Collaborative Research: Converging Design Methodology: Multi-objective Optimization of Resilient Structural Spines

合作研究:融合设计方法:弹性结构脊柱的多目标优化

基本信息

  • 批准号:
    2120683
  • 负责人:
  • 金额:
    $ 53万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2021
  • 资助国家:
    美国
  • 起止时间:
    2021-09-01 至 2024-08-31
  • 项目状态:
    已结题

项目摘要

Post-earthquake reconstruction efforts in New Zealand, Chile, and Japan are motivating the development of novel, low damage lateral force resisting systems to minimize social disruptions and property damage. These efforts, combined with earthquake scenarios highlighting seismic risks to cities in the United States, have led U.S. agencies to focus on increasing urban resilience against future extreme events by defining performance goals in terms of post-earthquake re-occupancy and functional recovery metrics. In parallel, non-profit organizations are driving the use of more sustainable building materials and construction practices. This project will create a new design paradigm within structural engineering that employs multi-objective optimization to maximize post-earthquake functional recovery while integrating sustainable building practices into the design process. The new design paradigm will be applied to the design and construction of resilient mass timber structural systems. The novelty of mass timber construction and limited availability of codes and standards make it uniquely positioned to pioneer innovative structural systems and new design paradigms, such as incorporating multi-objective optimization. The unique design paradigm developed in this project is called "converging design," as the methodology will be better able to converge across competing life-safety, post-earthquake functional recovery, and environmental sustainability objectives. The research will be complemented by an outreach program that includes training of the next generation of industry and academic leaders and fosters increased partnerships among academia, industry, building code officials, and government agencies. In addition, the research will lead to several undergraduate student experiences in STEM through an institutional Research and Extension Experiences for Undergraduate Student program and collaborations with NSF-funded Research Experiences for Undergraduates sites. This project will support the National Science Foundation (NSF) role in the National Earthquake Hazards Reduction Program. The goal of this project is to integrate functionality-based design and multi-objective optimization into a single converging design paradigm that will support resilient, sustainable seismic solutions for lateral force resisting systems. The project will integrate existing and new data from laboratory and numerical work to (1) define functional recovery and sustainability metrics, including quantification of uncertainty, for the design of innovative lateral force resisting systems employing mass timber spine solutions; (2) create and implement a multi-objective optimization converging seismic design methodology that considers resiliency and sustainability goals; and (3) develop optimized seismic lateral force resisting systems, whose performance is validated through a six-story full-scale building test program at the NSF-supported Natural Hazards Engineering Research Infrastructure (NHERI) outdoor shake table at the University of California, San Diego (UCSD). The six-story specimen re-uses an existing ten-story shake table specimen that will be tested on the UCSD shake table in 2021/2022. A series of expert elicitation interviews and participatory workshops will support the definition of resiliency metrics, including time to functionality and sustainability metrics (e.g., embodied carbon) to meet the goal of the research. Educational modules for industry and higher education will be created. An industry working group will promote increased collaboration and foster innovation among academia, industry, and government agencies. This project will lead to new seismic design possibilities and advance knowledge of the functionality and sustainability of mass timber structures based on decades of research in seismic design, advances in high-performance computing that support optimization in design, and functional-recovery modeling, including sustainability goals. Project data will be archived and made publicly available in the NHERI Data Depot (https://www.designsafe-ci.org).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.
新西兰、智利和日本的震后重建工作正在推动新型低损伤侧向力抵抗系统的开发,以尽量减少社会混乱和财产损失。这些努力,加上强调美国城市地震风险的地震情景,促使美国各机构通过确定震后重新入住和功能恢复指标方面的绩效目标,重点关注提高城市抵御未来极端事件的能力。与此同时,非营利组织正在推动使用更可持续的建筑材料和施工实践。该项目将在结构工程中创建一个新的设计范例,采用多目标优化来最大限度地实现震后功能恢复,同时将可持续建筑实践融入到设计过程中。新的设计范式将应用于弹性体量木结构系统的设计和施工。大规模木结构建筑的新颖性以及规范和标准的有限可用性使其在开创创新结构系统和新设计范式(例如纳入多目标优化)方面具有独特的地位。该项目开发的独特设计范式被称为“融合设计”,因为该方法将能够更好地融合相互竞争的生命安全、震后功能恢复和环境可持续性目标。这项研究将得到一项外展计划的补充,其中包括培训下一代行业和学术领袖,并促进学术界、行业、建筑规范官员和政府机构之间加强合作。此外,该研究还将通过本科生机构研究和推广体验项目以及与 NSF 资助的本科生研究体验站点的合作,为数名本科生带来 STEM 体验。该项目将支持美国国家科学基金会 (NSF) 在国家地震减灾计划中发挥的作用。 该项目的目标是将基于功能的设计和多目标优化集成到一个单一的聚合设计范式中,为抗侧力系统提供弹性、可持续的抗震解决方案。该项目将整合来自实验室和数值工作的现有数据和新数据,以(1)定义功能恢复和可持续性指标,包括不确定性的量化,用于设计采用大量木材脊柱解决方案的创新侧向力抵抗系统; (2) 创建并实施考虑弹性和可持续性目标的多目标优化聚合抗震设计方法; (3) 开发优化的抗震横向力系统,其性能通过在美国国家科学基金会 (NSF) 支持的加州大学圣路易斯分校自然灾害工程研究基础设施 (NHERI) 户外振动台上的六层全尺寸建筑测试项目进行验证迭戈(加州大学圣地亚哥分校)。该六层样本重复使用了现有的十层振动台样本,该样本将于 2021/2022 年在加州大学圣地亚哥分校振动台上进行测试。一系列专家启发式访谈和参与式研讨会将支持弹性指标的定义,包括实现功能的时间和可持续性指标(例如隐含碳),以实现研究目标。将创建工业和高等教育的教育模块。行业工作组将促进学术界、行业和政府机构之间加强合作并促进创新。该项目将基于数十年的抗震设计研究、支持设计优化的高性能计算的进步以及包括可持续性在内的功能恢复建模,带来新的抗震设计可能性,并加深对大型木结构功能和可持续性的了解。目标。项目数据将在 NHERI 数据仓库 (https://www.designsafe-ci.org) 中存档并公开提供。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评估进行评估,被认为值得支持。影响审查标准。

