CHS: Small: Collaborative Research: Robust High Order Meshing and Analysis for Design Pipeline Automation

CHS：小型：协作研究：用于设计流程自动化的鲁棒高阶网格划分和分析

• 批准号: 1908767
• 负责人: Daniele Panozzo
• 金额: $ 23.88万
• 依托单位: New York University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-10-01 至 2023-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1908767&HistoricalAwards=false
• 关键词: CHS; Small; Collaborative; Research; Robust

The simulation of many real-world phenomena (such as elastoplastic deformations, sound propagation, and heat diffusion) relies on an explicit discretization of the space, which allows storage of physical quantities and performance of computations upon them. However, the Computer Aided Design (CAD) tools used to design shapes rely on a different discretization, usually a collection of disconnected high-order polynomial patches, which cannot be used in simulations. It is thus necessary to convert CAD models into simulation meshes, a procedure that can introduce geometric errors due to the use of linear elements and requires manual interaction, which limits its use to high-end applications. This research will develop a novel, automatic approach to tackle this conversion "exactly" by using high order elements, thereby avoiding unnecessary geometric approximations. The project will study high-order mesh generation and simulation as a single problem, building upon recent advances in robust linear meshing and developing new finite element method techniques that will allow non-expert users to benefit from simulation at a fraction of the time and cost currently needed to accomplish that task, which in turn will open the doors to new applications in medicine and digital fabrication. The project will involve extensive testing of the developed algorithms on a large collection of real-world CAD models. Both the data collected during this project and the reference implementation of the algorithms will be released in the public domain to foster adoption of the new technique as well as future research in this direction.The goal of this project is to develop a robust meshing pipeline that generates curvilinear elements that can reproduce both CAD models and subdivision surfaces with high fidelity, uses a direct measure of approximation errors, leading to coarse meshes that are designed to match the simulation accuracy required by applications, and can robustly and automatically process large collections of real-world CAD models. For interactive applications, the combination of the generated curved elements and the new error estimate will lead to extremely coarse models ideal for fast simulation. In CAD settings, it will for the first time enable precise modeling of complex scenarios such as the driving of a screw or the simulations of the stress concentration on fillets. The approach will close the gap between design tools, providing an automatic conversion of curved geometry to analysis-suitable curved meshes.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

许多真实世界现象(如弹塑性变形、声音传播和热扩散)的模拟依赖于空间的显式离散化，这允许存储物理量并在其上执行计算。然而，用于设计形状的计算机辅助设计(CAD)工具依赖于不同的离散化，通常是不连续的高次多项式面片的集合，这不能在模拟中使用。因此，有必要将CAD模型转换为模拟网格，这一过程可能会由于使用线性元素而引入几何误差，并且需要手动交互，这限制了其在高端应用中的使用。这项研究将开发一种新颖的、自动的方法，通过使用高阶元素来“准确”地处理这种转换，从而避免不必要的几何近似。该项目将把高阶网格生成和模拟作为一个单独的问题来研究，建立在健壮的线性网格划分的最新进展的基础上，并开发新的有限元方法技术，使非专家用户能够以目前完成这一任务所需的时间和成本的一小部分从模拟中受益，这反过来将为医学和数字制造领域的新应用打开大门。该项目将在大量真实的CAD模型上对开发的算法进行广泛的测试。该项目的目标是开发一种健壮的网格划分管道，其生成的曲线元素可以高保真地再现CAD模型和细分曲面，使用直接的逼近误差度量，从而产生与应用程序所需的模拟精度相匹配的粗网格，并且能够健壮地自动处理大量真实的CAD模型。对于交互式应用，生成的曲线单元和新的误差估计的组合将导致非常粗糙的模型，非常适合快速模拟。在CAD设置中，它将首次实现复杂场景的精确建模，例如螺杆传动或圆角上应力集中的模拟。该方法将缩小设计工具之间的差距，提供从曲面几何图形到适合分析的曲面网格的自动转换。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

A Cross-Platform Benchmark for Interval Computation Libraries

区间计算库的跨平台基准

• 发表时间: 2022
• 期刊: PPAM 2022
• 作者: Tang Xuan;Ferguson, Zachary;Schneider, Teseo;Zorin, Denis;Kamil, Shoaib;Panozzo, Daniele
• 通讯作者: Panozzo, Daniele

Exact and efficient polyhedral envelope containment check

• DOI: 10.1145/3386569.3392426
• 发表时间: 2020-07
• 期刊: ACM Transactions on Graphics (TOG)
• 作者: Bolun Wang;T. Schneider;Yixin Hu;M. Attene;Daniele Panozzo

DHFSlicer: Double Height-Field Slicing for Milling Fixed-Height Materials

DHFSlicer：用于铣削固定高度材料的双高度场切片

• 发表时间: 2020
• 期刊: ACM transactions on graphics
• 影响因子: 6.2
• 作者: Yang, Jinfan;Araujo, Chrystiano;Vining, Nicholas;Ferguson, Zachary;Rosales, Enrique;Panozzo, Daniele;Lefebvre, Sylvain;Cignoni, Paolo;Sheffer, Alla
• 通讯作者: Sheffer, Alla

Hardware Design and Accurate Simulation for Benchmarking of 3D Reconstruction Algorithms

3D 重建算法基准测试的硬件设计和精确仿真

• 发表时间: 2022
• 期刊: Neural Information Processing Systems (NeurIPS 2021
• 作者: Sebastian Koch, Yurii Piadyk

Sparsity-Specific Code Optimization using Expression Trees

• DOI: 10.1145/3520484
• 发表时间: 2021-10
• 期刊: ACM Transactions on Graphics (TOG)
• 作者: Philipp Herholz;Xuan Tang;T. Schneider;Shoaib Kamil;Daniele Panozzo;O. Sorkine-Hornung