FMSG: Cyber: Does Nature Invoke the Optimum? A Bioinspired Hierarchical Manufacturing Process
FMSG: Cyber: Does Nature Invoke the Optimum? A Bioinspired Hierarchical Manufacturing Process
批准号:
2134534
负责人:
Costas Grigoropoulos
金额:
$50.0万
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
项目状态:
已结题
起止时间:
2021-11-01 至 2024-10-31
中文摘要
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英文摘要
This Future of Manufacturing grant aims to support advances in the manufacturing of innovative designs through biomimetic and bioinspired methodologies, setting the framework for the national prosperity and progress. Natural organisms are prominent paradigms of adaptive design. Through millions of years of evolutionary experiences, they fabricate themselves in an adaptive environment, in response to external stimuli. The versatility and complexity of nature’s design arsenal entails hierarchical features, at length scales of micrometers to nanometers. These intriguing designs involve perplexing structural features and enhanced mechanical performance. What can we learn from natural designs? Even more, can we do better by building on their success? From the perspective of the mechanical behavior, there is little success in a systematic definition of the design space using specific design parameters. Hence, even though these designs are effective, there is no guarantee that they are also optimal. This award supports the fundamental research required to unveil the modeling, optimization and fabrication processes necessary to design optimal biomimetic/bioinspired structures. The successful completion of this project will pave the way for the utility of these structures in tissue engineering, advanced materials, and augmented structures, becoming a catalyst for the U.S. economy and society. Students and postdocs will be involved and trained. Recent advances in additive manufacturing have enabled the fabrication of complex multifunctional structures. This progress has introduced the utility of biomimetic and bioinspired designs in every aspect of society, spanning from structural engineering to bioengineering. While modeling and experimental tools exist to analyze the final creation of nature, they have still not been merged in a strategic and coherent scheme to unravel the intermediate steps of the design process and elucidate how each step can be exploited in the manufacturing and design process of architected materials. The goal of this research is to design and fabricate three dimensional (3D) bioinspired structures with sophisticated multiscale hierarchical structure regarding their composition, dimensions, and geometry. To predict the structural development based on the external stimuli within a specific time frame, 3D growth continuum mechanics modeling techniques will be developed. In addition, multiscale printing techniques will be developed to fabricate both macroscale and micro/nanoscale features imitating the hierarchical “fabrication” process of nature through growth. Through stochastic optimization techniques augmented with advanced machine learning algorithms, the design space and identification of optima will be explored. Finally, using nature as reference, the optimum found by the algorithm will be compared with the actual natural organism through advanced characterization techniques, including in situ scanning electron microscopy tests. The findings of this research will show how lessons from nature are not merely imitated, but they can lead to novel approaches that will provide an answer to the question: Does Nature Invoke the Optimum? Based on this work, it will be possible to demonstrate a manufacturing strategy capable of producing structures of high mechanical performance, exhibiting resilience and damage tolerance.This project is jointly funded by the Division of Mathematical Sciences (DMS) within the Directorate of Mathematical and Physical Sciences (MPS), and by Industrial Innovation and Partnerships (IIP) within the Directorate of Engineering (ENG).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.
期刊论文(1)
专著(0)
科研奖励(0)
会议论文
DOI:
10.1016/j.eml.2023.102013
发表时间:
2023-03
期刊:
Extreme Mechanics Letters
影响因子:
4.7
作者:
[Z. Vangelatos;M. E. Yildizdag;C. Grigoropoulos]
通讯作者:
Z. Vangelatos;M. E. Yildizdag;C. Grigoropoulos
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