项目成果

期刊论文数量(0)
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Andre Barbosa其他文献

Seismic Resilience of Interdependent Built Environment for Integrating Structural Health Monitoring and Emerging Technologies in Decision-Making
相互依存的建筑环境的抗震能力,用于将结构健康监测和新兴技术纳入决策
  • DOI:
    10.1080/10168664.2023.2295901
  • 发表时间:
    2024-01-02
  • 期刊:
  • 影响因子:
    1.1
  • 作者:
    N. Makhoul;Milad Roohi;J. W. van de Lindt;Helder Sousa;Luís Oliveira Santos;S. Argyroudis;Andre Barbosa;Boumédiène Derras;Paolo Gardoni;Jong Sung Lee;S. Mitoulis;Brittany Moffett;Christopher Navarro;Jamie E. Padgett;Raul Rincon;Franziska Schmidt;Nefize Shaban;S. Stefanidou;Enrico Tubaldi;Y. Xenidis;Stefan Zmigrodzki
  • 通讯作者:
    Stefan Zmigrodzki

Andre Barbosa的其他文献

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{{ truncateString('Andre Barbosa', 18)}}的其他基金

RAPID/Collaborative Research: Post-Disaster, Reinforced Concrete Building Performance Data Collection following the April 25, 2015 Nepal Earthquake
RAPID/协作研究:2015 年 4 月 25 日尼泊尔地震后的灾后钢筋混凝土建筑性能数据收集
  • 批准号:
    1545632
  • 财政年份:
    2015
  • 资助金额:
    $ 53万
  • 项目类别:
    Standard Grant

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相似海外基金

Collaborative Research: Converging Design Methodology: Multi-objective Optimization of Resilient Structural Spines
合作研究:融合设计方法:弹性结构脊柱的多目标优化
  • 批准号:
    2120692
  • 财政年份:
    2021
  • 资助金额:
    $ 53万
  • 项目类别:
    Standard Grant
Collaborative Research: Converging Design Methodology: Multi-objective Optimization of Resilient Structural Spines
合作研究:融合设计方法:弹性结构脊柱的多目标优化
  • 批准号:
    2120684
  • 财政年份:
    2021
  • 资助金额:
    $ 53万
  • 项目类别:
    Standard Grant
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合作研究:融合 COVID-19、环境、健康和公平
  • 批准号:
    2037862
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    2020
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Collaborative Research: Converging COVID-19, environment, health, and equity
合作研究:融合 COVID-19、环境、健康和公平
  • 批准号:
    2037834
  • 财政年份:
    2020
  • 资助金额:
    $ 53万
  • 项目类别:
    Standard Grant
Collaborative Research: Converging Genomics, Phenomics, and Environments Using Interpretable Machine Learning Models
协作研究:使用可解释的机器学习模型融合基因组学、表型组学和环境
  • 批准号:
    1940062
  • 财政年份:
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    $ 53万
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