Developing algorithm aided fabrication methods for polyhedral structures

开发多面体结构的算法辅助制造方法

• 批准号: RGPIN-2022-04256
• 负责人: Nejur, Andrei
• 金额: $ 1.75万
• 依托单位: Université de Montréal
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=743828
• 关键词: Developing; algorithm; aided; fabrication; methods

The scope of this research is to facilitate the design of fabrication-aware multi-manifold polyhedral structural systems applicable at the large and mezzo scale in industries like construction, automotive, aeronautics, furniture, and others. The principal step towards enabling this development is the creation of a robust set of algorithms able to simultaneously handle structural optimization and cost-effective fabrication while preserving user design intent. The proposed project builds upon two of PI's previous streams of research dedicated to mesh segmentation for fabrication and 3D graphic statics through reciprocal polyhedral systems and brings them together into a computational framework dedicated to the design and materialization of optimized structural systems based on volumetric polyhedral meshes, fabricable from flat sheet materials. The proposal consists of multiple tasks grouped into three complementary thrusts. Thrust 1 proposes the creation of several robust algorithms for the rationalization and segmentation of general volumetric polyhedral meshes with the scope of fabricating them through discretization and unfolding and Thrust 2 proposes the extension of existing geometry-based structural form-finding methods to include flat metal sheet fabrication constraints and insights in the process of optimal form determination for complex bespoke volumetric structures. Thrust 3 proposes the extension of sheet metal-based rationalization, optimization, and fabrication methods to sheet material dominant hybrid structures. Intellectual merit. Now no general flat-sheet fabrication workflows exist for volumetric polyhedral meshes at any scale. Furthermore, no structural form-finding solution able to produce fully spatial structures contains fabrication-aware constraints for flat sheet materialization. This research aims at addressing this gap by bringing important contributions to generative structural design and fabrication through a) The creation of new general method of fabrication for volumetric polyhedral systems using folding, sheet metal only or sheet-metal and linear elements. b) Introducing fabrication-aware constraints, in the process of structural form-finding for the efficient materialization of structures. Broader impacts. The result of this research will open new avenues towards the efficient, economic, and ecologic materialization of complex, lightweight, high-performance spatial structures. The research will bring about new computational instruments to construct spatial structures from metals like aluminium thus bringing new relevance to the manufacturing industry in Québec/Canada as well as to the connected construction industry. It will also enable the industry to reduce its environmental impact through material reuse and serious reductions in new material use.

本研究的范围是促进制造感知多歧管多面体结构系统的设计，适用于建筑，汽车，航空，家具等行业的大规模和中等规模。实现这一发展的主要步骤是创建一套强大的算法，能够同时处理结构优化和具有成本效益的制造，同时保留用户的设计意图。 拟议的项目建立在PI以前的两个研究流的基础上，致力于通过倒易多面体系统进行制造网格分割和3D图形静态，并将它们整合到一个计算框架中，该框架致力于基于体积多面体网格的优化结构系统的设计和实现，可从平板材料制造。该提案由多项任务组成，分为三个互补的重点。推力1提出了几个强大的算法的合理化和分割的一般体积多面体网格的范围内制造它们通过离散化和展开和推力2提出了现有的几何为基础的结构找形方法的扩展，包括平板金属板制造的限制和见解的过程中的最佳形式确定复杂的定制体积结构。推力3提出了基于板材的合理化，优化和制造方法，以板材为主的混合结构的扩展。 智力上的优点。现在，对于任何比例的体积多面体网格，都不存在通用的平板制造工作流。此外，没有结构找形解决方案能够产生完全的空间结构包含制造感知约束的平板材料化。本研究旨在通过以下方式为生成式结构设计和制造做出重要贡献来解决这一差距：a）创建新的通用制造方法，用于使用折叠、仅使用金属板或使用金属板和线性元件的体积多面体系统。B）在结构找形过程中引入制造感知约束，以有效实现结构。更广泛的影响。这项研究的结果将为复杂、轻质、高性能的空间结构的高效、经济和生态物化开辟新的途径。该研究将带来新的计算工具，用于用铝等金属建造空间结构，从而为魁北克/加拿大的制造业以及相关的建筑业带来新的相关性。它还将使该行业能够通过材料再利用和大量减少新材料的使用来减少对环境的影响。