Physics-Based, Nonlinear, Multi-scale, Topology Optimization Framework for Designing Additively Manufactured Energy Dissipating Structural Fuses for Steel Building Systems

该奖项的长期愿景是使美国的钢结构建筑系统在极端地震事件中的表现更加坚固和有弹性，以减少破坏和生命损失，从而使国家在此类事件发生后继续繁荣和福祉。为了实现这一愿景，该项目的研究目标是创建一个基于物理的、非线性的、多尺度的拓扑优化(PB-NMSTO)框架，用于使用先进的附加制造方法设计建筑物内的最佳消能结构部件。该项目将通过提供一个集成的PB-NMSTO设计框架，使学术研究社区和实践设计工程师受益。该项目将培训本科生和研究生采用和使用添加剂制造技术，以解决自然灾害事件期间复杂的民用基础设施性能问题。该项目还将提供一个跳板，通过在以土著美国人和西班牙裔为主的初中和高中服务的外联活动来教育未来的美国工程师，并将促进STEM地区代表性不足群体的更多参与。该项目的数据将通过美国国家科学基金会支持的自然灾害工程研究基础设施数据库(https://www.designsafe-ci.org/).)公开提供在极端地震事件下，建筑系统的能量耗散是一个重要的设计问题。钢结构建筑系统的设计是这样的：塑性能量耗散(PED)发生在称为消能保险丝(EDF)的特殊部件中，而其余结构系统保持弹性。在钢材电除尘器中，能量通过与材料塑性和损伤有关的多尺度过程来耗散，而电除尘器的PED能力取决于其拓扑设计。目前，EDF设计大多是基于实验的，对于这些设计如何/是否是最优的，几乎没有深入的了解。更重要的是，由于设计空间受到可制造性的限制，这种设计方法严重限制了通过充分利用材料的PED能力所能实现的性能水平。为了将设计的重点放在功能最优化上，PB-NMSTO框架中将引入多尺度塑性损伤模型，结合拓扑优化和加法制造，以充分探索设计空间。这将通过以下方式实现：(A)发展对循环载荷下结构钢中PED的多尺度物理的基本理解，然后(B)利用该理解来解决拓扑优化的逆问题，目标是在优化的拓扑中最优地控制PED的物理。预计PB-NMSTO框架将为基于性能的EDF设计优化提供下一代最先进的设计范例，可以添加制造。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。

The long-term vision of this award is to render steel building systems in the United States to be more robust and resilient in their performance under extreme seismic events in order to reduce damage and loss of life, and thus enable continued national prosperity and welfare following such events. To achieve this vision, the research goal of this project is to create a physics-based, nonlinear, multi-scale, topology optimization (PB-NMSTO) framework for designing optimal energy dissipating structural components, within a building, using advanced additive manufacturing methods. This project will benefit the academic research community and practicing design engineers by providing an integrated PB-NMSTO design framework. The project will train undergraduate and graduate students in adopting and using additive manufacturing technologies for addressing complex civil infrastructure performance during natural hazard events. The project also will provide a springboard to educate future U.S. engineers through outreach activities at predominantly Native American and Hispanic serving middle and high schools and will foster increased participation of underrepresented groups in STEM areas. Data from this project will be made publicly available through the NSF-supported Natural Hazards Engineering Research Infrastructure Data Depot (https://www.designsafe-ci.org/). Dissipation of energy in building systems under extreme seismic events is a critical design concern. Steel building systems are designed such that plastic energy dissipation (PED) occurs in special components, called energy dissipating fuses (EDFs), while the remaining structural system stays elastic. In steel EDFs, energy is dissipated through multi-scale processes related to material plasticity and damage, and the PED capacity of an EDF depends on its topological design. At present, EDF designs are mostly experimental-based, and there is little insight on how/if these designs are optimal. More importantly, as the design space is constrained by manufacturability, this design methodology severely limits the performance levels that can be realized by full utilization of the material PED capacity. To focus the design efforts on functional optimality, multi-scale plastic-damage models, combined with topology optimization and additive manufacturing, will be introduced in the PB-NMSTO framework for the full exploration of the design space. This will be accomplished by: (a) developing a fundamental understanding of the multi-scale physics of PED in structural steel under cyclic loads, and then (b) using this understanding to solve the inverse problem of topology optimization with the goal of optimally controlling the physics of PED in optimized topologies. It is envisaged that the PB-NMSTO framework will provide the next generation state-of-the-art design paradigm for performance-based design optimization of EDFs that can be additively manufactured.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.