FMSG: Cyber: Does Nature Invoke the Optimum? A Bioinspired Hierarchical Manufacturing Process

这项制造业未来补助金旨在通过仿生和生物启发方法支持创新设计制造的进步，为国家繁荣和进步建立框架。自然生物是适应性设计的重要范例。通过数百万年的进化经验，它们在适应性环境中对外部刺激做出反应。大自然的设计武器库的多功能性和复杂性需要层次特征，在微米到纳米的长度尺度。这些有趣的设计涉及复杂的结构特征和增强的机械性能。我们可以从自然设计中学到什么？更重要的是，我们能否在他们成功的基础上做得更好？从机械性能的角度来看，使用特定的设计参数系统地定义设计空间几乎没有成功。因此，即使这些设计是有效的，也不能保证它们也是最优的。该奖项支持所需的基础研究，以揭示设计最佳仿生/仿生结构所需的建模，优化和制造过程。该项目的成功完成将为这些结构在组织工程、先进材料和增强结构中的应用铺平道路，成为美国经济和社会的催化剂。学生和博士后将参与和培训。增材制造的最新进展使得能够制造复杂的多功能结构。这一进展将仿生和仿生设计的实用性引入了社会的各个方面，从结构工程到生物工程。虽然存在建模和实验工具来分析自然的最终创造，但它们仍然没有被合并到一个战略和连贯的方案中，以解开设计过程的中间步骤，并阐明如何在建筑材料的制造和设计过程中利用每个步骤。本研究的目标是设计和制造三维（3D）仿生结构与复杂的多尺度层次结构，关于他们的组成，尺寸和几何形状。为了预测特定时间范围内基于外部刺激的结构发展，将开发3D生长连续介质力学建模技术。此外，将开发多尺度印刷技术，以通过生长模仿自然界的分层“制造”过程来制造宏观尺度和微米/纳米尺度特征。通过随机优化技术与先进的机器学习算法增强，设计空间和最优值的识别将被探索。最后，以自然界为参照，通过先进的表征技术，包括原位扫描电子显微镜测试，将算法找到的最佳值与实际的自然生物体进行比较。这项研究的结果将表明，自然界的经验教训不仅仅是模仿，而且可以导致新的方法，为这个问题提供答案：自然界是否遵循最佳状态？在此基础上，将有可能展示一种能够生产高机械性能结构的制造策略，表现出弹性和损伤容限。该项目由数学和物理科学理事会（MPS）数学科学部（DMS）共同资助，以及工程局（ENG）内的工业创新和伙伴关系（IIP）该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

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.