Design of Functionally Graded Materials Using Transient Nonlinear Simulations and Genetic Algorithm Optimization

使用瞬态非线性模拟和遗传算法优化设计功能梯度材料

• 批准号: 0423485
• 负责人: Senthil Vel
• 金额: $ 27.61万
• 依托单位: University of Maine
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-08-15 至 2008-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0423485&HistoricalAwards=false
• 关键词: Design; Functionally; Graded; Materials; Using

The objective of this research is to develop a robust methodology for the design of functionally graded materials (FGMs). FGMs are advanced composite materials that are engineered to have a smooth spatial variation of material properties. This is achieved by gradually varying the relative volume fractions and microstructure of the material constituents during fabrication. FGM components typically exhibit smaller stresses and higher factors of safety than discretely bonded monolithic materials. The aim of this research project is to create a unified framework for the simultaneous optimization of structural shape, compositional profile and microstructure of metal/ceramic FGMs that are subjected to time varying thermal and mechanical loads. The proposed technique utilizes a nonlinear elastoplastic model and numerical simulations using a meshless method to accurately analyze candidate designs. A robust multi-objective genetic algorithm will be used to simultaneously optimize structure shape, fractional composition and microstructure of the material. If successful, this project will result in a powerful design tool that could assist engineers and other professionals engaged in the design process with FGMs. It will benefit society by contributing new knowledge regarding the simulation and optimization of FGMs and by reducing the failure of mechanical components. A user-friendly software package implementing the proposed method will be developed and distributed freely on the Internet through the PI's web page. The educational plan will emphasize design as an important element of engineering education by incorporating computer-aided analysis, shape and material optimization to the PI's machine design and composite materials courses.

本研究的目的是发展一个强大的功能梯度材料（FGMs）的设计方法。功能梯度材料是先进的复合材料，其被设计成具有材料特性的平滑空间变化。这是通过在制造过程中逐渐改变材料成分的相对体积分数和微观结构来实现的。FGM部件通常表现出比离散结合的整体材料更小的应力和更高的安全系数。该研究项目的目的是建立一个统一的框架，同时优化金属/陶瓷功能梯度材料的结构形状，成分分布和微观结构，这些功能梯度材料承受时变的热载荷和机械载荷。所提出的技术利用非线性弹塑性模型和数值模拟，使用无网格方法来准确地分析候选设计。 一个强大的多目标遗传算法将被用来同时优化结构形状，分数组成和材料的微观结构。如果成功的话，这个项目将产生一个强大的设计工具，可以帮助工程师和其他专业人员参与功能梯度材料的设计过程。它将通过贡献关于功能梯度材料的模拟和优化的新知识以及通过减少机械部件的故障来造福社会。将开发一个便于使用的软件包，用于实施拟议的方法，并通过PI的网页在互联网上免费分发。教育计划将强调设计作为工程教育的一个重要组成部分，将计算机辅助分析，形状和材料优化纳入PI的机器设计和复合材料课程。