GOALI: Hybrid Cellular Automata for Topology and Topography Synthesis in Automotive Structural Design

GOALI：用于汽车结构设计中的拓扑和拓扑综合的混合元胞自动机

• 批准号: 0800290
• 负责人: Stephen Batill
• 金额: $ 27.41万
• 依托单位: University of Notre Dame
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-06-01 至 2012-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0800290&HistoricalAwards=false
• 关键词: GOALI; Hybrid; Cellular; Automata; Topology

0800290RenaudAbstractThe research objective of this award is the development of a crashworthy hybrid cellular automata (crasHCA) method for nonlinear-dynamic transient topology and topography optimization. Crashworthiness design methods are used to synthesize vehicle structures to protect occupants against injury. Currently, the HCA approach for structural design is limited to linear static analysis for structural synthesis. In addition, competing topology optimization approaches require sensitivity calculations and are therefore limited to linear static analysis. Because analytic expressions for sensitivities or numerical approaches for sensitivity calculation in nonlinear transient problems are not available, current practice is limited to the use of surrogate models for design optimization. The results of this research will provide users with a convergent nonlinear transient topology and topography optimization approach for crashworthiness design. The HCA framework to date has been limited by the ability to use only brick elements for topology optimization. In this investigation the HCA methodology will include the use of shell elements within a framework referred to as topography optimization for the design of stamped sheet metal components.If successful this proposal will facilitate novel, new designs that will lead to increased levels of protection for both drivers and passengers in automotive vehicles. In the automotive industry the use of topology optimization for structural component design is increasingly popular. The development of a topology optimization capability that facilitates nonlinear transient topology and topography optimization (crasHCA) will allow vehicle designers to significantly improve vehicle safety in reduced product development cycle times. CrasHCA topology optimization will allow designers to move beyond surrogate models and to facilitate structural synthesis under nonlinear transient dynamic loading. In this GOALI investigation the PI and students will interact with Honda R&D Americas to insure technology transfer to industry. The crasHCA methodology for nonlinear transient topology optimization will be validated using real application test problems provided by Honda. Fabrication and mechanical testing of the synthesized designs at Honda?s research facility will further contribute to verification and validation.

0800290 RenaudAbstract该奖项的研究目标是开发一种用于非线性动态瞬态拓扑和地形优化的耐撞混合元胞自动机（crasHCA）方法。耐撞性设计方法用于综合车辆结构以保护乘员免受伤害。目前，结构设计的HCA方法仅限于结构综合的线性静力分析。此外，竞争拓扑优化方法需要灵敏度计算，因此仅限于线性静态分析。由于在非线性瞬态问题中灵敏度的解析表达式或灵敏度计算的数值方法不可用，目前的实践仅限于使用代理模型进行设计优化。本研究结果将提供使用者一个收敛的非线性瞬态拓扑和地形优化方法的耐撞性设计。迄今为止，HCA框架一直受到仅使用砖元素进行拓扑优化的能力的限制。在这项研究中，HCA方法将包括在一个称为拓扑优化的框架内使用壳单元来设计冲压钣金部件。如果成功，该建议将促进新颖的新设计，从而提高对汽车驾驶员和乘客的保护水平。在汽车工业中，拓扑优化在结构部件设计中的应用越来越普遍。拓扑优化能力的发展，促进非线性瞬态拓扑和地形优化（crasHCA）将允许车辆设计人员显着提高车辆的安全性，减少产品开发周期时间。CrasHCA拓扑优化将允许设计人员超越代理模型，并促进非线性瞬态动态载荷下的结构综合。在这次GOALI调查中，PI和学生将与本田美国研发部进行互动，以确保技术转移到工业领域。非线性瞬态拓扑优化的crasHCA方法将使用本田提供的真实的应用测试问题进行验证。在本田的合成设计的制造和机械测试？的研究设施将进一步促进核查和确认。