and entertainment.

基于物理的建模，模拟和数字化现实世界模型的分析是极具挑战性的任务。基于物理的仿真方法，例如基于连续力学的有限元方法，在计算上是强化的，这使它们实时模拟和可视化大规模复杂数据不切实际。这项研究中的几何映射的引入提供了欧几里得参数域和复杂几何形状固有的常规结构，并提供有效的工具（例如基于GPU的计算）来加快仿真过程。这项研究通过探索与基于物理的模拟的保形和和谐几何映射之间的关系来解决物理模拟的速度瓶颈和可视化模型的可视化，并开发了有效的算法，从而使用户可以执行实时的物理模拟，碰撞检测，材料建模，并可视化大型，复杂的几何图。特别是，研究了有效和健壮的算法，以通过利用新颖的数值方法来求解基于表面和体积映射的图形硬件上的PDES/ ODE，以实现薄壳和体积对象的动态适应性物理变形。 PI使用多分辨率的几何图像来研究基于GPU的新型基于GPU的分层碰撞检测算法，以形成多分辨率的几何图像，以将边界变形树表示为图形硬件中的动态纹理，以有效地检测模拟过程中模型的碰撞和自我碰撞。该研究项目还开发了强大的基于GPU的多分辨率建模和并行可视化方法，以有效地表示和呈现模拟可变形模型的异质材料特性。这项调查对涵盖物理科学，机械工程，医学，K-12教育，培训和娱乐的一系列应用产生了广泛的影响。