Novel Topology Optimization Methods for Designing Multifunctional Heterogeneous Material Systems
Novel Topology Optimization Methods for Designing Multifunctional Heterogeneous Material Systems
批准号:
1663566
负责人:
Kai James
金额:
$28.45万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-08-01 至 2021-07-31
中文摘要
添加剂制造的新进展使得快速、廉价地制造包含多种材料的复杂设计成为可能,例如金属、陶瓷和聚合物,所有这些都在一个印刷作业中完成。这种能力使制造商能够生产不需要组装的异类、多组件设计,从而消除了组装过程施加的成本和设计限制。它还可以让设计者生产出比传统方法更高性能和/或更轻的部件。然而,我们制造这种设计的能力目前超过了我们优化它们的能力。这项研究项目将研究为多功能、异质系统生成最优结构几何和材料布局的新算法。这些算法将考虑设计中使用的不同类型材料的行为以及材料之间的相互作用。通过这种方式,我们将实现多组件设计的系统级优化,其成本和性能特性将远远超过使用传统方法创建的组件。这种新的设计方法可能会影响多个研究社区和行业,应用范围从生物医学设备到消费电子产品。通过这项研究,我们将引入一种新的设计公式来处理包含几类材料的多功能设计问题。这一目标将通过开发新的基于拓扑优化的算法来实现,该算法将非线性有限元分析与专门为异质问题创建的原始参数设计表示方案相结合。数值优化问题将使用基于梯度的方法来解决,其中函数梯度将指导设计空间的优化搜索。这些梯度将使用伴随灵敏度分析来计算,并将考虑正在研究的各种非线性来源,包括超弹性、塑性和材料损伤。最终的设计算法将使用优化设计的高保真计算模型进行验证,并对类似的商用设计进行分析,以量化每种算法产生的性能收益。
英文摘要
New advances in additive manufacturing have enabled rapid and inexpensive fabrication of complex designs containing multiple classes of materials, such as metals, ceramics, and polymers, all within a single print job. This capability allows manufacturers to produce heterogeneous, multi-component designs that do not require assembly, thereby eliminating the cost and design constraints imposed by the assembly process. It also can allow designers to produce higher-performing and/or lighter-weight components than is possible through traditional means. However, our capacity to manufacture such designs currently exceeds our capability to optimize them. This research project will investigate novel algorithms for generating optimal structural geometries and material layouts for multifunctional, heterogeneous systems. These algorithms will consider the behavior of the different types of materials used in a design and the interactions among the materials. In this way, we will enable system-level optimization of multicomponent designs that will exhibit cost and performance properties far exceeding components created using traditional approaches. This novel design approach has the potential for impacts across multiple research communities and industries, with applications ranging from biomedical devices to consumer electronics.Through this research, we will introduce a new design formulation for handling multifunctional design problems containing several classes of material. This objective will be achieved through the development of novel topology optimization-based algorithms that will combine nonlinear finite element analysis with an original parametric design representation scheme, created specifically for heterogeneous problems. The numerical optimization problem will be solved using gradient-based methods in which function gradients will guide the optimization search of the design space. These gradients will be computed using adjoint sensitivity analysis, and will take into account the various sources of nonlinearity being investigated, including hyperelasticity, plasticity, and material damage. The resulting design algorithms will be validated using high-fidelity computational modeling of the optimized designs, along with analysis of analogous commercially-available designs, to quantify the performance gains generated by each algorithm.
期刊论文(1)
专著(0)
科研奖励(0)
会议论文
DOI:
10.1007/s00158-020-02784-0
发表时间:
2021-02
期刊:
Structural and Multidisciplinary Optimization
影响因子:
3.9
作者:
[Anurag Bhattacharyya;K. James]
通讯作者:
Anurag Bhattacharyya;K. James
CAREER: Automated Synthesis of Compound Machines Using Computational Design Optimization
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批准号:2311078
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项目类别:Standard Grant
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资助金额:$50.0万
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财政年份:2022
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负责人:Kai James
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依托单位:
CAREER: Automated Synthesis of Compound Machines Using Computational Design Optimization
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批准号:1752054
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项目类别:Standard Grant
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资助金额:$50.0万
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财政年份:2018
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负责人:Kai James
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依托单位:
海外基金